• Systematic review
  • Open access
  • Published: 10 October 2019

An integrative review on methodological considerations in mental health research – design, sampling, data collection procedure and quality assurance

  • Eric Badu   ORCID: orcid.org/0000-0002-0593-3550 1 ,
  • Anthony Paul O’Brien 2 &
  • Rebecca Mitchell 3  

Archives of Public Health volume  77 , Article number:  37 ( 2019 ) Cite this article

21k Accesses

19 Citations

1 Altmetric

Metrics details

Several typologies and guidelines are available to address the methodological and practical considerations required in mental health research. However, few studies have actually attempted to systematically identify and synthesise these considerations. This paper provides an integrative review that identifies and synthesises the available research evidence on mental health research methodological considerations.

A search of the published literature was conducted using EMBASE, Medline, PsycINFO, CINAHL, Web of Science, and Scopus. The search was limited to papers published in English for the timeframe 2000–2018. Using pre-defined inclusion and exclusion criteria, three reviewers independently screened the retrieved papers. A data extraction form was used to extract data from the included papers.

Of 27 papers meeting the inclusion criteria, 13 focused on qualitative research, 8 mixed methods and 6 papers focused on quantitative methodology. A total of 14 papers targeted global mental health research, with 2 papers each describing studies in Germany, Sweden and China. The review identified several methodological considerations relating to study design, methods, data collection, and quality assurance. Methodological issues regarding the study design included assembling team members, familiarisation and sharing information on the topic, and seeking the contribution of team members. Methodological considerations to facilitate data collection involved adequate preparation prior to fieldwork, appropriateness and adequacy of the sampling and data collection approach, selection of consumers, the social or cultural context, practical and organisational skills; and ethical and sensitivity issues.

The evidence confirms that studies on methodological considerations in conducting mental health research largely focus on qualitative studies in a transcultural setting, as well as recommendations derived from multi-site surveys. Mental health research should adequately consider the methodological issues around study design, sampling, data collection procedures and quality assurance in order to maintain the quality of data collection.

Peer Review reports

In the past decades there has been considerable attention on research methods to facilitate studies in various academic fields, such as public health, education, humanities, behavioural and social sciences [ 1 , 2 , 3 , 4 ]. These research methodologies have generally focused on the two major research pillars known as quantitative or qualitative research. In recent years, researchers conducting mental health research appear to be either employing both qualitative and quantitative research methods separately, or mixed methods approaches to triangulate and validate findings [ 5 , 6 ].

A combination of study designs has been utilised to answer research questions associated with mental health services and consumer outcomes [ 7 , 8 ]. Study designs in the public health and clinical domains, for example, have largely focused on observational studies (non-interventional) and experimental research (interventional) [ 1 , 3 , 9 ]. Observational design in non-interventional research requires the investigator to simply observe, record, classify, count and analyse the data [ 1 , 2 , 10 ]. This design is different from the observational approaches used in social science research, which may involve observing (participant and non- participant) phenomena in the fieldwork [ 1 ]. Furthermore, the observational study has been categorized into five types, namely cross-sectional design, case-control studies, cohort studies, case report and case series studies [ 1 , 2 , 3 , 9 , 10 , 11 ]. The cross-sectional design is used to measure the occurrence of a condition at a one-time point, sometimes referred to as a prevalence study. This approach of conducting research is relatively quick and easy but does not permit a distinction between cause and effect [ 1 ]. Conversely, the case-control is a design that examines the relationship between an attribute and a disease by comparing those with and without the disease [ 1 , 2 , 12 ]. In addition, the case-control design is usually retrospective and aims to identify predictors of a particular outcome. This type of design is relevant when investigating rare or chronic diseases which may result from long-term exposure to particular risk factors [ 10 ]. Cohort studies measure the relationship between exposure to a factor and the probability of the occurrence of a disease [ 1 , 10 ]. In a case series design, medical records are reviewed for exposure to determinants of disease and outcomes. More importantly, case series and case reports are often used as preliminary research to provide information on key clinical issues [ 12 ].

The interventional study design describes a research approach that applies clinical care to evaluate treatment effects on outcomes [ 13 ]. Several previous studies have explained the various forms of experimental study design used in public health and clinical research [ 14 , 15 ]. In particular, experimental studies have been categorized into randomized controlled trials (RCTs), non-randomized controlled trials, and quasi-experimental designs [ 14 ]. The randomized trial is a comparative study where participants are randomly assigned to one of two groups. This research examines a comparison between a group receiving treatment and a control group receiving treatment as usual or receiving a placebo. Herein, the exposure to the intervention is determined by random allocation [ 16 , 17 ].

Recently, research methodologists have given considerable attention to the development of methodologies to conduct research in vulnerable populations. Vulnerable population research, such as with mental health consumers often involves considering the challenges associated with sampling (selecting marginalized participants), collecting data and analysing it, as well as research engagement. Consequently, several empirical studies have been undertaken to document the methodological issues and challenges in research involving marginalized populations. In particular, these studies largely addresses the typologies and practical guidelines for conducting empirical studies in mental health. Despite the increasing evidence, however, only a few studies have yet attempted to systematically identify and synthesise the methodological considerations in conducting mental health research from the perspective of consumers.

A preliminary search using the search engines Medline, Web of Science, Google Scholar, and Scopus Index and EMBASE identified only two reviews of mental health based research. Among these two papers, one focused on the various types of mixed methods used in mental health research [ 18 ], whilst the other paper, focused on the role of qualitative studies in mental health research involving mixed methods [ 19 ]. Even though the latter two studies attempted to systematically review mixed methods mental health research, this integrative review is unique, as it collectively synthesises the design, data collection, sampling, and quality assurance issues together, which has not been previously attempted.

This paper provides an integrative review addressing the available evidence on mental health research methodological considerations. The paper also synthesises evidence on the methods, study designs, data collection procedures, analyses and quality assurance measures. Identifying and synthesising evidence on the conduct of mental health research has relevance to clinicians and academic researchers where the evidence provides a guide regarding the methodological issues involved when conducting research in the mental health domain. Additionally, the synthesis can inform clinicians and academia about the gaps in the literature related to methodological considerations.

Methodology

An integrative review was conducted to synthesise the available evidence on mental health research methodological considerations. To guide the review, the World Health Organization (WHO) definition of mental health has been utilised. The WHO defines mental health as: “a state of well-being, in which the individual realises his or her own potentials, ability to cope with the normal stresses of life, functionality and work productivity, as well as the ability to contribute effectively in community life” [ 20 ]. The integrative review enabled the simultaneous inclusion of diverse methodologies (i.e., experimental and non-experimental research) and varied perspectives to fully understand a phenomenon of concern [ 21 , 22 ]. The review also uses diverse data sources to develop a holistic understanding of methodological considerations in mental health research. The methodology employed involves five stages: 1) problem identification (ensuring that the research question and purpose are clearly defined); 2) literature search (incorporating a comprehensive search strategy); 3) data evaluation; 4) data analysis (data reduction, display, comparison and conclusions) and; 5) presentation (synthesising findings in a model or theory and describing the implications for practice, policy and further research) [ 21 ].

Inclusion criteria

The integrative review focused on methodological issues in mental health research. This included core areas such as study design and methods, particularly qualitative, quantitative or both. The review targeted papers that addressed study design, sampling, data collection procedures, quality assurance and the data analysis process. More specifically, the included papers addressed methodological issues on empirical studies in mental health research. The methodological issues in this context are not limited to a particular mental illness. Studies that met the inclusion criteria were peer-reviewed articles published in the English Language, from January 2000 to July 2018.

Exclusion criteria

Articles that were excluded were based purely on general health services or clinical effectiveness of a particular intervention with no connection to mental health research. Articles were also excluded when it addresses non-methodological issues. Other general exclusion criteria were book chapters, conference abstracts, papers that present opinion, editorials, commentaries and clinical case reviews.

Search strategy and selection procedure

The search of published articles was conducted from six electronic databases, namely EMBASE, CINAHL (EBSCO), Web of Science, Scopus, PsycINFO and Medline. We developed a search strategy based on the recommended guidelines by the Joanna Briggs Institute (JBI) [ 23 ]. Specifically, a three-step search strategy was utilised to conduct the search for information (see Table  1 ). An initial limited search was conducted in Medline and Embase (see Table 1 ). We analysed the text words contained in the title and abstract and of the index terms from the initial search results [ 23 ]. A second search using all identified keywords and index terms was then repeated across all remaining five databases (see Table 1 ). Finally, the reference lists of all eligible studies were manually hand searched [ 23 ].

The selection of eligible articles adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 24 ] (see Fig.  1 ). Firstly, three authors independently screened the titles of articles that were retrieved and then approved those meeting the selection criteria. The authors reviewed all the titles and abstracts and agreed on those needing full-text screening. E.B (Eric Badu) conducted the initial screening of titles and abstracts. A.P.O’B (Anthony Paul O’Brien) and R.M (Rebecca Mitchell) conducted the second screening of titles and abstracts of all the identified papers. The authors (E.B, A.P.O’B and R.M) conducted full-text screening according to the inclusion and exclusion criteria.

figure 1

Flow Chart of studies included in the review

Data management and extraction

The integrative review used Endnote ×8 to screen and handle duplicate references. A predefined data extraction form was developed to extract data from all included articles (see Additional file 1 ). The data extraction form was developed according to Joanna Briggs Institute (JBI) [ 23 ] and Cochrane [ 24 ] manuals, as well as the literature associated with concepts and methods in mental health research. The data extraction form was categorised into sub-sections, such as study details (citation, year of publication, author, contact details of lead author, and funder/sponsoring organisation, publication type), objective of the paper, primary subject area of the paper (study design, methods, sampling, data collection, data analysis, quality assurance). The data extraction form also had a section on additional information on methodological consideration, recommendations and other potential references. The authors extracted results of the included papers in numerical and textual format [ 23 ]. EB (Eric Badu) conducted the data extraction, A.P.O’B (Anthony Paul O’Brien) and R.M (Rebecca Mitchell), conducted the second review of the extracted data.

Data synthesis

Content analysis was used to synthesise the extracted data. The content analysis process involved several stages which involved noting patterns and themes, seeing plausibility, clustering, counting, making contrasts and comparisons, discerning common and unusual patterns, subsuming particulars into general, noting relations between variability, finding intervening factors and building a logical chain of evidence [ 21 ] (see Table  2 ).

Study characteristics

The integrative review identified a total of 491 records from all databases, after which 19 duplicates were removed. Out of this, 472 titles and abstracts were assessed for eligibility, after which 439 articles were excluded. Articles not meeting the inclusion criteria were excluded. Specifically, papers excluded were those that did not address methodological issues as well as papers addressing methodological consideration in other disciplines. A total of 33 full-text articles were assessed – 9 articles were further excluded, whilst an additional 3 articles were identified from reference lists. Overall, 27 articles were included in the final synthesis (see Fig. 1 ). Of the total included papers, 12 contained qualitative research, 9 were mixed methods (both qualitative and quantitative) and 6 papers focused on quantitative data. Conversely, a total of 14 papers targeted global mental health research and 2 papers each describing studies in Germany, Sweden and China. The papers addressed different methodological issues, such as study design, methods, data collection, and analysis as well as quality assurance (see Table  3 ).

Mixed methods design in mental health research

Mixed methods research is defined as a research process where the elements of qualitative and quantitative research are combined in the design, data collection, and its triangulation and validation [ 48 ]. The integrative review identified four sub-themes that describe mixed methods design in the context of mental health research. The sub-themes include the categories of mixed methods, their function, structure, process and further methodological considerations for mixed methods design. These sub-themes are explained as follows:

Categorizing mixed methods in mental health research

Four studies highlighted the categories of mixed methods design applicable to mental health research [ 18 , 19 , 43 , 48 ]. Generally, there are differences in the categories of mixed methods design, however, three distinct categories predominantly appear to cross cut in all studies. These categories are function, structure and process. Some studies further categorised mixed method design to include rationale, objectives, or purpose. For instance, Schoonenboom and Johnson [ 48 ] categorised mixed methods design into primary and secondary dimensions.

The function of mixed methods in mental health research

Six studies explain the function of conducting mixed methods design in mental health research. Two studies specifically recommended that mixed methods have the ability to provide a more robust understanding of services by expanding and strengthening the conclusions from the study [ 42 , 45 ]. More importantly, the use of both qualitative and quantitative methods have the ability to provide innovative solutions to important and complex problems, especially by addressing diversity and divergence [ 48 ]. The review identified five underlying functions of a mixed method design in mental health research which include achieving convergence, complementarity, expansion, development and sampling [ 18 , 19 , 43 ].

The use of mixed methods to achieve convergence aims to employ both qualitative and quantitative data to answer the same question, either through triangulation (to confirm the conclusions from each of the methods) or transformation (using qualitative techniques to transform quantitative data). Similarly, complementarity in mixed methods integrates both qualitative and quantitative methods to answer questions for the purpose of evaluation or elaboration [ 18 , 19 , 43 ]. Two papers recommend that qualitative methods are used to provide the depth of understanding, whilst the quantitative methods provide a breadth of understanding [ 18 , 43 ]. In mental health research, the qualitative data is often used to examine treatment processes, whilst the quantitative methods are used to examine treatment outcomes against quality care key performance targets.

Additionally, three papers indicated that expansion as a function of mixed methods uses one type of method to answer questions raised by the other type of method [ 18 , 19 , 43 ]. For instance, qualitative data is used to explain findings from quantitative analysis. Also, some studies highlight that development as a function of mixed methods aims to use one method to answer research questions, and use the findings to inform other methods to answer different research questions. A qualitative method, for example, is used to identify the content of items to be used in a quantitative study. This approach aims to use qualitative methods to create a conceptual framework for generating hypotheses to be tested by using a quantitative method [ 18 , 19 , 43 ]. Three papers suggested that using mixed methods for the purpose of sampling utilize one method (eg. quantitative) to identify a sample of participants to conduct research using other methods (eg. qualitative) [ 18 , 19 , 43 ]. For instance, quantitative data is sequentially utilized to identify potential participants to participate in a qualitative study and the vice versa.

Structure of mixed methods in mental health research

Five studies categorised the structure of conducting mixed methods in mental health research, into two broader concepts including simultaneous (concurrent) and sequential (see Table 3 ). In both categories, one method is regarded as primary and the other as secondary, although equal weight can be given to both methods [ 18 , 19 , 42 , 43 , 48 ]. Two studies suggested that the sequential design is a process where the data collection and analysis of one component (eg. quantitative) takes place after the data collection and analysis of the other component (eg qualitative). Herein, the data collection and analysis of one component (e.g. qualitative) may depend on the outcomes of the other component (e.g. quantitative) [ 43 , 48 ]. An earlier review suggested that the majority of contemporary studies in mental health research use a sequential design, with qualitative methods, more often preceding quantitative methods [ 18 ].

Alternatively, the concurrent design collects and analyses data of both components (e.g. quantitative and qualitative) simultaneously and independently. Palinkas, Horwitz [ 42 ] recommend that one component is used as secondary to the other component, or that both components are assigned equal priority. Such a mixed methods approach aims to provide a depth of understanding afforded by qualitative methods, with the breadth of understanding offered by the quantitative data to elaborate on the findings of one component or seek convergence through triangulation of the results. Schoonenboom and Johnson [ 48 ] recommended the use of capital letters for one component and lower case letters for another component in the same design to indicate that one component is primary and the other is secondary or supplemental.

Process of mixed methods in mental health research

Five papers highlighted the process for the use of mixed methods in mental health research [ 18 , 19 , 42 , 43 , 48 ]. The papers suggested three distinct processes or strategies for combining qualitative and quantitative data. These include merging or converging the two data sets, connecting the two datasets by having one build upon the other; and embedding one data set within the other [ 19 , 43 ]. The process of connecting occurs when the analysis of one dataset leads to the need for the other data set. For instance, in the situation where quantitative results lead to the subsequent collection and analysis of qualitative data [ 18 , 43 ]. A previous study suggested that most studies in mental health sought to connect the data sets. Similarly, the process of merging the datasets brings together two sets of data during the interpretation, or transforms one type of data into the other type, by combining the data into new variables [ 18 ]. The process of embedding data into mixed method designs in mental health uses one dataset to provide a supportive role to the other dataset [ 43 ].

Consideration for using mixed methods in mental health research

Three studies highlighted several factors that need to be considered when conducting mixed methods design in mental health research [ 18 , 19 , 45 ]. Accordingly, these factors include developing familiarity with the topic under investigation based on experience, willingness to share information on the topic [ 19 ], establishing early collaboration, willingness to negotiate emerging problems, seeking the contribution of team members, and soliciting third-party assistance to resolve any emerging problems [ 45 ]. Additionally, Palinkas, Horwitz [ 18 ] recommended that mixed methods in the context of mental health research are mostly applied in studies that assess needs of services, examine existing services, developing new or adapting existing services, evaluating services in randomised control trials, and examining service implementation.

Qualitative study in mental health research

This theme describes the various qualitative methods used in mental health research. The theme also addresses methodological considerations for using qualitative methods in mental health research. The key emerging issues are discussed below:

Considering qualitative components in conducting mental health research

Six studies recommended the use of qualitative methods in mental health research [ 19 , 26 , 28 , 32 , 36 , 44 ]. Two qualitative research paradigms were identified, including the interpretive and critical approach [ 32 ]. The interpretive methodologies predominantly explore the meaning of human experiences and actions, whilst the critical approach emphasises the social and historical origins and contexts of meaning [ 32 ]. Two studies suggested that the interpretive qualitative methods used in mental health research are ethnography, phenomenology and narrative approaches [ 32 , 36 ].

The ethnographic approach describes the everyday meaning of the phenomena within a societal and cultural context, for instance, the way phenomena or experience is contrasted within a community, or by collective members over time [ 32 ]. Alternatively, the phenomenological approach explores the claims and concerns of a subject with a speculative development of an interpretative account within their cultural and physical environments focusing on the lived experience [ 32 , 36 ].

Moreover, the critical qualitative approaches used in mental health research are predominantly emancipatory (for instance, socio-political traditions) and participatory action-based research. The emancipatory traditions recognise that knowledge is acquired through critical discourse and debate but are not seen as discovered by objective inquiry [ 32 ]. Alternatively, the participatory action based approach uses critical perspectives to engage key stakeholders as participants in the design and conduct of the research [ 32 ].

Some studies highlighted several reasons why qualitative methods are relevant to mental health research. In particular, qualitative methods are significant as they emphasise naturalistic inquiry and have a discovery-oriented approach [ 19 , 26 ]. Two studies suggested that qualitative methods are often relevant in the initial stages of research studies to understand specific issues such as behaviour, or symptoms of consumers of mental services [ 19 ]. Specifically, Palinkas [ 19 ] suggests that qualitative methods help to obtain initial pilot data, or when there is too little previous research or in the absence of a theory, such as provided in exploratory studies, or previously under-researched phenomena.

Three studies stressed that qualitative methods can help to better understand socially sensitive issues, such as exploring the solutions to overcome challenges in mental health clinical policies [ 19 , 28 , 44 ]. Consequently, Razafsha, Behforuzi [ 44 ] recommended that the natural holistic view of qualitative methods can help to understand the more recovery-oriented policy of mental health, rather than simply the treatment of symptoms. Similarly, the subjective experiences of consumers using qualitative approaches have been found useful to inform clinical policy development [ 28 ].

Sampling in mental health research

The theme explains the sampling approaches used in mental health research. The section also describes the methodological considerations when sampling participants for mental health research. The sub-themes emerging are explained in the following sections:

Sampling approaches (quantitative)

Some studies reviewed highlighted the sampling approaches previously used in mental health research [ 25 , 34 , 35 ]. Generally, all quantitative studies tend to use several probability sampling approaches, whilst qualitative studies used non-probability techniques. The quantitative mental health studies conducted at community and population level employ multi-stage sampling techniques usually involving systematic sampling, stratified and random sampling [ 25 , 34 ]. Similarly, quantitative studies that recruit consumers in the hospital setting employ consecutive sampling [ 35 ]. Two studies reviewed highlighted that the identification of consumers of mental health services for research is usually conducted by service providers. For instance, Korver, Quee [ 35 ] research used a consecutive sampling approach by identifying consumers through clinicians working in regional psychosis departments, or academic centres.

Sampling approaches (qualitative)

Seven studies suggested that the sampling procedures widely used in mental health research involving qualitative methods are non-probability techniques, which include purposive [ 19 , 28 , 32 , 42 , 46 ], snowballing [ 30 , 32 , 46 ] and theoretical sampling [ 31 , 32 ]. The purposive sampling identifies participants that possess relevant characteristics to answer a research question [ 28 ]. Purposive sampling can be used in a single case study, or for multiple cases. The purposive sampling used in mental health research is usually extreme, or deviant case sampling, criterion sampling, and maximum variation sampling [ 19 ]. Furthermore, it is advised when using purposive sampling in a multistage level study, that it should aim to begin with the broader picture to achieve variation, or dispersion, before moving to the more focused view that considers similarity, or central tendencies [ 42 ].

Two studies added that theoretical sampling involved sampling participants, situations and processes based on concepts on theoretical grounds and then using the findings to build theory, such as in a Grounded Theory study [ 31 , 32 ]. Some studies highlighted that snowball sampling is another strategy widely used in mental health research [ 30 , 32 , 46 ]. This is ascribed to the fact that people with mental illness are perceived as marginalised in research and practically hard-to-reach using conventional sampling [ 30 , 32 ]. Snowballing sampling involves asking the marginalised participants to recommend individuals who might have direct knowledge relevant to the study [ 30 , 32 , 46 ]. Although this approach is relevant, some studies advise the limited possibility of generalising the sample, because of the likelihood of selection bias [ 30 ].

Sampling consideration

Four studies in this section highlighted some of the sampling considerations in mental health research [ 30 , 31 , 32 , 46 ]. Generally, mental health research should consider the appropriateness and adequacy of sampling approach by applying attributes such as shared social, or cultural experiences, or shared concern related to the study [ 32 ], diversity and variety of participants [ 31 ], practical and organisational skills, as well as ethical and sensitivity issues [ 46 ]. Robinson [ 46 ] further suggested that sampling can be homogenous or heterogeneous depending on the research questions for the study. Achieving homogeneity in sampling should employ a variety of parameters, which include demographic, graphical, physical, psychological, or life history homogeneity [ 46 ]. Additionally, applying homogeneity in sampling can be influenced by theoretical and practical factors. Alternatively, some samples are intentionally selected based on heterogeneous factors [ 46 ].

Data collection in mental health research

This theme highlights the data collection methods used in mental health research. The theme is explained according to three sub-themes, which include approaches for collecting qualitative data, methodological considerations, as well as preparations for data collection. The sub-themes are as follows:

Approaches for collecting qualitative data

The studies reviewed recommended the approaches that are widely applied in collecting data in mental health research. The widely used qualitative data collection approaches in mental health research are focus group discussions (FGDs) [ 19 , 28 , 30 , 31 , 41 , 44 , 47 ], extended in-depth interviews [ 19 , 30 , 34 ], participant and non-participant observation [ 19 ], Delphi data collection, quasi-statistical techniques [ 19 ] and field notes [ 31 , 40 ]. Seven studies suggest that FGDs are widely used data collection approaches [ 19 , 28 , 30 , 31 , 41 , 44 , 47 ] because they are valuable in gathering information on consumers’ perspectives of services, especially regarding satisfaction, unmet/met service needs and the perceived impact of services [ 47 ]. Conversely, Ekblad and Baarnhielm [ 31 ] recommended that this approach is relevant to improve clinical understanding of the thoughts, emotions, meanings and attitudes towards mental health services.

Such data collection approaches are particularly relevant to consumers of mental health services, due to their low self-confidence and self-esteem [ 41 ]. The approach can help to understand specific terms, vocabulary, opinions and attitudes of consumers of mental health services, as well as their reasoning about personal distress and healing [ 31 ]. Similarly, the reliance on verbal rather than written communication helps to promote the participation of participants with serious and enduring mental health problems [ 31 , 41 ]. Although FGD has several important outcomes, there are some limitations that need critical consideration. Ekblad and Baarnhielm [ 31 ] for example suggest, that marginalised participants may not always feel free to talk about private issues regarding their condition at the group level mostly due to perceived stigma and group confidentiality.

Some studies reviewed recommended that attempting to capture comprehensive information and analysing group interactions in mental health research requires the research method to use field notes as a supplementary data source to help validate the FGDs [ 31 , 40 , 41 ]. The use of field notes in addition to FGDs essentially provides greater detail in the accounts of consumers’ subjective experiences. Furthermore, Montgomery and Bailey [ 40 ] suggest that field notes require observational sensitivity, and also require having specific content such as descriptive and interpretive data.

Three studies in this section suggested that in-depth interviews are used to collect data from consumers of mental health services [ 19 , 30 , 34 ]. This approach is particularly important to explore the behaviour, subjective experiences and psychological processes; opinions, and perceptions of mental health services. de Jong and Van Ommeren [ 30 ] recommend that in-depth interviews help to collect data on culturally marked disorders, their personal and interpersonal significance, patient and family explanatory models, individual and family coping styles, symptom symbols and protective mediators. Palinkas [ 19 ] also highlights that the structured narrative form of extended interviewing is the type of in-depth interview used in mental health research. This approach provides participants with the opportunity to describe the experience of living with an illness and seeking services that assist them.

Consideration for data collection

Six studies recommended consideration required in the data collection process [ 31 , 32 , 37 , 41 , 47 , 49 ]. Some studies highlighted that consumers of mental health services might refuse to participate in research due to several factors [ 37 ] like the severity of their illness, stigma and discrimination [ 41 ]. Subsequently, such issues are recommended to be addressed by building confidence and trust between the researcher and consumers [ 31 , 37 ]. This is a significant prerequisite, as it can sensitise and normalise the research process and aims with the participants prior to discussing their personal mental health issues. Similarly, some studies added that the researcher can gain the confidence of service providers who manage consumers of mental health services [ 41 , 47 ], seek ethical approval from the relevant committee(s) [ 41 , 47 ], meet and greet the consumers of mental health services before data collection, and arrange a mutually acceptable venue for the groups and possibly supply transport [ 41 ].

Two studies further suggested that the cultural and social differences of the participants need consideration [ 26 , 31 ]. These factors could influence the perception and interpretation of ethical issues in the research situation.

Additionally, two studies recommended the use of standardised assessment instruments for mental health research that involve quantitative data collection [ 33 , 49 ]. A recent survey suggested that measures to standardise the data collection approach can convert self-completion instruments to interviewer-completion instruments [ 49 ]. The interviewer can then read the items of the instruments to respondents and record their responses. The study further suggested the need to collect demographic and behavioural information about the participant(s).

Preparing for data collection

Eight studies highlighted the procedures involved in preparing for data collection in mental health research [ 25 , 30 , 33 , 34 , 35 , 39 , 41 , 49 ]. These studies suggest that the preparation process involve organising meetings of researchers, colleagues and representatives of the research population. The meeting of researchers generally involves training of interviewers about the overall design, objectives and research questions associated with the study. de Jong and Van Ommeren [ 30 ] recommended that preparation for the use of quantitative data encompasses translating and adapting instruments with the aim of achieving content, semantic, concept, criterion and technical equivalence.

Quality assurance procedures in mental health research

This section describes the quality assurance procedures used in mental health research. Quality assurance is explained according to three sub-themes: 1) seeking informed consent, 2) the procedure for ensuring quality assurance in a quantitative study and 3) the procedure for ensuring quality control in a qualitative study. The sub-themes are explained in the following content.

Seeking informed consent

The papers analysed for the integrative review suggested that the rights of participants to safeguard their integrity must always be respected, and so each potential subject must be adequately informed of the aims, methods, anticipated benefits and potential hazards of the study and any potential discomforts (see Table 3 ). Seven studies highlight that potential participants of mental health research must be consented to the study prior to data collection [ 25 , 26 , 33 , 35 , 37 , 39 , 47 ]. The consent process helps to assure participants of anonymity and confidentiality and further explain the research procedure to them. Baarnhielm and Ekblad [ 26 ] argue that the research should be guided by four basic moral values for medical ethics, autonomy, non-maleficence, beneficence, and justice. In particular, potential consumers of mental health services who may have severe conditions and unable to consent themselves are expected to have their consent signed by a respective family caregiver [ 37 ]. Latvala, Vuokila-Oikkonen [ 37 ] further suggested that researchers are responsible to agree on the criteria to determine the competency of potential participants in mental health research. The criteria are particularly relevant when potential participants have difficulties in understanding information due to their mental illness.

Procedure for ensuring quality control (quantitative)

Several studies highlighted procedures for ensuring quality control in mental health research (see Table 3 ). The quality control measures are used to achieve the highest reliability, validity and timeliness. Some studies demonstrate that ensuring quality control should consider factors such as pre-testing tools [ 25 , 49 ], minimising non-response rates [ 25 , 39 ] and monitoring of data collection processes [ 25 , 33 , 49 ].

Accordingly, two studies suggested that efforts should be made to re-approach participants who initially refuse to participate in the study. For instance, Liu, Huang [ 39 ] recommended that when a consumer of mental health services refuse to participate in a study (due to low self-esteem) when approached for the first time, a different interviewer can re-approach the same participant to see if they are more comfortable to participate after the first invitation. Three studies further recommend that monitoring data quality can be accomplished through “checks across individuals, completion status and checks across variables” [ 25 , 33 , 49 ]. For example, Alonso, Angermeyer [ 25 ] advocate that various checks are used to verify completion of the interview, and consistency across instruments against the standard procedure.

Procedure for ensuring quality control (qualitative)

Four studies highlighted the procedures for ensuring quality control of qualitative data in mental health research [ 19 , 32 , 37 , 46 ]. A further two studies suggested that the quality of qualitative research is governed by the principles of credibility, dependability, transferability, reflexivity, confirmability [ 19 , 32 ]. Some studies explain that the credibility or trustworthiness of qualitative research in mental health is determined by methodological and interpretive rigour of the phenomenon being investigated [ 32 , 37 ]. Consequently, Fossey, Harvey [ 32 ] propose that the methodological rigour for assessing the credibility of qualitative research are congruence, responsiveness or sensitivity to social context, appropriateness (importance and impact), adequacy and transparency. Similarly, interpretive rigour is classified as authenticity, coherence, reciprocity, typicality and permeability of the researcher’s intentions; including engagement and interpretation [ 32 ].

Robinson [ 46 ] explained that transparency (openness and honesty) is achieved if the research report explicitly addresses how the sampling, data collection, analysis, and presentation are met. In particular, efforts to address these methodological issues highlight the extent to which the criteria for quality profoundly interacts with standards for ethics. Similarly, responsiveness, or sensitivity, helps to situate or locate the study within a place, a time and a meaningful group [ 46 ]. The study should also consider the researcher’s background, location and connection to the study setting, particularly in the recruitment process. This is often described as role conflict or research bias.

In the interpretive phenomenon, coherence highlights the ability to select an appropriate sampling procedure that mutually matches the research aims, questions, data collection, analysis, as well as any theoretical concepts or frameworks [ 32 , 46 ]. Similarly, authenticity explains the appropriate representation of participants’ perspectives in the research process and the interpretation of results. Authenticity is maximised by providing evidence that participants are adequately represented in the interpretive process, or provided an opportunity to give feedback on the researcher’s interpretation [ 32 ]. Again, the contribution of the researcher’s perspective to the interpretation enhances permeability. Fossey, Harvey [ 32 ] further suggest that reflexive reporting, which distinguishes the participants’ voices from that of the researcher in the report, enhances the permeability of the researcher’s role and perspective.

One study highlighted the approaches used to ensure validity in qualitative research, which includes saturation, identification of deviant or non-confirmatory cases, member checking and coding by consensus. Saturation involves completeness in the research process, where all relevant data collection, codes and themes required to answer the phenomenon of inquiry are achieved; and no new data emerges [ 19 ]. Similarly, member checking is the process whereby participants or others who share similar characteristics review study findings to elaborate on confirming them [ 19 ]. The coding by consensus involves a collaborative approach to analysing the data. Ensuring regular meetings among coders to discuss procedures for assigning codes to segments of data and resolve differences in coding procedures, and by comparison of codes assigned on selected transcripts to calculate a percentage agreement or kappa measure of interrater reliability, are commonly applied [ 19 ].

Two studies recommend the need to acknowledge the importance of generalisability (transferability). This concept aims to provide sufficient information about the research setting, findings and interpretations for readers to appropriately determine the replicability of the findings from one context, or population to another, otherwise known as reliability in quantitative research [ 19 , 32 ]. Similarly, the researchers should employ reflexivity as a means of identifying and addressing potential biases in data collection and interpretation. Palinkas [ 19 ] suggests that such bias is associated with theoretical orientations; pre-conceived beliefs, assumptions, and demographic characteristics; and familiarity and experience with the methods and phenomenon. Another approach to enhance the rigour of analysis involves peer debriefing and support meetings held among team members which facilitate detailed auditing during data analysis [ 19 ].

The integrative review was conducted to synthesise evidence into recommended methodological considerations when conducting mental health research. The evidence from the review has been discussed according to five major themes: 1) mixed methods study in mental health research; 2) qualitative study in mental health research; 3) sampling in mental health research; 4) data collection in mental health research; and 5) quality assurance procedures in mental health research.

Mixed methods study in mental health research

The evidence suggests that mixed methods approach in mental health are generally categorised according to their function (rationale, objectives or purpose), structure and process [ 18 , 19 , 43 , 48 ]. The mixed methods study can be conducted for the purpose of achieving convergence, complementarity, expansion, development and sampling [ 18 , 19 , 43 ]. Researchers conducting mental health studies should understand the underlying functions or purpose of mixed methods. Similarly, mixed methods in mental health studies can be structured simultaneously (concurrent) and sequential [ 18 , 19 , 42 , 43 , 48 ]. More importantly, the process of combining qualitative and quantitative data can be achieved through merging or converging, connecting and embedding one data set within the other [ 18 , 19 , 42 , 43 , 48 ]. The evidence further recommends that researchers need to understand the stage of integrating the two sets of data and the rationale for doing so. This can inform researchers regarding the best stage and appropriate ways of combining the two components of data to adequately address the research question(s).

The evidence recommended some methodological consideration in the design of mixed methods projects in mental health [ 18 , 19 , 45 ]. These issues include establishing early collaboration, becoming familiar with the topic, sharing information on the topic, negotiating any emerging problems and seeking contributions from team members. The involvement of various expertise could ensure that methodological issues are clearly identified. However, addressing such issues midway, or late through the design can negatively affect the implementation [ 45 ]. Any robust discoveries can rarely be accommodated under the existing design. Therefore, the inclusion of various methodological expertise during inception can lead to a more robust mixed-methods design which maximises the contributions of team members. Whilst fundamental and philosophical differences in qualitative and quantitative methods may not be resolved, some workable solutions can be employed, particularly if challenges are viewed as philosophical rather than personal [ 45 ]. The cultural issues can be alleviated by understanding the concepts, norms and values of the setting, further to respecting and including perspectives of the various stakeholders.

The review findings suggest that qualitative methods are relevant when conducting mental health research. The qualitative methods are mostly used where there has been limited previous research and an absence of theoretical perspectives. The approach is also used to gather initial pilot data. More importantly, the qualitative methods are relevant when we want to understand sensitive issues, especially from consumers of mental health services, where the ‘lived experience is paramount [ 19 , 28 , 44 ]. Qualitative methods can help understand the experiences of consumers in the process of treatment, as well as their therapeutic relationship with mental health professionals. The experiences of consumers from qualitative data are particularly important in developing clinical policy [ 28 ]. The review findings find two paradigms of qualitative methods are used in mental health research. These paradigms are the interpretive and critical approach [ 32 ]. The interpretive qualitative method(s) include phenomenology, ethnography and narrative approaches [ 32 , 36 ]. Conversely, critical qualitative approaches are participatory action research and emancipatory approach. The review findings suggest that these approaches to qualitative methods need critical considerations, particularly when dealing with consumers of mental health services.

The review findings identified several sampling techniques used in mental health research. Quantitative studies, usually employ probability sampling, whilst qualitative studies use non-probability sampling [ 25 , 34 ]. The most common sampling techniques for quantitative studies are multi-stage sampling, which involves systematic, stratified, random sampling and consecutive sampling. In contrast, the predominant sampling approaches for qualitative studies are purposive [ 19 , 28 , 32 , 42 , 46 ], snowballing [ 30 , 32 , 46 ] and theoretical sampling [ 31 , 32 ].

The sampling of consumers of mental health services requires some important considerations. The sampling should consider the appropriateness and adequacy of the sampling approach, diversity and variety of consumers of services, attributes such as social, or cultural experiences, shared concerns related to the study, practical and organisational skills, as well as ethical and sensitivity issues are all relevant [ 31 , 32 , 46 ]. Sampling consumers of mental health services should also consider the homogeneity and heterogeneity of consumers. However, failure to address these considerations can present difficulty in sampling and subsequently result in selection and reporting bias in mental health research.

The evidence recommends several data collection approaches in collecting data in mental health research, including focus group discussion, extended in-depth interviews, observations, field notes, Delphi data collection and quasi-statistical techniques. The focus group discussions appear as an approach widely used to collect data from consumers of mental health services [ 19 , 28 , 30 , 31 , 41 , 44 , 47 ]. The focus group discussion appears to be a significant source of obtaining information. This approach promotes the participation of consumers with severe conditions, particularly at the group level interaction. Mental health researchers are encouraged to use this approach to collect data from consumers, in order to promote group level interaction. Additionally, field notes can be used to supplement information and to more deeply analyse the interactions of consumers of mental health services. Field notes are significant when wanting to gather detailed accounts about the subjective experiences of consumers of mental health services [ 40 ]. Field notes can help researchers to capture the gestures and opinions of consumers of mental health services which cannot be covered in the audio-tape recording. Particularly, the field note is relevant to complement the richness of information collected through focus group discussion from consumers of mental health services.

Furthermore, it was found that in-depth interviews can be used to explore specific mental health issues, particularly culturally marked disorders, their personal and interpersonal significance, patient and family explanatory models, individual and family coping styles, as well as symptom symbols and protective mediators [ 19 , 30 , 34 ]. The in-depth interviews are particularly relevant if the study is interested in the lived experiences of consumers without the contamination of others in a group situation. The in-depth interviews are relevant when consumers of mental health services are uncomfortable in disclosing their confidential information in front of others [ 31 ]. The lived experience in a phenomenological context preferably allows the consumer the opportunity to express themselves anonymously without any tacit coercion created by a group context.

The review findings recommend significant factors requiring consideration when collecting data in mental health research. These considerations include building confidence and trust between the researcher and consumers [ 31 , 37 ], gaining confidence of mental health professionals who manage consumers of mental health services, seeking ethical approval from the relevant committees, meeting consumers of services before data collection as well as arranging a mutually acceptable venue for the groups and providing transport services [ 41 , 47 ]. The evidence confirms that the identification of consumers of mental health services to participate in research can be facilitated by mental health professionals. Similarly, the cultural and social differences of the consumers of mental health services need consideration when collecting data from them [ 26 , 31 ].

Moreover, our review advocates that standardised assessment instruments can be used to collect data from consumers of mental health services, particularly in quantitative data. The self-completion instruments for collecting such information can be converted to interviewer-completion instruments [ 33 , 49 ]. The interviewer can read the questions to consumers of mental health services and record their responses. It is recommended that collecting data from consumers of mental health services requires significant preparation, such as training with co-investigators and representatives from consumers of mental health services [ 25 , 30 , 33 , 34 , 35 , 39 , 49 ]. The training helps interviewers and other investigators to understand the research project, particularly translating and adapting an instrument for the study setting with the aim to achieve content, semantic, concept, criteria and technical equivalence [ 30 ]. The evidence indicates that there is a need to adequately train interviewers when preparing for fieldwork to collect data from consumers of mental health services.

The evidence provides several approaches that can be employed to ensure quality assurance in mental health research involving quantitative methods. The quality assurance approach encompasses seeking informed consent from consumers of mental health services [ 26 , 37 ], pre-testing of tools [ 25 , 49 ], minimising non-response rates and monitoring of the data collection process [ 25 , 33 , 49 ]. The quality assurance process in mental health research primarily aims to achieve the highest reliability, validity and timeliness, to improve the quality of care provided. For instance, the informed consent exposes consumers of mental health services to the aim(s), methods, anticipated benefits and potential hazards and discomforts of participating in the study. Herein, consumers of mental health services who cannot respond to the inform consent process because of the severity of their illness can have it signed by their family caregivers. The implication is that researchers should determine which category of consumers of mental health services need family caregivers involved in the consent process [ 37 ].

The review findings advises that researchers should use pre-testing to evaluate the data collection procedure on a small scale and then to subsequently make any necessary changes [ 25 ]. The pre-testing aims to help the interviewers get acquainted with the procedures and to detect any potential problems [ 49 ]. The researchers can discuss the findings of the pre-testing and then further resolve any challenges that may arise prior to the actual field work being commenced. The non-response rates in mental health research can be minimised by re-approaching consumers of mental health services who initially refuse to participate in the study.

In addition, quality assurance for qualitative data can be ensured by applying the principles of credibility, dependability, transferability, reflexivity, confirmability [ 19 , 32 ]. It was found that the credibility of qualitative research in mental health is achieved through methodological and interpretive rigour [ 32 , 37 ]. The methodological rigour for assessing credibility relates to congruence, responsiveness or sensitivity to a social context, appropriateness, adequacy and transparency. By contrast, ensuring interpretive rigour is achieved through authenticity, coherence, reciprocity, typicality and permeability of researchers’ intentions, engagement and interpretation [ 32 , 46 ].

Strengths and limitations

The evidence has several strengths and limitations that require interpretation and explanation. Firstly, we employed a systematic approach involving five stages of problem identification, literature search, data evaluation, data synthesis and presentation of results [ 21 ]. Similarly, we searched six databases and developed a data extraction form to extract information. The rigorous process employed in this study, for instance, searching databases and data extraction forms, helped to capture comprehensive information on the subject.

The integrative review has several limitations largely related to the search words, language limitations, time period and appraisal of methodological quality of included papers. In particular, the differences in key terms and words concerning methodological issues in the context of mental health research across cultures and organisational contexts may possibly have missed some relevant articles pertaining to the study. Similarly, limiting included studies to only English language articles and those published from January 2000 to July 2018 could have missed useful articles published in other languages and those published prior to 2000. The review did not assess the methodological quality of included papers using a critical appraisal tool, however, the combination of clearly articulated search methods, consultation with the research librarian, and reviewing articles with methodological experts in mental health research helped to address the limitations.

The review identified several methodological issues that need critical attention when conducting mental health research. The evidence confirms that studies that addressed methodological considerations in conducting mental health research largely focuses on qualitative studies in a transcultural setting, in addition to lessons from multi-site surveys in mental health research. Specifically, the methodological issues related to the study design, sampling, data collection processes and quality assurance are critical to the research design chosen for any particular study. The review highlighted that researchers conducting mental health research can establish early collaboration, familiarise themselves with the topic, share information on the topic, negotiate to resolve any emerging problems and seek the contribution of clinical (or researcher) team members on the ground. In addition, the recruitment of consumers of mental health services should consider the appropriateness and adequacy of sampling approaches, diversity and variety of consumers of services, their social or cultural experiences, practical and organisational skills, as well as ethical and sensitivity issues.

The evidence confirms that in an attempt to effectively recruit and collect data from consumers of mental health services, there is the need to build confidence and trust between the researcher and consumers; and to gain the confidence of mental health service providers. Furthermore, seeking ethical approval from the relevant committee, meeting with consumers of services before data collection, arranging a mutually acceptable venue for the groups, and providing transport services, are all further important considerations. The review findings establish that researchers conducting mental health research should consider several quality assurance issues. Issues such as adequate training prior to data collection, seeking informed consent from consumers of mental health services, pre-testing of tools, minimising non-response rates and monitoring of the data collection process. More specifically, quality assurance for qualitative data can be achieved by applying the principles of credibility, dependability, transferability, reflexivity, confirmability.

Based on the findings from this review, it is recommended that mental health research should adequately consider the methodological issues regarding study design, sampling, data collection procedures and quality assurance issues to effectively conduct meaningful research.

Availability of data and materials

Not applicable

Abbreviations

focus group discussions

Joanna Briggs Institute

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

National Ethics Advisory Committee. Ethical guidelines for intervention studies: revised edition. Wellington (New Zealand): Ministry of Health. 2012.

Mann C. Observational research methods. Research design II: cohort, cross sectional, and case-control studies. Emerg Med J. 2003;20(1):54–60.

Article   CAS   Google Scholar  

DiPietro NA. Methods in epidemiology: observational study designs. Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy. 2010;30(10):973–84.

Article   Google Scholar  

Hong NQ, Pluyr P, Fabregues S, Bartlett G, Boardman F, Cargo M, et al. Mixed Methods Appraisal Tool (MMAT). Canada.: Intellectual Property Office, Canada; 2018.

Creswell JW, Creswell JD. Research design: qualitative, quantitative, and mixed methods approaches: sage publications; 2017.

Google Scholar  

Wisdom J, Creswell JW. Mixed methods: integrating quantitative and qualitative data collection and analysis while studying patient-centered medical home models. Rockville: Agency for Healthcare Research and Quality; 2013.

Bonita R, Beaglehole R, Kjellström T. Basic epidemiology: World Health Organization; 2006.

Centers for Disease Control Prevention [CDC]. Principles of epidemiology in public health practice: an introduction to applied epidemiology and biostatistics. Atlanta, GA: US Dept. of Health and Human Services, Centers for Disease Control and Prevention (CDC), Office of Workforce and Career Development; 2012.

Parab S, Bhalerao S. Study designs. International journal of Ayurveda research. 2010;1(2):128.

Yang W, Zilov A, Soewondo P, Bech OM, Sekkal F, Home PD. Observational studies: going beyond the boundaries of randomized controlled trials. Diabetes Res Clin Pract. 2010;88:S3–9.

Department of Family Medicine (McGill University). Mixed Methods Appraisal Tool (MMAT) – Version 2011 Canada: McGill University; 2011 [Available from: http://mixedmethodsappraisaltoolpublic.pbworks.com/w/file/fetch/84371689/MMAT%202011%20criteria%20and%20tutorial%202011-06-29updated2014.08.21.pdf .

Besen J, Gan DS. A critical evaluation of clinical research study designs. J Investig Dermatol. 2014;134.

Axelrod DA, Hayward R. Nonrandomized interventional study designs (quasi-experimental designs). Clinical research methods for surgeons: Springer; 2006. p. 63–76.

Thiese MS. Observational and interventional study design types; an overview. Biochemia medica: Biochemia medica. 2014;24(2):199–210.

Velengtas P, Mohr P, Messner DA. Making informed decisions: assessing the strengths and weaknesses of study designs and analytic methods for comparative effectiveness research. National Pharmaceutical Council 2012.

Guerrera F, Renaud S, Tabbò F, Filosso PL. How to design a randomized clinical trial: tips and tricks for conduct a successful study in thoracic disease domain. Journal of thoracic disease. 2017;9(8):2692.

Bhide A, Shah PS, Acharya G. A simplified guide to randomized controlled trials. Acta Obstet Gynecol Scand. 2018;97(4):380–7.

Palinkas L, Horwitz SM, Chamberlain P, Hurlburt MS, Landsverk J. Mixed-methods designs in mental health services research: a review. Psychiatr Serv. 2011;62(3):255–63.

Palinkas L. Qualitative and mixed methods in mental health services and implementation research. J Clin Child Adolesc Psychol. 2014;43(6):851–61.

World Health Organization [WHO]. Mental health: a state of well-being 2014 [Available from: http://www.who.int/features/factfiles/mental_health/en/ .

Whittemore R, Knafl K. The integrative review: updated methodology. J Adv Nurs. 2005;52(5):546–53.

Hopia H, Latvala E, Liimatainen L. Reviewing the methodology of an integrative review. Scand J Caring Sci. 2016;30(4):662–9.

Pearson A, White H, Bath-Hextall F, Apostolo J, Salmond S, Kirkpatrick P. Methodology for JBI mixed methods systematic reviews. The Joanna Briggs Institute Reviewers Manual. 2014;1:5–34.

Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.

Alonso J, Angermeyer MC, Bernert S, Bruffaerts R, Brugha TS, Bryson H, et al. Sampling and methods of the European study of the epidemiology of mental disorders (ESEMeD) project. Acta Psychiatr Scand Suppl. 2004;109(420):8–20.

Baarnhielm S, Ekblad S. Qualitative research, culture and ethics: a case discussion. Transcultural Psychiatry. 2002;39(4):469–83.

Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77–101.

Brown C, Lloyd K. Qualitative methods in psychiatric research. Adv Psychiatr Treat. 2001;7(5):350–6.

Davidsen AS. Phenomenological approaches in psychology and health sciences. Qual Res Psychol. 2013;10(3):318–39.

de Jong JT, Van Ommeren M. Toward a culture-informed epidemiology: combining qualitative and quantitative research in transcultural contexts. Transcultural Psychiatry. 2002;39(4):422–33.

Ekblad S, Baarnhielm S. Focus group interview research in transcultural psychiatry: reflections on research experiences. Transcultural Psychiatry. 2002;39(4):484–500.

Fossey E, Harvey C, McDermott F, Davidson L. Understanding and evaluating qualitative research. Aust N Z J Psychiatry. 2002;36(6):717–32.

Jacobi F, Wittchen H-U, Holting C, Sommer S, Lieb R, Hofler M, et al. Estimating the prevalence of mental and somatic disorders in the community: aims and methods of the German National Health Interview and examination survey. Int J Methods Psychiatr Res 2002;11(1):1–18.

Koch A, Vogel A, Holzmann M, Pfennig A, Salize HJ, Puschner B, et al. MEMENTA-‘Mental healthcare provision for adults with intellectual disability and a mental disorder’. A cross-sectional epidemiological multisite study assessing prevalence of psychiatric symptomatology, needs for care and quality of healthcare provision for adults with intellectual disability in Germany: a study protocol. BMJ Open. 2014;4(5):e004878.

Korver N, Quee PJ, Boos HB, Simons CJ, de Haan L, Investigators G. Genetic risk and outcome of psychosis (GROUP), a multi site longitudinal cohort study focused on gene–environment interaction: objectives, sample characteristics, recruitment and assessment methods. Int J Methods Psychiatr Res. 2012;21(3):205–21.

Larkin M, Watts S, Clifton E. Giving voice and making sense in interpretative phenomenological analysis. Qual Res Psychol. 2006;3(2):102–20.

Latvala E, Vuokila-Oikkonen P, Janhonen S. Videotaped recording as a method of participant observation in psychiatric nursing research. J Adv Nurs. 2000;31(5):1252–7.

Leese MN, White IR, Schene AH, Koeter MW, Ruggeri M, Gaite L. Reliability in multi-site psychiatric studies. Int J Methods Psychiatr Res. 2001;10(1):29–42.

Liu Z, Huang Y, Lv P, Zhang T, Wang H, Li Q, et al. The China mental health survey: II. Design and field procedures. Soc Psychiatry Psychiatr Epidemiol. 2016;51(11):1547–57.

Montgomery P, Bailey PH. Field notes and theoretical memos in grounded theory. West J Nurs Res. 2007;29(1):65–79.

Owen S. The practical, methodological and ethical dilemmas of conducting focus groups with vulnerable clients. J Adv Nurs. 2001;36(5):652–8.

Palinkas L, Horwitz SM, Green CA, Wisdom JP, Duan N, Hoagwood K. Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Adm Policy Ment Health Ment Health Serv Res. 2015;42(5):533–44.

Palinkas L, Aarons GA, Horwitz S, Chamberlain P, Hurlburt M, Landsverk J. Mixed method designs in implementation research. Adm Policy Ment Health Ment Health Serv Res. 2011;38(1):44–53.

Razafsha M, Behforuzi H, Azari H, Zhang Z, Wang KK, Kobeissy FH, et al. Qualitative versus quantitative methods in psychiatric research. Methods Mol Biol. 2012;829:49–62.

Robins CS, Ware NC, Dosreis S, Willging CE, Chung JY, Lewis-Fernández R. Dialogues on mixed-methods and mental health services research: anticipating challenges, building solutions. Psychiatr Serv. 2008;59(7):727–31.

Robinson OC. Sampling in interview-based qualitative research: a theoretical and practical guide. Qual Res Psychol. 2014;11(1):25–41.

Schilder K, Tomov T, Mladenova M, Mayeya J, Jenkins R, Gulbinat W, et al. The appropriateness and use of focus group methodology across international mental health communities. International Review of Psychiatry. 2004;16(1–2):24–30.

Schoonenboom J, Johnson RB. How to construct a mixed methods research DesignWie man ein mixed methods-Forschungs-design konstruiert. KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie. 2017;69(2):107–31.

Yin H, Phillips MR, Wardenaar KJ, Xu G, Ormel J, Tian H, et al. The Tianjin mental health survey (TJMHS): study rationale, design and methods. Int J Methods Psychiatr Res. 2017;26(3):09.

Download references

Acknowledgements

The authors wish to thank the University of Newcastle Graduate Research and the School of Nursing and Midwifery, for the Doctoral Scholarship offered to the lead author. The authors are also grateful for the support received from Ms. Debbie Booth, the Librarian for supporting the literature search.

Author information

Authors and affiliations.

School of Nursing and Midwifery, The University of Newcastle, Callaghan, Australia

Faculty of Health and Medicine, School Nursing and Midwifery, University of Newcastle, Callaghan, Australia

Anthony Paul O’Brien

Faculty of Business and Economics, Macquarie University, North Ryde, Australia

Rebecca Mitchell

You can also search for this author in PubMed   Google Scholar

Contributions

EB, APO’B, and RM conceptualized the study. EB conducted the data extraction, APO’B, and RM, conducted the second review of the extracted data. EB, working closely with APO’B and RM performed the content analysis and drafted the manuscript. EB, APO’B, and RM, reviewed and made inputs into the intellectual content and agreed on its submission for publication. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Eric Badu .

Ethics declarations

Ethics approval and consent to participate, consent for publication, competing interests.

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Additional file

Additional file 1:.

Data extraction form. (DOCX 18 kb)

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Cite this article.

Badu, E., O’Brien, A.P. & Mitchell, R. An integrative review on methodological considerations in mental health research – design, sampling, data collection procedure and quality assurance. Arch Public Health 77 , 37 (2019). https://doi.org/10.1186/s13690-019-0363-z

Download citation

Received : 13 November 2018

Accepted : 22 July 2019

Published : 10 October 2019

DOI : https://doi.org/10.1186/s13690-019-0363-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Mental health
  • Methodological approach
  • Mixed methods
  • Data collection

Archives of Public Health

ISSN: 2049-3258

descriptive research design about mental health

Change Password

Your password must have 6 characters or more:.

  • a lower case character, 
  • an upper case character, 
  • a special character 

Password Changed Successfully

Your password has been changed

Create your account

Forget yout password.

Enter your email address below and we will send you the reset instructions

If the address matches an existing account you will receive an email with instructions to reset your password

Forgot your Username?

Enter your email address below and we will send you your username

If the address matches an existing account you will receive an email with instructions to retrieve your username

Psychiatry Online

  • March 01, 2024 | VOL. 75, NO. 3 CURRENT ISSUE pp.203-304
  • February 01, 2024 | VOL. 75, NO. 2 pp.107-201
  • January 01, 2024 | VOL. 75, NO. 1 pp.1-71

The American Psychiatric Association (APA) has updated its Privacy Policy and Terms of Use , including with new information specifically addressed to individuals in the European Economic Area. As described in the Privacy Policy and Terms of Use, this website utilizes cookies, including for the purpose of offering an optimal online experience and services tailored to your preferences.

Please read the entire Privacy Policy and Terms of Use. By closing this message, browsing this website, continuing the navigation, or otherwise continuing to use the APA's websites, you confirm that you understand and accept the terms of the Privacy Policy and Terms of Use, including the utilization of cookies.

Mixed-Methods Designs in Mental Health Services Research: A Review

  • Lawrence A. Palinkas , Ph.D. ,
  • Sarah M. Horwitz , Ph.D. ,
  • Patricia Chamberlain , Ph.D. ,
  • Michael S. Hurlburt , Ph.D. , and
  • John Landsverk , Ph.D.

Search for more papers by this author

Despite increased calls for use of mixed-methods designs in mental health services research, how and why such methods are being used and whether there are any consistent patterns that might indicate a consensus about how such methods can and should be used are unclear.

Use of mixed methods was examined in 50 peer-reviewed journal articles found by searching PubMed Central and 60 National Institutes of Health (NIH)-funded projects found by searching the CRISP database over five years (2005–2009). Studies were coded for aims and the rationale, structure, function, and process for using mixed methods.

A notable increase was observed in articles published and grants funded over the study period. However, most did not provide an explicit rationale for using mixed methods, and 74% gave priority to use of quantitative methods. Mixed methods were used to accomplish five distinct types of study aims (assess needs for services, examine existing services, develop new or adapt existing services, evaluate services in randomized controlled trials, and examine service implementation), with three categories of rationale, seven structural arrangements based on timing and weighting of methods, five functions of mixed methods, and three ways of linking quantitative and qualitative data. Each study aim was associated with a specific pattern of use of mixed methods, and four common patterns were identified.

Conclusions:

These studies offer guidance for continued progress in integrating qualitative and quantitative methods in mental health services research consistent with efforts by NIH and other funding agencies to promote their use. ( Psychiatric Services 62:255–263, 2011)

In the past decade, mental health services researchers have increasingly used qualitative methods in combination with quantitative methods ( 1 , 2 ). This use of mixed methods has been partly driven by theoretical models that encourage assessment of consumer perspectives and of contextual influences on disparities in the delivery of mental health services and the dissemination and implementation of evidence-based practices ( 3 , 4 ). These models call for research designs that use quantitative and qualitative data collection and analysis for a better understanding of a research problem than might be possible with use of either methodological approach alone ( 5 , 6 ). Numerous typologies and guidelines for the use of mixed-methods designs exist in the fields of nursing ( 7 , 8 ), evaluation ( 9 , 10 ), public health ( 11 , 12 ), primary care ( 13 ), education ( 14 ), and the social and behavioral sciences ( 5 , 15 ).

As Robins and colleagues ( 1 ) have observed, however, there has been little guidance in mental health services research on how to blend quantitative and qualitative methods to build upon the strengths of their respective epistemologies. Such guidance has been limited by the lack of consensus on the criteria that might be used to evaluate the quality of such research ( 5 ). From a policy perspective, the impact of the efforts of the National Institute of Mental Health (NIMH) ( 3 , 4 ) and other institutes of the National Institutes of Health (NIH) and funding agencies in encouraging the use of mixed methods in mental health services research also remains poorly understood.

To address these issues, we examined the application of mixed-methods designs in a sample of mental health services research studies published in peer-reviewed journals and in NIMH-funded research projects over five years. Our aim was to determine how and why such methods were being used and whether there are any consistent patterns that might indicate a consensus among researchers as to how such methods can and should be used. This aim is viewed as an initial step toward the development of standards for effective uses of mixed methods in mental health services research and articulation of criteria for evaluating the quality and impact of this research.

We conducted a literature review of mental health services research publications over a five-year period (January 2005 to September 2009), using the PubMed Central database and the following search terms: mental health services, mixed methods, and qualitative methods. Data were taken from the full text of each research article. Articles identified as potential candidates for inclusion had to report empirical research and meet one of the following selection criteria: a study specifically identified as a mixed-methods study in the title or abstract or through keywords; a qualitative study conducted as part of a larger project, including a randomized controlled trial, that also included use of quantitative methods; or a study that “quantitized” qualitative data ( 16 ) or “qualitized” quantitative data ( 17 ). On the basis of criteria used by McKibbon and Gadd ( 18 ) and Cresswell and Plano Clark ( 5 ), the analysis had to be fairly substantial; for example, a simple descriptive analysis of baseline demographic characteristics of participants was not sufficient to be included as a mixed-methods study. Further, qualitative studies that were not clearly linked to quantitative studies or methods were excluded from our review.

Using the same criteria and search terms, we also reviewed the NIH CRISP database (Computer Retrieval of Information on Scientific Projects) of projects funded over the same five-year period. Projects were limited to R series (independent research awards), F series (predissertation research awards), and K series (career development awards) grants. Data were taken from only the project descriptions provided by the applicant and contained in the database.

Using typologies employed in other fields of inquiry ( 5 – 7 , 9 ), we next assessed the use of mixed methods in each study to determine the study aims, rationale, structure, function, and process. Study aims referred to the objectives of the overall project that included both quantitative and qualitative studies or methods. The rationale for using mixed methods included conceptual reasons, such as exploration and confirmation ( 5 ), breadth and depth of understanding ( 19 ), and inductive and deductive theoretical drive ( 20 ). Pragmatic reasons for using mixed methods, such as addressing the weaknesses of one method by use of the other, and suitability to address research questions were also examined. Assessment of the structure of the research design was based on Morse's ( 7 ) taxonomy, which gives emphasis to timing (for example, using methods in sequence [represented by a → symbol] versus using them simultaneously [represented by a + symbol]) and to weighting (for example, primary method [represented by capital letters such as QUAN] versus secondary method [represented in lowercase letters such as qual]).

Assessment of the function of mixed methods was based on whether the two methods were being used to answer the same question or to answer related questions and whether they were used to achieve convergence, complementarity, expansion, development, or sampling ( 9 ). Finally, the process or strategies for combining qualitative and quantitative methods were assessed with the typology proposed by Cresswell and Plano Clark ( 5 ): merging or converging the two methods by actually bringing them together in the analysis or interpretation phase, connecting the two methods by having one build upon the results obtained by the other, or embedding one data set within the other so that one type of method provides a supportive role for the other method.

Our search identified 50 articles and 67 NIH-funded research projects published or funded between 2005 and 2009 that met our criteria for analysis. Seven of the NIH projects were excluded from further review because of missing data on the use of mixed methods. Three of the publications were based on one of the NIH-funded projects, and two other publications were based on one funded project each. Any redundant aims or strategies for combining qualitative and quantitative methods identified in linked publications and projects were counted only once in our analysis.

A list of the 26 journals in which the articles were published and the journals' impact factors (IFs) is presented in Table 1 . One-fifth of the articles were published in Psychiatric Services . The 2008 IFs of the journals for which information was available ranged from .74 ( Psychiatric Rehabilitation Journal ) to 4.84 ( Journal of the American Academy of Child and Adolescent Psychiatry ). Twenty-one of the 50 articles (42%) had an IF of 2.0 or greater. Of the funded grants, three were predissertation research grants (F31s), 28 were career development awards (K01, K08, K23, K24, and K99), and 29 were independent research awards (R01, R03, R18, R21, R24, and R34).

Table 2 presents the year of publication for the 50 articles and the start date of the 60 funded projects. Sixteen of the projects funded during this period had a start date before 2005. The smaller numbers of publications and of projects in 2009 reflect the shorter period of observation (nine months) for that year. There was an exponential increase in the number of publications between 2005 and 2008, and the number of grants from 2005 to 2009 was more than twice that of the previous five-year period (2000–2004).

Table 3 summarizes for comparison the use of mixed-methods designs on the basis of study aims. Our analyses revealed the use of mixed methods to accomplish five distinct types of study aims and three categories of rationale. We further identified seven structural arrangements, five uses or functions of mixed methods, and three ways of linking quantitative and qualitative data together. Some papers and projects included more than one objective, structure, or function; hence the raw numbers may occasionally sum to more than the total number of studies examined. Twelve of the 50 articles presented qualitative data only but were part of larger studies that included the use of quantitative measures. Further, we identified four commonly used designs, with each design associated with a specific aim or set of aims ( Figure 1 ).

As shown in Table 3 , the largest number of publications and projects (41 of 110, 37%) used mixed methods in observational or quasi-experimental studies of existing services. Almost one-quarter (24%) used mixed methods to study the implementation and dissemination of evidence-based practices. Mixed methods were also used to develop evidence-based practices, treatment, and interventions (17%); to conduct randomized controlled trials of interventions (14%); or to assess the needs of populations for mental health services (14%). Six studies had more than one aim (for example, two studies conducted a needs assessment before developing new interventions, and two studies examined implementation of an evidence-based practice within the context of a randomized controlled trial examining the practice's effectiveness.

Mixed-methods rationale

Forty-one of the 60 project abstracts (68%) and 25 of the 50 published articles (50%) did not provide an explicit rationale for the use of mixed methods; consequently, the rationale was inferred from statements found in project objectives. Of the 25 published articles that did provide an explicit rationale, only 11 provided one or more citations to justify use of mixed methods. The most common reason (93% of all articles and projects) for using mixed methods was based on the specific objectives of the study (for example, qualitative methods were needed for exploration or depth of understanding or quantitative methods were needed to test hypotheses). In other instances, use of mixed methods was dictated by the nature of the data; studies that included a focus on variables related to values and beliefs, the process of service delivery, or the context in which services are delivered relied on qualitative methods to describe and examine these phenomena. In 9% of articles and projects, investigators specifically indicated that both methods were used so that the strengths of one method could offset the weaknesses of the other ( Table 3 ).

Mixed-methods structure

The majority (58%) of the publications and projects used the methods in sequence, with qualitative methods more often preceding quantitative methods. Quantitative methods were the primary or dominant method in 74% of the publications and projects reviewed, and in 16 studies, qualitative and quantitative methods were given equal weight. In seven of the published studies, qualitative analyses were conducted on one or two open-ended questions attached to a survey, and 17 of the 50 published studies (34%) provided no references justifying their procedures for qualitative data collection or analysis. Only one published study ( 21 ) provided a figure that illustrated the timing and weighting of qualitative and quantitative data collection and analysis, and none used terms like QUAN and qual to describe this structure.

In studies that aimed to assess needs for mental health services, examine existing services, or develop new services or adapt existing services to new populations, sequential designs were used two to four times more frequently than simultaneous designs. The latter type of design was more commonly used in randomized controlled trials and in implementation studies.

Mixed-methods functions

Our review of the publications and projects revealed five distinct functions of mixing methods ( Table 3 ). The first function was convergence, in which qualitative and quantitative methods were used sequentially or simultaneously to answer the same question, either through triangulation (that is, the simultaneous use of one type of data to validate or confirm conclusions reached from analysis of the other type of data) or transformation (that is, the sequential quantification of qualitative data or use of qualitative techniques to transform quantitative data). For instance, Griswold and colleagues ( 22 ) triangulated quantitative trends in functional and health outcomes of psychiatric emergency department patients with qualitative findings of perceived benefits of care management and the value of integrated medical and mental health care to determine whether both types of data provided support for the effectiveness of a care management intervention (QUAN + QUAL). Using the technique of concept mapping ( 23 ), Aarons and colleagues ( 24 ) collected qualitative data on factors likely to have an impact on implementation of evidence-based practices in public-sector mental health settings. These data were then entered in a software program that uses multidimensional scaling and hierarchical cluster analysis to generate a visual display of statement clusters (QUAL → quan).

A second function of integrating quantitative and qualitative methods was complementarity, in which each method was used to answer related questions for the purpose of evaluation or elaboration. This function was evident in a majority (65%) of the published studies and projects examined. In evaluative designs, quantitative data were used to evaluate outcomes, whereas qualitative data were used to evaluate process. For instance, Bearsley-Smith and colleagues ( 25 ) described the use of quantitative methods to investigate the impact on clinical care of implementing interpersonal psychotherapy for adolescents within a rural mental health service and the use of qualitative methods to record the process and challenges (that is, feasibility, acceptability, and sustainability) associated with implementation and evaluation (QUAN + qual). In elaborative designs, qualitative methods were used to provide depth of understanding and quantitative methods were used to provide breadth of understanding. For instance, in a longitudinal study of mental health consumer-run organizations, Janzen and colleagues ( 26 ) used a quantitative tracking log for breadth of information about system-level activities and outcomes and key informant interviews and focus groups for greater insight into the impacts of these activities (QUAL + quan).

A third function of integrating qualitative and quantitative methods was expansion, in which one method was used in sequence to answer questions raised by the other method. This function was evident in 24% of the published studies and projects examined. In each instance, qualitative data were used to explain findings from the analyses of quantitative data. Brunette and colleagues ( 27 ) interviewed key informants and conducted ethnographic observations of implementation efforts to understand why some agencies adhered to established principles for integrated dual disorders treatment and others did not (QUAN + qual).

A fourth function of mixed methods was development, in which qualitative methods were used sequentially to identify form and content of items to be used in a quantitative study (for example, survey questions), to create a conceptual framework for generating hypotheses to be tested by using quantitative methods, or to develop new interventions or adapt existing interventions to new populations (qual → QUAN). This function was used in 34% of the published studies and projects. Blasinsky and colleagues ( 28 ) used qualitative findings from site visits to develop quantitative rating scales to construct predictors of outcomes and sustainability of a collaborative care intervention for older adults who had major depressive disorder or dysthymia. Green and colleagues ( 29 ) used qualitative data to generate a theoretical model of how relationships with clinics and clinicians' approach affect quality of life and recovery from serious mental illness and then tested the model using questionnaire data and health-plan and interview-based data in a covariance structure model. Several of the research projects funded through the R34 mechanism (for example, MH074509-01, Kilbourne, principal investigator [PI]; MH078583-01, Druss, PI; and MH073087-01, Lewis-Fernandez, PI) used qualitative data obtained from focus groups of consumers and providers to develop or adapt interventions for clients with specific conditions (for example, bipolar disorder, chronic medical conditions, and depressive disorders) (qual − QUAN).

The final function of mixed methods was sampling, the sequential use of one method to identify a sample of participants for research that uses the other method. This technique was used in only 7% of all studies. One form of sampling was the sequential use of quantitative data to identify potential participants for a qualitative study (quan − QUAL). For instance, Aarons and Palinkas ( 30 ) purposefully sampled candidates for qualitative interviews who had the most positive or most negative views of an evidence-based practice on the basis of a Web-based quantitative survey. The other form of sampling used qualitative data to identify samples of participants for quantitative analysis (qual − QUAN). Woltmann and colleagues ( 31 ) created categories of low, medium, and high staff turnover on the basis of staff perceptions of relevance of turnover obtained from qualitative interviews and then quantitatively examined the relationship between these turnover categories and implementation outcomes (qual + QUAN).

Only six of the published studies and none of the project abstracts explicitly referred to the function of mixed methods by using terms such as triangulation (four published studies) or complementarity (two published studies). As expected, the development function was used in a majority (84%) of studies that aimed to develop new practices or adapt existing practices to new populations. A majority of observational and quasi-experimental studies of existing services (71%), randomized controlled trials (67%), implementation studies (65%), and needs assessment studies (60%) utilized mixed methods for the purposes of answering related questions in complementary fashion. The use of one set of methods to explain the results of a study using another set of methods appears to have been limited to implementation studies (46%), randomized controlled trial evaluations (40%), and studies of existing services (20%).

Process of mixing methods

The final characteristic of mixed-methods designs that we examined was the process of mixing the quantitative and qualitative methods. The largest percentage (47%) of articles and projects sought to connect the data sets ( Table 3 ). This occurs when the analysis of one data set leads to (and thereby connects to) the need for the other data set, such as when quantitative results lead to the subsequent collection and analysis of qualitative data (that is, expansion) or when qualitative results are used to build to the subsequent collection and analysis of quantitative data, (for example, development) ( 5 ). For instance, Frueh and colleagues ( 32 ) conducted focus groups to obtain information on the target population, their providers, and state-funded mental health systems that would enable the researchers to further adapt and improve a cognitive-behavioral therapy-based intervention for treatment of posttraumatic stress disorder before implementing it (qual → QUAN). This type of mixing was found in almost all of the studies with aims to develop new practices or adapt existing practices to new populations; it was also more likely to be found in needs assessment and studies of existing services than in randomized controlled trials or implementation studies.

Over one-third (37%) of the studies merged the knowledge gained from the quantitative and qualitative data, either during the interpretation phase when two sets of results that had been analyzed separately were brought together or during the analysis phase when one type of data was transformed into the other type by consolidating the data into new variables ( 5 ). This type of mixing was found in slightly less than half of the needs assessment, observational, and implementation studies. For instance, Lucksted and colleagues ( 33 ) reported that a qualitative analysis of responses to an open-ended postintervention question supported the quantitative findings of the benefits of a relapse prevention and wellness program (QUAN + qual).

The embedding of small qualitative or qualitative-quantitative studies within larger quantitative studies was observed in 35% of the published studies and projects reviewed and described as “nested designs” in six of the studies. This type of mixing was more commonly found in randomized controlled trials and in implementation studies, where qualitative studies of treatment or implementation process or context were embedded within larger quantitative studies of treatment or implementation outcome. For instance, to better understand the essential components of the patient-provider relationship in a public health setting, Sajatovic and colleagues ( 34 ) conducted a qualitative investigation of patients' attitudes toward a collaborative care model and how individuals with bipolar disorder perceive treatment adherence within the context of a randomized controlled trial evaluating a collaborative practice model (QUAN + qual).

In 20% of published studies, more than one process was evident. For instance, Proctor and colleagues ( 35 ) connected the data by generating frequencies and rankings of qualitative data on perceptions of competing psychosocial problems collected from a community sample of 49 clients with a history of depression. These data were then merged with quantitative measures of depression status obtained through administration of the Patient Health Questionnaire-9 to explore the relationship of depression severity to problem categories and ranks.

The results of our analysis indicate that there has been substantial progress in using mixed-methods designs in mental health services research in response to efforts by NIMH ( 2 , 3 ) and other funding agencies to promote their use. Evidence for this progress is found in the increasing number of research projects that use mixed methods. The number of projects with mixed-methods designs funded over the five-year study period was more than twice the number that began in the previous five-year period (2000–2004). Furthermore, a majority (52%) of these funded projects were predissertation or career development awards used by junior and midlevel investigators to acquire expertise in mixed-methods research.

We also observed a notable increase in the number of studies based on mixed-methods designs published each year during this five-year period. The number of published mental health services research studies with mixed-methods designs increased by 67% between 2005 and 2006, by 80% between 2006 and 2007, and by 155% between 2007 and 2008. Furthermore, 21 of the 50 published studies (42%) that we reviewed appeared in journals with 2008 IFs of 2.0 or higher, including ten articles published in Psychiatric Services; four articles appeared in a journal with an IF of 4.0 or higher. In contrast, McKibbon and Gadd ( 18 ) reported that only 11 of 37 (30%) mixed-methods studies of health services appeared in a journal with an IF of 2.0 or higher in the year 2000.

Despite this progress, however, our review also suggests that there is room for improvement in use of mixed-methods designs. Most studies did not make explicit or provide support for the reasons for choosing a mixed-methods design; rather, we were forced to infer the rationale based on statements explaining what the methods were used for. Researchers may have felt that such explicit statements were as unnecessary as statements explaining the rationale for using certain quantitative methods, such as analysis of variance or survival analysis. However, the absence of an explicit rationale may also reflect a lack of understanding or appreciation of mixed-methods designs or a decision to use them without necessarily integrating or “mixing” them ( 5 , 6 ).

Most studies failed to provide explicit descriptions of the design structure or function that used terminology found in the mixed-methods literature; use of such terminology is consistent with the general standards for high-quality mixed-methods research recommended by Cresswell and Plano Clark ( 5 ). Further, three-fourths of the 50 published studies reviewed assigned priority to the use of quantitative methods, seven of the studies performed qualitative analyses of one or two open-ended questions attached to a survey, and 17 of the studies provided no references justifying their procedures for qualitative data collection or analysis. This may reflect an underappreciation of qualitative methods, as Robins and colleagues ( 1 ) have argued, or it may reflect a greater need for quantitative methods at the present time.

Although it was beyond the scope of this review to determine whether each study used mixed methods in effective ways, we note that each study was subjected to rigorous peer review before being published or funded, and each was judged by this process to make a valuable contribution to the field of mental health services research. These studies also provide evidence of meaningful and sensible variations in mixed-methods approaches to achieving various kinds of study aims and offer some guidance for integrating quantitative and qualitative methods in mental health services research. For instance, the choice of a mixed-methods design appears to be dictated by the nature of the questions being asked by mental health services researchers. Qualitative methods were used to explore a phenomenon when there was little or no previous research or to examine that phenomenon in depth, whereas quantitative methods were used to confirm hypotheses or examine the generalizability of the phenomenon and its associated predictors.

A majority of studies aiming to develop new practices or adapt existing practices to new populations had the same structure (beginning with a small qualitative study before developing or adapting the practice that was to be evaluated by using quantitative methods, which was found in 84% of the studies and projects) and the same process (connecting the findings of one set of methods with those of another set, which was found in 90% of the studies and projects). These studies reflect a growing awareness of the need to incorporate the preferences and perspectives of both service consumers and providers to ensure that new practices will be acceptable as well as feasible ( 32 , 36 – 39 ).

Studies of existing services also tended to be sequential in structure, with qualitative methods used to elaborate or explain the findings of quantitative studies. In the majority of these studies, the process of mixing methods involved either merging two sets of data to achieve convergence or connecting them to achieve expansion ( 5 ). A similar pattern was observed in studies that aimed to explore issues related to the needs for mental health services or provide more depth to our understanding of those needs. Such studies also appeared more likely to transform or “quantitize” qualitative data ( 24 , 35 ).

Randomized controlled trials and studies of implementation also shared similar patterns in use of mixed methods, including simultaneous use of both methods to achieve complementarity by embedding a qualitative or qualitative-quantitative study within a larger quantitative study, such as a randomized controlled trial. In the randomized controlled trials, qualitative methods were usually used to evaluate the process of providing the practice or intervention, whereas quantitative methods were used to evaluate the outcomes ( 25 , 40 ). In implementation research studies, qualitative methods were used to explore or provide depth to understanding barriers and facilitators of intervention implementation, whereas quantitative methods were used to confirm hypotheses and provide breadth to understanding by assessing the generalizability of findings ( 41 , 42 ).

The choice of mixed-methods designs was also dictated by how the individual questions being addressed by each method were related to one another. Studies that used different types of data to answer the same question reflected the function of convergence in a simultaneous structure, where data were merged for the purpose of triangulation, or a sequential structure, where qualitative data were transformed into quantitative data. Studies that used different types of data to answer related questions reflected the function of complementarity, in which quantitative methods were used to measure outcomes, describe content (for example, fidelity of services used and the nature of the mental health problem), and provide breadth (generalizability) of understanding, whereas qualitative methods were used to evaluate the process of service delivery ( 43 – 45 ), describe context (for example, setting) ( 26 , 34 , 46 ), describe consumer values or attitudes ( 35 , 42 , 47 ), and provide depth (meaning) of understanding ( 28 , 48 ) in a simultaneous structure and embedded data process. Expansion, development, and sampling were also used to provide answers to related questions that could not be answered by one method alone, usually in a sequential structure in which data sets were merged or connected together ( 24 , 30 , 37 ).

Finally, the choice of design appears to be based on the strengths of one method relative to the weaknesses of the other. For instance, expansion was used to explain findings based on quantitative data with qualitative data because explanation was not possible with the quantitative methods alone ( 25 , 27 , 40 ). In convergence, both sets of methods were used to confirm or validate one another, especially in instances where limited samples precluded testing of hypotheses with sufficient statistical power ( 30 , 49 ) and where limitations to qualitative data collection raised concerns about objectivity and transferability of results. In studies developing new methods, conceptual models, and interventions, qualitative methods also served to enhance quantitative analysis by laying the groundwork essential for more valid measurement and theory and more effective, usable, and sustainable interventions ( 37 ). Sampling also worked to enhance validity by using qualitative methods to enhance quantitative methods by developing targeted comparisons or by using quantitative methods to enhance qualitative methods by establishing criteria for purposeful sampling ( 36 ).

In summary, the choice of a mixed-methods design appears to be associated with three considerations: the nature of the question being asked (inductive-exploratory or deductive-confirmatory), how the questions being addressed by each method are related to one another, and the strengths of each method relative to the weaknesses of the other.

Caution should be exercised in interpreting these findings given limitations in our study design and analysis. Despite our efforts to be comprehensive in the search process and to select studies and projects on the basis of criteria with face validity, we undoubtedly excluded several articles or projects that used mixed methods. For example, we may have excluded mixed-methods projects listed in the CRISP database that did not specify use of qualitative or mixed methods in the abstracts. We may have also excluded published articles with qualitative data that were part of larger, primarily quantitative studies if the articles did not reference the larger studies, or we may have excluded articles not listed in PubMed Central. In the absence of explicit information, we were often forced to infer the structure, rationale, and function of the design based on statements contained in the available material. Similarly, the CRISP abstracts describe only what the investigators proposed to do with mixed methods and do not indicate what was actually done. Our use of existing typologies of structure, function, and process were intended to serve as a starting point in our analysis rather than an attempt to “pigeon-hole” each study into a specific typology. Our assessment of the progress made in the application of mixed-methods designs in response to calls for their use by funding agencies did not include indicators of whether these efforts had produced more useful, incisive, or insightful knowledge for the purpose of addressing mental health services questions and problems. Such an assessment would require comparisons with the products of studies based on monomethod designs, which was beyond the scope of this study.

Finally, it should be noted that the typology of mixed-methods use does not represent a set of standards for using mixed methods per se but is an important first step toward the development of such standards. Typologies by themselves do not explain why a particular method should be used and how to use a method appropriately. However, as Teddlie and Tashakkori ( 6 ) observed, there are five reasons or benefits to developing such a typology: typologies help to provide the field with an organizational structure, they provide examples of research designs that are clearly distinct from either qualitative or quantitative research designs, they help to establish a common language for the field, they help researchers decide how to proceed when designing their studies, and they are useful as a pedagogical tool. A consensus conference or workshop bringing together experts in mixed methods and mental health services research to evaluate the empirically generated typology found in current patterns of mixed-methods use would appear to be the next logical step in developing a set of standards. Such standards would also be required to adhere to the epistemological foundations of each method when used separately (for example, whether appropriate considerations are made to ensure the generalizability of quantitative results or theoretical saturation of qualitative data and whether each method is appropriately matched to the inductive or deductive theoretical drive of the study) and when combined (for example, whether the knowledge gained when using the two methods together is more insightful and of greater value than the knowledge gained when using them separately).

Conclusions

Despite the limitations described above, the findings suggest an increasing use of mixed-methods designs to address changing priorities in mental health services research and a consensus as to how such methods should be applied. The lack of explicit statements explaining the rationale for using mixed methods and the evident priority assigned to quantitative methods suggest that there is room for improvement. However, these studies appear to utilize a common set of designs and provide guidance for using mixed methods, with varying approaches based on the nature of the question being asked (exploratory or confirmatory), how questions being addressed by each method are related to one another, and the strengths of each method relative to the weaknesses of the other.

Acknowledgments and disclosures

This study was funded through NIMH grant P50-MH50313-07.

The authors report no competing interests.

1 Robins CS , Ware NC , dosReis S , et al. : Dialogues on mixed methods and mental health services research: anticipating challenges, building solutions . Psychiatric Services 59:727–731, 2008 Link ,  Google Scholar

2 Hopper K : Qualitative and quantitative research: two cultures . Psychiatric Services 59:711, 2008 Link ,  Google Scholar

3 Hoagwood K , Jensen PS , Petti T , et al. : Outcomes of mental health care for children and adolescents: I. a comprehensive conceptual model . Journal of the American Academy of Child and Adolescent Psychiatry 35:1055–1063, 1996 Crossref , Medline ,  Google Scholar

4 Hohmann AA : A contextual model for clinical mental health effectiveness research . Mental Health Services Research 1:83–91, 1999 Crossref ,  Google Scholar

5 Cresswell JW , Plano Clark VL : Designing and Conducting Mixed Method Research . Thousand Oaks, Calif, Sage, 2007 Google Scholar

6 Teddlie C , Tashakkori A : Major issues and controversies in the use of mixed methods in the social and behavioral sciences; in Handbook of Mixed Methods in the Social and Behavioral Sciences . Edited by Tashakkori ATeddlie C Thousand Oaks, Calif, Sage, 2003 Google Scholar

7 Morse JM : Approaches to qualitative-quantitative methodological triangulation . Nursing Research 40:120–123, 1991 Crossref , Medline ,  Google Scholar

8 Sandelowski M : Combining qualitative and quantitative sampling, data collection, and analysis techniques in mixed method studies . Research in Nursing and Health 23:246–255, 2000 Crossref , Medline ,  Google Scholar

9 Greene JC , Caracelli VJ , Graham WF : Toward a conceptual framework for mixed method evaluation designs . Educational Evaluation and Policy Analysis 11:255–274, 1989 Crossref ,  Google Scholar

10 Patton MQ : Qualitative Evaluation and Research Methods , 3rd ed. Newbury Park, Calif, Sage, 2002 Google Scholar

11 Morgan DL : Practical strategies for combining qualitative and quantitative methods: applications to health research . Qualitative Health Research 8:262–276, 1998 Crossref ,  Google Scholar

12 Steckler A , McLeroy KR , Goodman RM , et al. : Toward integrating qualitative and quantitative methods: an introduction . Health Education Quarterly 19:1–8, 1992 Crossref , Medline ,  Google Scholar

13 Cresswell JW , Fetters MD , Ivankova NV : Designing a mixed methods study in primary care . Annals of Family Medicine 2:7–12, 2004 Crossref , Medline ,  Google Scholar

14 Cresswell JW : Mixed method research: introduction and application; in Handbook of Educational Policy . Edited by Cizek GJ San Diego, Academic Press, 1999 Crossref ,  Google Scholar

15 Waszak C , Sines MC : Mixed methods in psychological research; in Handbook of Mixed Methods in the Social and Behavioral Sciences . Edited by Tashakkori ATeddlie C Thousand Oaks, Calif, Sage 2003 Google Scholar

16 Miles MB , Huberman AM : Qualitative Data Analysis: An Expanded Sourcebook , 2nd ed. Thousand Oaks, Calif, Sage, 1994 Google Scholar

17 Tashakkori A , Teddlie C : Mixed Methodology: Combining the Qualitative and Quantitative Approaches . Thousand Oaks, Calif, Sage, 1998 Google Scholar

10.1186/1472-6947-4-11 Crossref , Medline ,  Google Scholar

19 Miller WL , Crabtree BF Clinical research; in Handbook of Qualitative Research , 2nd ed. Edited by Denzin NKLincoln YS Thousand Oaks, Calif, Sage, 2001 Google Scholar

20 Morse JM Principles of mixed methods and multimethod research design; in Handbook of Mixed Methods in the Social and Behavioral Sciences . Edited by , Tashakkori A , Teddlie C Thousand Oaks, Calif, Sage, 2003 Google Scholar

10.1186/1472-6963-8-156 Crossref , Medline ,  Google Scholar

22 Griswold KS , Zayas LE , Pastore PA , et al. : Primary care after psychiatric crisis: a qualitative analysis . Annals of Family Medicine 6:38–43, 2008 Crossref , Medline ,  Google Scholar

23 Trochim WM : An introduction to concept mapping for planning and evaluation . Evaluation and Program Planning 12:1–16, 1989 Crossref ,  Google Scholar

24 Aarons GA , Wells R , Zagursky K , et al. : Advancing a conceptual model of evidence-based practice implementation in child welfare . American Journal of Public Health 99:2087–2095, 2009 Crossref , Medline ,  Google Scholar

10.1186/1471-244X-7-53 Crossref ,  Google Scholar

26 Janzen R , Nelson G , Hausfather N , et al. : Capturing system level activities and impacts of mental health consumer-run organizations . American Journal of Community Health 39:287–299, 2007 Google Scholar

27 Brunette MF , Asher D , Whitley R , et al. : Implementation of integrated dual disorders treatment: a qualitative analysis of facilitators and barriers . Psychiatric Services 59:989–995, 2008 Link ,  Google Scholar

28 Blasinsky M , Goldman HH , Unützer J : Project IMPACT: a report on barriers and facilitators to sustainability . Administration and Policy in Mental Health and Mental Health Services 33:718–729, 2006 Crossref , Medline ,  Google Scholar

29 Green CA , Polen MR , Janoff SL , et al. : Understanding how clinician-patient relationships and relational continuity of care affect recovery from serious mental illness: STARS Study results . Psychiatric Rehabilitation Journal 32:9–22, 2008 Crossref , Medline ,  Google Scholar

30 Aarons GA , Palinkas LA : Implementation of evidence-based practice in child welfare: service provider perspectives . Administration and Policy in Mental Health and Mental Health Services Research 34:411–419, 2007 Crossref , Medline ,  Google Scholar

31 Woltmann EM , Whitley R , McHugo GJ , et al. : The role of staff turnover in the implementation of evidence-based practices in health care . Psychiatric Services 59:732–737, 2008 Link ,  Google Scholar

32 Frueh BC , Cusack KJ , Grubaugh AL , et al. : Clinicians' perspectives on cognitive-behavioral treatment for PTSD among persons with severe mental illness . Psychiatric Services 57:1027–1031, 2006 Link ,  Google Scholar

33 Lucksted A , McNulty K , Brayboy L , et al. : Initial evaluation of the Peer-to-Peer Program . Psychiatric Services 60:250–253, 2009 Link ,  Google Scholar

34 Sajatovic M , Davies M , Bauer MS , et al. : Attitudes regarding the collaborative practice model and treatment adherence among individuals with bipolar disorder . Comprehensive Psychiatry 46:272–277, 2005 Crossref , Medline ,  Google Scholar

35 Proctor EK , Hascke L , Morrow-Howell N , et al. : Perceptions about competing psychosocial problems and treatment priorities among older adults with depression . Psychiatric Services 59:670–675, 2008 Link ,  Google Scholar

36 Woolfson R , Woolfson L , Mooney L , et al. : Young people's views of mental health education in secondary schools: a Scottish study . Child: Care, Health and Development 35:790–798, 2009 Crossref , Medline ,  Google Scholar

37 Proctor EK , Knudsen KL , Fedoravicius N , et al. : Implementation of evidence-based practice in community behavioral health: agency director perspectives . Administration and Policy in Mental Health and Mental Health Services Research 34:479–488, 2007 Crossref , Medline ,  Google Scholar

38 Institute of Medicine : Crossing the Quality Chasm: A New Health System for the 21st Century . Washington, DC, National Academies Press, 2000 Google Scholar

39 Mental Health : A Report of the Surgeon General . Rockville, Md, US Department of Health and Human Services, US Public Health Service, 1999 Google Scholar

10.1186/1472-6963-8-274 Crossref , Medline ,  Google Scholar

41 Gioia D , Dziadosz G : Adoption of evidence-based practices in community mental health: a mixed method study of practitioner experience . Community Mental Health Journal 44:347–357, 2008 Crossref , Medline ,  Google Scholar

42 Ostler T , Haight W , Black J , et al. : Case series: mental health needs and perspectives of rural children raised by parents who abuse methamphetamine . Journal of the American Academy of Child and Adolescent Psychiatry 46:500–507, 2007 Crossref , Medline ,  Google Scholar

10.1186/1748-3-14 Crossref , Medline ,  Google Scholar

10.1186/1472-6963-7-117 Crossref , Medline ,  Google Scholar

45 Young AT , Green CA , Estroff SE : New endeavors, risk taking, and personal growth in the recovery process: findings from the STARS study . Psychiatric Services 59:1430–1436, 2008 Link ,  Google Scholar

46 Sharkey S , MacIver S , Cameron D , et al. : An exploration of factors affecting the implementation of a randomized controlled trial of a transitional discharge model for people with serious mental illness . Journal of Psychiatric and Mental Health Nursing 12:51–56, 2005 Crossref , Medline ,  Google Scholar

47 Lee BR , Munson MR , Ware NR , et al. : Experiences of and attitudes toward mental health services among older youths in foster care . Psychiatric Services 57:487–492, 2006 Link ,  Google Scholar

48 Becker D , Whitley R , Bailey EL , et al. : Long-term employment trajectories among participants with severe mental illness in supported employment . Psychiatric Services 58:922–928, 2007 Link ,  Google Scholar

49 Wetherell JL , Ayers CR , Sorrell JT , et al. : Modular psychotherapy for anxiety in older primary care patients . American Journal of Geriatric Psychiatry 17:483–492, 2009 Crossref , Medline ,  Google Scholar

Figures and Tables

Figure 1 Common mixed-methods designs used in mental health services research

Table 1 Journals in which the 50 articles reviewed were published, with number published and 2008 impact factor

Table 2 Year of publication or of project initiation of articles and projects reviewed

Table 3 Characteristics of 50 published studies and 60 funded projects that used mixed-methods designs, by study aims

  • A multi- and mixed-method adaptation study of a patient-centered perioperative mental health intervention bundle 27 October 2023 | BMC Health Services Research, Vol. 23, No. 1
  • Physician Assistant Student Attitudes About People With Serious Mental Illness 21 November 2023 | Journal of Physician Assistant Education, Vol. 66
  • Educators’ Perspectives on Training Mechanisms That Facilitate Evidence-Based Practice Use for Autistic Students in General Education Settings: A Mixed-Methods Analysis 2 July 2023 | Teacher Education and Special Education: The Journal of the Teacher Education Division of the Council for Exceptional Children, Vol. 46, No. 4
  • Community-led identification of mental health support, challenges, and needs among Ethiopian immigrants to the U.S.: opportunities for partnership with faith communities 15 January 2024 | Mental Health, Religion & Culture, Vol. 26, No. 9
  • Social network and mental health of Chinese immigrants in affordable senior housing during the COVID-19 pandemic: a mixed-methods study 22 May 2023 | Aging & Mental Health, Vol. 27, No. 10
  • Incazelo nomlando oqukethwe emagameni aqanjwe abesifazane abashade ngaphambi konyaka we-1990 esigodini sakaGcaliphiwe eMaphephetheni 22 December 2023 | South African Journal of African Languages, Vol. 43, No. 3
  • Implementation Science and Practice-Oriented Research: Convergence and Complementarity 30 August 2023 | Administration and Policy in Mental Health and Mental Health Services Research, Vol. 27
  • Adapting to Unprecedented Times: Community Clinician Modifications to Parent–Child Interaction Therapy During COVID-19 11 August 2023 | Evidence-Based Practice in Child and Adolescent Mental Health, Vol. 8, No. 3
  • Evaluating the validity of depression-related stigma measurement among diabetes and hypertension patients receiving depression care in Malawi: A mixed-methods analysis 17 May 2023 | PLOS Global Public Health, Vol. 3, No. 5
  • Potential advantages of combining randomized controlled trials with qualitative research in mood and anxiety disorders - A systematic review Journal of Affective Disorders, Vol. 325
  • Mental Health Therapist Perspectives on the Role of Executive Functioning in Children’s Mental Health Services 10 January 2022 | Evidence-Based Practice in Child and Adolescent Mental Health, Vol. 8, No. 1
  • Therapist and supervisor perspectives about two train-the-trainer implementation strategies in schools: A qualitative study 3 August 2023 | Implementation Research and Practice, Vol. 4
  • Efficacy of Therapist Guided Internet Based Cognitive Behavioural Therapy for Depression: A Qualitative Exploration of Therapists and Clients Experiences 31 December 2022 | Journal of Professional & Applied Psychology, Vol. 3, No. 4
  • Prevalence of Research Designs and Efforts at Integration in Mixed Methods Research: A Systematic Review 31 December 2022 | International Journal of Multiple Research Approaches, Vol. 14, No. 3
  • The measurement-based care to opioid treatment programs project (MBC2OTP): a study protocol using rapid assessment procedure informed clinical ethnography 19 August 2022 | Addiction Science & Clinical Practice, Vol. 17, No. 1
  • Barbershops as a setting for supporting men's mental health during the COVID-19 pandemic: a qualitative study from the UK 27 June 2022 | BJPsych Open, Vol. 8, No. 4
  • A mixed methods study of provider factors in buprenorphine treatment retention International Journal of Drug Policy, Vol. 105
  • Evaluation of a systems-level technical assistance program to support youth with complex behavioral health needs Evaluation and Program Planning, Vol. 92
  • Barriers to students opting-in to universities notifying emergency contacts when serious mental health concerns emerge: A UK mixed methods analysis of policy preferences Journal of Affective Disorders Reports, Vol. 7
  • Development of an Online Resource for People Bereaved by Suicide: A Mixed-Method User-Centered Study Protocol 21 December 2021 | Frontiers in Psychiatry, Vol. 12
  • Protocol for a hybrid type 2 cluster randomized trial of trauma-focused cognitive behavioral therapy and a pragmatic individual-level implementation strategy 7 January 2021 | Implementation Science, Vol. 16, No. 1
  • Understanding adaptations in the Veteran Health Administration’s Transitions Nurse Program: refining methodology and pragmatic implications for scale-up 13 July 2021 | Implementation Science, Vol. 16, No. 1
  • Defining effective care coordination for mental health referrals of refugee populations in the United States 19 November 2018 | Ethnicity & Health, Vol. 26, No. 5
  • A Mixed-method Evaluation of the Behavioral Health Integration and Complex Care Initiative Using the Consolidated Framework for Implementation Research 13 May 2021 | Medical Care, Vol. 59, No. 7
  • Parent Training for Youth with Autism Served in Community Settings: A Mixed-Methods Investigation Within a Community Mental Health System 2 September 2020 | Journal of Autism and Developmental Disorders, Vol. 51, No. 6
  • Client, clinician, and administrator factors associated with the successful acceptance of a telehealth comprehensive recovery service: A mixed methods study Psychiatry Research, Vol. 300
  • “Don’t … Break Down on Tuesday Because the Mental Health Services are Only in Town on Thursday”: A Qualitative Study of Service Provision Related Barriers to, and Facilitators of Farmers’ Mental Health Help-Seeking 15 September 2020 | Administration and Policy in Mental Health and Mental Health Services Research, Vol. 48, No. 3
  • Social media and community-oriented policing: examining the organizational image construction of municipal police on Twitter and Facebook 9 November 2020 | Police Practice and Research, Vol. 22, No. 1
  • The ‘shift reflection’ model of group reflective practice: a pilot study in an acute mental health setting Mental Health Practice, Vol. 24, No. 1
  • Challenges Experienced by Behavioral Health Organizations in New York Resulting from COVID-19: A Qualitative Analysis 23 October 2020 | Community Mental Health Journal, Vol. 57, No. 1
  • Incorporating telehealth into health service psychology training: A mixed-method study of student perspectives 24 February 2021 | DIGITAL HEALTH, Vol. 7
  • An eHealth Intervention for Promoting COVID-19 Knowledge and Protective Behaviors and Reducing Pandemic Distress Among Sexual and Gender Minorities: Protocol for a Randomized Controlled Trial (#SafeHandsSafeHearts) 10 December 2021 | JMIR Research Protocols, Vol. 10, No. 12
  • Promotion of mental health in young adults via mobile phone app: study protocol of the ECoWeB (emotional competence for well-being in Young adults) cohort multiple randomised trials 22 September 2020 | BMC Psychiatry, Vol. 20, No. 1
  • Adaption and pilot implementation of an autism executive functioning intervention in children’s mental health services: a mixed-methods study protocol 27 April 2020 | Pilot and Feasibility Studies, Vol. 6, No. 1
  • Improving the implementation and sustainment of evidence-based practices in community mental health organizations: a study protocol for a matched-pair cluster randomized pilot study of the Collaborative Organizational Approach to Selecting and Tailoring Implementation Strategies (COAST-IS) 25 February 2020 | Implementation Science Communications, Vol. 1, No. 1
  • Using mixed methods in health services research: A review of the literature and case study 21 September 2020 | Journal of Health Services Research & Policy, Vol. 4
  • Healthcare attendance styles among long-term unemployed people with substance-related and mood disorders Public Health, Vol. 186
  • Mixed-Methods-Studien in der Gesundheitsförderung. Ergebnisse eines systematischen Reviews deutschsprachiger Publikationen Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen, Vol. 153-154
  • Mixed method study of workforce turnover and evidence-based treatment implementation in community behavioral health care settings Child Abuse & Neglect, Vol. 102
  • Mixing Beyond Measure: Integrating Methods in a Hybrid Effectiveness–Implementation Study of Operating Room to Intensive Care Unit Handoffs 4 May 2019 | Journal of Mixed Methods Research, Vol. 14, No. 2
  • The search for the ejecting chair: a mixed-methods analysis of tool use in a sedentary behavior intervention 25 November 2018 | Translational Behavioral Medicine, Vol. 10, No. 1
  • SIPsmartER delivered through rural, local health districts: adoption and implementation outcomes 18 September 2019 | BMC Public Health, Vol. 19, No. 1
  • An integrative review on methodological considerations in mental health research – design, sampling, data collection procedure and quality assurance 10 October 2019 | Archives of Public Health, Vol. 77, No. 1
  • Five Challenges in the Design and Conduct of IS Trials for HIV Prevention and Treatment JAIDS Journal of Acquired Immune Deficiency Syndromes, Vol. 82, No. 3
  • Mental health recovery narratives: their impact on service users and other stakeholder groups Mental Health and Social Inclusion, Vol. 23, No. 4
  • A Mixed Methods Study of Organizational Readiness for Change and Leadership During a Training Initiative Within Community Mental Health Clinics 19 June 2019 | Administration and Policy in Mental Health and Mental Health Services Research, Vol. 46, No. 5
  • Associations Among Job Role, Training Type, and Staff Turnover in a Large-Scale Implementation Initiative 3 January 2019 | The Journal of Behavioral Health Services & Research, Vol. 46, No. 3
  • American Journal of Community Psychology
  • Internet Interventions, Vol. 18
  • Journal of Public Child Welfare, Vol. 13, No. 3
  • Method Sequence and Dominance in Mixed Methods Research: A Case Study of the Social Acceptance of Wind Energy Literature 12 April 2019 | International Journal of Qualitative Methods, Vol. 18
  • JMIR Research Protocols, Vol. 8, No. 1
  • Sundhedsprofessionelles begejstringfor fortællinger fra levet erfaring Tidsskrift for psykisk helsearbeid, Vol. 15, No. 4
  • Availability of comprehensive services in permanent supportive housing in Los Angeles 6 October 2017 | Health & Social Care in the Community, Vol. 26, No. 2
  • Nursing Outlook, Vol. 66, No. 2
  • Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen, Vol. 133
  • Social Work in Mental Health, Vol. 16, No. 4
  • International Journal of Family & Community Medicine, Vol. 2, No. 4
  • A mixed-methods study of system-level sustainability of evidence-based practices in 12 large-scale implementation initiatives 7 December 2017 | Health Research Policy and Systems, Vol. 15, No. 1
  • Fostering Psychotropic Medication Oversight for Children in Foster Care: A National Examination of States’ Monitoring Mechanisms 10 February 2016 | Administration and Policy in Mental Health and Mental Health Services Research, Vol. 44, No. 2
  • Beliefs and Behaviors of Pregnant Women with Addictions Awaiting Treatment Initiation 17 November 2016 | Child and Adolescent Social Work Journal, Vol. 34, No. 1
  • Psychiatric Quarterly, Vol. 88, No. 3
  • Quality & Quantity, Vol. 51, No. 1
  • Translational Behavioral Medicine, Vol. 7, No. 3
  • Psychology, Health & Medicine, Vol. 22, No. 5
  • Use of Mixed Methods Research in Research on Coronary Artery Disease, Diabetes Mellitus, and Hypertension Circulation: Cardiovascular Quality and Outcomes, Vol. 10, No. 1
  • Changes in Social Networks and HIV Risk Behaviors Among Homeless Adults Transitioning Into Permanent Supportive Housing 8 July 2016 | Journal of Mixed Methods Research, Vol. 11, No. 1
  • Victoria D. Ojeda , Ph.D., M.P.H. ,
  • Sarah P. Hiller , M.P.I.A. ,
  • Samantha Hurst , Ph.D. ,
  • Nev Jones , Ph.D. ,
  • Sara McMenamin , Ph.D. ,
  • James Burgdorf , Ph.D. ,
  • Todd P. Gilmer , Ph.D.
  • Mixed-Methods Research in the Discipline of Nursing Advances in Nursing Science, Vol. 39, No. 3
  • Impact of Caregiver Factors on Youth Service Utilization of Trauma-Focused Cognitive Behavioral Therapy in a Community Setting 27 February 2016 | Journal of Child and Family Studies, Vol. 25, No. 6
  • Measuring Current Drug Use in Female Sex Workers and Their Noncommercial Male Partners in Mexico: Concordance Between Data Collected From Surveys Versus Semi-Structured Interviews 18 December 2015 | Substance Use & Misuse, Vol. 51, No. 1
  • Administration and Policy in Mental Health and Mental Health Services Research, Vol. 43, No. 4
  • Implementation and Outcomes of Forensic Housing First Programs 5 October 2015 | Community Mental Health Journal, Vol. 52, No. 1
  • Academic Psychiatry, Vol. 40, No. 4
  • Journal of Psychoactive Drugs, Vol. 48, No. 5
  • Rural Society, Vol. 25, No. 2
  • The 4KEEPS study: identifying predictors of sustainment of multiple practices fiscally mandated in children’s mental health services 9 March 2016 | Implementation Science, Vol. 11, No. 1
  • Perceptions of clinicians treating young people with first‐episode psychosis for post‐traumatic stress disorder 27 June 2013 | Early Intervention in Psychiatry, Vol. 9, No. 1
  • Administration and Policy in Mental Health and Mental Health Services Research, Vol. 42, No. 2
  • Administration and Policy in Mental Health and Mental Health Services Research, Vol. 42, No. 5
  • Journal of Religion and Health, Vol. 54, No. 1
  • The Journal of Behavioral Health Services & Research, Vol. 42, No. 4
  • BMC Palliative Care, Vol. 14, No. 1
  • Implementation Science, Vol. 11, No. 1
  • International Journal of Environmental Research and Public Health, Vol. 12, No. 5
  • Evidence-Based Programs in “Real World” Settings: Finding the Best Fit
  • Ana Stefancic , M.A.
  • Marian L. Katz , Ph.D.
  • Marisa Sklar , M.S.
  • Sam Tsemberis , Ph.D.
  • Lawrence A. Palinkas , Ph.D.
  • Causality and Causal Inference in Social Work 22 May 2014 | Research on Social Work Practice, Vol. 24, No. 5
  • A Systematic Review of Strategies for Implementing Empirically Supported Mental Health Interventions 8 October 2013 | Research on Social Work Practice, Vol. 24, No. 2
  • Critical Care Medicine, Vol. 42, No. 4
  • Implementation Science, Vol. 9, No. 1
  • Implementation Science, Vol. 8, No. 1
  • Topics in research Current Opinion in Supportive & Palliative Care, Vol. 6, No. 4
  • Mixed Methods for Implementation Research 5 December 2011 | Child Maltreatment, Vol. 17, No. 1
  • RO1 Funding for Mixed Methods Research 2 September 2011 | Journal of Mixed Methods Research, Vol. 5, No. 4

descriptive research design about mental health

Descriptive research and the mental health counselor

  • Published: June 1986
  • Volume 14 , pages 169–178, ( 1986 )

Cite this article

  • Miles Davidson 1  

41 Accesses

Explore all metrics

This article makes the case that is is usually inappropriate for management to require mental health counselors to be data-takers from their clients on descriptive research projects that pose as necessary evaluative research. This is true because the goals of descriptive research and those of clinical treatment differ. Group methodology and exhaustive descriptive questioning are unhelpful and sometimes even destructive to the development of a positive clinical relationship between counselor and client. Numerous problems are cited which arise when descriptive research is done as evaluation and counselors are drafted into service as data-takers. The article concludes by urging the use of single-case quantitative methodology when counselors are required to perform service effectiveness evaluation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Apsler, Robert. (1977) In defense of the experimental paradigm as a tool for evaluation research. Evaluation, 4 , 14, 15.

Google Scholar  

Beck, D.F. (1979) Patterns for university-agency cooperation in the teaching of research. Social Casework, 60 (6), 345.

Berger, R.M. & Witkin, S. (1978) Berger and Witkin comment. In series of exchanges on “Evaluating one's own effectiveness.” Social Work, 23 (3), 254.

Bloom, M. & Block, S.R. (1977) Evaluating one's own effectiveness and efficiency. Social Work, 22 (2), 136, 132, 130–136.

Bloom, M. & Block, S.R. (1978) Bloom and Block reply. In Series of exchanges on “Evaluating one's own effectiveness.” Social Work, 23 (3), 255.

Boring, E.G. (1950) A history of experimental psychology . 2nd edition, Englewood Cliffs, New Jersey: Prentice-Hall, Inc., 570–578.

Brenner, M.N. (1976) The quest for viable research in social services: Development of the ministudy. Social Service Review, 50 (3), 435, 442, 428, 426, 441–442, 441–442.

Brody, R. & Krailo, H. (1978) An approach to reviewing the effectiveness of programs. Social Work, 23 (3), 226.

Brown, E.G. (1977) Book review of Task-centered practice . W.J. Reid & L. Epstein (Eds.). New York: Columbia University Press, 1977. In Social Service Review, 51 (4), 701.

Chea, M.W. (1972) Research on recording. Social Casework, 53 (3), 178, 177, 180.

Chommie, P.W. & Hudson, J. (1974) Evaluation of outcome and process. Social Work, 19 (6), 682–683, 685, 687.

Covey, H.C. (1982) Basic problems of applying experiments to social programs. Social Service Review, 56 (3), 431–432, 434.

Davis, H.R. (1973) Four ways to goal attainment, an overview. Evaluation: A Forum for Human Service Decision-Makers , 1, 23–28.

Davis, H.R., Windle, C. & Sharfstein, S.S. (1977) Developing guidelines for program evaluation capability in community mental health centers. Evaluation, 4 , 26, 28, 29.

Eldridge, W.D. (1982) Coping with accountability: guidelines for supervisors. Social Case-work, 63 (8), 490–491, 493.

Eldridge, W.D. (1983) Practitioners and self-evaluation. Social Casework , 64(7), 426.

Ewalt, P.L. (1982) Book review of Research techniques for clinical social workers . T. Tripodi & I. Epstein. New York: Columbia University Press, 1980. In Social Casework, 63 (5), 314–315.

Geismar, L.L. & Wood, K.M. (1982) Evaluating practive: science as faith. Social Casework, 63 (3), 267, 271.

Gingerich, W.J. (1978) Measurings the process. Social Work, 23 (3), 251.

Gripton, J. (1981) Book review of Empirical clinical practice . S. Jayarantne & R.L. Levy. New York: Columbia University Press, 1979. In Social Work, 26 (1), 94.

Haselkorn, F. (1978) Accountability in clinical practice. Social Casework, 59 (6), 330, 332–334.

Ho, M.K. (1976) Evaluation: a means of treatment. Social Work, 21 (1), 24, 27.

Honigfeld, G. & Klein, D.F. (1973) The hillside hospital patient progress record: explorations in clinical management by objective and exception. Evaluation: A Forum for Human Service Decision-Makers, 1 , 20, 22.

Hoshino, G. (1973) Social services: the problem of accountability. Social Service Review, 47 (3), 373–374, 380–381.

Howe, M.W. (1974) Casework self-evaluation: a single-subject approach. Social Service Review, 48 (1), 1–23.

Hudson, W.W. (1977) Elementary techniques for assessing single-client/single-worker interventions. Social Service Review, 51 (2), 312–313.

Hudson, W.W. (1978) Research training in professional social work education. Social Service Review, 52 (1), 118–119.

Kagle, J.D. (1983) The contemporary socials work record. Social Work, 28 (2), 149–153.

Kagle, J.D. (1984) Restoring the clinical record. Social Work, 29 (1), 47.

Karger, H.J. (1983) Science, research, and social work: who controls the profession? Social Work, 28 (3), 202–204.

Kiresuk, T.J. (1973) Goal attainment scaling at a county mental health service. Evaluation, 1 , 12–18.

Kivens, L. & Bolin, D.C. (1976) Evaluation in a community mental health center: Hillsborough CMHC, Tampa, Florida. Evaluation, 3 (1–2), 99, 103.

Lawrence, H. & Walter, C.L. (1978) Testing a behavioral approach with groups. Social Work, 23 (2), 132.

Lebedun, M. (1970) Measuring movement in group marital counseling. Social Casework, 51 (1), 35.

Levine, A.S. (1968) Cost-benefit analysis and social welfare program evaluation. Social Service Review, 42 (2), 175.

Mannino, F.V. & Shore, M.F. (1974) Demonstrating effectiveness in an aftercare program. Social Work, 19 (3), 354.

Meld, M.B. (1974) The politics of evaluation of social programs. Social Work, 19 (4), 448, 454.

Mushkin, S.J. (1973) Evaluations: use with caution. Evaluation, 1 (2), 31–33.

Newman, E. & Turem, J. (1974) The crisis of accountability. Social Work, 19 (1), 6, 8, 12.

Polansky, N.A. (Ed.) (1975) Social work research: methods for the helping professions . Chicago: University of Chicago Press, 62.

Reid, W.J. (1973) Book review of Family and community functioning: a manual of measurement for social work practive and policy . L.L. Geismar. Metuchen, New Jersey: Scarecrow Press, 1971. In Social Service Review, 47 (2), 298.

Rosenberg, M.L. & Brody, R. (1974) The threat or challenge of accountability. Social Work, 19 (3), 346, 348–349.

Ruckdeschel, R.A. & Farris, B.E. (1981) Assessing practice: a critical look at the single-case design. Social Casework, 62 (7), 413–419.

Salasin, S. (1980) Evaluation as a tool for restoring the mental health of victims: an interview with Frank Ochberg. Evaluation and Change , 25.

Schinke, S.P. (1979) Evaluating social work practice: a conceptual model and example. Social Casework, 60 (4), 195–197.

Selltiz, C., Wrightsman, L.S. & Cook, S.W. (1976) Research methods in social relations , 3rd edition, New York: Holt, Rinehart, & Winston, 90, 101–103.

Smith, M.J. (1980) Book review of Social R & D: research and development in the human services . Jack Rothman. Englewood Cliffs, New Jersey: Prentice-Hall, Inc., n.d. In Social Service Review, 54 (4), 609.

Stein, T.J. & Gambrill, E.D. (1976) Behavioral techniques in foster care. Social Work, 21 (1), 34–39.

Summerfield, J. (1981) Book review of Improving effectiveness and reducing costs in mental health . Brian T. Yates. Springfield, Illinois: Charles C. Thomas, 1980. In Social Service Review, 55 (2), 362.

Thomson, R. (1968) The pelican history of psychology . Baltimore, Maryland: Penguin, 325–344.

Urbanowski, M.L. (1974) Recording to measure effectiveness. Social Casework, 55 (9), 552.

Vattano, A.J. (1978) Self-management procedures for coping with stress. Social Work, 23 (2), 118.

Weatherley, R., Kottwitz, C.B., Lishner, D., Reid, K., Roset, G., and Wong, K. (1980) Accountability of social service workers at the front line. Social Service Review, 54 (4), 556–557, 563–564, 568–569.

Weinberger, R. & Tripodi, T. (1969) Trends in types of research reported in selected social work journals, 1956–65. Social Service Review, 43 (4), 439.

Weiss, C.H. (1974) Alternative models of program evaluation. Social Work, 19 (6), 675.

Wood, K.M. (1978) Casework effectiveness: a new look at the research evidence. Social Work, 23 (6), 437–458.

Download references

Author information

Authors and affiliations.

Community Treatment Program, Herbert Lipton Community Mental Health Center, 45 Summer Street, 01453, Leominster, MA

Miles Davidson

You can also search for this author in PubMed   Google Scholar

Rights and permissions

Reprints and permissions

About this article

Davidson, M. Descriptive research and the mental health counselor. Clin Soc Work J 14 , 169–178 (1986). https://doi.org/10.1007/BF00755617

Download citation

Issue Date : June 1986

DOI : https://doi.org/10.1007/BF00755617

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Mental Health
  • Clinical Treatment
  • Effectiveness Evaluation
  • Numerous Problem
  • Health Counselor
  • Find a journal
  • Publish with us
  • Track your research

Elsevier QRcode Wechat

  • Research Process

Descriptive Research Design and Its Myriad Uses

  • 3 minute read

Table of Contents

The design of a research study can be of two broad types—observational or interventional. In interventional studies, at least one variable can be controlled by the researcher. For example, drug trials that examine the efficacy of novel medicines are interventional studies. Observational studies, on the other hand, simply examine and describe uncontrollable variables¹ .   

What is descriptive research design?¹

Descriptive design is one of the simplest forms of observational study design. It can either quantify the distribution of certain variables (quantitative descriptive research) or simply report the qualities of these variables without quantifying them (qualitative descriptive research).   

When can descriptive research design be used?¹

It is useful when you wish to examine the occurrence of a phenomenon, delineate trends or patterns within the phenomenon, or describe the relationship between variables. As such, descriptive design is great for¹ :  

  • A survey conducted to measure the changes in the levels of customer satisfaction among shoppers in the US is the perfect example of quantitative descriptive research.  
  • Conversely, a case report detailing the experiences and perspectives of individuals living with a particular rare disease is a good example of qualitative descriptive research.  
  • Cross-sectional studies : Descriptive research is ideal for cross-sectional studies that capture a snapshot of a population at a specific point in time. This approach can be used to observe the variations in risk factors and diseases in a population. Take the following examples:   
  • In quantitative descriptive research: A study that measures the prevalence of heart disease among college students in the current academic year.  
  • In qualitative descriptive research: A cross-sectional study exploring the cultural perceptions of mental health across different communities.  
  • Ecological studies : Descriptive research design is also well-suited for studies that seek to understand relationships between variables and outcomes in specific populations. For example:  
  • A study that measures the relationship between the number of police personnel and homicides in India can use quantitative descriptive research design  
  • A study describing the impact of deforestation on indigenous communities’ cultural practices and beliefs can use qualitative descriptive research design.  
  • Focus group discussion reports : Descriptive research can help in capturing diverse perspectives and understanding the nuances of participants’ experiences.   
  • First, an example of quantitative descriptive research: A study that uses two focus groups to explore the perceptions of mental health among immigrants in London.  
  • Next, an example of qualitative descriptive research: A focus group report analyzing the themes and emotions associated with different advertising campaigns.  

Benefits of descriptive research design¹  

  • Easy to conduct: Due to its simplicity, descriptive research design can be employed by researchers of all experience levels.  
  • Economical: Descriptive research design is not resource intensive. It is a budget-friendly approach to studying many phenomena without costly equipment.   
  • Provides comprehensive and useful information: Descriptive research is a more thorough approach that can capture many different aspects of a phenomena, facilitating a wholistic understanding.  
  • Aids planning of major projects or future research: As a tool for preliminary exploration, descriptive research guides can guide strategic decision-making and guide major projects.  

The Bottom Line  

Descriptive research plays a crucial role in improving our lives. Surveys help create better policies and cross-sectional studies help us understand problems affecting different populations including diseases. Used in the right context, descriptive research can advance knowledge and inform decision making¹ .  

We, at Elsevier Language Services, understand the value of your descriptive research, as well as the importance of communicating it correctly. If you have a manuscript based on a descriptive study, our experienced editors can help improve its myriad aspects. By improving the logical flow, tone, and accuracy of your writing, we ensure that your descriptive research gets published in a top tier journal and makes maximum impact in academia and beyond. Contact us for a comprehensive list of services!   

Type in wordcount for Plus Total: USD EUR JPY Follow this link if your manuscript is longer than 9,000 words. Upload

References 

  • Aggarwal, R., & Ranganathan, P. (2019). Study designs: Part 2 – Descriptive studies. Perspectives in Clinical Research , 10 (1), 34. https://doi.org/10.4103/picr.picr_154_18 .  

AI in Manuscript Editing

  • Manuscript Review

Is The Use of AI in Manuscript Editing Feasible? Here’s Three Tips to Steer Clear of Potential Issues

Errors in Academic English Writing

Navigating “Chinglish” Errors in Academic English Writing

You may also like.

Doctor doing a Biomedical Research Paper

Five Common Mistakes to Avoid When Writing a Biomedical Research Paper

descriptive research design about mental health

Making Technical Writing in Environmental Engineering Accessible

Risks of AI-assisted Academic Writing

To Err is Not Human: The Dangers of AI-assisted Academic Writing

Importance-of-Data-Collection

When Data Speak, Listen: Importance of Data Collection and Analysis Methods

choosing the Right Research Methodology

Choosing the Right Research Methodology: A Guide for Researchers

Why is data validation important in research

Why is data validation important in research?

Writing a good review article

Writing a good review article

Scholarly Sources What are They and Where can You Find Them

Scholarly Sources: What are They and Where can You Find Them?

Input your search keywords and press Enter.

  • Open access
  • Published: 04 October 2023

A scoping review of the barriers and facilitators to accessing and utilising mental health services across regional, rural, and remote Australia

  • Bianca E. Kavanagh   ORCID: orcid.org/0000-0002-1656-2775 1 ,
  • Kayla B. Corney 2 ,
  • Hannah Beks   ORCID: orcid.org/0000-0002-2851-6450 1 ,
  • Lana J. Williams   ORCID: orcid.org/0000-0002-1377-1272 2 ,
  • Shae E. Quirk 2 , 3 , 4 &
  • Vincent L. Versace   ORCID: orcid.org/0000-0002-8514-1763 1  

BMC Health Services Research volume  23 , Article number:  1060 ( 2023 ) Cite this article

2801 Accesses

2 Citations

1 Altmetric

Metrics details

Inadequate healthcare access and utilisation are implicated in the mental health burden experienced by those living in regional, rural, and remote Australia. Facilitators that better enable access and utilisation are also reported in the literature. To date, a synthesis on both the barriers and facilitators to accessing and utilising mental health services within the rural Australian context has not been undertaken. This scoping review aims to (1) synthesise the barriers and facilitators to accessing and utilising mental health services in regional, rural, and remote Australia, as identified using the Modified Monash Model; and (2) better understand the relationship between barriers and facilitators and their geographical context.

A systematic search of Medline Complete, EMBASE, PsycINFO, Scopus, and CINAHL was undertaken to identify peer-reviewed literature. Grey literature was collated from relevant websites. Study characteristics, including barriers and facilitators, and location were extracted. A descriptive synthesis of results was conducted.

Fifty-three articles were included in this scoping review. Prominent barriers to access and utilisation included: limited resources; system complexity and navigation; attitudinal and social matters; technological limitations; distance to services; insufficient culturally-sensitive practice; and lack of awareness. Facilitators included person-centred and collaborative care; technological facilitation; environment and ease of access; community supports; mental health literacy and culturally-sensitive practice. The variability of the included studies precluded the geographical analysis from being completed.

Both healthcare providers and service users considered a number of barriers and facilitators to mental health service access and utilisation in the regional, rural, and remote Australian context. Barriers and facilitators should be considered when re-designing services, particularly in light of the findings and recommendations from the Royal Commission into Victoria’s Mental Health System, which may be relevant to other areas of Australia. Additional research generated from rural Australia is needed to better understand the geographical context in which specific barriers and facilitators occur.

Peer Review reports

Introduction

The mental health of Australians who live in regional, rural, and remote Australia is an ongoing concern [ 1 ]. Poor healthcare access is one of the key determinants of adverse mental health outcomes, with access issues being more pronounced in regional, rural, and remote Australia (hereafter referred to as rural , in line with the Australian Government’s definition under the Rural Health Multidisciplinary Training [RHMT] Program [ 2 ]), compared to metropolitan Australia [ 3 ]. People living in rural Australia often face difficulties in obtaining healthcare, and this care is often delayed and more expensive for the patient [ 4 ]. These difficulties in accessing and utilising healthcare are implicated in the higher mental disorder burden experienced by those living in rural Australia, shown by the higher rates of suicide, compared with major cities [ 5 ]. Moreover, this group is less likely than those living in major cities to take-up and complete mental health treatment [ 6 ]. Workforce maldistribution plays a role in these health inequalities [ 7 , 8 , 9 , 10 ], with more clinical full time equivalent (FTE) mental health professionals working in major cities, compared with rural areas (i.e., 92 vs. 30–80 mental health nurses, 15 vs. 2–6 psychiatrists, and 90 vs. 15–55 psychologists per 100,000/population) [ 3 ]. Other areas of the health workforce are similarly maldistributed across the country (i.e., 403 vs. 223–309 clinical FTE medical practitioners and 531 vs. 382–469 clinical FTE allied health professionals per 100,000/population in major cities versus rural areas) [ 11 ].

There are a number of factors that are implicated — both directly and indirectly — in the access and utilisation of mental health services, and these factors may be pertinent to the level of remoteness experienced. This includes particular aspatial (i.e., social) and spatial (i.e., geographical) dimensions [ 12 , 13 ]. Aspatial dimensions consist of the factors that affect the affordability , acceptability , accommodation , and awareness of healthcare access. In the rural context of Australia, this tends to relate to social matters [ 14 , 15 ] including stoicism, low help-seeking behaviours, and confidentiality concerns [ 16 ]. Spatial dimensions are concerned with the availability and accessibility of service access, including geographical isolation [ 14 ], service delivery capacity [ 17 ] [ 18 ], and dual-roles [ 14 ] (i.e., the intersection of professional and personal relationships) in rural areas. While here we define access as factors that pertain to the attributes/expectations of the individual and their alignment with the provider/services [ 12 ], other models conceptualise access as the opportunity to identify healthcare needs, seek services, reach resources, obtain or use services, and have the need for services fulfilled [ 19 ]. Utilisation refers to the generation of a healthcare plan throughout a healthcare encounter, as well as its implementation and follow-through [ 20 ].

Conceivably, mitigating the barriers and augmenting the facilitators to the utilisation of mental health services may be particularly important when considering the obstacles that people from rural areas face when accessing services. One previous study on rurally-based Australian adolescents suggested that barriers to accessing services, such as social exclusion and ostracism by members of their community, also likely prevented the continued utilisation of services and negatively affected treatment outcomes [ 21 ]. Cheesmond et al. [ 22 ], in a review of residents in rural Australia, Canada, and the United States of America, highlighted a link between sociocultural rurality, rural identity, and help-seeking behaviour. Cheesmond et al. [ 22 ] suggested that specific place-sensitive approaches are needed to overcome barriers to help-seeking, and that a greater understanding of help-seeking in the rural context is required. This includes further exploration of rurality as a concept, conducting research within diverse environments, allowing participants to contextualise barriers to help-seeking, and exploring the co-existence of multiple help-seeking barriers. Parallel to this, a paucity of research has focussed on the facilitators to accessing and utilising mental health services in rural Australia.

To the authors’ knowledge, no previous reviews have specifically focussed on understanding the barriers and facilitators to accessing and utilising mental health services within the rural Australian context. A scoping review was chosen as the preferred approach to this work because of the emerging and cross-disciplined nature of the research. The aim of this scoping review is to: (1) explore the barriers and facilitators to accessing and utilising mental health services for Australians living in rural areas; and (2) better understand the relationship between barriers and facilitators and their geographical context.

This scoping review conforms to the guidelines put forward by Arksey and O’Malley [ 23 ], follows the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews (PRISMA-ScR) [ 24 ], and a published protocol [ 25 ].

Eligibility criteria

The scope of this review was intentionally broad to allow explanation of the nature and extent of the literature describing the barriers and facilitators to accessing and utilising mental health services across regional, rural, and remote Australia. Articles were eligible for inclusion if they met the following criteria:

Included individuals with a diagnosed mental disorder, experienced mental health issues, or were part of a mental health community service; or included healthcare providers that provided diagnostic, assessment, or treatment services for mental health issues.

Explained obstacles that impeded the uptake, quality, or level of mental health services being accessed or described facilitators that allowed the uptake, quality, or level of mental health services being received.

Included service users, healthcare providers, or services that were based in regional, rural, or remote Australia according to the Modified Monash Model (MMM) 2–7 ( regional centres to very remote communities ) [ 4 ] (i.e. the current RHMT definition of rural).

The population/concept/context (PCC) framework was used to generate the eligibility criteria for this scoping review and is described in Table  1 . The eligibility criteria for this review varied slightly from the published protocol [ 25 ]. In this review, we included pharmacists as healthcare providers, as it was identified that pharmacists play a key role in mental health services in some rural areas. We excluded mental health programs and health promotion activities that were considered to be a “structured activity” delivered by a service, reviews, viewpoints, declarations, tailpieces, frameworks, and commentaries. We also excluded articles that did not provide sufficient detail to describe the barriers or facilitators to accessing or utilising services, as well as articles that pooled results across participants from metropolitan and regional/rural/remote areas. The only exception to this was when authors referred to the study setting as regional/rural/remote, but upon further investigation using the health workforce locator [ 26 ] (see Sect.  2.8 Geographical analysis ), the location was deemed to be metropolitan according to the MMM [ 4 ] — this exception was allowed due to the differences in geographical models applied to Australian health research [ 27 , 28 ]. Separately, we decided to include articles that reported on the barriers and/or facilitators of a specific rural mental health service implementation activity or service model, as we felt that these articles offered important insights that may be translated to new service initiatives or research activities.

Information sources

The following databases were systematically searched: Medline Complete, EMBASE, PsycINFO, Scopus, and Cumulative Index of Nursing and Allied Health Literature (CINAHL). Websites of the Australian federal and state government’s Department of Health, Primary Health Network (PHN), key rural and remote peak bodies/agencies known to the authors from their collective experience on the topic, and Google were also searched to ascertain grey literature. The search was performed on 11th January 2022 and a 2012-current date filter was employed using the ‘start’ and ‘end’ publication year functions. Additional sources were identified through ‘snowball’ searching of included studies. Where needed, additional location information was obtained via a study’s first or corresponding author.

The search strategy was developed in consultation with two scholarly services librarians (JS and BK) to identify peer-reviewed studies and grey literature records. Relevant keywords, search terms, and wildcard symbols were applied to each database. An adapted search string was searched in Google using the advanced search function. The “all these words” and “any of these words” search options were engaged, and PDF files were requested. All (n = 11) pages of the search results were assessed for eligibility by one reviewer (BEK), and the research term agreed on their inclusion.

The full search strategy and grey literature sources are presented in Additional Table  1 .

Selection of sources of evidence

One reviewer (BEK) applied the search strategy to the databases and websites. Two reviewers (BEK and KBC) independently screened all articles using Covidence [ 29 ]. Where discrepancies concerning the eligibility of an article occurred, a meeting was held to determine consensus; if consensus could not be reached, a third reviewer (LJW) was consulted to make the final decision.

Data charting process

To ensure that the data charting process was consistent with the research question, a charting form was developed and piloted by two authors (BEK and KBC). One author (BEK) then charted the data for each of the eligible articles, using Microsoft Excel.

The following data items were extracted from eligible studies: author and year, study objective, study design, location, sample size, characteristics of participants, mental health diagnosis/issue and assessment method, healthcare provider type/role, barriers, facilitators, mental health service, regional/rural/remote area of Australia, and summary of findings (Additional Table  2 ). For literature that included participants from both metropolitan and regional/rural/remote areas, only information that pertained to those from regional/rural/remote areas was extracted, except for instances where statistical differences between groups were reported for comparison. Likewise, in instances where articles included participants who were eligible (e.g., healthcare providers) as well as participants who were ineligible (e.g., no evidence of mental health diagnosis/engagement with services), only information from eligible participants was extracted. First or corresponding authors of studies that did not specifically state where the study was conducted were contacted to provide additional location information.

Synthesis of results

A descriptive synthesis was conducted by providing an overview of the included study characteristics, setting and target groups, and barries and facilitators. Links to aspatial and spatial access factors were also described, where relevant. The study characteristics are presented in Table  2 and the barriers and facilitators pertaining to each included study are presented in Additional Table  3 . A quality appraisal of the included studies was not undertaken as scoping reviews aim to offer an overview or map of the pertinent evidence [ 30 ].

Geographical analysis

Geographical coordinates provided by the health workforce locator [ 26 ] were used to determine the remoteness of the study locations according to the MMM categories. These data were inputted into STATA to determine the number and proportion of each of the MMM categories.

The database search yielded 1,278 articles, of which 555 articles were removed due to duplication. Subsequently, 723 titles and abstracts were screened, and 441 were excluded due to ineligibility. At the full text stage, 282 articles were screened, with 181 studies being excluded, resulting in 47 articles meeting the eligibility criteria. The grey literature search yielded 128 potentially relevant sources, of which six were eligible after removing three for duplication. In total, 53 articles were included in this scoping review. A snowball search of the references of included records was also conducted and two additional records were identified but were deemed ineligible as they reported on studies/samples that were already included in the review. Figure  1 displays the PRISMA flow throughout each screening stage.

figure 1

PRISMA flow diagram of studies considered in this review

Study characteristics

Of the 53 included studies, 25 articles described barriers and/or facilitators from the healthcare provider perspective, 13 were from the point of view of the service user, eight reported on combined perspectives of both the healthcare provider and service user, and seven reported on barriers/facilitators from neither the healthcare provider nor service user perspective directly but did consider the barriers/facilitators of the service environment (e.g., service evaluations).

Most studies (n = 29, 54.7%) employed qualitative methods, including interviews and/or focus groups; 12 studies utilised quantitative cross-sectional or longitudinal methods, seven were mixed-methods research designs, and two were service description and classification studies.

The highest proportion of studies were conducted in New South Wales (NSW) (n = 13) [ 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ], followed by Australia broadly (n = 12) [ 33 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 ], South Australia (SA) (n = 10) [ 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 ], Victoria (VIC) (n = 6) [ 65 , 66 , 67 , 68 , 69 , 70 ], Queensland (QLD) (n = 5) [ 71 , 72 , 73 , 74 , 75 ], Western Australia (WA) (n = 3) [ 76 , 77 , 78 ], Tasmania (TAS) (n = 2) [ 79 , 80 ], and Northern Territory (NT) (n = 1) [ 81 ]. One study pertained to areas within NSW, QLD, and VIC [ 82 ], and another study concerned NSW and WA [ 83 ]. No studies were centred on Australian Capital Territory (ACT). Table  2 depicts the characteristics of the included studies.

Setting and target groups

Mental health service setting.

Fourteen studies reported on general or community-based mental health services [ 18 , 33 , 43 , 48 , 53 , 54 , 57 , 64 , 72 , 74 , 77 , 78 , 83 ]. Four studies described mental health services provided within emergency departments (EDs) and/or urgent care centres (UCCs) [ 40 , 41 , 46 , 65 ]. The remaining studies described mental health services provided by counsellors and GPs [ 38 ], nurses, peer-workers [ 71 ], personal helpers and mentors [ 35 ], pharmacists [ 47 ], and a combination of several healthcare providers [ 59 ]. Seven studies reported on technology-based or -enhanced mental health services [ 51 , 60 , 61 , 62 , 63 , 75 , 76 ].

Target groups

The population group focus of studies varied. Of the studies that commented on, or specified that they targeted specific subpopulations, four studies discussed care pertinent to Indigenous or Aboriginal and/or Torres Strait Islander Peoples [ 66 , 67 , 68 , 81 ]. Four studies discussed mental health services for young people [ 55 , 63 , 73 , 82 ]. Three studies specifically included at least a proportion of service users who were under the age of 18 years old [ 55 , 61 , 79 ]. Two studies reported on mental health services for older people [ 50 , 58 ]. Other studies described barriers and or facilitators specific to sex workers [ 80 ], medical doctors [ 45 ], LGBTIQA + people [ 51 ], immigrants [ 49 ], and women [ 39 ] or men [ 70 ] with specific mental health issues. Three studies described mental health services that were specific for supporting people with depression [ 34 , 39 , 55 ]; two studies were focussed on suicide [ 68 , 70 ]; two studies described care for people with eating disorders [ 42 , 52 ]; and one study was centred on perinatal and infant support [ 75 ].

Barriers and facilitators

The included studies varied significantly. This included differences in the purpose and type of study, participant sample, and methodology, and reporting of findings. Barriers and facilitators were grouped into prominent concepts based on terminology used by the relevant literature and are presented in Table  3 . Barriers related to limited resources; system complexity and navigation; attitudinal and social matters; technological limitations; distance to services; insufficient culturally-sensitive practice; and lack of awareness. Facilitators related to person-centred and collaborative care; technological facilitation; environment and ease of access; community supports; mental health literacy; and culturally-sensitive practice.

Prominent barrier concepts

Barriers affecting healthcare providers and service users.

Limited resources. Across the studies, the most considerable barrier was limited resources [ 18 , 33 , 34 , 35 , 36 , 38 , 39 , 42 , 45 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 71 , 74 , 75 , 78 , 79 , 80 , 82 ]. This key concept considered limited resources at the healthcare provider and service user level. Notably, lack of available general and specialist services, limited service capacity, workforce shortages, difficulty attracting and retaining staff, and staff turnover were frequently reported as considerable spatial barriers to service delivery, hampering access to services. Moreover, financial costs, disadvantage, or appointment fees [ 34 , 37 , 52 , 53 , 61 , 62 , 78 ], and lack of transport [ 34 , 50 , 52 , 53 , 58 , 62 , 71 , 78 ] restricted access to mental health services for the service user. These issues reflect the lower relative socio-economic advantage seen in rural areas of Australia [ 2 ].

System complexity and navigation. The complexity in using and navigating the system was a common aspatial barrier [ 18 , 33 , 36 , 40 , 41 , 42 , 45 , 46 , 51 , 52 , 53 , 57 , 58 , 59 , 61 , 63 , 65 , 66 , 69 , 73 , 74 , 78 , 80 ], which affected healthcare providers in coordinating patient care and service users in utilising such care. These issues were most frequently reflected in reports on extended wait times and delays in assessment and diagnosis [ 34 , 40 , 46 , 53 , 55 , 57 , 58 , 62 , 66 , 78 , 80 ].

Attitudinal or social matters. Many studies reported that attitudinal or social matters were a barrier for the service user [ 34 , 35 , 36 , 38 , 39 , 43 , 50 , 51 , 52 , 60 , 61 , 64 , 66 , 67 , 68 , 70 , 78 , 80 , 81 ], particularily concerning privacy or confidentiality concerns [ 39 , 51 , 60 , 61 , 62 , 63 , 66 , 67 , 78 ], affecting aspatial access to care. The need to be stoic was reported as a barrier to seeking psychological help among regional medical doctors, relating to their perceptions of regional practitioner identity [ 45 ], and among service users [ 50 , 67 , 70 ].

Technological limitations. Several studies cited limitations to services delivered via technological means [ 51 , 53 , 60 , 61 , 62 , 64 , 78 ]. Some studies acknowledged that technology can enhance physical mental health services, but cannot replace them [ 62 , 64 ], particularly for specific client groups, including the older population and Aboriginal and Torres Strait Islander people, who reportedly prefer face-to-face service delivery [ 78 ]. In addition, poor connectivity and high costs of technology use were reported as aspatial barriers to accessing technology-delivered mental health services and may also affect their utilisation [ 53 , 62 , 78 ].

Lack of awareness. Lack of awareness about mental health issues, needs, or services available was reported as an aspatial barrier in the current review [ 43 , 50 , 52 , 67 , 78 ]. This lack of awareness was reported at the healthcare provider level in one study, and was described as the healthcare provider having a limited understanding of the mental health needs in older people, resulting in a lack of referral to appropriate services [ 50 ]. At the service user level, a lack of awareness precluded individuals from recognising mental health problems [ 67 ], while a lack of awareness of services was a barrier to seeking help [ 52 , 78 ].

Barriers affecting service users

Distance to services. The spatial distance required to travel to physical services is a considerable issue for people residing in rural localities, and this distance has been shown to reduce service access and utilisation in the current review [ 52 , 62 , 63 , 64 , 67 , 71 , 78 ]. There is also an additional burden experienced by those with physical disability, or those who don’t have a support person to assist them [ 53 ].

Insufficient culturally-sensitive practice. A limited capacity to meet the needs of culturally and linguistically diverse (CALD) and Aboriginal and Torres Strait Islander communities was reported, affecting aspatial access and utilisation of services. This tended to be a result of service users not feeling culturally safe within the service environment, perceptions that health professionals had cultural assumptions about the service user, and inappropriate assessment tools [ 48 , 49 , 58 , 73 , 78 ].

Prominent facilitator concepts

Facilitators affecting healthcare providers and service users .

Person-centred and collaborative care. Many studies reported that person- (or client-) centred care that is non-judgemental and permits collaboration to be an important aspatial facilitator to mental health service access and utilisation [ 31 , 34 , 35 , 36 , 41 , 42 , 56 , 57 , 58 , 59 , 61 , 63 , 64 , 65 , 72 , 74 , 81 ]. It is noteworthy that person centred care was specifically reported in studies pertaining to the service user [ 61 ] and healthcare provider [ 63 , 64 ] in the current review, suggesting that this approach is recognised as important by both those delivering and using the service. Care that is regular and non-intrusive was seen as a way to facilitate service utilisation [ 34 , 57 ].

Technological facilitation. Technology-based services, including integrated mental health services, telehealth, live chat, SMS appointment reminders and coordination, and mental health web-pages, were reported to be useful in filling spatial and aspatial gaps in service delivery for physical services [ 51 , 53 , 58 , 60 , 61 , 62 , 63 , 75 , 76 , 78 ]. These services were reported to facilitate connection and information sharing [ 62 ], clinical supervision, contact with specialists [ 60 ], workforce upskilling, and security [ 75 ] for the healthcare provider. For the service user, technology-based services facilitated immediacy of consultations, cost savings, and anonymity, and reduced mental health hospitalisations and admissions, additional client appointments, the need to travel, stigma, and family stress [ 60 ].

Environment and ease of access. The mental health service environment and the ease of which one may access services — granted that all other access issues are overcome — were frequently reported as spatial facilitators [ 31 , 49 , 65 , 73 , 80 , 81 ]. Specifically, services that permitted a non-clinical and comfortable environment were deemed as important aspatial factors for young people [ 61 , 73 ]. Co-located services were also considered important for access, as this allows service integration and facilitated information sharing [ 31 , 41 , 63 ].

Community supports. The community was considered to be an important aspatial facilitator. This included healthcare providers being involved and connected with the community [ 56 , 65 , 66 ], as well as having a sense of community [ 59 ], as a way to facilitate care via information sharing, collaboration, and knowing community members and local issues. For the service user, community and place was seen as a source of strength as noted by one study [ 39 ].

Facilitators affecting service users

Mental health literacy. Several studies reported that having awareness of mental health issues and being confident in using services were aspatial facilitators to mental health service access and utilisation [ 52 , 57 , 59 , 66 , 70 ]. These factors are generally referred to as mental health literacy within the wider literature, which is a crucial component of healthcare [ 84 ].

Culturally-sensitive practice. Of the studies that reported on cultural elements of mental health service provision, it was noted that Indigenous and other culturally appropriate staff (i.e., a Koori Mental Health Liaison Officer or Aboriginal Mental Health Worker), as well as the involvement of Community Elders and spiritual healers [ 48 ] assisted with service access and utilisation [ 48 , 66 ]. Further, culturally appropriate décor and flexibility in meeting places [ 66 ], and the use of culturally acceptable models of mental health [ 48 ] were also seen as important aspatial dimensions.

Overall, thirty studies were described as being relevant to rural areas [ 18 , 31 , 33 , 34 , 35 , 36 , 38 , 39 , 42 , 43 , 48 , 49 , 50 , 53 , 57 , 58 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 73 , 76 , 78 , 83 ], three studies were pertinent to regional areas [ 39 , 56 , 79 ], two studies were concerned with remote areas [ 77 , 81 ], and the remaining studies involved combinations of regional/rural/remote populations of Australia [ 37 , 40 , 41 , 44 , 45 , 46 , 47 , 51 , 52 , 54 , 55 , 59 , 60 , 71 , 74 , 75 , 80 , 82 ]. Over one third of the studies (n = 21, 39.6%) reported or provided specific spatial data, which allowed the MMM [ 4 ] to be applied directly to the study location; n = 10 (47.6%) of these studies included multiple locations, resulting in a total of 41 MMM categories. Studies were conducted most frequently in MM5 small rural towns (n = 10, 24.4%) and MM3 large rural towns (n = 9, 22.0%) and least frequently in MM6 remote communities (n = 3, 7.3%). The first author’s location was used as a proxy location for 28 studies (52.8%). Of these studies, the most frequent location was MM1 metropolitan settings (n = 16, 57.1%), likely due to the high proportion of study locations being taken from the first author’s location, and that many universities and research centres are located in major cities. There were no studies conducted in MM5 small rural towns (n = 0, 0%). Three author locations (5.7%) could not be determined due to limited information provided. Table  4 displays details of the MMM categories according to spatial data reported or obtained and proxy locations. Due to the heterogeneity and lack of mutual exclusivity of the data, an analysis of the association between geographical area and specific barriers and facilitators was unable to be completed.

Discussion and implications

This scoping review identified the barriers and facilitators experienced by healthcare providers delivering mental health services and individuals accessing, or attempting to access mental health services in rural Australia. Prominent barriers included: limited resources; system complexity and navigation; attitudinal and social matters; technological limitations; distance to services; insufficient culturally-sensitive practice; and lack of awareness. Facilitators included person-centred and collaborative care; technological facilitation; environment and ease of access; community supports; mental health literacy and culturally-sensitive practice. We also aimed to understand these barriers and facilitators in relation to their geographical context; however, the variability in the data precluded the geographical analysis from being completed.

This study revealed a paucity of research conducted in MM6 remote and MM7 very remote communities in Australia when specific spatial data are considered, as well as in the ACT — however, it is noted that the majority of the ACT is classified as metropolitan, with 99.83% (387,887 residents) of the population residing in MM1 at the time of the 2016 census [ 2 ]. Moreover, when proxy study locations are used, many studies are conducted by researchers located in metropolitan areas. Only three studies specifically included service users who were under the age of 18 years old, representing a significant gap in understanding the mental health service needs of the younger population. Although it is acknowledged that there are considerable research ethics restrictions in place to protect children and young people, the onset of many mental health issues tends to occur between 14.5 and 18 years of age [ 85 ], highlighting the importance of understanding barriers and facilitators to accessing mental health services amongst the younger cohort. Due to the heterogeneity of the findings, the following discussion considers the most prominent barriers and facilitator concepts identified across the studies.

Review findings support limited resources as being one of the biggest restrictors of mental health service access and utilisation within rural Australia. Thes findings echo reports at the national scale, which show the mental health workforce is heavily concentrated in metropolitan areas compared to other remoteness areas, relative to the population [ 86 ]. Considerable efforts need to be made to reduce the resource inequalities, including the dearth of mental health professionals practicing outside of metropolitan cities. Recently, the National Mental Health Workforce Strategy Taskforce (the Strategy) was established to deliberate the quality, supply, distribution, structure, and methods to improve attracting, training, and retaining Australia’s mental health workforce [ 87 ]. The Consultation Draft of the Strategy highlights six objectives, including (1) careers in mental health are recognised as, attractive; (2) data underpins workforce planning; (3) the entire mental health workforce is utilised; (4) the mental health workforce is appropriately skilled; (5) the mental health workforce is retained in the sector; and (6) the mental health workforce is distributed to deliver support and treatment when and where consumers need it [ 88 ]. These objectives reflect the systemic resource issues cited in the current scoping review and emphasise the importance of a contemporary approach to increasing resources for mental health services in rural Australia. This contemporary approach is important, as it has previously been acknowledged that increasing graduates has not resolved workforce maldistribution in other areas of healthcare (i.e., medical physicians), but rather, an improved distribution of both human and other resources is needed [ 89 , 90 ].

For the service user, resource issues spanned both aspatial and spatial dimensions and include the affordability (i.e., perceived worth relative to cost) and accessibility of the service (i.e., the location of the service and ease of getting to that location) [ 12 , 13 ]. Transport issues were commonly reported to be a resource issue within the current review and the wider literature. Limited transport compounds access issues for specific subpopulations, such the elderly, particularly when they do not have personal transport and when there is no public transport available [ 50 ]. This issue is likely compounded by resource limitations, including the cost of travel, and is specifically related to spatial distance to services. Distance to services is a significant barrier to accessing healthcare. Wood et al. [ 91 ] in a systematic review, identified that there is a lack of research which measures spatial access specific to mental health services in Australia, and highlighted a need for consensus on what is reasonable access to healthcare services. Further, reports have noted that while distance alone is a significant barrier to accessing healthcare, accommodation may sometimes need to be sought depending on the time of the appointment, adding to the cost of attending the appointment [ 92 ] and further perpetuating the resource issues experienced by those living in rural areas of Australia. In addition, although not specifically reported in the current review, it is likely that the time required for traveling to and attending such appointments may require the individual to choose between tending to work or family needs or receiving the help needed.

Transport and other resource issues, as well as distance to services, may be mitigated through telehealth appointments, which have been central to the provision of healthcare since the beginning of the COVID-19 pandemic. However, the utilisation of telehealth requires many patients to have had a face-to-face consultation with their GP in the previous 12 months [ 93 ], which may preclude some Australians from rural areas from its use, considering the significant workforce maldistribution previously discussed. Moreover, rural areas of Australia also experience digital disadvantage as a result of lower internet connectivity — brought about by the high costs of installing internet infrastructure in rural and remote areas — and the socio-economic disadvantage experienced by those who live outside of metropolitan areas [ 94 ]. These issues are compounded by an ageing population, lower educational levels, a larger primary industry sector, a higher unemployment rate, and a higher Indigenous population in rural and remote Australia [ 94 ]. High cost, connectivity issues, and suitability for specific client groups should be key considerations in the delivery of technology-based mental health services. Notwithstanding these issues, the current review identified that technology-based services may be a useful adjunct to physical services, particularly in relation to reducing the need to travel, consultation immediacy, and clinician upskilling. This finding partially supports a recent systematic review, which found that youth located in rural and remote areas of Australia and Canada prefer to see mental health professionals in person, with telehealth provided as an additional option [ 95 ]. As such, the benefits and limitations to technology-based mental health services needs to be carefully considered by those designing services.

A key barrier to both access and utilisation in the current review was the complexity of using and navigating the mental health system. These issues typically occur at the system and organisation level and affect the way a service operates and its culture, making it challenging for service users to receive effective care. A complex mental health system and service fragmentation has been previously reported to lead to confusion and a lengthy amount time spent trying to navigate the system, with these issues being even greater amongst those who are younger, less autonomous, or who have less experience navigating the system [ 96 ]. System navigation initiatives may address this gap and have previously been implemented via the Partners in Recovery (PIR) program — established to facilitate care coordination for people with severe and persistent mental illness — with positive impacts for those who used the program [ 97 ]. However, the introduction of the National Disability Insurance Scheme has superseded the PIR program, and has rendered many former PIR program participants ineligible for support [ 98 , 99 ], representing a significant gap in mental health service navigation and care coordination support. Isaacs et al. [ 100 ], identified that it is more cost effective to support people with severe and persistent mental illness to access PIR supports than to not provide this support, due to the potential increased need for other services (e.g., hospital admissions, homelessness supports, residential supports). Indeed, the Australian Government’s Productivity Commission (Productivity Commission) recommended that life insurers should have greater flexibility to fund approved mental health services to reduce the likelihood of hospitalisation for mental health issues [ 101 ]. In addition, Isaacs et al. [ 100 ] reported that co-located services — which were reported as a facilitator in the current review — and the increased need of non-clinical support through mental health community support services, offered via non-governmental and not-for-profit organisations, were demonstrated to be important considerations for cost effective mental health care.

Attitudinal or social matters are frequently reported to be key barriers for rural Australians to accessing care and are considered to be an aspatial dimension [ 12 , 13 ]. These matters which include stigma, fear of judgement, stoicism, lack of trust, preference for keeping to oneself, and reluctance to seek help have been reported on the global scale as impacting upon help-seeking in rural areas in relation to rural identity [ 22 ]. Stoicism, in particular, is ordinarily viewed as a positive trait, with rural participants of a global review contextualising stoicism as an inflexible element to their core identity, however, this trait has repeatedly been reported as a barrier to the uptake of mental health services in this review [ 45 , 50 , 67 , 70 ] and in the wider literature [ 22 ]. In terms of addressing attitudinal and social matters, previous Australian research [ 16 ] has identified that intentions to seek help for a mental or emotional issue decreased with a higher classification of remoteness. Moreover, stoicism and attitudes towards seeking professional help were predictive of help-seeking intentions for participants from both rural and metropolitan areas, but sex, suicidality, and previous engagement with a mental health professional were additionally predictive of help-seeking intentions for rural Australians [ 16 ]. The current scoping review identified few studies that specifically reported on these issues in relation to barriers to accessing services [ 37 , 55 , 68 , 70 ], suggesting a need to increase research focus on these issues. Interestingly, Kaukiainen and Kõlves [ 16 ] study, found that attitudes towards seeking professional help mediated the relationship between stoicism and help-seeking intentions for participants from both rural and metropolitan locations, suggesting that attitudes towards seeking professional help may be a fruitful avenue to target to increase help-seeking intentions for all Australians [ 16 ]. Education programs delivered in secondary school or tertiary settings have been suggested as a way to improve attitudes towards help-seeking and stigma [ 102 ]. These avenues may also be useful to increase mental health literacy (i.e., the public knowledge and recognition of mental disorders and knowing where and how to seek help) [ 84 ] in the community, given that lack of awareness was a barrier and mental health literacy was a facilitator in the current review.

Providing person-centred and collaborative care was reported as a key facilitator in the current review. Person-centred care is generally defined as care that is holistic and incorporates the person’s context, individual expression, beliefs, and preferences, and includes families and caregivers, as well as prevention and promotion activities [ 103 ]. Indeed, person-centred care is a prominent practice model in mental health care, and this model of care may be particularly beneficial in rural Australia, given that it aims to decrease barriers between health service providers via shared knowledge. This model of care is collaborative by nature, although it should be noted that collaborative care is a distinct, though related model of care. Collaborative care refers to health professionals and patients working together to overcome a mental health problem [ 104 ]. This model of care has been shown to improve depression and anxiety outcomes across the short to long term (i.e., 0–24 months), and has benefits on medication use, patient satisfaction, and mental health quality of life [ 104 ]. The Productivity Commission recommended the trial of innovation funds to diffuse best practice in mental health service delivery and to eliminate practices that are no longer supported by evidence [ 101 ]. Such innovation funds may allow healthcare providers to maintain currency on practices such as person-centred and collaborative care. Importantly, the Royal Commission into Victoria’s Mental Health System (the Royal Commission) [ 90 ] identified person-centred care as a way to promote inclusion and prevent inequalities, and was specifically linked to providing culturally safe mental health care — which was noted as a facilitator to access and utilisation in the current review and has been highlighted as an important approach to eliminate health inequalities [ 105 ]. Moreover, the Royal Commission recommended the use of an integrated service approach — where service providers can work together to provide care [ 90 ]. This approach to care may mitigate service fragmentation and system complexity and navigation barriers, and also permit environments that are comfortable and allow ease of use — as identified as facilitators in the current review.

Community support, both in the sense of individuals feeling connected to the community and healthcare providers being seen within the community, was a key concept in the current review. For the service user, Johnson et al. [ 39 ] reported that accessing services under the scrutiny of the community was seen as a challenge, but that the community was also seen a source of strength. Crotty et al. [ 56 ] noted the duality for healthcare providers being involved with the community in both a social and professional sense, leading to both challenges and a feeling of togetherness. This sense of togetherness reflects the historical view that rural and remote communities have been connected over several generations [ 106 ]. Notably, in the current review, one study on healthcare provider perspectives on workforce retention reported that personal connections and a ‘natural’ connection to the community were key factors in the decision for staff working in remote areas to stay [ 33 ], suggesting the importance of embedded relationships in this setting. Preferences to stay in rural and remote towns have been associated with a sense of belonging and the quality of diverse and interesting activities, particularly for younger people [ 107 ], and these factors should be strengthened to permit the retention of the rural mental health workforce.

It is noteworthy that many of the studies were undertaken at metropolitan locations, suggesting that much of the research completed on rural locations was not necessarily conducted within this setting. However, it is acknowledged that many university locations are affiliated with major campuses, which are often located in metropolitan areas. Simultaneously, many rurally-based health and community services do not have the resources to undertake locally-generated research, and this consequently limits the evidence available for policymakers to make informed decisions regarding the health of the rural population — noting that place-based approaches are gaining traction [ 108 , 109 , 110 ]. This area is a key focus of the RHMT program [ 111 ]. The RHMT program aims to maximise investment in of Australia via academic networks, developing an evidence-base, and providing training in rural areas for health professionals. To date the RHMT program has seen that health graduates who undertook clinical placements in the most rural settings are working more in rural locations [ 112 ], and this is likely to have flow-on effects for healthcare providers to build connections to these areas, retain the workforce, and increase health outcomes for the community.

This review highlights the need for a contemporary approach to mental health services in rural Australia. This includes encouraging and educating the public about mental health issues and how to seek and engage in timely mental health care that is appropriate to one’s needs. Simultaneously, this review suggests a need to reconsider how the public navigates mental health services, and to redesign services that are easy to engage with, culturally safe, comfortable to use, and have technological capabilities. This may be more accurately achieved when services are designed with local issues and the community in mind via the integration of bottom-up place-based strategies and top-down place-sensitive approaches, particularly given that a one-size-fits-all approach to policy — and thus mental health service design — does not favour regions and localities [ 113 ]. It is critical that rural mental health services are invested in to remove barriers and improve health equity. The fiscal implications of such investment may be offset using this integrated approach, which leverages local and external assets, encourages workforce retention, and may reduce costs in other areas healthcare service delivery.

Strengths and limitations

The strengths of this scoping review include the use of peer-reviewed and grey literature, the full-span of the child-adult age range, and the wide variety of included studies. In addition, this scoping review applied a consistent approach to applying remoteness categories, albeit this application was not without issues. For example, Wand et al. [ 40 ] and Wand et al. [ 41 ] reports on work done in Maitland (MM1) and Dubbo (MM3). Maitland (NSW) is of particular interest in the context of remoteness settings as it has historically been described as a regional area. In the early 2000s when the Australian Bureau of Statistics was defining the most accessible category of the Accessibility/Remoteness Index of Australia (ARIA), Maitland (as well as other locations such as Wollongong, NSW and Geelong, Victoria) was included in the most accessible category [ 114 ].

Several limitations must also be considered. Firstly, many sources — particularly grey literature sources — included potentially relevant information; however, a lack of clear evidence that the data specifically pertained to those living in regional/rural/remote areas prevented many of these sources from being included. In addition, findings were limited by the available literature, especially among community service organisations, which have limited resources to generate research outputs. The search strategy was limited to 2012–2022 and did not include search terms specific to certain subgroups of the population who have been known to experience barriers to mental health services in rural areas (e.g., farmers and people from CALD backgrounds), and some search results may have been omitted as a result of this. It was not possible to discern whether findings related specifically to access or utilisation in many studies, and as such, a nuanced discussion of these dimensions is not provided. Further, the data were heterogeneous and results tended to be grouped across regional, rural, and/or remote contexts, precluding an analysis of the association between geographical area and barriers and facilitators from taking place. Future research may consider completing a comprehensive geographical analysis once additional data on the topic becomes available. Lastly, although data screening was completed by two reviewers, only one reviewer coded the extracted data into key concepts, and this may have introduced bias into the results, however the key concepts were agreed upon by the research team.

This scoping review found a number of barriers to accessing and utilising mental health services that may be overcome through initiatives that have been implemented or suggested by the government. Importantly, many of the spatial barriers associated with access and utilisation may be mitigated through innovative solutions, such as a combination of face-to-face and technology-based service provision, provided that careful consideration is given to the technological and resource limitations seen in the rural context of Australia. Parallel with this, several facilitators to accessing and utilising mental health services were noted, some of which may already be prominent in the provision of services, but could be further strengthened through additional training, service re-design, and community initiatives.

The included studies varied in their aim, setting, and study design, and many studies were grouped across MMM categories, disallowing a nuanced understanding of how barriers and facilitators operate within specific geographical contexts. This, paired with the finding that many studies were conducted at a metropolitan location, highlights the importance of conducting research within the rural setting. Additional research generated from rural areas, as well as consideration for how remoteness is measured, would assist in providing a more comprehensive understanding of the barriers and facilitators to mental health services within the geographic contexts they occur.

Data Availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Australian Capital Territory

Accessibility/Remoteness Index of Australia

Culturally and linguistically diverse

Cumulative Index of Nursing and Allied Health Literature

Emergency department

Full time equivalent

General practitioner

Lesbian, gay, bisexual, transgender, intersex, queer/questioning, asexual

Modified Monash Model

Population/concept/context

Primary Health Network

Partners in Recovery

Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews

New South Wales

Northern Territory

Rural Health Multidisciplinary Training

South Australia

Urgent care centre

Western Australia

5 References

Inder KJ, Berry H, Kelly BJ. Using cohort studies to investigate rural and remote mental health. Aust J Rural Health. 2011;19(4):171–8.

Article   PubMed   Google Scholar  

Versace VL, Skinner TC, Bourke L, Harvey P, Barnett T. National analysis of the modified Monash Model, population distribution and a socio-economic index to inform rural health workforce planning. Aust J Rural Health. 2021;29(5):801–10.

Australian Institute of Health and Welfare. Mental health workforce 2023 [Available from: https://www.aihw.gov.au/mental-health/topic-areas/workforce ].

Australian Department of Health. Modified Monash Model 2019 [Available from: https://www.health.gov.au/resources/publications/modified-monash-model-fact-sheetaccess ].

Australian Government. Deaths by suicide by remoteness areas. In: Australian Institute of Health and Welfare, editor.; 2021.

Rost K, Fortney J, Fischer E, Smith J. Use, quality, and outcomes of care for mental health: the rural perspective. Med Care Res Rev. 2002;59(3):231–65.

Fitzpatrick SJ, Perkins D, Luland T, Brown D, Corvan E. The effect of context in rural mental health care: understanding integrated services in a small town. Health Place. 2017;45:70–6.

Francis K. Health and health practice in rural Australia: where are we, where to from here? Online J Rural Nurs Health Care. 2012;5(1):28–36.

Article   Google Scholar  

Fuller J, Edwards J, Martinez L, Edwards B, Reid K. Collaboration and local networks for rural and remote primary mental healthcare in South Australia. Health Soc Care Commun. 2004;12(1):75–84.

Russell DJ, Humphreys JS, Ward B, Chisholm M, Buykx P, McGrail M, et al. Helping policy-makers address rural health access problems. Aust J Rural Health. 2013;21(2):61–71.

Australian Institute of Health and Welfare. Health workforce 2023 [Available from: https://www.aihw.gov.au/reports/workforce/health-workforce#rural ].

Penchansky R, Thomas JW. The concept of access: definition and relationship to consumer satisfaction. Med Care. 1981;19(2):127–40.

Article   PubMed   CAS   Google Scholar  

Khan AA. An integrated approach to measuring potential spatial access to health care services. Socio-Economic Plann Sci. 1992;26(4):275–87.

Article   CAS   Google Scholar  

Bourke L, Humphreys JS, Wakerman J, Taylor J. Understanding rural and remote health: a framework for analysis in Australia. Health Place. 2012;18(3):496–503.

Saurman E. Improving access: modifying Penchansky and Thomas’s theory of access. J Health Serv Res Policy. 2016;21(1):36–9.

Kaukiainen A, Kõlves K. Too tough to ask for help? Stoicism and attitudes to mental health professionals in rural Australia. Rural Remote Health. 2020;20(2):5399.

PubMed   Google Scholar  

Catherine C, Myfanwy M, Rafat H. Work challenges negatively affecting the job satisfaction of early career community mental health professionals working in rural Australia: findings from a qualitative study. J Mental Health Train Educ Pract. 2018;13(3):173–86.

Cosgrave C, Maple M, Hussain R. Work challenges negatively affecting the job satisfaction of early career community mental health professionals working in rural Australia: findings from a qualitative study. The Journal of Mental Health Training, Education and Practice; 2018.

Levesque J-F, Harris MF, Russell G. Patient-centred access to health care: conceptualising access at the interface of health systems and populations. Int J Equity Health. 2013;12(1):18.

Article   PubMed   PubMed Central   Google Scholar  

Liu C, Watts B, Litaker D. Access to and utilization of healthcare: the provider’s role. Expert Rev PharmacoEcon Outcomes Res. 2006;6(6):653–60.

Aisbett D, Boyd CP, Francis KJ, Newnham K. Understanding barriers to mental health service utilization for adolescents in rural Australia. Rural Remote Health. 2007;7(1):1–10.

Google Scholar  

Cheesmond NE, Davies K, Inder KJ. Exploring the role of rurality and rural identity in mental health help-seeking behavior: a systematic qualitative review. J Rural Mental Health. 2019;43(1):45–59.

Arksey H, O’Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. 2005;8(1):19–32.

Tricco AC, Lillie E, Zarin W, O’Brien KK, Colquhoun H, Levac D, et al. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med. 2018;169(7):467–73.

Kavanagh B, Beks H, Versace V, Quirk S, Williams L. Exploring the barriers and facilitators to accessing and utilising mental health services in regional, rural, and remote Australia: a scoping review protocol. PLoS ONE. 2022;17(12).

Australian Government Department of Health and Aged Care. Health workforce locator 2022 [Available from: https://www.health.gov.au/resources/apps-and-tools/health-workforce-locator ].

Versace VL, Beks H, Charles J. Towards consistent geographic reporting of australian health research. Med J Australia. 2021;215(11):525.

Beks H, Walsh S, Alston L, Jones M, Smith T, Maybery D et al. Approaches used to describe, measure, and analyze place of practice in Dentistry, Medical, nursing, and Allied Health Rural Graduate Workforce Research in Australia: a systematic scoping review. Int J Environ Res Public Health [Internet]. 2022; 19(3).

Veritas Health Innovation. Covidence systematic review software, Melbourne, Australia [Available from: www.covidence.org.

Munn Z, Peters MDJ, Stern C, Tufanaru C, McArthur A, Aromataris E. Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Med Res Methodol. 2018;18(1):143.

Barraclough F, Longman J, Barclay L. Integration in a nurse practitioner-led mental health service in rural Australia. Aust J Rural Health. 2016;24(2):144–50.

Cosgrave C, Maple M, Hussain R. Work challenges negatively affecting the job satisfaction of early career community mental health professionals working in rural Australia: findings from a qualitative study. J Mental Health Train Educ Pract. 2018;13(3):173–86.

Cosgrave C, Hussain R, Maple M. Retention challenge facing Australia’s rural community mental health services: service managers’ perspectives. Austr J Rural Health. 2015;23(5):272–6.

De Silva T, Prakash A, Yarlagadda S, Johns MD, Sandy K, Hansen V et al. General practitioners’ experiences and perceptions of mild moderate depression management and factors influencing effective service delivery in rural Australian communities: A qualitative study. International Journal of Mental Health Systems. 2017;11(1).

Dunstan DA, Todd AK, Kennedy LM, Anderson DL. Impact and outcomes of a rural personal helpers and mentors service. Aust J Rural Health. 2014;22(2):50–5.

Evans J, Horn K, Cowan D, Brunero S. Development of a clinical pathway for screening and integrated care of eating disorders in a rural substance use treatment setting. Int J Ment Health Nurs. 2020;29(5):878–87.

Handley TE, Kay-Lambkin FJ, Inder KJ, Lewin TJ, Attia JR, Fuller J et al. Self-reported contacts for mental health problems by rural residents: predicted service needs, facilitators and barriers. BMC Psychiatry. 2014;14.

Hussain R, Guppy M, Robertson S, Temple E. Physical and mental health perspectives of first year undergraduate rural university students. BMC Public Health. 2013;13:848.

Johnson S, Brough M, Darracott R. Unmasking depression: challenging structural oppression whilst recognising individual agency. Qualitative Social Work: Research and Practice. 2021;20(3):738–54.

Wand T, Collett G, Cutten A, Buchanan-Hagen S, Stack A, White K. Patient and staff experience with a new model of emergency department based mental health nursing care implemented in two rural settings. Int Emerg Nurs. 2021;57:N.PAG-N.PAG.

Wand T, Collett G, Keep J, Cutten A, Stack A, White K. Mental health nurses’ experiences of working in the emergency department of two rural australian settings. Issues Ment Health Nurs. 2021.

Weber M, Davis K. Food for thought: enabling and constraining factors for effective rural eating disorder service delivery. Aust J Rural Health. 2012;20(4):208–12.

Wilson RL, Cruickshank M, Lea J. Experiences of families who help young rural men with emergent mental health problems in a rural community in New South Wales, Australia. Contemp Nurse. 2012;42(2):167–77.

Batterham PJ, Kazan D, Banfield M, Brown K. Differences in mental health service use between urban and rural areas of Australia. Australian Psychol. 2020;55(4):327–35.

Clough BA, March S, Leane S, Ireland MJ. What prevents doctors from seeking help for stress and burnout? A mixed-methods investigation among metropolitan and regional-based australian doctors. J Clin Psychol. 2019;75(3):418–32.

Duggan M, Harris B, Chislett W-K, Calder R. Nowhere else to go: Why Australia’s health system results in people with mental illness getting ‘stuck’in emergency departments. 2020.

Hays C, Sparrow M, Taylor S, Lindsay D, Glass B. Pharmacists’ full scope of practice: knowledge, attitudes and practices of rural and remote australian pharmacists. J Multidisciplinary Healthc. 2020;13:1781–9.

Mirza T. First Australians deserve first-class psychiatric care: towards a better sociocultural understanding. Aust N Z J Psychiatry. 2019;53:66.

Mollah TN, Antoniades J, Lafeer FI, Brijnath B. How do mental health practitioners operationalise cultural competency in everyday practice? A qualitative analysis. BMC Health Serv Res. 2018;18(1):480.

Muir-Cochrane E, O’Kane D, Barkway P, Oster C, Fuller J. Service provision for older people with mental health problems in a rural area of Australia. Aging Ment Health. 2014;18(6):759–66.

Bowman S, Nic Giolla Easpaig B, Fox R. Virtually caring: a qualitative study of internet-based mental health services for LGBT young adults in rural Australia. Rural Remote Health. 2020;20(1):5448.

Butterfly Foundation. Maydays 2020 survey report: Barriers to accessing eating disorder healthcare & support. 2020. Available from: https://butterfly.org.au/get-involved/campaigns/maydays/

Mental Health Council of Tasmania. Submission to the Senate Community Affairs Reference Committee inquiry into accessibility and quality of mental health serices in rural and remote Australia. 2018.

National Rural Health Alliance. Mental health in rural and remote Australia. National Rural Health Alliance; 2017.

Black G, Roberts RM, Li-Leng T. Depression in rural adolescents: relationships with gender and availability of mental health services. Rural Remote Health. 2012;12(3):2092.

Crotty MM, Henderson J, Fuller JD. Helping and hindering: perceptions of enablers and barriers to collaboration within a rural South australian mental health network. Aust J Rural Health. 2012;20(4):213–8.

Dawson S, Gerace A, Muir-Cochrane E, O’Kane D, Henderson J, Lawn S, et al. Accessing mental health services for older people in rural South Australia. Australian Nurs Midwifery J. 2016;23(7):50.

Henderson J, Crotty MM, Fuller J, Martinez L. Meeting unmet needs? The role of a rural mental health service for older people. Adv Mental Health. 2014;12(3):182–91.

Henderson J, Dawson S, Fuller J, O’Kane D, Gerace A, Oster C, et al. Regional responses to the challenge of delivering integrated care to older people with mental health problems in rural Australia. Aging Ment Health. 2018;22(8):1025–31.

Newman L, Bidargaddi N, Schrader G. Service providers’ experiences of using a telehealth network 12 months after digitisation of a large australian rural mental health service. Int J Med Informatics. 2016;94:8–20.

Orlowski S, Lawn S, Antezana G, Venning A, Winsall M, Bidargaddi N, et al. A rural youth consumer perspective of technology to enhance face-to-face mental health services. J Child Fam stud. 2016;25(10):3066–75.

Orlowski S, Lawn S, Matthews B, Venning A, Wyld K, Jones G, et al. The promise and the reality: a mental health workforce perspective on technology-enhanced youth mental health service delivery. BMC Health Serv Res. 2016;16:562.

Orlowski S, Lawn S, Matthews B, Venning A, Jones G, Winsall M, et al. People, processes, and systems: an observational study of the role of technology in rural youth mental health services. Int J Ment Health Nurs. 2017;26(3):259–72.

Procter N, Ferguson M, Backhouse J, Cother I, Jackson A, Murison J, et al. Face to face, person to person: skills and attributes deployed by rural mental health clinicians when engaging with consumers. Aust J Rural Health. 2015;23(6):352–8.

Beks H, Healey C, Schlicht KG. When you’re it’: a qualitative study exploring the rural nurse experience of managing acute mental health presentations. Rural & Remote Health. 2018;18(3):1–11.

Isaacs AN, Maybery D, Gruis H. Mental health services for aboriginal men: mismatches and solutions. Int J Ment Health Nurs. 2012;21(5):400–8.

Isaacs AN, Maybery D, Gruis H. Help seeking by Aboriginal men who are mentally unwell: a pilot study. Early Intervent Psychiatry. 2013;7(4):407–13.

Isaacs AN, Sutton K, Hearn S, Wanganeen G, Dudgeon P. Health workers’ views of help seeking and suicide among Aboriginal people in rural Victoria. Aust J Rural Health. 2017;25(3):169–74.

Kidd T, Kenny A, Meehan-Andrews T. The experience of general nurses in rural australian emergency departments. Nurse Educ Pract. 2012;12(1):11–5.

Trail K, Oliffe JL, Patel D, Robinson J, King K, Armstrong G, et al. Promoting healthier masculinities as a suicide Prevention intervention in a Regional Australian Community: a qualitative study of stakeholder perspectives. Front Sociol. 2021;6:728170.

Byrne L, Happell B, Reid-Searl K. Acknowledging rural disadvantage in Mental Health: views of peer workers. Perspect Psychiatr Care. 2017;53(4):259–65.

Knight D, Plumb T, Gorey C. A STARR is born! A shining example of Integrated Care. Int J Integr Care. 2018;18:1–2.

Malatzky C, Bourke L, Farmer J. I think we’re getting a bit clinical here’: a qualitative study of professionals’ experiences of providing mental healthcare to young people within an australian rural service. Health & Social Care in the Community; 2020.

Onnis L-A, Kinchin I, Pryce J, Ennals P, Petrucci J, Tsey K. Evaluating the implementation of a Mental Health Referral Service connect to Wellbeing: a Quality Improvement Approach. Front Public Health. 2020;8:585933.

Taylor M, Kikkawa N, Hoehn E, Haydon H, Neuhaus M, Smith AC, et al. The importance of external clinical facilitation for a perinatal and infant telemental health service. J Telemed Telecare. 2019;25(9):566–71.

Richardson L, Reid C, Dziurawiec S. Going the extra mile’: satisfaction and alliance findings from an evaluation of videoconferencing telepsychology in rural western Australia. Australian Psychol. 2015;50(4):252–8.

Salinas-Perez JA, Gutierrez-Colosia MR, Furst MA, Suontausta P, Bertrand J, Almeda N, et al. Patterns of mental health care in remote areas: Kimberley (Australia), Nunavik (Canada), and Lapland (Finland). Can J Psychiatry / La Revue canadienne de psychiatrie. 2020;65(10):721–30.

Consumers of Mental Health WA. Accessibility and quality of mental health services in rural and remote Australia Submission 31. 2018. Available from: https://comhwa.org.au/resources-publications

Bridgman H, Ashby M, Sargent C, Marsh P, Barnett T. Implementing an outreach headspace mental health service to increase access for disadvantaged and rural youth in Southern Tasmania. Aust J Rural Health. 2019;27(5):444–7.

Reynish TD, Hoang H, Bridgman H, Nic Giolla Easpaig B. Mental health and related service use by sex workers in rural and remote Australia: ‘there’s a lot of stigma in society’. Culture, Health & Sexuality. 2021:1–16.

Hinton R, Kavanagh DJ, Barclay L, Chenhall R, Nagel T. Developing a best practice pathway to support improvements in indigenous Australians’ mental health and well-being: a qualitative study. BMJ Open. 2015;5(8).

Ellem K, Baidawi S, Dowse L, Smith L. Services to young people with complex support needs in rural and regional Australia: beyond a metro-centric response. Child Youth Serv Rev. 2019;99:97–106.

van Spijker BA, Salinas-Perez JA, Mendoza J, Bell T, Bagheri N, Furst MA, et al. Service availability and capacity in rural mental health in Australia: Analysing gaps using an integrated mental health atlas. Aust N Z J Psychiatry. 2019;53(10):1000–12.

Jorm AF. Mental health literacy: empowering the community to take action for better mental health. Am Psychol. 2012;67(3):231.

Solmi M, Radua J, Olivola M, Croce E, Soardo L, Salazar de Pablo G, et al. Age at onset of mental disorders worldwide: large-scale meta-analysis of 192 epidemiological studies. Mol Psychiatry. 2022;27(1):281–95.

Australian Government Australian Institute of Health and Welfare. Mental health services in Australia 2022 [Available from: https://www.aihw.gov.au/reports/mental-health-services/mental-health-services-in-australia/report-contents/mental-health-workforce ].

Australian Government Department of Health and Aged Care. National Mental Health Workforce Strategy Taskforce 2021 [Available from: https://www.health.gov.au/committees-and-groups/national-mental-health-workforce-strategy-taskforce ].

ACIL Allen. National Mental Health Workforce Strategy consultation draft. 2021. Available from: https://acilallen.com.au/uploads/media/NMHWS-ConsultationDraftStrategy-040821-1628234534.pdf

May JA, Scott A. The road less travelled: supporting physicians to practice rurally. Med J Aust. 2021;215(1):29–30.

State of Victoria. Royal Commission into Victoria’s Mental Health System. 2021.

Wood SM, Alston L, Beks H, Mc Namara K, Coffee NT, Clark RA, et al. The application of spatial measures to analyse health service accessibility in Australia: a systematic review and recommendations for future practice. BMC Health Serv Res. 2023;23(1):330.

Mental Health Council of Tasmania. Submission to Legislative Council Inquiry into Rural Health Services: Access to timely and appropriate mental health care in rural and remote Tasmanian communities. 2021.

Australian Government Department of Health and Aged Care. Providing health care remotely during the COVID-19 pandemic 2022 [Available from: https://www.health.gov.au/health-alerts/covid-19/coronavirus-covid-19-advice-for-the-health-and-disability-sector/providing-health-care-remotely-during-the-covid-19-pandemic ].

Park S. Digital inequalities in rural Australia: a double jeopardy of remoteness and social exclusion. J Rural Stud. 2017;54:399–407.

Mseke EP, Jessup B, Barnett T. A systematic review of the preferences of rural and remote youth for mental health service access: Telehealth versus face-to‐face consultation. Aust J Rural Health. 2023.

Robards F, Kang M, Steinbeck K, Hawke C, Jan S, Sanci L, et al. Health care equity and access for marginalised young people: a longitudinal qualitative study exploring health system navigation in Australia. Int J Equity Health. 2019;18(1):41.

Stewart V, Slattery M, Roennfeldt H, Wheeler AJ. Partners in recovery: paving the way for the National Disability Insurance Scheme. Aust J Prim Health. 2018;24(3):208–15.

Consortia HaLMMPiR. Submission to the joint standing committee on the NDIS: The provision of services under the NDIS for people with psychosocial disabilities related to mental health conditions. Joint submisson by the Hume and Loddon Mallee Murray Partners in Recovery Consortia. 2017.

Hancock N, Smith-Merry J, Gillespie JA, Yen I. Is the Partners in Recovery program connecting with the intended population of people living with severe and persistent mental illness? What are their prioritised needs? Aust Health Rev. 2016;41(5):566–72.

Isaacs AN, Dalziel K, Sutton K, Maybery D. Referral patterns and implementation costs of the Partners in Recovery initiative in Gippsland: learnings for the National Disability Insurance Scheme. Australasian Psychiatry. 2018;26(6):586–9.

Productivity Commission. 5-year Productivity Inquiry: Advancing Prosperity. Canberra., ; 2023. Contract No.: Inquiry Report no. 100. Available from: https://www.pc.gov.au/inquiries/completed/productivity/report

Mehta N, Clement S, Marcus E, Stona A-C, Bezborodovs N, Evans-Lacko S, et al. Evidence for effective interventions to reduce mental health-related stigma and discrimination in the medium and long term: systematic review. Br J Psychiatry. 2015;207(5):377–84.

Article   PubMed   PubMed Central   CAS   Google Scholar  

Santana MJ, Manalili K, Jolley RJ, Zelinsky S, Quan H, Lu M. How to practice person-centred care: a conceptual framework. Health Expect. 2018;21(2):429–40.

Archer J, Bower P, Gilbody S, Lovell K, Richards D, Gask L et al. Collaborative care for depression and anxiety problems. Cochrane Database of Systematic Reviews. 2012(10).

Curtis E, Jones R, Tipene-Leach D, Walker C, Loring B, Paine S-J, et al. Why cultural safety rather than cultural competency is required to achieve health equity: a literature review and recommended definition. Int J Equity Health. 2019;18(1):174.

Wainer J, Chesters J. Rural mental health: neither romanticism nor despair. Aust J Rural Health. 2000;8(3):141–7.

Pretty GH, Chipuer HM, Bramston P. Sense of place amongst adolescents and adults in two rural australian towns: the discriminating features of place attachment, sense of community and place dependence in relation to place identity. J Environ Psychol. 2003;23(3):273–87.

Alston L, Bourke L, Nichols M, Allender S. Responsibility for evidence-based policy in cardiovascular disease in rural communities: implications for persistent rural health inequalities. Aust Health Rev. 2020;44(4):527–34.

Alston L, Versace VL. Place-based research in small rural hospitals: an overlooked opportunity for action to reduce health inequities in Australia? Lancet Reg Health–Western Pac. 2023;30.

Alston L, Field M, Brew F, Payne W, Aras D, Versace VL. Addressing the lack of research in rural communities through building rural health service research: establishment of a research unit in Colac, a medium rural town. Aust J Rural Health. 2022;30(4):536.

Walsh S, Lyle DM, Thompson SC, Versace V, Browne LJ, Knight S et al. The role of national policies to address rural allied health, nursing and dentistry workforce maldistribution. 2020.

Australian Government Department of Health and Aged Care. Rural Health Multidisciplinary Training (RHMT) program 2022 [Available from: https://www.health.gov.au/our-work/rhmt ].

Sotarauta M. Place-based policy, place sensitivity and place leadership. Working paper 46/2020: Tampere University; 2020.

Australian Bureau of Statistics. ABS views on remoteness 2001 2001 [Available from: https://www.ausstats.abs.gov.au/ausstats/free.nsf/0/FCC8158C 85424727CA256C0F000035 75/$File/12440_2001.pdf.

Batterham PJ, Calear AL, Christensen H, Carragher N, Sunderland M. Independent effects of mental disorders on suicidal behavior in the community. Suicide and Life-Threatening Behavior. 2018;48(5):512–21.

Australian Institute of Health and Welfare. Emergency department care 2017–18: Australian hospital statistics Canberra: Australian Institute of Health and Welfare; 2018 [Available from: https://www.aihw.gov.au/getmedia/9ca4c770-3c3b-42fe-b071-3d758711c23a/aihw-hse-216.pdf.aspx?inline=true ].

Mental Health Services Australia A. [Available from: https://mhsa.aihw.gov.au/services/medicare/ ].

Download references

Acknowledgements

Not applicable.

BEK, HB, and VLV are funded by the Rural Health Multidisciplinary Training (RHMT) program. LJW is supported by a National Health and Medical Research Council (NHMRC) Emerging Leadership Fellowship [1174060].

Author information

Authors and affiliations.

Deakin Rural Health, School of Medicine, Deakin University, Princes Highway, Warrnambool, VIC, 3280, Australia

Bianca E. Kavanagh, Hannah Beks & Vincent L. Versace

Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Deakin University, Barwon Health, Geelong, VIC, Australia

Kayla B. Corney, Lana J. Williams & Shae E. Quirk

Institute of Clinical Medicine, Psychiatry, University of Eastern Finland, Kuopio, Finland

Shae E. Quirk

Institute of Clinical Medicine, Kuopio Musculoskeletal Research Unit (KMRU), University of Eastern Finland, Kuopio, Finland

You can also search for this author in PubMed   Google Scholar

Contributions

BEK conceptualised the research question; completed the search, data screening, extraction, and analysis; and wrote the original draft of this manuscript. KBC contributed to data screening and extraction. HB and VLV assisted with the geographical analysis. All authors edited and approved the final version of this manuscript.

Corresponding author

Correspondence to Bianca E. Kavanagh .

Ethics declarations

Ethics approval and consent to participate.

As this scoping review utilised published literature only, ethics approval and consent to participate was not required.

Consent for publication

Competing interests.

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Additional Table 1: Search strategy for Medline Complete via EBSCO

Additional table 2: charting form used for data extraction, 12913_2023_10034_moesm3_esm.docx.

Additional Table 3: Barriers and/or facilitators of access and/or utilisation factors in regional, rural, and remote Australia

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Kavanagh, B.E., Corney, K.B., Beks, H. et al. A scoping review of the barriers and facilitators to accessing and utilising mental health services across regional, rural, and remote Australia. BMC Health Serv Res 23 , 1060 (2023). https://doi.org/10.1186/s12913-023-10034-4

Download citation

Received : 15 May 2023

Accepted : 14 September 2023

Published : 04 October 2023

DOI : https://doi.org/10.1186/s12913-023-10034-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Mental health
  • Rural health
  • Mental health services
  • Rural Health Services

BMC Health Services Research

ISSN: 1472-6963

descriptive research design about mental health

  • Research article
  • Open access
  • Published: 13 March 2024

Evidence linking COVID-19 and the health/well-being of children and adolescents: an umbrella review

  • Chengchen Duan   ORCID: orcid.org/0009-0008-1380-0417 1   na1 ,
  • Liu Liu   ORCID: orcid.org/0000-0001-8681-3413 1 , 2   na1 ,
  • Tianyi Wang   ORCID: orcid.org/0000-0002-0402-3707 1   na1 ,
  • Guanru Wang 1 , 3 ,
  • Zhishen Jiang 1 ,
  • Honglin Li 1 , 3 ,
  • Gaowei Zhang 1 , 3 ,
  • Li Ye 1 , 3 ,
  • Chunjie Li 1 , 3 , 5 &
  • Yubin Cao   ORCID: orcid.org/0000-0001-8553-1430 1 , 4 , 5  

BMC Medicine volume  22 , Article number:  116 ( 2024 ) Cite this article

22 Accesses

2 Altmetric

Metrics details

Experiences during childhood and adolescence have enduring impacts on physical and mental well-being, overall quality of life, and socioeconomic status throughout one’s lifetime. This underscores the importance of prioritizing the health of children and adolescents to establish an impactful healthcare system that benefits both individuals and society. It is crucial for healthcare providers and policymakers to examine the relationship between COVID-19 and the health of children and adolescents, as this understanding will guide the creation of interventions and policies for the long-term management of the virus.

In this umbrella review (PROSPERO ID: CRD42023401106), systematic reviews were identified from the Cochrane Database of Systematic Reviews; EMBASE (OvidSP); and MEDLINE (OvidSP) from December 2019 to February 2023. Pairwise and single-arm meta-analyses were extracted from the included systematic reviews. The methodological quality appraisal was completed using the AMSTAR-2 tool. Single-arm meta-analyses were re-presented under six domains associated with COVID-19 condition. Pairwise meta-analyses were classified into five domains according to the evidence classification criteria. Rosenberg’s FSN was calculated for both binary and continuous measures.

We identified 1551 single-arm and 301 pairwise meta-analyses from 124 systematic reviews that met our predefined criteria for inclusion. The focus of the meta-analytical evidence was predominantly on the physical outcomes of COVID-19, encompassing both single-arm and pairwise study designs. However, the quality of evidence and methodological rigor were suboptimal. Based on the evidence gathered from single-arm meta-analyses, we constructed an illustrative representation of the disease severity, clinical manifestations, laboratory and radiological findings, treatments, and outcomes from 2020 to 2022. Additionally, we discovered 17 instances of strong or highly suggestive pairwise meta-analytical evidence concerning long-COVID, pediatric comorbidity, COVID-19 vaccines, mental health, and depression.

Conclusions

The findings of our study advocate for the implementation of surveillance systems to track health consequences associated with COVID-19 and the establishment of multidisciplinary collaborative rehabilitation programs for affected younger populations. In future research endeavors, it is important to prioritize the investigation of non-physical outcomes to bridge the gap between research findings and clinical application in this field.

Peer Review reports

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been spreading globally for more than 3 years [ 1 , 2 ]. As of April 20, 2023, there have been over 765 million confirmed cases and over 6.9 million deaths reported worldwide [ 3 ]. COVID-19 has had varied effects on the health of children and adolescents, both directly and indirectly. COVID-19 infection can cause symptoms and impact the physical health of young people, affecting multiple organ systems directly [ 4 , 5 , 6 ]. Additionally, the policies implemented during the pandemic, as well as the preventive measures aimed at reducing the direct impact of COVID-19, often give rise to indirect consequences for children and adolescents. These indirect effects of COVID-19 have a disruptive impact on routine healthcare services and social interactions, which can further exacerbate mental and cognitive health challenges and worsen existing health disparities among this vulnerable population [ 7 , 8 ]. Child and adolescent health refer to the physical, mental/cognitive, quality of life, and social well-being, of individuals from newborns until the age of 19. Experiences during childhood and adolescence have enduring impacts on physical and mental health, quality of life, and socioeconomic status over the lifespan [ 9 ]. Consequently, exploring the subsequent effects of COVID-19 on the health of children and adolescents has the potential to influence the future provision and design of comprehensive services for those affected by COVID‐19. By gaining insights into an individual’s informational, spiritual, psychological, social, and physical requirements during follow-up phases, personalized services can be developed to enhance the survivor experience. This endeavor plays a vital role in establishing a resilient and prosperous healthcare system that benefits both individuals and society.

Currently, the World Health Organization (WHO) has declared that the global health emergency caused by COVID-19 has ended. This highlights the need to transition from an emergency response to the long-term management of COVID-19 and other infectious diseases [ 10 , 11 ]. Even after the emergency phase concludes, the ongoing transmission and emergence of new COVID-19 variants, as well as the remaining unvaccinated younger individuals and the significant global impact on health inequity, societal consequences, and economic repercussions, collectively emphasize the importance of continually assessing the available evidence on the correlation between COVID-19 and the health of children and adolescents. This assessment will inform stakeholders, including patients, healthcare providers, and policymakers, to mitigate conflicting effects and prioritize resources, interventions, and policies.

During the first year of the pandemic, a study analyzed all 6338 pediatric emergency admissions in England related to COVID-19 and found that adolescents have a higher likelihood of being hospitalized due to COVID-19 compared to younger children [ 12 ]. Surveys conducted among 13,002 American and 11,681 Chinese adolescents showed a similar 1-year prevalence of clinically significant depressive and anxiety symptoms during the COVID-19 pandemic [ 13 , 14 ]. These nationally representative studies, conducted with large sample sizes, are commonly regarded as robust evidence to establish a link between COVID-19 and child and adolescent health across diverse domains and time periods. However, the changing public health policies of COVID-19 and the emergence of new viral strains could introduce complexities and inconsistencies in the overall evidence [ 15 , 16 ]. In addition, many primary studies examining the relationship between COVID-19 and the health of children and adolescents used convenience sampling, including cross-sectional and observational designs that lacked control or comparison groups. The meta-analytical estimates from these studies may not accurately represent the true effects of the disease, as they are prone to biases such as measurement errors, poor control of confounders, biased participant selection, and data publication issues, ultimately weakening the strength of the aggregated scientific evidence [ 17 ]. The emergence of meta-analytical evidence through rapid reviews, compared to formal systematic reviews, further complicates this issue due to inadequate reporting of evidence, limited literature search, and increased publication bias [ 18 ].

The umbrella review, which involves quantifying systematic reviews and meta-analyses, provides a comprehensive assessment that captures the most extensive and high-quality medical evidence available [ 19 ]. By utilizing umbrella reviews, studies have reported evidence on the characteristic features of COVID-19 in children and adolescents during the initial phase of the pandemic [ 20 ], as well as the epidemiological impact and associations with mental health problems among this demographic [ 21 , 22 ]. Although these studies to some extent synthesized evidence on various factors influencing pediatric health outcomes during the COVID-19 pandemic, they fell short of providing a comprehensive perspective on the diverse array of health and well-being outcomes among children and adolescents. Moreover, the conclusions drawn from these umbrella reviews lack an assessment based on evidence grading criteria, neglecting the systematic grading of the evidence obtained from studies. This oversight regarding the overall strength of evidence could potentially limit the credibility of the conclusions presented in umbrella reviews. Therefore, this study aims to conduct an umbrella review to evaluate the strength of meta-analytic estimates and summarize the current evidence linking direct and indirect impacts of COVID-19 to the health/well-being of children and adolescents. Furthermore, we intend to explore the potential impact of future research on the conclusions drawn from existing significant meta-analyses.

Protocol and reporting

The protocol of this umbrella review was prospectively defined and registered on the PROSPERO [ 23 ] website (ID: CRD42023401106) ( https://www.crd.york.ac.uk/PROSPERO/ ). The differences between registered protocol and review were provided in Additional file 1 . This review is reported according to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) 2020 statement guidelines and a PRISMA checklist is included (Additional file 2 ) [ 24 ].

Study search and selection

We performed a comprehensive systematic literature search without any restrictions on the date or language of publication. Three key electronic databases including the Cochrane Database of Systematic Reviews (CDSR) via The Cochrane Library; EMBASE (OvidSP) and MEDLINE (OvidSP) were searched from December 2019 to February 2023. Moreover, the Google Scholar and WHO database of publications on COVID-19 and reference lists of included studies were also searched manually to identify reports of additional studies. We merged keywords and subject headings appropriately for each database using the following search terms: (COVID-19 [MeSH] OR 2019-nCoV.m.p. OR SARS-CoV-2.m.p. OR novel coronavirus pneumonia.m.p.) AND (pediatrics [MeSH] OR pediatrics.m.p. OR neonate.m.p. OR children.m.p. OR adolescence.m.p. OR teenagers.m.p.) AND (meta-analysis [MeSH] OR systematic review.m.p.) (Additional file 3 ). Two independent authors (C.D. and T.W.) carried out the electronic database search and decided the final inclusion according to the following criteria: (1) systematic reviews with meta-analysis; (2) results from children and adolescents between 0 and 19 years old; (3) observing COVID-19 as the exposure. Full texts were obtained and independently assessed for eligibility if certain studies seemed to have any potentiality for inclusion if they could not be judged completely by titles and abstracts. Any disagreements were settled by consulting a third review author (L.L.). Observational studies, intervention studies, other types of reviews (descriptive, scoping), program evaluations, animal studies, conference abstracts, and letters/comments were excluded from the review.

Data extraction

Two independent reviewers (C.D. and L.L.) screened the titles and abstracts, assigning unique identification numbers to all the included articles. Two authors (C.D. and T.W.) independently extracted the necessary data from each eligible review through a pre-designed extraction table and resolved any disagreements by discussion with a third reviewer (L.L.). Pooled estimates, including prevalence, odds ratio (OR), relative risk (RR), hazard ratio (HR), and standard mean difference (SMD), were extracted from each systematic review for all eligible health and well-being outcomes. The pre-designed extraction table included study identification (authors, year, and origin country), number of studies and participants included in the meta-analysis, outcome domain (physical, psychological/cognitive, quality of life, social, and health system), direct or indirect impact(s), COVID-19 condition(s) being assessed, health and well-being condition(s) of children and adolescents being assessed, methodological quality tool used, effect size and 95% CI, heterogeneity ( I 2 statistic), and publication bias assessment. We defined the “direct effects” as the consequences that directly correlate with COVID-19 infection or transmission, specifically within outcome domains. On the other hand, the “indirect effects” encompassed the broader consequences that arise from the pandemic, as well as the public health or political regulations associated with it. Furthermore, two senior researchers (Z.J. and G.W.), specializing in epidemiology and disease prevention, critically reviewed both the methodology and the coding results.

To address missing data, we initially reached out to the authors of the meta-analytical studies in an attempt to acquire the missing information directly from the original research teams. If the pooled estimates were not provided and no response was received from the authors, the entire row of data was excluded without any further statistical transformations [ 25 ]. In cases where the statistical significance of the combined effect in the meta-analysis was determined using Z -tests but did not include reported P -values, we calculated the corresponding P -values based on the respective Z -value [ 26 ]. All data domains were verified to be free of missing values through the aforementioned processes.

Methodological quality appraisal, evidence grading, and presentation

Methodological quality of the systematic review will be made using the A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR-2) [ 27 ] tool by two examiners (C.D. and T.W.). In this sense, systematic reviews are categorized as: High (Zero or one non-critical weakness); Moderate (More than one non-critical weakness); Low (One critical flaw with or without non-critical weaknesses); and Critically Low (More than one critical flaw with or without non-critical weaknesses).

For pairwise meta-analytical evidence, statistical quality was assessed by applying the previously published evidence grading protocol [ 28 , 29 ]. Significant associations shown in meta-analyses were categorized into four evidence levels: strong, highly suggestive, suggestive, and weak evidence. Strong evidence was considered if all the following criteria were met: > 1000 cases included in the meta-analysis; a P -value ≤ 10 −6 of statistical significance in valid meta-analysis; heterogeneity ( I 2 ) below 50%; the null value was excluded by the 95% prediction interval; and no evidence of small study effects and excess significance bias. Highly suggestive evidence was set if meta-analyses with > 1000 cases; a random effects P -value ≤ 10 −6 , and the largest study in the meta-analysis was statistically significant. Suggestive evidence was defined if meta-analyses with > 1000 cases, random effects P -value ≤ 10 −3 were categorized. If the latter conditions were not verified, the meta-analysis was classified as weak evidence. The classifications were subgrouped based on health domains, and the results were tabulated accordingly: the main focus of interest for this study encompassed the direct and indirect impacts associated with COVID-19, which included physical, psychological/cognitive, quality of life, and social impacts. The data was compared by considering the evidence grade and subgroups, and various methods such as counting and clustering were employed.

For single-arm meta-analytical evidence, six pre-defined COVID-19 condition domains were created: laboratory-confirmed COVID-19, COVID-19-associated MIS-C, newborns from COVID-19-diagnosed mothers, long-COVID, events caused by the COVID-19 vaccine, and health impacts during the pandemic. The domain of newborns from COVID-19 diagnosed mothers is exclusively limited to infants. The remaining domains, however, encompass children and adolescents aged 0–19 years old. Summarizations were conducted under each domain using all relevant meta-analytical evidence regardless of topic overlap to present and describe the current body of systematic review evidence on impacts of COVID-19 on children and adolescents. The most meta-analytical evidence was centered around laboratory-confirmed COVID-19. It is important to acknowledge that data on patient disease presentations collected during the early stages of the COVID-19 pandemic may differ significantly from those observed in later phases. Nonetheless, the effect summaries and publication years of original meta-analyses may not accurately capture these variations. To examine the changing trends in the occurrence rates of various symptoms during the pandemic, taking into account viral strain evolution and diverse health interventions, we conducted additional reanalysis of primary studies in this domain. Specifically, we screened and extracted relevant information from the primary studies included in each systematic review, including details of the authors, data collection years, outcome indicators, number of events, and sample sizes. Subsequently, we removed duplicated evidence and reanalyzed the primary data reported for at least 2 years within the meta-analytical evidence. To account for heterogeneity among the included studies, a random effects model was used to combine the primary data outcomes if Q  < 0.05 or I 2  > 50% [ 30 ]. Alternatively, a fixed-effects model was applied to pool outcomes if these criteria were not met [ 30 , 31 ].

We adhered to the presentation guidelines outlined in the Cochrane Handbook for Systematic Reviews of Interventions to effectively present our current work [ 25 ]. To present pairwise meta-analytical evidence, we initially employed the “summarizing outcome data” [ 25 ] strategy. This strategy enabled us to systematically summarize the meta-analyzed data, along with the previously mentioned quality assessments, without considering any overlap in study topics. By doing so, we were able to provide a comprehensive overview of the current body of evidence from systematic reviews on the study topic. To present single-arm meta-analytical evidence, we also utilized the “summarizing outcome data” strategy to offer a comprehensive perspective on the available evidence. Additionally, we conducted a “reanalyzing outcome data” [ 25 ] specifically for primary studies of laboratory-confirmed COVID-19. This reanalysis aided in the elimination of duplicated primary studies and standardized the collection years of data. As a result, we achieved a more coherent and consistent presentation of disease severity, clinical manifestations, laboratory and radiological findings, treatments, and outcomes associated with laboratory-confirmed COVID-19 across different years.

Calculations of FSN

The Rosenberg’s FSN is the number of missing studies averaging a z -value of zero that should be added to make the combined effect size statistically insignificant. For statistically significant meta-analytic evidence, Rosenberg’s FSN was calculated using the workbook “Meta-Essentials” [ 32 ] for binary and continuous measures.

Data handling and processing

All the data were collected using MS Office 365. Data processing and statistical analysis were conducted in the R programming environment (version 4.1.0). The “bibliometrix” package (version 4.1.2) was employed to perform bibliometric analysis on the included studies, following its standard analyzing protocol [ 33 ]. The “meta” package (version 6.2.1) was used for statistical transformation and reanalysis of the primary studies from single-arm meta-analytical evidence [ 34 ]. To visualize the reanalyzed data, the “forestploter” package (version 1.1.2) was utilized ( https://github.com/cran/forestploter ). Data table formatting and cleaning were achieved through the utilization of the “tidyverse” (version 1.3.1) and “reshape2” packages (version 1.4.4) [ 35 , 36 ].

Selection and characteristics of the included meta-analyses

We retrieved a total of 1100 records from databases and registers (Fig.  1 ). After removing duplicates ( n  = 87), the title and abstract of 1013 records were screened against including criteria, and 814 records were excluded. Cohen’s kappa coefficient for title and abstract screening was 0.97 (95% CI 0.95–0.99). The full-text analysis was conducted on the remaining 199 records, 76 records were excluded, and 1 additional record was added through citation searching of reference lists. The list of excluded studies with reasons for exclusion is detailed in Additional file 4 . Cohen’s kappa coefficient for full-text screening was 0.93 (95% CI 0.86–0.94), confirming excellent inter-examiner reliability. Ultimately, 124 systematic reviews with meta-analyses were included for data extraction and further analysis (Additional file 5 ) [ 4 , 6 , 20 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 ]. Cohen’s kappa coefficient for data extraction was 0.90 (95% CI 0.89–0.91).

figure 1

The PRISMA flowchart. This flow diagram provides a visual summary of the screening and selection processes, illustrating the number of articles recorded at each different stage

All the included systematic reviews were published in 2020–2023. There was an increased trend of publishing relevant systematic reviews (Fig.  2 a). The top 15 most cited journals in the field of interest are shown in Fig.  2 b, in which 5 journals are multidisciplinary, 7 journals are focusing on pediatrics, and 3 journals are focusing on infectious disease and virology. Based on the number and relationship of publications in each country, a collaborative network was constructed and visualized (Fig.  2 c). China, the USA, Australia, India, and the UK shared most collaborations.

figure 2

Bibliometrics for included systematic reviews. a Number of included publications by years. b Top 15 most cited journals in the field of interest. c The geographical collaborative distribution of included systematic reviews

Most included studies adhered to PRISMA guidelines ( n  = 99, 78.6%), followed by Meta-analyses of Observational Studies in Epidemiology (MOOSE) guidelines ( n  = 12, 9.5%) or a combination of multiple reporting guidelines ( n  = 9, 7.1%). However, a small portion of studies ( n  = 7, 7.9%) did not report following any systematic review reporting guidelines. To assess methodological quality, the Newcastle–Ottawa Scale (NOS) was used in most studies ( n  = 36, 28.6%), followed by the National Institutes of Health (NIH) Quality Assessment Tool ( n  = 14, 11.1%) and Joanna Briggs Institute (JBI) tools ( n  = 13, 10.3%).

In addition to encompassing the field of neonates for COVID19-diagnosed mothers, other domains include children and adolescents aged 0–19 years. We also explicitly indicate the age group sources of the relevant evidence for each subset within these domains. The descriptive characteristics of included meta-analyses under five major outcome domains (physical, psychological/cognitive, quality of life, social, and health system) are summarized in Tables  1 and  2 . For pre-defined COVID-19 condition domains, the six domains were not evenly distributed: most topics focused on laboratory-confirmed infections ( n  = 60; 48.4%), followed by health impacts during the pandemic ( n  = 21; 16.9%), adverse events (AEs) caused by the COVID-19 vaccine ( n  = 20; 16.1%), COVID-19 associated multisystem inflammatory syndrome (MIS-C) ( n  = 15; 12.1%), newborns from diagnosed mothers ( n  = 6; 4.8%), and long-COVID ( n  = 2; 1.6%).

Methodological quality assessment

The Cohen kappa score for the AMSTAR-2 assessments was 0.89 (95% CI 0.83–0.91). No meta-analysis gained high overall confidence for methodological quality, 1 with moderate (0.8%), 18 studies were scored as low quality (14.5%), and 105 studies presented as critically low quality (84.7%) (Additional file 6 ). For critical flaws, most studies did not report a list of excluded studies and justify the exclusions ( n  = 116, 93.5%). In addition, inadequate accounting for the risk of bias (RoB) in primary studies when interpreting/discussing the results ( n  = 92, 74.2%), lacking report review methods as a priori ( n  = 60, 48.4%), and neglecting publication bias analysis during conducting relevant meta-analyses ( n  = 22, 17.7%) were also evident critical flaws. Most included studies have non-critical flaws such as lacking reports on the sources of funding ( n  = 115, 92.7%), inadequate assessment of the impact of individual RoB when performing evidence synthesis ( n  = 105, 84.7%), inadequate discussion of heterogeneity ( n  = 80), and lacking statements of the study designs for inclusion ( n  = 50, 40.3%).

COVID-19-related evidence from single-arm meta-analyses

In total, 1551 meta-analytical comparisons were included in this umbrella review. These single-armed meta-analyses commonly utilized prevalence as effect size ( n  = 1464; 94.4%). Figures  3 and  4 present a comprehensive overview based on the reanalysis of primary data (Additional file 7 ) on the disease severity, clinical manifestations, laboratory and radiological findings, treatments, and outcomes related to laboratory-confirmed COVID-19.

figure 3

Forest plot for disease severity, and clinical manifestation associated with single-arm meta-analytical evidence of laboratory-confirmed COVID-19. Data are presented as effect size (ES) with 95% confidence intervals (CI). NA not available

figure 4

Forest plot for laboratory findings, radiological findings, treatment, and outcomes associated with single-arm meta-analytical evidence of laboratory-confirmed COVID-19. Data are presented as effect size (ES) with 95% confidence intervals (CI). SAA serum amyloid A, PCT procalcitonin, LDH lactate dehydrogenase, LFTs liver function tests, CK-MB creatine kinase-MB, IL-6 interleukin-6, ALT alanine transaminase, BNP brain natriuretic peptide, CRP C-reactive protein, AST aspartate aminotransferase, CT computed tomography, ECMO extracorporeal membrane oxygenation, ICU intensive care unit, NA not available

Disease severity

In the past 3 years, mild symptoms consistently remained the primary manifestation of the disease, with a prevalence of approximately 50%. In contrast, the prevalence of severe and critical symptoms consistently stayed below 15% over the same period, showing a declining trend year by year. Notably, there was an upward trend in the prevalence of asymptomatic cases. In 2020, the percentage was 29.0% (95% CI 24.0–33.0%), which increased to 34.0% (95% CI 28.0–39.0%) in 2021, and further increased to 45.0% (95% CI 21.0–69.0%) in 2022.

Clinical manifestations

Fever consistently emerged as the most frequently reported symptom over the past 3 years, with a prevalence close to 50%. Concurrently, respiratory symptoms, primarily cough, also sustained a prevalence exceeding 30% throughout this period. Noteworthy patterns emerged in 2020, indicating a higher incidence of hematologic symptoms such as anemia, lymphocytosis, lymphocytopenia, neutropenia, thrombocytopenia, and thrombocytosis, with prevalence rates ranging from 22 to 46%. Subsequent observations in 2021 revealed a more frequent occurrence of low oxygen saturation (46%, 95% CI 23.0–70.0%) compared to preceding years. However, conjunctivitis (50.0%, 95% CI 31.0–69.0%) and rhinorrhea (32.0%, 95% CI 0–80.0%) appeared to be more prevalent in 2022. Conversely, cardiovascular and neurologic symptoms exhibited considerably lower combined prevalence rates of 4.0% (95% CI 0–9.0%) and 3.0% (95% CI 1.0–5.0%), respectively.

Laboratory findings

Most laboratory results were reported in studies conducted between 2020 and 2021. In 2020, there seemed to be a more pronounced prevalence of abnormal laboratory markers, with abnormalities observed in fibrinogen, troponin, ferritin, SAA, BNP, ESR, and albumin, each surpassing 40%. Contrastingly, by 2021, the prevalence of albumin, troponin, BNP, and SAA abnormalities did not exceed 6%. In 2022, abnormalities in D-dimer, PCT, and LDH became more prevalent, surpassing the threshold of 40%.

Radiological findings

In 2021 and 2022, normal CT scans and lung chest radiographs exhibited a high prevalence of 65.0% (CI 52.0–77.0%) and 54.0% (CI 35.0–72.0%), respectively, surpassing the prevalence of 38.0% (CI 30.0–47.0%) observed in 2020. Abnormal imaging findings such as bilateral pneumonia lesions, unilateral pneumonia lesions, and multiple lung lobe lesions were notably prevalent in 2020, exceeding 30% prevalence, which markedly decreased in the subsequent 2 years.

COVID-19-related treatments

During the 3-year duration, antibiotics emerged as a common treatment for COVID-19 in youths. However, therapies such as anticoagulation, antiviral medications, glucocorticoids, and intravenous immunoglobulin were sparingly utilized, each with a prevalence not exceeding 37.0%. The use of oxygen therapy exhibited an increasing trend, reaching 39.0% (CI 9.0–70.0%) in 2022. Conversely, mechanical ventilation was predominantly employed in 2020, with a prevalence of 15.0% (95% CI 11.0–19.0%), which notably decreased to 3.0% (95% CI 1.0–5.0%) by 2022.

COVID-19-related outcomes

Reported outcomes and prognoses for COVID-19 patients among youths consistently show relatively high rates of recovery and discharge. Additionally, a declining trend in the prevalence of ICU admissions and mortality has been observed year by year. Merely 3% (CI 0–6%) of cases necessitated ICU admission, and there were no reported mortalities in 2022.

Additional File 8 provides further details on COVID-19-related evidence obtained from single-arm meta-analyses. Additional file 9 [ 40 , 69 , 75 , 97 , 108 , 109 , 117 , 122 , 123 , 132 , 137 ] summarizes single-arm evidence about COVID-19-associated MIS-C. Additional file 10 [ 62 , 156 , 157 ] summarizes single-arm evidence about newborns from COVID-19-diagnosed mothers. Additional file 11 [ 47 , 87 ] summarizes single-arm evidence about long-COVID. Additional file 12 [ 54 , 67 , 77 , 139 , 153 ] summarizes single-arm evidence about events caused by the COVID-19 vaccine. Additional file 13 [ 49 , 50 , 58 , 82 , 99 , 113 , 142 ] summarizes single-arm evidence about health impacts during the pandemic.

COVID-19-related evidence from pairwise meta-analyses

Three hundred one meta-analytic comparisons from 47 pairwise systematic reviews were analyzed. Out of these, only 1.7% ( n  = 5) were considered to have strong meta-analytical evidence, while 4.0% ( n  = 12) and 8.0% ( n  = 24) were categorized as highly suggestive and suggestive evidence respectively (Table  2 ). A stricter P -value threshold revealed that 8.9% ( n  = 27) and 7.3% ( n  = 22) of the meta-analyses had significance at 10 −3 and 10 −6 . The remaining 39.9% ( n  = 120) were statistically significant ( p  < 0.05). In terms of heterogeneity, approximately 49.2% ( n  = 148) of the included meta-analyses had high heterogeneity ( I 2  > 50%), while 29.6% ( n  = 89) presented low heterogeneity ( I 2  ≤ 25%).

A total of 176 meta-analyses (58.4%) explored the direct impact of COVID-19 on children and adolescents. The existing evidence base is largely skewed in favor of a biomedical evaluation of health outcomes in COVID-19-infected individuals, focusing primarily on physical outcomes and suggesting an increased risk of impaired health (Fig.  5 ). Only one had strong meta-analytical evidence: long COVID-19 impact on physical outcomes ( n  = 1), while pediatric comorbidities presented highly suggestive evidence of impacting COVID-19 severity ( n  = 2). In addition, suggestive evidence was found on the effect of long-COVID ( n  = 1) as well as survival and associated complications ( n  = 1) on physical outcomes. Furthermore, transmission and risks for COVID-19 in children present suggestive evidence on both physical ( n  = 1) and social ( n  = 1) outcomes. A total of 84 meta-analyses indicated weak evidence, leaving 85 meta-analyses with no statistically significant results.

figure 5

Evidence grading on direct effects of COVID-19 on physical, psychological/cognitive, quality of life, social, and health system domains. The right side illustrates associations that elevate the risk for the respective health condition (in red), while the left side demonstrates associations that lower the risk (in green). COVID coronavirus disease, MIS-C multisystem inflammatory syndrome in children, ICU intensive care unit

The COVID-19 pandemic’s indirect impacts on children and adolescents were reported in 125 meta-analyses (41.6%). Existing evidence tends to show an increased health risk for children and adolescents, particularly in physical, psychological, and quality of life outcomes. Specifically, among these meta-analyses, two were categorized as having strong evidence (Fig.  6 ), indicating an elevated risk of depression ( n  = 1) and weight gain ( n  = 1). Five meta-analyses presented highly suggestive evidence, associating the increased risk with myopia progression ( n  = 2), depression ( n  = 2), and mental health issues ( n  = 1). The population examined in the meta-analysis, which yielded highly suggestive evidence regarding mental health issues, consisted of children aged 5 to 13 years. In terms of health system outcomes, an additional meta-analysis offered highly suggestive evidence, highlighting an increased risk of asthma-related hospitalization during the COVID-19 pandemic. A further twenty meta-analyses had suggestive evidence, ten of which pertained to associations that already received strong or highly suggestive evidence. The remaining ten meta-analyses showed an increased risk in outcomes, including complicated appendicitis ( n  = 2), neurodevelopmental impairment ( n  = 1), pediatric new-onset type 1 diabetes and diabetic ketoacidosis ( n  = 2), pregnancy and neonatal outcomes ( n  = 1), sleep quality ( n  = 2), and physical activity decline ( n  = 1). A total of 53 meta-analyses were supported by weak evidence, while the remaining 48 meta-analyses did not have nominally statistically significant findings. Additionally, the health system outcomes section notably emphasized evidence concerning the effectiveness and safety of COVID-19 vaccines. Two more meta-analyses focusing on the effectiveness of COVID-19 vaccines ( n  = 2) were categorized as having strong evidence (Fig.  6 ). Four other meta-analyses presented highly suggestive evidence, reporting the effectiveness ( n  = 3) and safety ( n  = 1) of COVID-19 vaccines. The meta-analysis that provided highly suggestive evidence regarding the effectiveness of COVID-19 vaccines focused on a study population comprising children aged 5 to 11 years.

figure 6

Evidence grading on indirect effects of COVID-19 on physical, psychological/cognitive, quality of life, social, and health system domains. The right side illustrates associations that elevate the risk for the respective health condition (in red), while the left side demonstrates associations that lower the risk (in green). COVID coronavirus disease

Number of additional studies needed to change current pairwise meta-analytic evidence

For strong evidence, the median fail-safe number (FSN) was 8 (range 4–25). For highly suggestive and suggestive evidence the median FSN were 13 (range 4–158) and 11 (range 1–163), respectively. The FSN in 73.2% of these studies ( n  = 30) were higher than the number of studies included in the meta-analyses, meaning that adding studies in the future is unlikely to change the robustness of the statistical significance for these metanalytic evidence. For weak evidence, the median FSN was 11 (range 1–2569), and only 37.8% of studies ( n  = 48) had FSN higher than the number of studies included in the meta-analyses.

Main findings from the single-arm meta-analytical evidence

Single-arm meta-analyses have provided extensive evidence on the prevalence and estimations across six domains associated with COVID-19 condition. These domains include laboratory-confirmed COVID-19, COVID-19-associated MIS-C, newborns from COVID-19-diagnosed mothers, long-COVID, events caused by the COVID-19 vaccine, and health impacts during the pandemic.

In this umbrella review, we specifically focus on laboratory-confirmed COVID-19 infections. Through reanalyzing the primary studies from these meta-analyses by removing overlapping data and remapping the actual data collection year, we investigated the distinct clinical characteristics, management, and outcomes of children and adolescents with COVID-19 infections from 2020 to 2022. Clinical manifestations among children exhibited variability over the years, illustrating a diverse range of features. More than half of these manifestations demonstrated a downward trend over time. Our analysis illustrates prevailing patterns in prevalence, indicating an increase in asymptomatic cases and a decrease in other severity levels of cases. In terms of COVID-19-related outcomes, there was a decrease in both admissions to the intensive care unit (ICU) and mortality rates over the years, while the number of discharged and recovered cases remained relatively stable. Interestingly, hospitalization rates rebounded in 2022, potentially attributed to the emergence and spread of novel COVID-19 strains with immune escape mechanisms [ 158 ]. COVID-19-related MIS-C is characterized by recurring high fever, damage to multiple organs, heightened inflammatory indicators, and frequent severe outcomes. Newborns from mothers diagnosed with COVID-19 generally experienced mild symptoms and had a low risk of vertical transmission, although adverse health outcomes were still possible. Furthermore, our findings suggest that children and adolescents affected by long-COVID commonly report symptoms such as fatigue, dyspnea, sore throat, mood changes, and sleep disorders. For events caused by COVID-19 vaccines, we observed that AEs were more frequently reported following booster doses compared to earlier doses. Solicited local and systemic AEs were also found to be common across all doses. Lastly, regarding the domain of pandemic lockdown, our findings reveal a significant correlation between social isolation and adverse effects on the mental health, sleep habits, and physical activity of children and adolescents.

Main findings from the pairwise meta-analytical evidence

Among the pairwise meta-analyses, we observed strong evidence for five effects and highly suggestive evidence for 12 effects. These results were supported by highly significant findings. Based on the available evidence, we have classified the strong and highly suggestive evidence into three primary categories: (i) the direct effects of COVID-19 infection on children’s health, (ii) the indirect impacts of the COVID-19 pandemic on children’s well-being, and (iii) the efficacy and safety of COVID-19 vaccines. The direct effect is demonstrated by a higher risk of severe COVID-19 in children with comorbidities and persistent negative health challenges resulting from long-COVID. Several factors can explain the manifestations linked with long-COVID, including persistent acute organ damage, the presence of the virus in the body, and the activation of autoimmune mechanisms that target both the COVID-19 virus and host tissues [ 159 ]. Moreover, the indirect effects of COVID-19 had strong correlations with significant economic disruptions, increased social isolation, mental health challenges, and a shift towards remote work and online activities for children and adolescents [ 160 ]. Our study revealed that these indirect impacts are manifested in increased anxiety and depression levels, accelerated myopia progression, as well as significant increases in body weight and BMI during the COVID-19 pandemic home quarantine. The effectiveness and safety of COVID-19 vaccines have been confirmed to a certain extent, although several potential AEs have been reported.

Similarities and disparities of the previous and current studies

In our study, we investigated and presented evidence of the negative physical correlations observed in individuals with long-COVID. Previous umbrella reviews, which primarily focused on adults, have examined the long-term consequences experienced by COVID-19 survivors beyond the acute phase. However, these evaluations were limited by the absence of graded evidence [ 161 , 162 ]. In contrast, our study pooled single-arm meta-analyses specifically on long-COVID in children and adolescents, demonstrating similar outcomes. Nonetheless, it is important to note that these findings did not achieve high-level evidence ranking like those obtained through pairwise meta-analysis. This limitation can be attributed to the constraints imposed by the study design and sample size, which were influenced by limited time, resources, and evolving understanding of long-term consequences associated with acute COVID-19 [ 17 ]. The management of individuals with post-COVID conditions presents significant challenges due to the diverse range of symptoms, unpredictable duration, and absence of definitive risk factors. Furthermore, the symptoms of long-COVID can manifest in various combinations from patient to patient, with fluctuations in both frequency and severity. This dynamic nature adds an extra layer of complexity to the issue of long-COVID.

This umbrella review offered a comprehensive analysis of the correlation between the COVID-19 pandemic and the mental health of children and adolescents. Similar to previous umbrella reviews, we observed differing impacts regarding various mental health issues among this demographic. However, the methodological approaches of these umbrella reviews varied considerably. Due to significant heterogeneity in the methods and outcomes of the reviews included, some lead to a narrative synthesis presentation and an omission in evidence grading [ 21 , 163 ]. One umbrella review [ 164 ] conducted a reanalysis of systematic reviews to re-examine data from preliminary studies captured within each systematic review, aiming to reduce potential biases that could have previously impacted the assessment of mental health during the pandemic. Despite the absence of evidence grading, the insights provided by this evidence remain significant. It is also important to acknowledge that disentangling the direct impact of the pandemic on the mental health of children and adolescents remains challenging due to the complexity of mental health disorders. Additionally, the implementation of bundled mitigation strategies at national or subnational levels complicates the identification of individual strategies that may have contributed to exacerbated mental health effects. To sum up, the integration of our current findings with previous studies has the potential to substantially enhance policymaking and practice in the field of mental and child health, thereby guiding future research endeavors to strengthen the global knowledge base.

Mechanisms and implications from current evidence

The gradual reduction of health risk of covid-19 in children and adolescents.

The health risk of COVID-19 in children and adolescents appears to decrease gradually over time. Our research also indicates a rise in the number of asymptomatic cases among children over the years, alongside a decline in ICU admissions and mortality rates. These trends may be attributed to a globally prevalent variant strain during the period when the data included in the study was collected. With the ongoing pandemic, the Omicron variant (B.1.1.529) emerged as the dominant strain during that time, surpassing Delta in its transmission rate [ 165 ]. Additionally, the Omicron variant has demonstrated a lower rate of hospitalization, ICU admission, invasive mechanical ventilation (IMV), and in-hospital deaths, along with a higher prevalence of asymptomatic cases compared to the Delta variant [ 166 , 167 ]. These observations suggest that the Omicron variant may have reduced pathogenicity and milder symptoms than previous variants. Our findings indicate that the most frequently reported symptoms are fever and cough, which aligns with the previous umbrella reviews not limited by age [ 20 ]. However, our study discovered a higher incidence of conjunctivitis in 2022, with a rate of 48.4%. This symptom is considered rare, as its prevalence among positive cases typically ranges from 0.8 to 31.6% [ 168 ]. Our findings indicate that the most frequently reported symptoms are fever and cough, which aligns with the previous umbrella reviews not limited by age [ 20 ]. However, our study discovered a higher incidence of conjunctivitis in 2022, with a rate of 48.4%. This symptom is considered rare, as its prevalence among positive cases typically ranges from 0.8 to 31.6% [ 168 ]. It has been established that frequency of hand-eye contact presents as an independent risk factor for COVID-19-related conjunctivitis [ 169 ].

Another key finding in our study is the lower health risk of COVID-19 for children and adolescents when compared to adults. The current umbrella review provides ample evidence to support the notion that most children and adolescents infected with COVID-19 exhibit mild or even asymptomatic symptoms. During the Omicron epidemic, the proportion of asymptomatic cases across all age groups was 33.72% in 2022 and 23.57% in 2021, both of which indicate a lower proportion of asymptomatic cases among adults compared to our reported findings [ 170 ]. Umbrella reviews without age limitations often overlook the critical role of age in influencing both COVID-19 susceptibility and disease severity [ 171 ]. The relative susceptibility among children and adolescents aged 0–19 years was also notably lower, ranging from 6 to 16% compared to adult groups, with the rate of critical illness in adults being 4.95 times higher than that in children [ 172 ]. However, the reasons behind this phenomenon remain incompletely understood, despite available data suggesting similar viral loads in both children and adults at the time of presentation [ 173 ]. Several hypotheses have been proposed to explain the disparity in COVID-19 severity between younger and older individuals, including more efficient local tissue responses [ 174 ], better thymic function [ 175 ], and cross-reactive immunity [ 176 ]. Currently, the prevailing viewpoint suggests that the lower incidence and severity of COVID-19 disease in infants can be explained by maternal immune transfer [ 177 ], an immature immune system [ 178 ], and reduced expression of COVID-19 attachment receptors such as ACE-2 [ 179 ]. However, there is also evidence suggesting that maternal COVID-19 may impact the neonatal immune system, potentially leading to an exacerbated inflammatory response and immune activation [ 180 ]. Consequently, the programming of the neonatal immune system by the maternal inflammatory milieu induced by COVID-19 remains uncertain.

From the perspective of childhood growth evolution, recent evidence suggests that the body’s energy allocation often avoids costly systemic inflammatory responses [ 181 ]. By prioritizing disease tolerance rather than maximal resistance, children are more likely to experience mild or even asymptomatic illness. However, this approach may result in a lower efficiency in clearing viruses, which could lead to some degree of viral persistence and the subsequent manifestation of other diseases associated with such persistence. Therefore, personalized treatments tailored to the severity of the disease should be implemented for pediatric patients, along with thorough long-term monitoring and follow-up care. Furthermore, our findings indicate that dysautonomia often presents symptoms commonly associated with long-COVID. However, whether dysautonomia is a direct consequence of COVID-19 infection or an immune-mediated process remains unclear [ 182 ]. Although current evidence suggests that long-COVID has a relatively milder health impact on pediatric patients compared to adults, the life course implications, including psychological, social, and economic impacts, are not fully revealed by current evidence and require more extensive long-term follow-up studies [ 183 ]. Insufficient lifecycle observations limit the evidence of the impact of long-COVID on pediatric patients, requiring caution when interpreting the relatively lower impact on this group. Nevertheless, school closure and social distancing measures may further compromise the social well-being of children with long-COVID symptoms [ 184 ]. It is crucial to implement social policies that promote the return to school and participation in extracurricular activities among young individuals to address specific risk factors like obesity associated with long-COVID. Additionally, this can help mitigate the negative cultural impact and psychological consequences caused by remote learning [ 184 , 185 ].

The immune microenvironment, physiological and psychological factors, and social activities contribute to disparities in disease susceptibility among children and adolescents at different developmental stages [ 186 , 187 ]. Previous literature has reported a higher susceptibility to severe COVID-19 and increased hospital admissions among pediatric patients aged ≤ 4 years or 12–17 years, indicating a bimodal age distribution [ 188 ]. Our research shows that serious consequences such as dyspnea, ICU admission, and death have also been observed and cannot be ignored, although a lower health risk of COVID-19 for children and adolescents due to uncommon vertical transmission during neonatal admission from infected mothers was observed.

However, at the umbrella review level, the current available primary and meta-analytical evidence has limited the evaluation process of COVID-19’s impact on age-specific subgroups of children and adolescents. Most of the included evidence has focused on the 0–19 age group as a whole [ 4 , 6 , 20 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 , 150 , 151 ], with only a few studies examining specific age ranges. For example, Yasuhara J’s study included children and adolescents aged 12–19 years [ 152 ], while Watanabe A’s study included children aged 5–11 years [ 153 ], without direct comparison to other age-specific subgroups. The lack of age-specific research and comparisons poses challenges for subgroup analyses across various age groups, excluding neonatal groups that are typically distinguished in the literature and technically feasible to evaluate [ 154 , 155 , 156 , 157 ]. Therefore, our main analysis includes the 0–19 age group, with a separate domain for newborns from COVID-19-diagnosed mothers, to demonstrate the impact of COVID-19 on children and adolescents at different developmental stages.

The mental health risks of COVID-19-related social isolation on children and adolescents

Over the past 3 years, significant efforts have been made to control the spread of COVID-19 through various interventions, such as social distancing, mobility restrictions, and school closures. Nevertheless, these measures may have unintended and detrimental effects on the mental health of children and adolescents [ 189 , 190 ]. The present umbrella review provides evidence supporting the idea that the pandemic has resulted in an increased burden of mental health concerns among this population, including conditions like depression and sleep disorders. These findings are consistent with previous research studies [ 21 , 22 ]. However, their report indicated a pooled prevalence rate of 32% for depression (95% CI 27–38%) and 32% for anxiety (95% CI 27–37%) among children and adolescents worldwide following COVID-19 mitigation measures, which was lower than our findings. This suggests that the deterioration of mental health in the younger population during the pandemic may not solely be attributed to indirect impacts during the gradual relaxation of mandatory control measures in many countries. The underlying causes of this phenomenon may vary and encompass financial stressors [ 191 ], social isolation [ 192 ], physical health concerns [ 193 ], and heightened anxiety and fear stemming from the uncertainties of COVID-19 [ 194 ]. Therefore, it is crucial to monitor the negative impact on the mental health of children and adolescents in the future, with dedicated efforts aimed at enhancing their well-being. Policymakers and healthcare professionals should adopt a holistic approach that addresses these multifaceted issues to effectively mitigate the detrimental effects on mental health.

The safety and efficacy of vaccines for children

The present study indicates that COVID-19 vaccines effectively prevent severe illness and reduce transmission. Evidence from pooled studies in healthy children and adolescents suggests that the occurrence of AEs, including local and systemic AEs, is similar between the vaccine and placebo groups. Furthermore, serious AEs are mostly unrelated to vaccination [ 195 ]. Recent studies have also confirmed the favorable and safe response to COVID-19 vaccination among pediatric patients with inflammatory rheumatic diseases [ 196 ], endocrinological disorders [ 197 ], or inflammatory bowel disease [ 198 ], addressing concerns about potential AEs in vulnerable populations with inadequate or overactive immune responses. However, it is important to note that the evidence supporting these findings is currently limited to cross-sectional studies. Additionally, both local and systemic AEs were reported to occur slightly more frequently than in the adult population. Nonetheless, this does not suggest evidence against the vaccine’s safety, as reactogenicity is more common in young individuals than in adults [ 199 ]. Although side effects may vary depending on the person, they typically tend to be mild and temporary, similar to common childhood vaccines [ 200 ]. Based on emerging safety and efficacy data, along with increased vaccine availability, widespread vaccination is recommended, particularly for high-risk children.

COVID-19-related global policies related to children and adolescents

The impact of COVID-19-related global policies is a matter of great concern for the health and well-being of children and adolescents. The effects of policies and regulations implemented to control the COVID-19 outbreak are intricate and multifaceted. Policies that specifically target children and young people, such as school closures and healthcare restrictions, have direct consequences on their social interactions [ 201 ], education [ 202 ], and access to healthcare resources [ 203 ]. Moreover, policy decisions and measures have resulted in numerous social conflicts, further impacting the daily lives of children and adolescents. For example, children often find themselves caught in the midst of disputes between parents, friends, schoolmates, teachers, and activity leaders regarding COVID-19 measures [ 204 ]. Additionally, the social and economic repercussions of policy measures become apparent in later stages of the pandemic, underscoring the direct impact these challenges have on the everyday lives of children. As an illustration, school children from underprivileged families face multiple hurdles due to the pandemic, including financial insecurity and disparities in remote learning caused by a lack of digital devices [ 205 ]. These complex impacts make it difficult to establish a clear link between policies and child health, and limited research has focused on the long-term effects of policies on affected children. Furthermore, as COVID-19 continues to significantly impact the mental health of the general population, countries have developed and revised policies, guidelines, and new initiatives to address the psychological well-being of their citizens. These supportive policies further complicate the discussion surrounding policy impacts.

Evidence of the impact of COVID-19-related policies on children and adolescents is limited. As stated above, current meta-analytical evidence suggests that children may be less affected by certain social settings as a result of policy development, such as the reopening of schools and workplaces. However, the physical and psychological/cognitive effects of the virus may hinder a child’s ability to return to school for several weeks or months. Research on health system utilization in this area primarily focuses on medical resources, such as emergency services and ICU admissions. However, conflicting evidence exists, with only a limited number of studies available. Based on current meta-analytical data, it appears that health system utilization for life-threatening diseases and situations in younger patients is not significantly different from or may even be lower than the pre-pandemic era, except in cases involving younger patients with asthma and obesity. It is important to interpret these results cautiously since medical crowding and inadequate resources may overshadow the utilization of the health system by pediatric COVID-19 patients [ 206 ].

Strengths and weaknesses

The strengths and weaknesses of this umbrella review are quite straightforward. First, one of the strengths is that we provided a comprehensive summary of the current available evidence by reviewing previous meta-analyses on the association between COVID-19 and various health outcomes in children and adolescents. Second, our study protocol was registered in PROSPERO, ensuring transparency and robustness in the planned analysis and results. Considering the worldwide prolonged transmission and evolving nature of COVID-19, this study holds clinical and social importance in shaping preventive strategies for children and adolescents in the post-pandemic era. Next, this study utilized a systematic approach, involving thorough searching, selection, and data extraction conducted by two independent authors with excellent inter-examiner reliability. Methodological quality and evidence classification were assessed using two established criteria, AMSTAR-2 [ 27 ] and evidence grading criteria [ 28 , 29 ] to assess the methodological quality and evidence classification. Without limiting study designs and statistical significance, the current umbrella review filled the knowledge gaps and captured temporal changes in key aspects of COVID-19 in children and adolescents. However, some limitations still exist in this review. Firstly, most of the meta-analyses included in this review are based on observational studies, and the prospective or randomized study designs were not prominently featured. This observational nature of the studies introduces the potential for selection bias, as differences in baseline characteristics and confounding factors can exist among the study populations [ 207 ]. Consequently, these studies only provide associations between variables and cannot account for all possible confounders or factors that may influence the results. Secondly, many studies within this topic rely on self-reported data, which can be subjective and susceptible to recall bias [ 208 ]. The use of self-reporting may lead to inconsistencies or inaccuracies in the data collected. Moreover, the absence of a comparison group in single-arm studies makes it challenging to accurately establish the effects of COVID-19 on children and adolescents. The evaluation of the impact of COVID-19 on age-specific subgroups of children and adolescents is incomplete due to the limited availability of primary and meta-analytical evidence. The lack of age-specific research and comparisons poses challenges for subgroup analyses across various developmental stages, potentially resulting in an incomplete depiction of the differential impacts of COVID-19 across different developmental stages of children and adolescents. In this current study, we chose to present all available meta-analytical data from single-arm studies and categorized them into six predefined COVID-19 condition domains [ 25 ]. This approach allows us to illustrate the main findings of COVID-19 on children and adolescents in a time-dependent manner, considering the dynamic changes in disease severity, clinical manifestations, laboratory and radiological findings, treatment, and outcomes. Although this approach has its limitations, it provides valuable insights that can inform public health measures and interventions targeted at this population. It also emphasizes the need for further controlled studies tailored to address the specific impacts of COVID-19 on children and adolescents.

Implications for practice and research

For practice, the effect estimates combined with different topic domains categorized from primary studies can help practitioners identify high-risk younger patients for COVID-19-related direct and indirect health outcomes. However, when it comes to children and adolescents with rare disease conditions, identifying high-risk groups remains a challenge. These individuals are often underrepresented in primary studies, likely due to decreased medical care utilization during the pandemic. This oversight may result in the neglect of rare disease conditions in both practice and policy decisions. Based on the complete picture of available evidence and the COVID-19 and health domains linking mechanisms, policymakers could better prioritize the prevention and intervention methods for children and adolescents affected by COVID-19 (in)directly. Connecting these individuals with appropriate support services is another key question in COVID-19 management. The effects and evidence summarized in this umbrella review suggests that such services could include medical/surgical management of physical illness and comorbidities, psychotherapy, physio and occupational therapy, and nursing. Multidisciplinary collaboration units dedicated to younger COVID-19 patients or pandemic lockdowns can be invaluable in providing tailored prevention and intervention strategies [ 209 , 210 ]. Shifting the focus of COVID-19 global health emergency management to long-term management, alongside other infectious diseases, can accelerate the implementation of surveillance systems for COVID-19-related health consequences and rehabilitation programs for affected younger patients.

For research, the effect estimates in this review are heavily focused on the physical outcomes, investigating the relationship between COVID-19 and disease severity, clinical manifestations, laboratory/radiological findings, treatment, and outcomes in younger patients. Gaps still exist between available evidence in non-physical outcomes and current clinical practice. Furthermore, some meta-analytical results did not reveal significant associations with many COVID-19-related health conditions, such as the direct effects of long-COVID on the psychological/cognitive well-being and quality of life of younger patients in pairwise studies, which lead to the overall evidence consistency due to poor meta-analytic or methodological reasons. Future studies can provide a more nuanced understanding of how COVID-19 affects children and adolescents at different developmental stages by expanding the scope of research to include a wider range of age groups. This will enable the analysis of the impacts of COVID-19 on various stages of childhood and adolescence, facilitating the development of tailored interventions and guidelines specifically designed for these populations. It is important to note that this does not imply the absence of robust associations, but rather the current body of evidence does not yet support such inferences [ 211 ]. Therefore, updating and transforming this review into a living review would be valuable in incorporating emerging evidence from future meta-analytical studies on the impacts of COVID-19 on children and adolescents.

In summary, this work evaluated the meta-analytical evidence regarding the associations between the (in)direct COVID-19 effects and multiple health and well-being domains of children and adolescents. The findings of this study can serve as a comprehensive evidence map to inform, educate, and train various interested parties, including key stakeholders such as policymakers, patients, and practitioners. It is also important to acknowledge that the majority of the findings and recommendations presented in this study are derived from observational studies that have methodological limitations. Thus, it is crucial to exercise caution when interpreting the results and implementing the implications of this study. Additionally, future research should prioritize the execution of high-quality studies utilizing prospective, long-term, or randomized designs to more comprehensively understand the causal effects of COVID-19, both direct and indirect, on children and adolescents.

Availability of data and materials

All data generated and analyzed that support findings in this study are supplemented in the Supplementary Information. The Rscript snippets for generating descriptive summaries and reanalyzing single-arm studies are available on GitHub using the following link: https://github.com/Piperacillin/Child_COVID19_Umbrellareview .

Abbreviations

Adverse events

A Measurement Tool to Assess Systematic Reviews 2

Coronavirus disease 2019

C-reactive protein

Joanna Briggs Institute

Serum lactate dehydrogenase

Multisystem inflammatory syndrome

Meta-analyses of Observational Studies in Epidemiology

National Institutes of Health

Newcastle-Ottawa Scale

Procalcitonin

Preferred Reporting Items for Systematic Reviews and Meta‐Analyses

Risk of bias

Severe acute respiratory syndrome coronavirus 2

White blood cell

World Health Organization

Abrams EM, Szefler SJ. COVID-19 and the impact of social determinants of health. Lancet Respir Med. 2020;8(7):659–61.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Chow EJ, Uyeki TM, Chu HY. The effects of the COVID-19 pandemic on community respiratory virus activity. Nat Rev Microbiol. 2023;21(3):195–210.

CAS   PubMed   Google Scholar  

COVID-19 weekly epidemiological update, edition 139, 2023 [ https://www.who.int/publications/m/item/weekly-epidemiological-update-on-covid-19---20-april-2023 ]

Sumner MW, Kanngiesser A, Lotfali-Khani K, Lodha N, Lorenzetti D, Funk AL, Freedman SB. Severe outcomes associated with SARS-CoV-2 infection in children: a systematic review and meta-analysis. Front Pediatr. 2022;10:916655.

Article   PubMed   PubMed Central   Google Scholar  

Yoon S, Li H, Lee KH, Hong SH, Kim D, Im H, Rah W, Kim E, Cha S, Yang J, et al. Clinical characteristics of asymptomatic and symptomatic pediatric Coronavirus disease 2019 (COVID-19): a systematic review. Medicina (Kaunas). 2020;56(9):474.

Article   PubMed   Google Scholar  

Zhao Y, Yin L, Patel J, Tang L, Huang Y. The inflammatory markers of multisystem inflammatory syndrome in children (MIS-C) and adolescents associated with COVID-19: a meta-analysis. J Med Virol. 2021;93(7):4358–69.

Nearchou F, Flinn C, Niland R, Subramaniam SS, Hennessy E. Exploring the impact of COVID-19 on mental health outcomes in children and adolescents: a systematic review. Int J Environ Res Public Health. 2020;17(22):8479.

Djurdjević S, Ghigliazza IC, Dukanac V, Djurdjević A. Anxiety and depressive symptomatology among children and adolescents exposed to the COVID-19 pandemic–a systematic review. Vojnosanit Pregl. 2022;79(4):389–99.

Article   Google Scholar  

Goodman A, Joyce R, Smith JP. The long shadow cast by childhood physical and mental problems on adult life. Proc Natl Acad Sci U S A. 2011;108(15):6032–7.

Sosin AN, Choo E, Lincoln M. The covid public health emergency is ending: it now joins the ordinary emergency that is American health. BMJ. 2023;381:949.

Wise J. Covid-19: WHO declares end of global health emergency. BMJ. 2023;381:1041.

Ward JL, Harwood R, Smith C, Kenny S, Clark M, Davis PJ, Draper ES, Hargreaves D, Ladhani S, Linney M, et al. Risk factors for PICU admission and death among children and young people hospitalized with COVID-19 and PIMS-TS in England during the first pandemic year. Nat Med. 2022;28(1):193–200.

Article   CAS   PubMed   Google Scholar  

Cao Y, Huang L, Si T, Wang NQ, Qu M, Zhang XY. The role of only-child status in the psychological impact of COVID-19 on mental health of Chinese adolescents. J Affect Disord. 2021;282:316–21.

McGuine TA, Biese KM, Petrovska L, Hetzel SJ, Reardon C, Kliethermes S, Bell DR, Brooks A, Watson AM. Mental health, physical activity, and quality of life of US adolescent athletes during COVID-19-related school closures and sport cancellations: a study of 13 000 athletes. J Athl Train. 2021;56(1):11–9.

Wagner CE, Saad-Roy CM, Grenfell BT. Modelling vaccination strategies for COVID-19. Nat Rev Immunol. 2022;22(3):139–41.

Mostafiz MI, Musteen M, Saiyed A, Ahsan M. COVID-19 and the global value chain: Immediate dynamics and long-term restructuring in the garment industry. J Bus Res. 2022;139:1588–603.

Cucherat M, Laporte S, Delaitre O, Behier JM, participants of Giens XRTCR, d’Andon A, Binlich F, Bureau S, Cornu C, Fouret C, et al. From single-arm studies to externally controlled studies Methodological considerations and guidelines. Therapie. 2020;75(1):21–7.

Tricco AC, Antony J, Zarin W, Strifler L, Ghassemi M, Ivory J, Perrier L, Hutton B, Moher D, Straus SE. A scoping review of rapid review methods. BMC Med. 2015;13:224.

Papatheodorou S. Umbrella reviews: what they are and why we need them. Eur J Epidemiol. 2019;34:543–6.

Shah K, Upadhyaya M, Kandre Y, Pandya A, Saraf V, Saxena D, Mavalankar D. Epidemiological, clinical and biomarker profile of pediatric patients infected with COVID-19. QJM. 2021;114(7):476–95.

Hossain MM, Nesa F, Das J, Aggad R, Tasnim S, Bairwa M, Ma P, Ramirez G. Global burden of mental health problems among children and adolescents during COVID-19 pandemic: an umbrella review. Psychiatry Res. 2022;317:114814.

Harrison L, Carducci B, Klein JD, Bhutta ZA. Indirect effects of COVID-19 on child and adolescent mental health: an overview of systematic reviews. BMJ Glob Health. 2022;7(12):e010713.

Schiavo JH. PROSPERO: an international register of systematic review protocols. Med Ref Serv Q. 2019;38(2):171–80.

Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Syst Rev. 2021;10(1):89.

Pollock M, Fernandes RM, Becker LA, Pieper D, Hartling L. Chapter V: Overviews of Reviews. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editors. Cochrane Handbook for Systematic Reviews of Interventions version 6.4 (updated August 2023). Cochrane; 2023. Available from www.training.cochrane.org/handbook .

Lin J-T. Approximating the normal tail probability and its inverse for use on a pocket calculator. Appl Stat. 1989;38(1):69–70.

Article   MathSciNet   Google Scholar  

Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, Moher D, Tugwell P, Welch V, Kristjansson E. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ. 2017;358:j4008.

Huang Y, Chen Z, Chen B, Li J, Yuan X, Li J, Wang W, Dai T, Chen H, Wang Y, et al. Dietary sugar consumption and health: umbrella review. BMJ. 2023;381:e071609.

Papadimitriou N, Markozannes G, Kanellopoulou A, Critselis E, Alhardan S, Karafousia V, Kasimis JC, Katsaraki C, Papadopoulou A, Zografou M. An umbrella review of the evidence associating diet and cancer risk at 11 anatomical sites. Nat Commun. 2021;12(1):4579.

Huedo-Medina TB, Sanchez-Meca J, Marin-Martinez F, Botella J. Assessing heterogeneity in meta-analysis: Q statistic or I2 index? Psychol Methods. 2006;11(2):193–206.

Huang Y, Cao D, Chen Z, Chen B, Li J, Wang R, Guo J, Dong Q, Liu C, Wei Q, et al. Iron intake and multiple health outcomes: umbrella review. Crit Rev Food Sci Nutr. 2023;63(16):2910–27.

Suurmond R, van Rhee H, Hak T. Introduction, comparison, and validation of meta-essentials: a free and simple tool for meta-analysis. Res Synth Methods. 2017;8(4):537–53.

Aria M, Cuccurullo C. bibliometrix : an R-tool for comprehensive science mapping analysis. J Informetr. 2017;11(4):959–75.

Balduzzi S, Rucker G, Schwarzer G. How to perform a meta-analysis with R: a practical tutorial. Evid Based Ment Health. 2019;22(4):153–60.

Wickham H, Averick M, Bryan J, Chang W, McGowan L, François R, Grolemund G, Hayes A, Henry L, Hester J, et al. Welcome to the tidyverse. J Open Source Softw. 2019;4(43):1686.

Wickham H. Reshaping data with thereshapepackage. J Stat Softw. 2007;21(12):1–20.

Akobeng AK, Grafton-Clarke C, Abdelgadir I, Twum-Barimah E, Gordon M. Gastrointestinal manifestations of COVID-19 in children: a systematic review and meta-analysis. Front Gastroenterol. 2021;12(4):332–7.

Article   CAS   Google Scholar  

Alhumaid S, Alabdulqader M, Al Dossary N, Al Alawi Z, Alnaim AA, Al Mutared KM, Al Noaim K, Al Ghamdi MA, Albahrani SJ, Alahmari AA, et al. Global coinfections with bacteria, fungi, and respiratory viruses in children with SARS-CoV-2: a systematic review and meta-analysis. Trop Med Infect Dis. 2022;7(11):380.

Amanati A, Vali M, Fatemian H, Maleki Z, Foroozand H, Sahebi K, Rahmanian MR, Meybodi MJE. A comprehensive comparison of COVID-19 characteristics (Wuhan Strain) between children and adults during initial pandemic phase: a meta-analysis study. Arch Pediatr Infect. 2022;10(4):e119701.

Google Scholar  

Arantes Junior MAF, Conegundes AF, Branco Miranda BC, Radicchi Campos ASR, Franca Vieira AL, Faleiro MD, Campos MA, Kroon EG, Bentes AA. Cardiac manifestations in children with the multisystem inflammatory syndrome (MIS-C) associated with SARS-CoV-2 infection: systematic review and meta-analysis. Rev Med Virol. 2023;33:e2432.

Assaker R, Colas AE, Julien-Marsollier F, Bruneau B, Marsac L, Greff B, Tri N, Fait C, Brasher C, Dahmani S. Presenting symptoms of COVID-19 in children: a meta-analysis of published studies. Br J Anaesth. 2020;125(3):e330–2.

Badal S, Thapa Bajgain K, Badal S, Thapa R, Bajgain BB, Santana MJ. Prevalence, clinical characteristics, and outcomes of pediatric COVID-19: a systematic review and meta-analysis. J Clin Virol. 2021;135:104715.

Behnood SA, Shafran R, Bennett SD, Zhang AXD, O’Mahoney LL, Stephenson TJ, Ladhani SN, De Stavola BL, Viner RM, Swann OV. Persistent symptoms following SARS-CoV-2 infection amongst children and young people: a meta-analysis of controlled and uncontrolled studies. J Infect. 2022;84(2):158–70.

Bhuiyan MU, Stiboy E, Hassan MZ, Chan M, Islam MS, Haider N, Jaffe A, Homaira N. Epidemiology of COVID-19 infection in young children under five years: a systematic review and meta-analysis. Vaccine. 2021;39(4):667–77.

Bolia R, Dhanesh Goel A, Badkur M, Jain V. Gastrointestinal manifestations of pediatric Coronavirus disease and their relationship with a severe clinical course: a systematic review and meta-analysis. J Trop Pediatr. 2021;67(2):fmab051.

Bussieres EL, Malboeuf-Hurtubise C, Meilleur A, Mastine T, Herault E, Chadi N, Montreuil M, Genereux M, Camden C, Team P-C. Consequences of the COVID-19 pandemic on children’s mental health: a meta-analysis. Front Psychiatry. 2021;12:691659.

Campos C, Prokopich S, Loewen H, Sanchez-Ramirez DC. Long-term effect of COVID-19 on lung imaging and function, cardiorespiratory symptoms, fatigue, exercise capacity, and functional capacity in children and adolescents: a systematic review and meta-analysis. Healthc (Basel). 2022;10(12):2492.

Carmona CA, Kuziez M, Freitas CF, Cyrus JW, Bain J, Karam O. Cardiac manifestations of multisystem inflammatory syndrome of children after SARS-CoV-2 infection: a systematic review and meta-analysis. Cardiol Young. 2023;33(11):1–9.

Chaabna K, Chaabane S, Jithesh A, Doraiswamy S, Mamtani R, Cheema S. Effect of the COVID-19 pandemic on the proportion of physically active children and adults worldwide: a systematic review and meta-analysis. Front Public Health. 2022;10:1009703.

Chai J, Xu H, An N, Zhang P, Liu F, He S, Hu N, Xiao X, Cui Y, Li Y. The prevalence of mental problems for Chinese children and adolescents during COVID-19 in China: a systematic review and meta-analysis. Front Pediatr. 2021;9:661796.

Chang TH, Chen YC, Chen WY, Chen CY, Hsu WY, Chou Y, Chang YH. Weight gain associated with COVID-19 lockdown in children and adolescents: a systematic review and meta-analysis. Nutrients. 2021;13(10):3668.

Chang TH, Wu JL, Chang LY. Clinical characteristics and diagnostic challenges of pediatric COVID-19: A systematic review and meta-analysis. J Formos Med Assoc. 2020;119(5):982–9.

Chen J, Yang K, Cao Y, Du Y, Wang N, Qu M. Depressive symptoms among children and adolescents in China during the Coronavirus disease-19 epidemic: a systematic review and meta-analysis. Front Psychiatry. 2022;13:870346.

Chou OHI, Mui J, Chung CT, Radford D, Ranjithkumar S, Evbayekha E, Nam R, Pay L, Satti DI, Garcia-Zamora S, et al. COVID-19 vaccination and carditis in children and adolescents: a systematic review and meta-analysis. Clin Res Cardiol. 2022;111(10):1161–73.

Cui X, Zhai Y, Wang S, Ding K, Yang Z, Tian Y, Huo T. Effect of the COVID-19 pandemic on serum vitamin D levels in people under age 18 years: a systematic review and meta-analysis. Med Sci Monit. 2022;28:e935823.

Dara N, Hosseini A, Sayyari AA, Gaman M-A, Fatahi S. Gastrointestinal manifestations and dynamics of liver enzymes in children and adolescents with COVID-19 infection: a systematic review and meta-analysis. Iran J Pediatr. 2020;30(5):1–9.

de Medeiros KS, Sarmento ACA, Costa APF, Macedo LTA, da Silva LAS, de Freitas CL, Simoes ACZ, Goncalves AK. Consequences and implications of the coronavirus disease (COVID-19) on pregnancy and newborns: a comprehensive systematic review and meta-analysis. Int J Gynaecol Obstet. 2022;156(3):394–405.

Deng J, Zhou F, Hou W, Heybati K, Lohit S, Abbas U, Silver Z, Wong CY, Chang O, Huang E, et al. Prevalence of mental health symptoms in children and adolescents during the COVID-19 pandemic: a meta-analysis. Ann N Y Acad Sci. 2023;1520(1):53–73.

Di Toro F, Gjoka M, Di Lorenzo G, De Santo D, De Seta F, Maso G, Risso FM, Romano F, Wiesenfeld U, Levi-D’Ancona R, et al. Impact of COVID-19 on maternal and neonatal outcomes: a systematic review and meta-analysis. Clin Microbiol Infect. 2021;27(1):36–46.

Ding Y, Yan H, Guo W. Clinical characteristics of children with COVID-19: a meta-analysis. Front Pediatr. 2020;8:431.

Du Y, Chen L, Shi Y. Safety, immunogenicity, and efficacy of COVID-19 vaccines in adolescents, children, and infants: a systematic review and meta-analysis. Front Public Health. 2022;10:829176.

Dubey P, Reddy SY, Manuel S, Dwivedi AK. Maternal and neonatal characteristics and outcomes among COVID-19 infected women: an updated systematic review and meta-analysis. Eur J Obstet Gynecol Reprod Biol. 2020;252:490–501.

El-Qushayri AE, Benmelouka AY, Dahy A, Hashan MR. COVID-19 outcomes in paediatric cancer: A large scale pooled meta-analysis of 984 cancer patients. Rev Med Virol. 2022;32(5):e2344.

Elgenidy A, Awad AK, Saad K, Atef M, El-Leithy HH, Obiedallah AA, Hammad EM, Ahmad FA, Ali AM, Dailah HG, et al. Incidence of diabetic ketoacidosis during COVID-19 pandemic: a meta-analysis of 124,597 children with diabetes. Pediatr Res. 2023;93(5):1149–60.

Gabriel IWM, Lima DGS, Pires JP, Vieira NB, Brasil A, Pereira YTG, de Oliveira EG, de Menezes HL, Lima NNR, Reis AOA, et al. Impacts of COVID-19 on children and adolescents: a systematic review analyzing its psychiatric effects. World J Psychiatry. 2022;12(11):1313–22.

Gao P, Cai S, Liu Q, Du M, Liu J, Liu M. Effectiveness and safety of SARS-CoV-2 vaccines among children and adolescents: a systematic review and meta-analysis. Vaccines (Basel). 2022;10(3):421.

Gao P, Kang LY, Liu J, Liu M. Immunogenicity, effectiveness, and safety of COVID-19 vaccines among children and adolescents aged 2–18 years: an updated systematic review and meta-analysis. World J Pediatr. 2023;19(11):1041–54.

Gaythorpe KAM, Bhatia S, Mangal T, Unwin HJT, Imai N, Cuomo-Dannenburg G, Walters CE, Jauneikaite E, Bayley H, Kont MD, et al. Children’s role in the COVID-19 pandemic: a systematic review of early surveillance data on susceptibility, severity, and transmissibility. Sci Rep. 2021;11(1):13903.

Haghighi Aski B, Manafi Anari A, Abolhasan Choobdar F, Zareh Mahmoudabadi R, Sakhaei M. Cardiac abnormalities due to multisystem inflammatory syndrome temporally associated with Covid-19 among children: a systematic review and meta-analysis. Int J Cardiol Heart Vasc. 2021;33:100764.

PubMed   PubMed Central   Google Scholar  

Han Y, Chen Y, Sun C, Zhou Z. The impact of COVID lockdown on glycaemic control in paediatric patients with type 1 diabetes: a systematic review and meta-analysis of 22 observational studies. Front Endocrinol (Lausanne). 2022;13:1069559.

Henry BM, Benoit SW, de Oliveira MHS, Hsieh WC, Benoit J, Ballout RA, Plebani M, Lippi G. Laboratory abnormalities in children with mild and severe coronavirus disease 2019 (COVID-19): A pooled analysis and review. Clin Biochem. 2020;81:1–8.

Hessami K, Norooznezhad AH, Monteiro S, Barrozo ER, Abdolmaleki AS, Arian SE, Zargarzadeh N, Shekerdemian LS, Aagaard KM, Shamshirsaz AA. COVID-19 pandemic and infant neurodevelopmental Impairment: a systematic review and meta-analysis. JAMA Netw Open. 2022;5(10):e2238941.

Irfan O, Li J, Tang K, Wang Z, Bhutta ZA. Risk of infection and transmission of SARS-CoV-2 among children and adolescents in households, communities and educational settings: A systematic review and meta-analysis. J Glob Health. 2021;11:05013.

Irfan O, Muttalib F, Tang K, Jiang L, Lassi ZS, Bhutta Z. Clinical characteristics, treatment and outcomes of paediatric COVID-19: a systematic review and meta-analysis. Arch Dis Child. 2021;106(5):440–8.

Jiang L, Tang K, Irfan O, Li X, Zhang E, Bhutta Z. Epidemiology, clinical features, and outcomes of Multisystem Inflammatory Syndrome in Children (MIS-C) and adolescents-a live systematic review and meta-analysis. Curr Pediatr Rep. 2022;10(2):19–30.

Kandiah T, Li X, MacMillan Y, Malvankar-Mehta MS. Access to pediatric eye care during a pandemic: systematic review and meta-analysis. Pediatr Ann. 2023;52(2):e68–75.

Katoto P, Brand AS, Byamungu LN, Tamuzi JL, Mahwire TC, Kitenge MK, Wiysonge CS, Gray G. Safety of COVID-19 Pfizer-BioNtech (BNT162b2) mRNA vaccination in adolescents aged 12–17 years: a systematic review and meta-analysis. Hum Vaccin Immunother. 2022;18(6):2144039.

Kharoud HK, Asim R, Siegel L, Chahal L, Singh GD: Review of clinical characteristics and laboratory findings of COVID-19 in children-Systematic review and Meta-analysis. medRxiv 2020, https://doi.org/10.1101/2020.09.23.20200410 . (Accessed Feb 15,2024)

Kim JH, Ahn C. A meta-analysis of testicular torsion and orchiectomy in pediatric patients during the COVID-19 pandemic. J Pediatr Surg. 2022;57(8):1708–9.

Kumar J, Meena J, Yadav A, Yadav J. Radiological findings of COVID-19 in children: a systematic review and meta-analysis. J Trop Pediatr. 2021;67(3):fmaa045.

La Fauci G, Montalti M, Di Valerio Z, Gori D, Salomoni MG, Salussolia A, Solda G, Guaraldi F. Obesity and COVID-19 in children and adolescents: reciprocal detrimental influence-systematic literature review and meta-analysis. Int J Environ Res Public Health. 2022;19(13):7603.

Lee H, Kim E. Global prevalence of physical and psychological child abuse during COVID-19: a systematic review and meta-analysis. Child Abuse Negl. 2023;135:105984.

Li B, Zhang S, Zhang R, Chen X, Wang Y, Zhu C. Epidemiological and clinical characteristics of COVID-19 in children: a systematic review and meta-analysis. Front Pediatr. 2020;8:591132.

Li M, Wang X, Feng J, Feng Z, Li W, Ya B. Myocarditis or Pericarditis following the COVID-19 vaccination in adolescents: a systematic review. Vaccines (Basel). 2022;10(8):1316.

Liu C, He Y, Liu L, Li F, Shi Y. Children with COVID-19 behaving milder may challenge the public policies: a systematic review and meta-analysis. BMC Pediatr. 2020;20(1):410.

Lo TC, Chen YY. Ocular and systemic manifestations in paediatric multisystem inflammatory syndrome associated with COVID-19. J Clin Med. 2021;10(13):2953.

Lopez-Leon S, Wegman-Ostrosky T, Ayuzo Del Valle NC, Perelman C, Sepulveda R, Rebolledo PA, Cuapio A, Villapol S. Long-COVID in children and adolescents: a systematic review and meta-analyses. Sci Rep. 2022;12(1):9950.

Ludwig-Walz H, Dannheim I, Pfadenhauer LM, Fegert JM, Bujard M. Increase of depression among children and adolescents after the onset of the COVID-19 pandemic in Europe: a systematic review and meta-analysis. Child Adolesc Psychiatry Ment Health. 2022;16(1):109.

Ma L, Mazidi M, Li K, Li Y, Chen S, Kirwan R, Zhou H, Yan N, Rahman A, Wang W, et al. Prevalence of mental health problems among children and adolescents during the COVID-19 pandemic: a systematic review and meta-analysis. J Affect Disord. 2021;293:78–89.

Ma X, Liu S, Chen L, Zhuang L, Zhang J, Xin Y. The clinical characteristics of pediatric inpatients with SARS-CoV-2 infection: a meta-analysis and systematic review. J Med Virol. 2021;93(1):234–40.

Madigan S, Eirich R, Pador P, McArthur BA, Neville RD. Assessment of changes in child and adolescent screen time during the COVID-19 pandemic: a systematic review and meta-analysis. JAMA Pediatr. 2022;176(12):1188–98.

Mansourian M, Ghandi Y, Habibi D, Mehrabi S. COVID-19 infection in children: a systematic review and meta-analysis of clinical features and laboratory findings. Arch Pediatr. 2021;28(3):242–8.

Mantovani A, Rinaldi E, Zusi C, Beatrice G, Saccomani MD, Dalbeni A. Coronavirus disease 2019 (COVID-19) in children and/or adolescents: a meta-analysis. Pediatr Res. 2021;89(4):733–7.

Meena J, Yadav J, Saini L, Yadav A, Kumar J. Clinical features and outcome of SARS-CoV-2 infection in children: a systematic review and meta-analysis. Indian Pediatr. 2020;57(9):820–6.

Mongkonsritragoon W, Prueksapraoprong C, Kewcharoen J, Tokavanich N, Prasitlumkum N, Huang J, Poowuttikul P. Prevalence and risk associated with asthma in children hospitalized with SARS-CoV-2: a meta-analysis and systematic review. J Allergy Clin Immunol Pract. 2022;10(5):1382-1384.e1381.

Navolokina A, Smereka J, Bottiger BW, Pruc M, Juarez-Vela R, Rahnama-Hezavah M, Rafique Z, Peacock FW, Safiejko K, Szarpak L. The impact of COVID-19 on pediatric cardiac arrest outcomes: a systematic review and meta-analysis. Int J Environ Res Public Health. 2023;20(2):1104.

Nepal G, Shrestha GS, Rehrig JH, Gajurel BP, Ojha R, Agrawal A, Panthi S, Khatri B, Adhikari I. Neurological manifestations of COVID-19 associated multi-system inflammatory syndrome in children: a systematic review and meta-analysis. J Nepal Health Res Counc. 2021;19(1):10–8.

Nino G, Zember J, Sanchez-Jacob R, Gutierrez MJ, Sharma K, Linguraru MG. Pediatric lung imaging features of COVID-19: a systematic review and meta-analysis. Pediatr Pulmonol. 2021;56(1):252–63.

Panda PK, Gupta J, Chowdhury SR, Kumar R, Meena AK, Madaan P, Sharawat IK, Gulati S. Psychological and behavioral impact of lockdown and quarantine measures for COVID-19 pandemic on children, adolescents and caregivers: a systematic review and meta-analysis. J Trop Pediatr. 2021;67(1):fmaa122.

Panda PK, Sharawat IK, Panda P, Natarajan V, Bhakat R, Dawman L. Neurological complications of SARS-CoV-2 infection in children: a systematic review and meta-analysis. J Trop Pediatr. 2021;67(3):070.

Pogorelic Z, Anand S, Artukovic L, Krishnan N. Comparison of the outcomes of testicular torsion among children presenting during the Coronavirus Disease 2019 (COVID-19) pandemic versus the pre-pandemic period: a systematic review and meta-analysis. J Pediatr Urol. 2022;18(2):202–9.

Pogorelic Z, Anand S, Zuvela T, Singh A, Krizanac Z, Krishnan N. Incidence of complicated appendicitis during the COVID-19 pandemic versus the pre-pandemic period: a systematic review and meta-analysis of 2782 pediatric Appendectomies. Diagnostics (Basel). 2022;12(1):127.

Qi K, Zeng W, Ye M, Zheng L, Song C, Hu S, Duan C, Wei Y, Peng J, Zhang W, et al. Clinical, laboratory, and imaging features of pediatric COVID-19: a systematic review and meta-analysis. Medicine (Baltimore). 2021;100(15):e25230.

Raccanello D, Rocca E, Vicentini G, Brondino M. Eighteen months of COVID-19 pandemic through the lenses of self or others: a meta-analysis on children and adolescents’ mental health. Child Youth Care Forum. 2022;52:1–24.

Rahmati M, Keshvari M, Mirnasuri S, Yon DK, Lee SW, Il Shin J, Smith L. The global impact of COVID-19 pandemic on the incidence of pediatric new-onset type 1 diabetes and ketoacidosis: a systematic review and meta-analysis. J Med Virol. 2022;94(11):5112–27.

Raschetti R, Vivanti AJ, Vauloup-Fellous C, Loi B, Benachi A, De Luca D. Synthesis and systematic review of reported neonatal SARS-CoV-2 infections. Nat Commun. 2020;11(1):5164.

Richter SA, Ferraz-Rodrigues C, Schilling LB, Camargo NF, Nunes ML. Effects of the COVID-19 pandemic on sleep quality in children and adolescents: a systematic review and meta-analysis. J Sleep Res. 2023;32(1):e13720.

Rodriguez-Gonzalez M, Castellano-Martinez A, Cascales-Poyatos HM, Perez-Reviriego AA. Cardiovascular impact of COVID-19 with a focus on children: a systematic review. World J Clin Cases. 2020;8(21):5250–83.

Ruvinsky S, Voto C, Roel M, Fustinana A, Veliz N, Brizuela M, Rodriguez S, Ulloa-Gutierrez R, Bardach A. Multisystem inflammatory syndrome temporally related to COVID-19 in children from Latin America and the Caribbean Region: a systematic review with a meta-analysis of data from regional surveillance systems. Front Pediatr. 2022;10:881765.

Sabu JM, Zahid I, Jacob N, Alele FO, Malau-Aduli BS. Effectiveness of the BNT162b2 (Pfizer-BioNTech) vaccine in children and adolescents: a systematic review and meta-analysis. Vaccines (Basel). 2022;10(11):1880.

Shah K, Varna VP, Pandya A, Saxena D. Low vitamin D levels and prognosis in a COVID-19 pediatric population: a systematic review. QJM. 2021;114(7):447–53.

Sharma D, Bhaskar SMM. Prevalence of paediatric hyperinflammatory conditions in paediatric and adolescent hospitalized COVID-19 patients: a systematic review and meta-analysis. APMIS. 2022;130(2):101–10.

Sharma M, Aggarwal S, Madaan P, Saini L, Bhutani M. Impact of COVID-19 pandemic on sleep in children and adolescents: a systematic review and meta-analysis. Sleep Med. 2021;84:259–67.

Shi Q, Wang Z, Liu J, Wang X, Zhou Q, Li Q, Yu Y, Luo Z, Liu E, Chen Y, et al. Risk factors for poor prognosis in children and adolescents with COVID-19: a systematic review and meta-analysis. EClinicalMedicine. 2021;41:101155.

Silverberg SL, Zhang BY, Li SNJ, Burgert C, Shulha HP, Kitchin V, Sauvé L, Sadarangani M. Child transmission of SARS-CoV-2: a systematic review and meta-analysis. BMC Pediatr. 2022;22(1):172.

Smith ER, Oakley E, Grandner GW, Ferguson K, Farooq F, Afshar Y, Ahlberg M, Ahmadzia H, Akelo V, Aldrovandi G, et al. Adverse maternal, fetal, and newborn outcomes among pregnant women with SARS-CoV-2 infection: an individual participant data meta-analysis. BMJ Glob Health. 2023;8(1):009495.

Sood M, Sharma S, Sood I, Sharma K, Kaushik A. Emerging evidence on multisystem inflammatory syndrome in children associated with SARS-CoV-2 infection: a systematic review with meta-analysis. SN Compr Clin Med. 2021;3(1):38–47.

Taheri L, Gheiasi SF, Taher M, Basirinezhad MH, Shaikh ZA, Dehghan Nayeri N. Clinical features of COVID-19 in newborns, infants, and children: a systematic review and meta-analysis. Compr Child Adolesc Nurs. 2022;45(2):137–55.

Tang Y, Dang X, Lv M, Norris SL, Chen Y, Ren L, Liu E. Changes in the prevalence of respiratory pathogens in children due to the COVID-19 pandemic: a systematic review and meta-analysis. J Infect. 2023;86(2):154–225.

Tian Y, Chen L, Shi Y. Safety, efficacy, and immunogenicity of varying types of COVID-19 vaccines in children younger than 18 years: an update of systematic review and meta-analysis. Vaccines (Basel). 2022;11(1):87.

Toba N, Gupta S, Ali AY, ElSaban M, Khamis AH, Ho SB, Popatia R. COVID-19 under 19: a meta-analysis. Pediatr Pulmonol. 2021;56(6):1332–41.

Toraih EA, Hussein MH, Elshazli RM, Kline A, Munshi R, Sultana N, Taghavi S, Killackey M, Duchesne J, Fawzy MS, et al. Multisystem inflammatory syndrome in pediatric COVID-19 patients: a meta-analysis. World J Pediatr. 2021;17(2):141–51.

Tripathi AK, Pilania RK, Bhatt GC, Atlani M, Kumar A, Malik S. Acute kidney injury following multisystem inflammatory syndrome associated with SARS-CoV-2 infection in children: a systematic review and meta-analysis. Pediatr Nephrol. 2023;38(2):357–70.

Tsankov BK, Allaire JM, Irvine MA, Lopez AA, Sauve LJ, Vallance BA, Jacobson K. Severe COVID-19 infection and pediatric comorbidities: a systematic review and meta-Analysis. Int J Infect Dis. 2021;103:246–56.

Viner R, Waddington C, Mytton O, Booy R, Cruz J, Ward J, Ladhani S, Panovska-Griffiths J, Bonell C, Melendez-Torres GJ. Transmission of SARS-CoV-2 by children and young people in households and schools: a meta-analysis of population-based and contact-tracing studies. J Infect. 2022;84(3):361–82.

Viner RM, Mytton OT, Bonell C, Melendez-Torres GJ, Ward J, Hudson L, Waddington C, Thomas J, Russell S, van der Klis F, et al. Susceptibility to SARS-CoV-2 infection among children and adolescents compared with adults: a systematic review and meta-analysis. JAMA Pediatr. 2021;175(2):143–56.

Vitaliti G, Giacchi V, Sciacca M, Ruggieri M, Falsaperla R. Thrombotic events in children and adolescent patients with SARS-CoV-2 infection: a systematic review with meta-analysis on incidence and management. Expert Rev Hematol. 2022;15(7):635–43.

Vosoughi F, Makuku R, Tantuoyir MM, Yousefi F, Shobeiri P, Karimi A, Alilou S, LaPorte R, Tilves C, Nabian MH, et al. A systematic review and meta-analysis of the epidemiological characteristics of COVID-19 in children. BMC Pediatr. 2022;22(1):613.

Wang J, Yuan X. Digestive system symptoms and function in children with COVID-19: a meta-analysis. Medicine (Baltimore). 2021;100(11):e24897.

Wang JG, Cui HR, Tang HB, Deng XL. Gastrointestinal symptoms and fecal nucleic acid testing of children with 2019 coronavirus disease: a systematic review and meta-analysis. Sci Rep. 2020;10(1):17846.

Wang JG, Mo YF, Su YH, Wang LC, Liu GB, Li M, Qin QQ. Computed tomography features of COVID-19 in children: a systematic review and meta-analysis. Medicine (Baltimore). 2021;100(38):e22571.

Wang JG, Zhong ZJ, Li M, Fu J, Su YH, Ping YM, Xu ZJ, Li H, Chen YH, Huang YL. Coronavirus disease 2019-related multisystem inflammatory syndrome in children: a systematic review and meta-analysis. Biochem Res Int. 2021;2021:5596727.

Wang JG, Zhong ZJ, Mo YF, Wang LC, Chen R. Epidemiological features of coronavirus disease 2019 in children: a meta-analysis. Eur Rev Med Pharmacol Sci. 2021;25(2):1146–57.

PubMed   Google Scholar  

Wang S, Chen L, Ran H, Che Y, Fang D, Sun H, Peng J, Liang X, Xiao Y. Depression and anxiety among children and adolescents pre and post COVID-19: a comparative meta-analysis. Front Psychiatry. 2022;13:917552.

Wang Z, Zhou Q, Wang C, Shi Q, Lu S, Ma Y, Luo X, Xun Y, Li W, Baskota M, et al. Clinical characteristics of children with COVID-19: a rapid review and meta-analysis. Ann Transl Med. 2020;8(10):620.

Watcharapalakorn A, Poyomtip T, Tawonkasiwattanakun P. Coronavirus disease 2019 outbreak and associated public health measures increase the progression of myopia among children and adolescents: evidence synthesis. Ophthalmic Physiol Opt. 2022;42(4):744–52.

Williams V, Dash N, Suthar R, Mohandoss V, Jaiswal N, Kavitha TK, Nallasamy K, Angurana SK. Clinicolaboratory profile, treatment, intensive care needs, and outcome of pediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2: a systematic review and meta-analysis. J Pediatr Intensive Care. 2022;11(1):1–12.

Xiao F, Tang M, Yan K, Zhou W. Clinical features of infants with SARS-CoV-2 infection: a systematic review and meta-analysis. Ann Palliat Med. 2022;11(11):3394–408.

Xu W, Tang J, Chen C, Wang C, Wen W, Cheng Y, Zhou M, Wu Q, Zhang X, Feng Z, et al. Safety and efficacy of the COVID-19 vaccine in children and/or adolescents: a meta-analysis. J Infect. 2022;84(5):722–46.

Yadav M, Singh A, Meena J, Sankar JM. A systematic review and meta-analysis of otorhinolaryngological manifestations of coronavirus disease 2019 in paediatric patients. J Laryngol Otol. 2022;136(7):588–603.

Yan Q, Qiu D, Liu X, Guo X, Hu Y. Prevalence of smell or taste dysfunction among children with COVID-19 infection: a systematic review and meta-Analysis. Front Pediatr. 2021;9:686600.

Yang F, Wen J, Huang N, Riem MME, Lodder P, Guo J. Prevalence and related factors of child posttraumatic stress disorder during COVID-19 pandemic: a systematic review and meta-analysis. Eur Psychiatry. 2022;65(1):e37.

Yang J, D’Souza R, Kharrat A, Fell DB, Snelgrove JW, Murphy KE, Shah PS. Coronavirus disease 2019 pandemic and pregnancy and neonatal outcomes in general population: a living systematic review and meta-analysis (updated Aug 14, 2021). Acta Obstet Gynecol Scand. 2022;101(1):7–24.

Yang Z, Wang X, Wan XG, Wang ML, Qiu ZH, Chen JL, Shi MH, Zhang SY, Xia YL. Pediatric asthma control during the COVID-19 pandemic: a systematic review and meta-analysis. Pediatr Pulmonol. 2022;57(1):20–5.

Yang Z, Wang X, Zhang S, Ye H, Chen Y, Xia Y. Pediatric myopia progression during the COVID-19 pandemic home quarantine and the risk factors: a systematic review and meta-analysis. Front Public Health. 2022;10:835449.

Yasuhara J, Watanabe K, Takagi H, Sumitomo N, Kuno T. COVID-19 and multisystem inflammatory syndrome in children: a systematic review and meta-analysis. Pediatr Pulmonol. 2021;56(5):837–48.

Zang ST, Han X, Cui Q, Chang Q, Wu QJ, Zhao YH. Imaging characteristics of coronavirus disease 2019 (COVID-19) in pediatric cases: a systematic review and meta-analysis. Transl Pediatr. 2021;10(1):1–16.

Zhang L, Peres TG, Silva MVF, Camargos P. What we know so far about Coronavirus Disease 2019 in children: a meta-analysis of 551 laboratory-confirmed cases. Pediatr Pulmonol. 2020;55(8):2115–27.

Zhao Y, Patel J, Huang Y, Yin L, Tang L. Cardiac markers of multisystem inflammatory syndrome in children (MIS-C) in COVID-19 patients: a meta-analysis. Am J Emerg Med. 2021;49:62–70.

Zheng B, Wang H, Yu C. An increasing public health burden arising from children infected with SARS-CoV2: a systematic review and meta-analysis. Pediatr Pulmonol. 2020;55(12):3487–96.

Zou H, Lu J, Liu J, Wong JH, Cheng S, Li Q, Shen Y, Li C, Jia X. Characteristics of pediatric multi-system inflammatory syndrome (PMIS) associated with COVID-19: a meta-analysis and insights into pathogenesis. Int J Infect Dis. 2021;102:319–26.

Yasuhara J, Masuda K, Aikawa T, Shirasu T, Takagi H, Lee S, Kuno T. Myopericarditis after COVID-19 mRNA vaccination among adolescents and young adults: a systematic review and meta-analysis. JAMA Pediatr. 2023;177(1):42–52.

Watanabe A, Kani R, Iwagami M, Takagi H, Yasuhara J, Kuno T. Assessment of efficacy and safety of mRNA COVID-19 vaccines in children aged 5 to 11 years: a systematic review and meta-analysis. JAMA Pediatr. 2023;144(4):384–94.

Cui X, Zhao Z, Zhang T, Guo W, Guo W, Zheng J, Zhang J, Dong C, Na R, Zheng L, et al. A systematic review and meta-analysis of children with coronavirus disease 2019 (COVID-19). J Med Virol. 2021;93(2):1057–69.

Dorantes-Acosta E, Avila-Montiel D, Klunder-Klunder M, Juarez-Villegas L, Marquez-Gonzalez H. Survival and complications in pediatric patients with cancer and COVID-19: a meta-analysis. Front Oncol. 2020;10:608282.

Mustafa NM. L AS: characterisation of COVID-19 pandemic in paediatric age group: a systematic review and meta-analysis. J Clin Virol. 2020;128:104395.

Neef V, Buxmann H, Rabenau HF, Zacharowski K, Raimann FJ. Characterization of neonates born to mothers with SARS-CoV-2 infection: review and meta-analysis. Pediatr Neonatol. 2021;62(1):11–20.

Carabelli AM, Peacock TP, Thorne LG, Harvey WT, Hughes J, Consortium C-GU, Peacock SJ, Barclay WS, de Silva TI, Towers GJ, et al. SARS-CoV-2 variant biology: immune escape, transmission and fitness. Nat Rev Microbiol. 2023;21(3):162–77.

CAS   PubMed   PubMed Central   Google Scholar  

Stephenson T, Shafran R, Ladhani SN. Long COVID in children and adolescents. Curr Opin Infect Dis. 2022;35(5):461–7.

Golberstein E, Wen H, Miller BF. Coronavirus disease 2019 (COVID-19) and mental health for children and adolescents. JAMA Pediatr. 2020;174(9):819–20.

Paterson C, Davis D, Roche M, Bissett B, Roberts C, Turner M, Baldock E, Mitchell I. What are the long-term holistic health consequences of COVID-19 among survivors? An umbrella systematic review. J Med Virol. 2022;94(12):5653–68.

Nittas V, Gao M, West EA, Ballouz T, Menges D, Wulf Hanson S, Puhan MA. Long COVID through a public health lens: an umbrella review. Public Health Rev. 2022;43:1604501.

Witteveen AB, Young SY, Cuijpers P, Ayuso-Mateos JL, Barbui C, Bertolini F, Cabello M, Cadorin C, Downes N, Franzoi D, et al. COVID-19 and common mental health symptoms in the early phase of the pandemic: an umbrella review of the evidence. Plos Med. 2023;20(4):e1004206.

Bevilacqua L, Fox-Smith L, Lewins A, Jetha P, Sideri A, Barton G, Meiser-Stedman R, Beazley P. Impact of COVID-19 on the mental health of children and young people: an umbrella review. J Epidemiol Community Health. 2023;77(11):704–9.

Fan Y, Li X, Zhang L, Wan S, Zhang L, Zhou F. SARS-CoV-2 Omicron variant: recent progress and future perspectives. Signal Transduct Target Ther. 2022;7(1):141.

Iuliano AD, Brunkard JM, Boehmer TK, Peterson E, Adjei S, Binder AM, Cobb S, Graff P, Hidalgo P, Panaggio MJ, et al. Trends in disease severity and health care utilization during the early omicron variant period compared with previous SARS-CoV-2 high transmission periods - United States, December 2020-January 2022. MMWR Morb Mortal Wkly Rep. 2022;71(4):146–52.

Garrett N, Tapley A, Andriesen J, Seocharan I, Fisher LH, Bunts L, Espy N, Wallis CL, Randhawa AK, Miner MD, et al. High asymptomatic carriage with the omicron variant in South Africa. Clin Infect Dis. 2022;75(1):e289–92.

Mocanu V, Bhagwani D, Sharma A, Borza C, Rosca CI, Stelian M, Bhagwani S, Haidar L, Kshtriya L, Kundnani NR, et al. COVID-19 and the human eye: conjunctivitis, a lone COVID-19 finding - a case-control study. Med Princ Pract. 2022;31(1):66–73.

Al-Namaeh M. Ocular manifestations of COVID-19. Ther Adv Ophthalmol. 2022;14:25158414221083376.

Shang W, Kang L, Cao G, Wang Y, Gao P, Liu J, Liu M. Percentage of asymptomatic infections among SARS-CoV-2 omicron variant-positive individuals: a systematic review and meta-analysis. Vaccines (Basel). 2022;10(7):1049.

Zhang JJ, Dong X, Liu GH, Gao YD. Risk and protective factors for COVID-19 morbidity, severity, and mortality. Clin Rev Allergy Immunol. 2023;64(1):90–107.

Zhao S, Luo K, Guo Y, Fang M, Sun Q, Dai Z, Yang H, Zhan Z, Hu S, Chen T, et al. Analysis of factors influencing the clinical severity of omicron and delta variants. Trop Med Infect Dis. 2023;8(6):330.

Jones TC, Biele G, Muhlemann B, Veith T, Schneider J, Beheim-Schwarzbach J, Bleicker T, Tesch J, Schmidt ML, Sander LE, et al. Estimating infectiousness throughout SARS-CoV-2 infection course. Science. 2021;373(6551):eabi5273.

Reyman M, Clerc M, van Houten MA, Arp K, Chu M, Hasrat R, Sanders EAM, Bogaert D. Microbial community networks across body sites are associated with susceptibility to respiratory infections in infants. Commun Biol. 2021;4(1):1233.

Bastard P, Gervais A, Le Voyer T, Rosain J, Philippot Q, Manry J, Michailidis E, Hoffmann HH, Eto S, Garcia-Prat M, et al. Autoantibodies neutralizing type I IFNs are present in ~4% of uninfected individuals over 70 years old and account for ~20% of COVID-19 deaths. Sci Immunol. 2021;6(62):eabl4340.

Niessl J, Sekine T, Lange J, Konya V, Forkel M, Maric J, Rao A, Mazzurana L, Kokkinou E, Weigel W, et al. Identification of resident memory CD8(+) T cells with functional specificity for SARS-CoV-2 in unexposed oropharyngeal lymphoid tissue. Sci Immunol. 2021;6(64):eabk0894.

Flannery DD, Gouma S, Dhudasia MB, Mukhopadhyay S, Pfeifer MR, Woodford EC, Triebwasser JE, Gerber JS, Morris JS, Weirick ME, et al. Assessment of maternal and neonatal cord blood SARS-CoV-2 antibodies and placental transfer ratios. JAMA Pediatr. 2021;175(6):594–600.

Grimsholm O, Piano Mortari E, Davydov AN, Shugay M, Obraztsova AS, Bocci C, Marasco E, Marcellini V, Aranburu A, Farroni C, et al. The interplay between CD27(dull) and CD27(bright) B cells ensures the flexibility, stability, and resilience of human B cell memory. Cell Rep. 2020;30(9):2963-2977.e2966.

Saheb Sharif-Askari N, Saheb Sharif-Askari F, Alabed M, Temsah MH, Al Heialy S, Hamid Q, Halwani R. Airways expression of SARS-CoV-2 receptor, ACE2, and TMPRSS2 is lower in children than adults and increases with smoking and COPD. Mol Ther Methods Clin Dev. 2020;18:1–6.

Bradley T, Tucker M, Sampath V: Triggered - does maternal COVID-19 program an exaggerated immune response in neonates? Pediatr Res 2024 early eprint. https://www.nature.com/articles/s41390-023-03007-0#citeas .

Brodin P. SARS-CoV-2 infections in children: Understanding diverse outcomes. Immunity. 2022;55(2):201–9.

Noval Rivas M, Porritt RA, Cheng MH, Bahar I, Arditi M. Multisystem inflammatory syndrome in children and long COVID: The SARS-CoV-2 viral superantigen hypothesis. Front Immunol. 2022;13:941009.

Borel M, Xie L, Kapera O, Mihalcea A, Kahn J, Messiah SE. Long-term physical, mental and social health effects of COVID-19 in the pediatric population: a scoping review. World J Pediatr. 2022;18(3):149–59.

Kikkenborg Berg S, Palm P, Nygaard U, Bundgaard H, Petersen MNS, Rosenkilde S, Thorsted AB, Ersboll AK, Thygesen LC, Nielsen SD, et al. Long COVID symptoms in SARS-CoV-2-positive children aged 0–14 years and matched controls in Denmark (LongCOVIDKidsDK): a national, cross-sectional study. Lancet Child Adolesc Health. 2022;6(9):614–23.

Bloise S, Isoldi S, Marcellino A, De Luca E, Dilillo A, Mallardo S, Martucci V, Sanseviero M, Del Giudice E, Iorfida D, et al. Clinical picture and long-term symptoms of SARS-CoV-2 infection in an Italian pediatric population. Ital J Pediatr. 2022;48(1):79.

Miller GE, Chen E, Parker KJ. Psychological stress in childhood and susceptibility to the chronic diseases of aging: moving toward a model of behavioral and biological mechanisms. Psychol Bull. 2011;137(6):959–97.

Cao X, Ma C, Zheng Z, He L, Hao M, Chen X, Crimmins EM, Gill TM, Levine ME, Liu Z. Contribution of life course circumstances to the acceleration of phenotypic and functional aging: a retrospective study. EClinicalMedicine. 2022;51:101548.

Siegel DA, Reses HE, Cool AJ, Shapiro CN, Hsu J, Boehmer TK, Cornwell CR, Gray EB, Henley SJ, Lochner K, et al. Trends in COVID-19 cases, emergency department visits, and hospital admissions among children and adolescents aged 0–17 Years - United States, August 2020-August 2021. MMWR Morb Mortal Wkly Rep. 2021;70(36):1249–54.

de Miranda DM, da Silva AB, Oliveira ACS, Simoes-e-Silva AC. How is COVID-19 pandemic impacting mental health of children and adolescents? Int J Disaster Risk Reduction. 2020;51:101845.

Loades ME, Chatburn E, Higson-Sweeney N, Reynolds S, Shafran R, Brigden A, Linney C, McManus MN, Borwick C, Crawley E. Rapid systematic review: the impact of social isolation and loneliness on the mental health of children and adolescents in the context of COVID-19. J Am Acad Child Adolesc Psychiatry. 2020;59(11):1218-1239 e1213.

Shelleby EC, Pittman LD, Bridgett DJ, Keane J, Zolinski S, Caradec J. Associations between local COVID-19 case rates, pandemic-related financial stress and parent and child functioning. J Fam Psychol. 2022;36(6):932–42.

Suarez-Lopez JR, Cairns MR, Sripada K, Quiros-Alcala L, Mielke HW, Eskenazi B, Etzel RA, Kordas K. COVID-19 and children’s health in the United States: consideration of physical and social environments during the pandemic. Environ Res. 2021;197:111160.

Tandon PS, Zhou C, Johnson AM, Gonzalez ES, Kroshus E. Association of children’s physical activity and screen time with mental health during the COVID-19 pandemic. JAMA Netw Open. 2021;4(10):e2127892.

Montero-Marin J, Hinze V, Mansfield K, Slaghekke Y, Blakemore SJ, Byford S, Dalgleish T, Greenberg MT, Viner RM, Ukoumunne OC, et al. Young people’s mental health changes, risk, and resilience during the COVID-19 pandemic. JAMA Netw Open. 2023;6(9):e2335016.

Tian F, Yang R, Chen Z. Safety and efficacy of COVID-19 vaccines in children and adolescents: a systematic review of randomized controlled trials. J Med Virol. 2022;94(10):4644–53.

Haslak F, Gunalp A, Cebi MN, Yildiz M, Adrovic A, Sahin S, Barut K, Kasapcopur O. Early experience of COVID-19 vaccine-related adverse events among adolescents and young adults with rheumatic diseases: a single-center study. Int J Rheum Dis. 2022;25(3):353–63.

Erbas IM, Erbas IC, Kagizmanli GA, Yuksek Acinikli K, Besci O, Demir K, Bober E, Belet N, Abaci A. Adverse events associated with COVID-19 vaccination in adolescents with endocrinological disorders: a cross-sectional study. J Clin Res Pediatr Endocrinol. 2023;15(3):248–56.

Kastl AJ, Weaver KN, Zhang X, Strople JA, Adler J, Dubinsky MC, Bousvaros A, Watkins R, Dai X, Chen W, et al. Humoral immune response and safety of SARS-CoV-2 vaccination in pediatric inflammatory bowel disease. Am J Gastroenterol. 2023;118(1):129–37.

Thomas SJ, Moreira ED Jr, Kitchin N, Absalon J, Gurtman A, Lockhart S, Perez JL, Pérez Marc G, Polack FP, Zerbini C, et al. Safety and efficacy of the BNT162b2 mRNA Covid-19 vaccine through 6 months. N Engl J Med. 2021;385(19):1761–73.

Price AM, Olson SM, Newhams MM, Halasa NB, Boom JA, Sahni LC, Pannaraj PS, Irby K, Bline KE, Maddux AB, et al. BNT162b2 protection against the omicron variant in children and adolescents. N Engl J Med. 2022;386(20):1899–909.

Breaux R, Cash AR, Lewis J, Garcia KM, Dvorsky MR, Becker SP. Impacts of COVID-19 quarantine and isolation on adolescent social functioning. Curr Opin Psychol. 2023;52:101613.

Viner RM, Russell SJ, Croker H, Packer J, Ward J, Stansfield C, Mytton O, Bonell C, Booy R. School closure and management practices during coronavirus outbreaks including COVID-19: a rapid systematic review. Lancet Child Adolesc Health. 2020;4(5):397–404.

Graetz D, Agulnik A, Ranadive R, Vedaraju Y, Chen Y, Chantada G, Metzger ML, Mukkada S, Force LM, Friedrich P, et al. Global effect of the COVID-19 pandemic on paediatric cancer care: a cross-sectional study. Lancet Child Adolesc Health. 2021;5(5):332–40.

Jiao WY, Wang LN, Liu J, Fang SF, Jiao FY, Pettoello-Mantovani M, Somekh E. Behavioral and emotional disorders in children during the COVID-19 epidemic. J Pediatr. 2020;221(264–266): e261.

Masse LC, Edache IY, Pitblado M, Hutchison SM. The impact of financial and psychological wellbeing on children’s physical activity and screen-based activities during the COVID-19 pandemic. Int J Environ Res Public Health. 2021;18(16):8694.

Wilder JL, Parsons CR, Growdon AS, Toomey SL, Mansbach JM. Pediatric hospitalizations during the COVID-19 pandemic. Pediatrics. 2020;146(6):e2020005983.

Dekkers OM, Vandenbroucke JP, Cevallos M, Renehan AG, Altman DG, Egger M. COSMOS-E: Guidance on conducting systematic reviews and meta-analyses of observational studies of etiology. Plos Med. 2019;16(2):e1002742.

Varsavsky T, Graham MS, Canas LS, Ganesh S, Capdevila Pujol J, Sudre CH, Murray B, Modat M, Jorge Cardoso M, Astley CM, et al. Detecting COVID-19 infection hotspots in England using large-scale self-reported data from a mobile application: a prospective, observational study. Lancet Public Health. 2021;6(1):e21–9.

Essig RM, Jones BA. Challenges in the multidisciplinary management of pediatric patients with intestinal failure during the COVID-19 pandemic. Pediatr Ann. 2022;51(7):e277–80.

Sniderman ER, Graetz DE, Agulnik A, Ranadive R, Vedaraju Y, Chen Y, Devidas M, Chantada GL, Hessissen L, Dalvi R, et al. Impact of the COVID-19 pandemic on pediatric oncology providers globally: a mixed-methods study. Cancer. 2022;128(7):1493–502.

Gelman A, Stern H. The difference between “significant” and “not significant” is not itself statistically significant. Am Stat. 2006;60(4):328–31.

Download references

Acknowledgements

This work is supported by the National Natural Science Foundation of China (82301106), Natural Science Foundation of Sichuan province (24NSFSC3535), Fundamental Research Funds for the Central Universities and Research and Develop Program, West China Hospital of Stomatology Sichuan University (RD-02–202409).

Author information

Chengchen Duan, Liu Liu, and Tianyi Wang contributed equally to this article.

Authors and Affiliations

State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, No.14, 3rd Section of Ren Min Nan Rd., Chengdu, 610041, China

Chengchen Duan, Liu Liu, Tianyi Wang, Guanru Wang, Zhishen Jiang, Honglin Li, Gaowei Zhang, Li Ye, Chunjie Li & Yubin Cao

Department of Conservative Dentistry and Endodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, China

Department of Head and Neck Oncology, West China Hospital of Stomatology, Sichuan University, Chengdu, China

Guanru Wang, Honglin Li, Gaowei Zhang, Li Ye & Chunjie Li

Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, China

Department of Evidence-Based Stomatology, West China Hospital of Stomatology, Sichuan University, Chengdu, China

Chunjie Li & Yubin Cao

You can also search for this author in PubMed   Google Scholar

Contributions

The research was conceptualized and designed by Y.C. and L.C. The data were obtained and compiled by T.W., C.D., G.Z., L.Y., and L.L., and analyzed by L.L. and C.D. The manuscript was drafted by L.L., C.D., T.W., and G.W., and critically reviewed for significant intellectual content by L.L., C.D., T.W., Z.J., H.L., C.L., and Y.C. All authors read and approved the final manuscript.

Authors’ Twitter handles

@LiuLiu_DDS (Liu Liu); @YubinCao (Yubin Cao).

Corresponding author

Correspondence to Yubin Cao .

Ethics declarations

Consent for publication.

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1..

Differences between protocol and review.

Additional file 2.

PRISMA 2020 checklist.

Additional file 3.

Search strategy.

Additional file 4.

List of excluded studies with justification for exclusion.

Additional file 5.

Detailed information on the characteristics of the included systematic reviews.

Additional file 6.

AMSTAR2 methodological quality assessments.

Additional file 7.

Primary studies data extracted from single-armed meta-analyses of laboratory-confirmed COVID-19.

Additional file 8.

Additional COVID-19-related evidence from single-armed meta-analyses.

Additional file 9.

Effect sizes and forest plots on COVID-19-associated multisystem inflammatory syndrome.

Additional file 10.

Effect sizes and forest plots on newborns from COVID-19-diagnosed mothers.

Additional file 11.

Effect sizes and forest plots on long-COVID.

Additional file 12.

Effect sizes and forest plots on events caused by the COVID-19 vaccine.

Additional file 13.

Effect sizes and forest plots on health impacts during the pandemic.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Duan, C., Liu, L., Wang, T. et al. Evidence linking COVID-19 and the health/well-being of children and adolescents: an umbrella review. BMC Med 22 , 116 (2024). https://doi.org/10.1186/s12916-024-03334-x

Download citation

Received : 03 August 2023

Accepted : 04 March 2024

Published : 13 March 2024

DOI : https://doi.org/10.1186/s12916-024-03334-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • COVID-19, Children and adolescents
  • Comorbidity
  • Mental health
  • Umbrella review

BMC Medicine

ISSN: 1741-7015

descriptive research design about mental health

  • Open access
  • Published: 05 September 2023

Factors associated with suicide in people who use drugs: a scoping review

  • Joan Devin 1 , 2 ,
  • Suzi Lyons 1 ,
  • Lisa Murphy 1 ,
  • Michael O’Sullivan 1 &
  • Ena Lynn 1  

BMC Psychiatry volume  23 , Article number:  655 ( 2023 ) Cite this article

1925 Accesses

2 Citations

16 Altmetric

Metrics details

Suicide is a significant contributor to global mortality. People who use drugs (PWUD) are at increased risk of death by suicide relative to the general population, but there is a lack of information on associated candidate factors for suicide in this group. The aim of this study was to provide a comprehensive overview of existing evidence on potential factors for death by suicide in PWUD.

A scoping review was conducted according to the Arksey and O’Malley framework. Articles were identified using Medline, CINAHL, PsycINFO, SOCIndex, the Cochrane Database of Systematic Reviews and the Campbell Collaboration Database of Systematic Reviews; supplemented by grey literature, technical reports, and consultation with experts. No limitations were placed on study design. Publications in English from January 2000 to December 2021 were included. Two reviewers independently screened full-text publications for inclusion. Extracted data were collated using tables and accompanying narrative descriptive summaries. The review was reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines.

The initial search identified 12,389 individual publications, of which 53 met the inclusion criteria. The majority (87%) of included publications were primary research, with an uncontrolled, retrospective study design. The most common data sources were drug treatment databases or national death indexes. Eleven potential factors associated with death by suicide among PWUD were identified: sex; mental health conditions; periods of heightened vulnerability; age profile; use of stimulants, cannabis, or new psychoactive substances; specific medical conditions; lack of dual diagnosis service provision; homelessness; incarceration; intravenous drug use; and race or ethnicity. Opioids, followed by cannabis and stimulant drugs were the most prevalent drugs of use in PWUD who died by suicide. A large proportion of evidence was related to opioid use; therefore, more primary research on suicide and explicit risk factors is required.

Conclusions

The majority of studies exploring factors associated with death by suicide among PWUD involved descriptive epidemiological data, with limited in-depth analyses of explicit risk factors. To prevent suicide in PWUD, it is important to consider potential risk factors and type of drug use, and to tailor policies and practices accordingly.

Peer Review reports

Suicide is a significant global public health concern [ 1 , 2 ]. The World Health Organization (WHO) estimates that over 700,000 people die by suicide each year, with more deaths attributed to suicide than malaria, HIV/AIDS, breast cancer, or war and homicide [ 3 ]. The Global Burden of Disease Study 2016 [ 2 ] found that while age standardised mortality rates for suicide have greatly reduced since 1990, suicide remains an important contributor to mortality.

Suicide is defined as a death caused by intentional, self-directed injury [ 4 ]. The factors that contribute to suicide are complex and wide-ranging [ 1 , 5 , 6 ]. Suicidal behaviour varies according to sex, age, geographic distribution, and socio-political setting [ 3 , 7 , 8 ]. Rates of suicide are consistently higher in men than in women, although women outnumber men in suicide attempts [ 3 , 7 , 9 , 10 ].

The effects of suicide in society are significant. For the families, friends and communities bereaved through suicide there is a severe emotional toll [ 11 , 12 , 13 ]. Direct monetary costs linked to suicide include the cost of emergency services, medical care, medicolegal costs and funeral expenses, while indirect costs to society include loss of earnings due to premature mortality [ 14 , 15 ]. The WHO Comprehensive Mental Health Action Plan 2013–2030 [ 16 ] sets a target of reducing global suicide mortality by one third by 2030. A defined action for WHO Member States to reach this target, is the development and implementation of strategies for mental health promotion and suicide prevention, with emphasis on locally-identified vulnerable and marginalized groups, with a recommendation to include people with mental disorders as a vulnerable and marginalized group [ 16 ].

One such vulnerable population known to be at increased risk of death by suicide are people who use drugs (PWUD) [ 17 , 18 , 19 , 20 , 21 ]. Evidence from epidemiological and clinical research indicates a 7- to 22-fold increase in suicide mortality among PWUD relative to that expected in the general population [ 20 , 21 , 22 , 23 ]. While there have been several literature reviews on risk factors for suicide among PWUD [ 5 , 19 , 24 , 25 , 26 ], and previous systematic reviews [ 18 , 23 , 27 , 28 , 29 ] and meta-analyses [ 22 , 30 , 31 ] that aimed to quantify the association of problem drug use with suicide mortality among high-risk groups, no study has sought to systematically identify and thematically map the available evidence on potential factors associated with suicide among PWUD.

Suicide prevention strategies may be universal (such as mental health policies, alcohol reduction policies, and restricting access to means of suicide), or targeted and selective (such as strategies focusing on young people, or education programmes for doctors to help them identify at-risk individuals) [ 1 , 16 , 32 ]. Given that PWUD remain a high-risk group for dying by suicide, they may not benefit from universal prevention strategies to the same extent as the general population. Therefore, understanding specific, characteristics, risks and the contexts in which risk may be amplified in this population are critical precursors to developing targeted interventions and suicide prevention strategies. Due to the limited clarity on the extent, range, and nature of the evidence regarding factors associated with death by suicide among PWUD, as well as ambiguity regarding the overall progress and direction of this field of research, a scoping review was judged to be an appropriate study design to address this issue.

The aim of this review was to provide a comprehensive overview of existing evidence on factors associated with death by suicide, specifically among PWUD, using a scoping review methodology. The objectives were:

To map the extent, range, and nature of available evidence on factors associated with death by suicide among PWUD.

To identify knowledge gaps and limitations in this body of evidence, and.

To inform suicide prevention policy and best practice guidelines for working with PWUD, where appropriate.

Scoping reviews are an increasingly popular form of knowledge synthesis that aim to systematically search and map the breadth of available evidence (including evidence in published and grey literature), categorise key concepts, identify knowledge gaps and research deficits, and propose recommendations to guide future research [ 33 , 34 ]. A key characteristic of a scoping review is the incorporation of stakeholder consultation into the methodological framework to both inform and validate the study findings [ 35 ]. This process provides opportunity for knowledge transfer and exchange with experts working at the intersection of research, policy and practice.

The review was guided by the methodological framework for scoping reviews outlined by Arksey and O’Malley [ 36 ], and updated by Peters et al. [ 35 ]. This framework involves six stages, discussed in further detail below. The scoping review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) (Appendix 1) [ 37 ]. A protocol for this study was previously published in 2021 [ 38 ].

Stage 1: Identifying the research question

The following research question was identified based on the overarching aim of the scoping review: What is the extent, range, and nature of evidence regarding factors associated with death by suicide among PWUD? Further explanation of the definitions used to guide the research question are provided in Appendix 2.

Stage 2: Identify and retrieve relevant items

A comprehensive search strategy to identify relevant literature was developed in accordance with scoping review guidance and was peer-reviewed by an information specialist [ 39 ].

The inclusion and exclusion criteria for the review were developed through an iterative process as the searches progressed. For the purposes of the scoping review, PWUD was considered an umbrella phrase under which various terms indicative of problem drug use are subsumed, including, but not limited to, any of the following: people who use, misuse, or abuse drugs (including non-medical use of licit drugs and illicit drug use); people with a diagnosis of substance use disorder (SUD) / drug use disorder (DUD); people with drug dependence; people who are regular or ‘casual’ users of drugs; and people who report recent drug use. All peer-reviewed and non-peer-reviewed articles, reports, and reviews published in the English language were eligible for inclusion. Searches were limited to evidence sources published between January 2000 and December 2021 inclusive, with the most recent literature search executed in December 2021. No limitations were placed on study design. Full inclusion and exclusion criteria are provided in Table  1 .

The bibliographic databases Medline, CINAHL, PsycINFO, SOCIndex, the Cochrane Database of Systematic Reviews, and the Campbell Collaboration Database of Systematic Reviews were searched. Key academic journals were hand searched for relevant published articles. Grey literature databases, including Open Grey, were searched using keywords and phrases identified in published literature. Finally, the review team contacted academic experts, professional societies and relevant organisations to ascertain the availability of any additional evidence sources not identified in previous searches. See Appendix 3 for full search terms.

Stage 3: Selecting studies

Titles and abstracts retrieved from databases were screened in Eppi-Reviewer 4.0, a software program for managing and analysing data used in literature reviews, including scoping reviews [ 40 ]. Four reviewers (EL, LM, MOS, and SL) screened all titles and abstracts against the inclusion criteria. At the full-text stage of screening, pdf copies of the relevant publications were imported to and managed using the Zotero bibliographic management software and reviewed independently by two reviewers (JD and EL). Reasons for exclusion of full texts included: study not focused on PWUD, suicide deaths not an outcome, studies with a pathology or toxicology focus, use of illicit drugs only to complete the act of suicide, or if clear factors for death by suicide could not be identified. Quality appraisal of full texts was not performed, as this is generally not recommended in scoping reviews because the aim is to map the available evidence rather than provide a synthesized and clinically meaningful answer to a question [ 39 ]. Where the review team identified sources with obvious overlap in either participant samples or datasets, sources that provide the most information relevant to the aims of the scoping review only were included. Any uncertainty in relation to publication eligibility was resolved through discussion with the other authors.

Stage 4: Mapping/charting the data

Full texts were examined and sorted in Zotero according to emerging themes. Data were charted by all authors using a data charting form. Data identified for extraction were informed by the purpose of the scoping review and, as with the other stages, this was an iterative process, progressing as the charting of this scoping review developed. Consultation took place throughout the data charting process with literature excluded if the authors agreed through consensus that there was insufficient data on the topic. The following information was collated on the data charting form: study characteristics, aim of the study/report, study design, setting, population characteristics, the use of diagnostic inclusion criteria for drug use or the authors definition of drug use, the presence/absence of a control or comparison group, definition of suicide, risk factors for death by suicide, data analysis, the main findings, interpretation of findings, recommendations for future research, study limitations, and themes. A final selection of 53 studies was agreed for inclusion. This included three additional publications captured through the consultation exercise (Fig.  1 ).

figure 1

PRISMA (Flow diagram of study selection [ 41 ]

Stage 5: Collating, summarising, and reporting the results

The data were collated and summarised in accordance with the overall aim and objectives of the scoping review. A narrative account of the findings was presented. Descriptive analysis of studies included information related to geographic distribution, publication dates, evidence source, study design, and primary drug of focus. An overview of research limitations, and considerations for policy and practice extracted from reports and policy documents were also charted, summarised, and integrated into the review findings.

Stage 6: Expert consultation

Consultations took place with national experts from the Irish National Drug-Related Deaths Index (NDRDI) Steering Committee and the Technical Advisory Group of the National Office of Suicide Prevention, and international experts from the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA), the World Health Organization (WHO), and key authors in the area of addiction research. These consultations, which were primarily by email, provided references for review and insights into international issues associated with factors for death by suicide in PWUD not previously found in the literature.

Publication characteristics

Characteristics related to 152 publications were charted, with a final selection of 53 publications included in the scoping review.

The majority (n = 46, 87%) of publications included primary research, with an uncontrolled, retrospective study design [ 20 , 21 , 24 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 ] (Table  2 ). The most common type of data sources used in primary research studies were drug treatment databases or national death indexes, followed by coroner’s records and medical records. Secondary research consisted of literature reviews or reports (n = 6, 11%) [ 23 , 25 , 85 , 86 , 87 , 88 ], and one editorial article [ 89 ].

Almost half (n = 22, 42%) of publications contained data from studies carried out in the European countries of Denmark, the United Kingdom, Spain, Norway, France, Slovenia, Scotland, Finland, Italy, Switzerland, and Sweden [ 20 , 42 , 43 , 44 , 48 , 49 , 50 , 51 , 56 , 59 , 60 , 61 , 62 , 63 , 65 , 66 , 70 , 82 , 83 , 84 , 87 , 89 ]. The next largest group were studies carried out in Australia (n = 11, 21%) [ 53 , 54 , 55 , 57 , 58 , 71 , 73 , 74 , 77 , 78 , 81 ], followed by the United States (US) (n = 7, 14%) [ 21 , 24 , 45 , 47 , 52 , 67 , 68 ]. Over three quarters (n = 40, 75%) of publications were published since 2013.

Thirty-six (68%) publications focused on PWUD as the population [ 20 , 25 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 86 , 87 , 88 ], while the remaining 17 (32%) included outcomes for PWUD as a sub-group [ 21 , 23 , 24 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 85 , 89 ]. Diagnostic inclusion criteria for drug use included a clinical diagnosis or clear history of drug use, corresponding International Classification of Diseases (ICD) codes, or inclusion in opioid agonist treatment registers. Interviews or survey methods, either of the person themselves or next of kin, were used in three (6%) publications to determine a participant’s drug use [ 47 , 52 , 54 ].

The definition of suicide varied across the publications, depending on the primary data source used (Table  2 ). The most common way to determine suicide was through use of ICD codes (n = 23, 43%), and coroner’s verdicts and autopsy findings (n = 14, 26%), followed by manner of death as recorded in general mortality registers (n = 7, 13%). Overall, there was limited in-depth analysis of explicit risk factors for suicide among PWUD, highlighting this as a gap in research.

Drugs identified in publications exploring suicide in PWUD

The majority of publications included in the review focused on the use of a particular type of drug. Twenty-four publications examined opioid use, including the use of opioid agonist treatment (OAT) in PWUD. Two publications focused on cannabis use and mortality [ 55 , 86 ], one on cocaine use disorder in patients with concurrent alcohol or opioid disorder [ 56 ], one on use of methamphetamines [ 57 ], one on opioid or amphetamine use [ 58 ], and one on new psychoactive substances (NPS) [ 59 ]. The remaining 24 publications included any type of DUD population [ 20 , 21 , 23 , 29 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 60 , 61 , 62 , 63 , 64 , 87 , 89 ].

Overall, opioids were the most commonly reported drug type used by PWUD who died by suicide (n = 34, 64%), followed by cannabis (n = 10, 19%), and cocaine (n = 8, 15%). Polydrug use was linked to death by suicide in ten (19%) publications. A breakdown of the primary drugs linked to PWUD who died by suicide is provided in Table  3 .

Where the suicide decedent used opioids, the concurrent presence of central nervous system depressants such as benzodiazepines, or antidepressants, was linked to increased risk of death by suicide in three publications [ 65 , 66 , 88 ]. The distinction between whether a person who used opioids was abusing prescription or illicit opioids was not made in most publications, although 15 studies focused on PWUD who were prescribed opioid agonist treatment such as methadone or buprenorphine [ 49 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 85 ]. A further two studies identified PWUD who misused licit or prescription opioids, including oxycodone and dihydrocodeine, and who died by suicide [ 66 , 79 ].

The majority of publications presented aggregate data on suicide method in PWUD. Twelve studies provided specific data on the method of suicide [ 45 , 48 , 54 , 55 , 57 , 58 , 59 , 60 , 62 , 65 , 74 , 80 ]. Non-poisoning deaths, such as hangings or death by firearms, appeared more frequent than poisoning deaths in PWUD, in these particular publications.

Factors associated with death by suicide in PWUD

Themes and associated publications are provided in Table  4 .

Sex was reported as a candidate factor in 26 (53%) publications. Twelve were primary research studies [ 25 , 45 , 47 , 53 , 54 , 55 , 57 , 58 , 62 , 64 , 72 , 77 , 81 ], one was a technical report [ 87 ], and one was a narrative review [ 25 ].

Male sex was reported as a factor associated with death by suicide in 14 (54%) publications. Men who used drugs were more likely to die by suicide than women in 11 primary research studies [ 45 , 53 , 54 , 55 , 57 , 58 , 62 , 64 , 72 , 73 , 77 ]. Darke and Ross [ 25 ] reported a higher prevalence of death by suicide among men who used heroin relative to women who used heroin throughout the literature. The EMCDDA also reported that PWUD who died by suicide in Europe were predominantly male.

Cannabis use was identified as a risk factor for suicide in men in three publications [ 47 , 55 , 62 ]. Stimulants, such as amphetamines, were also more common among men who use drugs and died by suicide, than women [ 45 , 57 , 58 , 62 ].

Thirteen (50%) of the 26 publications that reported on sex reported links with female sex and risk of death by suicide [ 21 , 24 , 46 , 47 , 48 , 49 , 50 , 51 , 63 , 75 , 76 , 78 , 84 ]. While it is generally accepted men are at higher risk of death by suicide than women in the general population [ 3 , 16 ], eight studies reported proportionally higher risk of suicide in women with DUD than in men with DUD [ 21 , 24 , 46 , 47 , 51 , 75 , 78 , 84 ]. Onyeka et al. [ 63 ] identified a higher mean potential years of life lost (PYLL) due to suicide for women who used drugs than men who used drugs (44.9 years vs. 39.1), even though men had higher absolute numbers of deaths.

While Adams et al. [ 49 ] did not demonstrate an increased risk of death by suicide among women in comparison to men in their study, they identified higher proportions of sedative, hypnotic or anxiolytic-related disorders, and psychoactive substance use disorders among women who died by suicide than in men.

In the two studies that solely focused exclusively on women who used drugs, high rates of mental health problems were linked to risk of death by suicide [ 48 , 76 ]. No studies focused exclusively on men. Of note is the lack of evidence in the area of trans and gender-diverse people who use drugs and die as a result of suicide.

Mental health conditions

Long-term SUD have been linked to mental health issues, and conversely, mental health conditions have been linked to increased levels of drug or alcohol use [ 90 ]. The term dual diagnosis, or the combined presence of a mental health problem and a substance use problem, may be used in practice as a diagnostic label [ 90 ]. There was a high prevalence of mental health problems among PWUD who died by suicide in the review. Twenty-two (42%) publications identified mental health as a candidate factor for death by suicide in this population [ 20 , 24 , 25 , 42 , 43 , 44 , 46 , 48 , 49 , 54 , 57 , 62 , 65 , 66 , 67 , 69 , 74 , 76 , 79 , 80 , 88 , 89 ].

Depressive disorders were the most frequently cited comorbid mental health condition identified in the review. Thirteen publications identified high prevalence of depression or anxiety, a history of self-harm, or a previous suicide attempt among PWUD who died by suicide [ 25 , 44 , 48 , 54 , 57 , 65 , 66 , 69 , 74 , 76 , 79 , 80 , 88 ]. The prevalence of depressive disorders or history of suicide attempt in people who use opioids who later died by suicide was as high as 65% [ 69 ] and 89% [ 54 ] in two studies respectively, although both studies had low overall numbers of suicide.

One study identified that depression in people who exclusively used cannabis, resulted in a lower risk of dying by suicide in comparison to people with depression without any SUD [ 42 ].

Schizophrenia spectrum disorders (SSD) or a history of psychosis was reported in five publications [ 42 , 46 , 48 , 57 , 79 ]. For women with DUD, Zaheer et al. [ 46 ] reported that a subsequent diagnosis of any SSD was a risk factor for death by suicide in comparison to men with the same condition. Poor compliance with medications for SSD or psychosis was reported in two studies [ 48 , 57 ]. It is unknown whether the psychosis reported in several studies was drug-induced, or related to SSD, but Darke et al. [ 57 ] hypothesised that use of methamphetamines may induce psychosis or exacerbate a pre-existing condition.

Other types of mental health conditions, including attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), bulimia nervosa, personality disorder, adjustment disorder, and post-traumatic stress disorder (PTSD) were also linked to risk of death by suicide in PWUD [ 43 , 48 , 49 , 67 , 79 ]. Interestingly, one study found no increased risk of all-cause mortality in dual diagnosis patients who were PWUD, but specific data were not provided for suicide and dual diagnosis risk [ 62 ].

Periods of heightened vulnerability

For PWUD, there were periods where risk of suicide was heightened. Eight (15%) publications addressed various vulnerable periods related to OAT administration and timing [ 70 , 71 , 76 , 77 , 88 ], healthcare attendance patterns [ 61 , 89 ], or recent imprisonment [ 48 ].

Initiating and ceasing OAT was identified as a period where risk of death by suicide was increased [ 71 , 88 ]. Poor retention of individuals in OAT was a risk factor for death by suicide in women [ 76 ]. Repeated unsuccessful episodes of OAT were also linked to increased risk of suicide [ 70 , 77 ].

For PWUD who were attending mental health or addiction services, a loss of contact was observed in the period immediately before a person’s suicide [ 89 ], indicating that this was a candidate risk factor. In a record-linkage study of drug-related death and suicide after hospital discharge in PWUD in Scotland for the years 1996–2006, hospitalisation and discharge marked the start of a period of heightened vulnerability for PWUD with respect to non-poisoning suicide, with 51 of 269 non-poisoning suicides occurring while hospitalised or in the 28 day period after being discharged [ 61 ]. The authors suggest that in this cohort, hospital contact may represent a desperate call for help.

The initial months of being in prison were a vulnerable period for women who used drugs. In case studies of 13 women who died by suicide in prison in the UK between 1992 and 2001, ten (76.9%) of the 13 women died by suicide within two months of being imprisoned [ 48 ]. The women all had multiple problems or upheaval in the days and weeks prior to their deaths, including withdrawal from drugs, lack of contact with families, bereavement, and relationship problems outside and within prison. More than two thirds had also recently been relocated, often against their wishes and to other prison accommodation that they found less acceptable.

Age profile

Seven (11%) publications included an age profile as a candidate factor [ 20 , 62 , 63 , 65 , 68 , 70 , 87 ]. Death by suicide was linked to a younger age profile or higher number of PYLL in six publications [ 20 , 62 , 63 , 65 , 68 , 87 ], although the definition of ‘younger age’ varied by study, from teens to PWUD aged in their forties. A technical report by the EMCCDA on drug-related mortality in Europe identified that PWUD who were in their teens and early 20s, were at greatest risk of suicide among PWUD across 14 European countries [ 87 ]. Stenbacka et al. [ 62 ] reported that nearly 20% of PWUD aged 24 years or younger in their longitudinal cohort study died by suicide.

Five studies focused on PWUD seeking treatment for opioid use [ 20 , 63 , 65 , 68 , 70 ]. One study involving people who used heroin, aged between 15 and 59 and seeking OAT treatment in Slovenia, found that older age at treatment entry was an important risk factor for death by suicide. The hazard risk for death by suicide was significantly higher in patients entering the cohort when older (HR = 1.08, 95% CI: 1.02–1.13, p = 0.003) [ 70 ].

Stimulants, cannabis, and new psychoactive substance (NPS) use and method of death

Where publications provided data on whether a suicide was a poisoning or non-poisoning, an emergent theme was the association of stimulants, cannabis, and NPS with violent deaths. Six (11%) publications identified these substances as possible candidate risk factors for violent, non-poisoning suicide deaths [ 45 , 48 , 55 , 57 , 59 , 60 ].

The majority (85%) of suicide deaths in people who used methamphetamine in an Australian cohort study were violent suicide deaths. Zahra et al. [ 55 ] found that 92% of people who used cannabis and died by suicide in Australia, died by violent means. In a retrospective review of autopsy reports, Delaveris et al. [ 60 ] identified that the illicit drug toxicology profiles in non-poisoning suicides were more similar to homicide deaths than poisoning suicides. The toxicology profile of poisonings was more similar to accidental overdoses in PWUD. Cannabis was present in almost half of these suicides followed by amphetamines (35.3%), opioids (15.1%), and cocaine (8.4%). Mackenzie et al. [ 48 ] also identified a high prevalence of cocaine use in their case series of incarcerated women, all of whom died by violent method of suicide.

Elliott and Evans [ 59 ] identified that 17% of deaths where NPS were present were fatal hangings, with a further 5% other types of violent suicide. Cathinone drugs such as mephedrone, were more prevalent that other types of NPS in these suicides. However, it is important to note that this study did not compare NPS rates in non-poisoning suicides.

One study found a significant link between opioid use and suicide by firearms, but this was a study that solely focused on violent methods of suicide, and similarly to the study above, no comparative toxicology data for poisoning suicides were available [ 45 ].

Medical conditions

Blood borne viruses (BBV) were the most prevalent medical condition identified in the review. Four (8%) studies identified BBV status as a factor associated with suicide deaths in PWUD [ 25 , 44 , 77 , 85 ]. Intravenous drug use increases the incidence of HIV and other BBV such as Hepatitis B and C, through high-risk practices such as sharing or reusing needles and syringes. BBV are known to precipitate chronic diseases and increase risk of premature mortality [ 77 ]. HIV infection in particular was linked to suicide and overdose among people who use heroin or other opioids [ 25 , 77 ]. Vajdic et al. [ 77 ], in their study of 29,571 opioid-dependent people in Australia, found that risk of death by suicide increased with notification of HIV infection in bivariable analyses, but not multivariable analyses.

Two (4%) studies identified other medical conditions as candidate factors for death by suicide [ 21 , 79 ]. Madadi et al. [ 79 ] found that a history of cancer and chronic pain were risk factors for death by suicide in a cohort of people who used opioids. The Charlson Comorbidity Index (CCI) was used by Lynch et al. [ 21 ] to measure non-psychiatric medical comorbidities, such as cancer and cardiovascular disease, in a case-control study of substance use disorders and suicide risk in the US general population. PWUD who died by suicide were more likely than controls to have a higher CCI score, indicating more severe medical illness at the time of death.

Mackenzie et al. [ 48 ] found that 38.5% of the women who died by suicide while incarcerated had a physical illness, such as epilepsy or asthma.

Dual diagnosis service provision

Issues in relation to dual diagnosis service provision and wider policies, were identified as contributory towards risk of death by suicide in four (8%) publications. The combined presence of a mental health problem and a substance use problem has previously been identified as a barrier to accessing treatment, where individuals are unable to access mental health services because of addiction, and vice versa [ 90 ].

Appleby [ 89 ] identified a high risk of suicide in PWUD who were dual diagnosis patients, and highlighted the fact that separation of services led to disrupted patterns of care and loss of contact with individuals prior to their suicide. Zahra et al. [ 55 ] identified the need for integration of mental health and addiction services in Australia, suggesting that it would be beneficial for professionals treating people with cannabis dependence to also screen individuals for suicide ideation, given their increased risk of suicide.

Untreated or inappropriately managed comorbid mental health issues in PWUD were suggestive of a lack of dual diagnosis service provision in two further cohort studies. In Denmark, men who were prescribed drugs used to treat addictive disorders (e.g. buprenorphine), who were previously diagnosed with reaction to severe stress and with adjustment disorder but who were not prescribed antidepressants, antipsychotics, or anxiolytics, had an 84% suicide risk using a machine learning model relative to the comparison group, consisting of a 5% random sample of individuals living in Denmark who had a diagnosis of SUD during the study period [ 49 ]. In a cohort of opioid users, use of hypnotics and sedatives were associated with increased risk of death by suicide in comparison to accidental overdose. Prescribed antidepressants were also more common in this group. This could suggest poorly medicated withdrawal symptoms in dual diagnosis patients [ 66 ], and highlights the complex medical and psychological needs of this group of people.

Homelessness

PWUD are overrepresented in homeless populations [ 91 , 92 , 93 ]. Homelessness was identified as a risk factor in three (6%) studies in the review, two of which were longitudinal cohort studies. Arnautovska et al. [ 53 ] compared all suicide deaths in homeless and non-homeless people over a 20-year period, and found that homelessness significantly increased the risk of death by suicide in PWUD, in comparison to PWUD in the non-homeless population (42.4% vs. 20.4%). There was a high degree of social isolation in this population. Feodor Nilsson et al. [ 51 ] found that drug use resulted in an elevated hazard ratio (HR) for suicide in both men and women who were homeless at any point during a period of ten years, with a higher risk estimate for women (HR = 3.1, 95% CI = 1.8–5.4) than men (HR = 2.2, 95% CI = 1.8–2.8).

In an editorial piece by Appleby [ 89 ], discussing suicide data collected by the UK Confidential Inquiry between 1996 and 1998, PWUD accounted for 49% of suicide deaths among homeless people, a higher proportion than reported in the two previous cohort studies.

Incarceration

Incarceration was identified as a candidate factor in three (6%) publications [ 48 , 73 , 85 ]. There was a clear link between the absence of OAT in prison, and increased risk of death by suicide [ 48 , 85 ], with the provision of OAT strongly protective [ 73 ]. Modelling carried out by Degenhardt et al. [ 85 ] suggested that scaling the provision of OAT up to the levels advised by the WHO in prisons could potentially avert between 13.7% and 51.1% of suicide deaths in Kentucky, Kyiv, and Tehran (the three international locations used for analysis in their study).

Intravenous (IV) drug use

Three (6%) studies suggested that IV drug use, particularly poly IV drug use, was a candidate factor for death by suicide [ 23 , 57 , 64 ]. Heroin was the primary IV drug of use identified [ 23 , 64 ], with methamphetamine [ 23 , 57 ], cocaine [ 23 , 64 ], and other opioids [ 23 ] also identified.

Darke et al. [ 57 ], found that 25% of people who used methamphetamine and died by suicide in an Australian cohort study, had a history of IV drug use, or were currently injecting drugs. Hayashi et al. [ 64 ] identified poly IV drug use in a cohort of people who were injecting drugs in Canada, with the age-adjusted rate ratio for suicide risk significantly increased in men, in comparison to women. Wilcox et al. [ 23 ], in their review of cohort studies, identified an SMR of 1373 (95% CI 1029–1796) for poly IV drug use, indicating that individuals with opioid use disorder and poly IV drug use bore an elevated risk for death by suicide. The authors noted that this risk was also higher than the risk of suicide associated with individuals suffering from alcoholism in their review.

Race/ethnicity

Race and ethnicity as a potential factor was not a common theme, but was identified in two cohort studies [ 52 , 82 ]. In a study of people who used heroin and were accessing substance use treatment in Italy, those born outside of Italy (non-natives) were distinguished for their higher percentage of suicide deaths. The standardised mortality ratio (SMR) for suicide among people who used heroin and were non-natives was 13.25 (6.63–26.50) versus 4.88 (95% CI 3.82–6.24) for those born in Italy.

Willis et al. [ 52 ] found that cocaine use was four times more likely among African Americans than White Americans in their study of a nationally representative sample of death certificates. Cocaine use was associated with increased risk of death by suicide among African Americans, in comparison to White Americans who also used cocaine (OR 4.59, 95% CI 1.97–10.72).

Both of these studies used relatively dated data; data from Willis et al. [ 52 ] were drawn from a 1993 sample, while Pavarin et al. [ 82 ] used data from between 1975 and 2016.

Protective factors against death by suicide in PWUD

Current attendance in OAT or other medication-assisted drug treatment was identified as a protective factor against death by suicide in eight (15%) publications [ 67 , 68 , 70 , 73 , 76 , 77 , 85 , 88 ]. Methadone was the most common type of OAT identified, but buprenorphine-naloxone, and naltrexone were also identified as protective. However, as discussed above, the period immediately after initiating or ceasing OAT, was identified as a period of increased risk of suicide in PWUD [ 71 , 88 ].

Exclusive cannabis use was also identified as a protective factor against suicide in people with comorbid depression [ 42 ].

The objectives of this scoping review were to explore the evidence on factors associated with death by suicide among PWUD, to identify gaps in knowledge for future research, and to inform suicide prevention policy and best practice guidelines for working with PWUD, where appropriate. The majority of the evidence reviewed on suicide among PWUD was primary research, originating in Europe, and were based on surveillance systems that captured epidemiological data and trends. Publications generally lacked in-depth analysis of explicit risk factors for death by suicide in PWUD. The most prevalent candidate factor explored was sex, with approximately half of the included publications presenting sex-segregated data for overall numbers of suicide in PWUD. Specific associated factors were commonly not segregated by sex although five studies provided information on the different types of drugs used by men and women who died by suicide [ 24 , 47 , 50 , 51 , 63 ].

Men account for the majority of completed suicides worldwide [ 3 , 94 ]. This is thought to be related to male tendency for higher lethality methods of suicide, and the reluctance of men to seek help for depression or suicidal ideation [ 1 , 94 ]. Freeman et al. [ 10 ] argue that suicide attempts in females may represent less of an intention to die, and more a desire to communicate distress or change their social environment. In this review, absolute numbers of death by suicide were higher for men with DUD than for women with DUD, where sex-segregated data were available. However, there was a higher proportion of suicide in women with DUD than men with DUD in several studies [ 21 , 24 , 46 , 47 , 51 , 75 , 78 , 84 ].

The fact that only five studies reported sex-segregated data highlights a deficit in how studies describing suicide in PWUD report on sex and gender. Where this factor was reported, it was mainly related to biological sex rather than gender identity, resulting in a knowledge gap. A key element to improving the lives of women and girls worldwide is to address sex and gender inequalities, as highlighted in the United Nation’s Global Agenda for Sustainable Development [ 95 ]. It is essential to include sex and gender in public health research to bridge the gap in public health knowledge and to advance gender and sex equality.

Increased rates of death by suicide in female PWUD were linked to high rates of mental health problems, high prevalence of opioid and other central nervous depressant drug use, and poor retention in DUD treatment. Lynn et al. [ 96 ] identified opioids and antidepressants as the main drugs implicated in suicide drug poisonings among women, a similar finding to the drug profile in females identified in this review. This suggests that female PWUD with depressive disorders are a more vulnerable population than women with depression without a DUD. Although OAT was identified as a protective factor against death by suicide among people who use opioids, poor retention in OAT was associated with increased risk of death by suicide in women. Women with DUD may encounter barriers in accessing OAT in comparison to men, such as stigma, lack of social supports including childcare, and lack of knowledge of services [ 96 , 97 , 98 ]. Migrant women may be particularly isolated and unable to access treatment [ 97 ], with ethnicity also a candidate factor for suicide in this review.

Mental health conditions increased risk of death by suicide for both men and women who were PWUD, both through the conditions themselves, and through issues concerning dual diagnosis service provision. Previous research has suggested that drug use may exacerbate underlying risk of suicide, or interact with mental illness to increase risk of engaging in suicidal behaviours [ 8 ]. Darke and Ross [ 25 ] suggest that between a quarter and a third of people who use heroin meet the criteria for a life-time diagnosis of major depression, a figure much higher than levels seen in the general population. Depressive disorders were the most common type of mental health condition reported in publications in the review.

Historically, some mental health services did not accept PWUD for treatment, and some services dedicated to treating SUD may not be equipped to deal with dual diagnosis [ 90 ], compounding the mental health difficulties experienced by PWUD with dual diagnosis. Fragmented healthcare services may also make it difficult to recognise when PWUD decrease or change their service use pattern, a risk factor for death by suicide identified by some publications in the review. As PWUD also frequently experience social exclusion [ 87 ], also known to be a risk factor for suicide [ 99 ], healthcare services may represent an important point of contact. There is therefore a need for integrated addiction and mental health treatment to decrease the risk of suicide in this population [ 89 , 90 ]. Integrated care models which were shown to improve health outcomes among people with dual diagnosis in clinical trials are complex and challenging to scale-up in real world settings [ 100 ]. However, integrated care pathways for people with a dual diagnosis is an important step to ensure provision of services for people with dual diagnosis involves a single care pathway. In Ireland, a new model of care for dual diagnosis, which was developed in partnership with key stakeholders, has recently been launched, which is welcoming [ 101 ].

Suicide by hanging has previously been reported as the most common method of suicide in 16 European countries [ 102 ]. Darke and Ross [ 25 ] identified that people who use heroin were unlikely to use poisoning by heroin as a method of suicide. Violent methods of suicide were more frequent than suicides by poisoning in this review, in publications that reported method of death.

Impulsivity and substance use has previously been associated with suicidal ideation and suicidal behaviour [ 103 ]. Stimulant drugs and cannabis were most frequently identified in non-poisoning suicides in the review. Delaveris et al. [ 60 ] reported that the non-poisoning suicide illicit drug toxicology profile among PWUD appeared similar to the homicide toxicology profile, whereas the toxicology profile of poisonings was more similar to accidental overdoses. Amphetamines, cannabis, and cocaine were more prevalent in non-poisoning suicide deaths and homicides, while opioids were the most prevalent drug in poisoning suicide deaths and accidental overdoses [ 60 ]. Aggression and psychosis prior to suicide was also seen in both men and women who used methamphetamine [ 57 ]. This suggests that risk-taking and violent behaviour, including violent methods of suicide, may be increased with the ingestion of stimulant drugs. This differs to the presentation for people who use opioids, with high rates of depression, and therefore may require a different approach to reduce risk of suicide in this population.

Two studies identified race as a risk factor for suicide among PWUD. In people of colour who use drugs, the roles of systemic racism and racial violence may contribute to disproportionate harm, including risk of suicide.

The factors associated with suicide in PWUD identified in this review are those that primarily occur at the level of the individual, although they may point to broader community or societal issues [ 104 ]. This was necessary, in order to address the aims of the review, however, we acknowledge that there is a large body of literature exploring the structural conditions in which suicide in PWUD may occur.

Peer-led user movements and advocacy work in the areas of decriminalisation of drugs and expansion of access to harm reduction and social care for PWUD relevant to the local context and needs [ 105 ], as well as transformative justice approaches which seek to address the impact of drug-related stigma and harm [ 106 ], may also be considered important approaches to suicide prevention [ 107 ].

Considerations for policy and practice

PWUD are at increased risk of death by suicide in comparison to the general population. While this review has used a scoping review design to identify factors associated with death by suicide in this population, there is a need for more high-quality, prospective primary research studies on suicide that include explicit risk factors.

A large proportion of the existing evidence on suicide in PWUD is related to opioid use. People who use opioids are a group that are relatively easier to capture and study in comparison to people who use non-opioid drugs, due to OAT registers or other drug treatment databases. While opioids are still responsible for the majority of drug-related deaths, cannabis is the most used substance worldwide, cocaine production is at a record high, and seizures of amphetamine and methamphetamine have increased [ 101 ]. It is therefore important to consider non-opioid drugs and their impact on suicide risk, in light of changing drug production and consumption patterns globally. Further studies in this area are needed.

Strengths and limitations

To the best of our knowledge, this is the first scoping review undertaken on factors associated with death by suicide in PWUD. A strength of this review was the inclusion of all publications, including peer-reviewed articles and grey literature, as well as consultation with experts in the area. However, a limitation to scoping reviews is the lack of in-depth quality appraisal of the evidence. The search was limited to publications in between 2000 and 2021; our results are up to date as of November 2021 only; therefore, it is possible that potentially relevant publications before 2000 or after November 2021 could have been missed. However, we included secondary research that cited older seminal literature, and so captured additional relevant publications in this manner.

We included only English language publications, which may not be representative of all the evidence. This was necessary in order to avoid introducing erroneous conclusions by including papers that were not thoroughly understood, particularly when the context of suicide was so important to the objectives of the review.

Much US literature, which overlapped with veteran research, was excluded due to the absence of explicit candidate factors for death by suicide in PWUD within the study samples. This resulted in an over-representation of publications from Europe and Australia in this review, and so findings may not be reflective of the sociocultural context of drug use in the US.

Similarly, people with HIV were over-represented in studies that explored IV drug use or BBV in the review. HIV infection may be a potential confounder for risk of death by suicide in PWUD, as this illness confers additional medical complications.

The majority of data available on death by suicide among PWUD were extracted from epidemiological research, with limited in-depth analysis of explicit risk factors for suicide in this cohort. Opioids were the most prevalent drugs of use in PWUD who died by suicide, followed by cannabis and stimulant drugs. Violent methods of suicide were more prevalent in cannabis and stimulant users. Sex, age profile, comorbid medical conditions, mental health conditions, and inadequate dual diagnosis service provision, were factors associated with death by suicide in PWUD. To prevent suicide in PWUD, it is important to consider risk factors and type of drug use, and to tailor policies and practices accordingly.

Data Availability

All data generated or analysed during this study are included in this published article [and its supplementary information files].

Abbreviations

Attention deficit hyperactivity disorder

Acquired Immune Deficiency Syndrome

Blood Borne Viruses

Charlson Comorbidity Index

Confidence Interval

Cumulative Index to Nursing and Allied Health Literature

Crude Mortality Rate

Drug Use Disorder

European Monitoring Centre for Drugs and Drug Addiction

Human Immunodeficiency Virus

Hazard Ratio

International Classification of Diseases

Intravenous

National Drug-Related Deaths Index

New Psychoactive Substances

Opioid Agonist Treatment

Obsessive-compulsive disorder

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

PRISMA Extension for Scoping Reviews

Post-traumatic stress disorder

People Who Use Drugs

Potential Years of Life Lost

Standardised Mortality Rate

Schizophrenia Spectrum Disorder

Substance Use Disorder

United Kingdom

World Health Organization. Preventing suicide: a global imperative. Geneva: WHO. ; 2014. Available from: https://www.who.int/publications/i/item/9789241564779 (Accessed 15 Mar. 23).

Naghavi M. Global, regional, and national burden of suicide mortality 1990 to 2016: systematic analysis for the global burden of Disease Study 2016. BMJ. 2019;364:l94.

PubMed   PubMed Central   Google Scholar  

World Health Organization. Suicide worldwide in 2019: Global Health Estimates. Geneva: WHO. ; 2021 Jun. Available from: https://www.who.int/publications/i/item/9789240026643 (Accessed 15 Mar. 23).

Crosby A, Ortega L, Melanson C, Division of Violence Prevention. Self-directed violence surveillance; uniform definitions and recommended data elements. Centers for Disease Control and Prevention, National Center for Injury Prevention and Control, ; 2011. Available from: https://stacks.cdc.gov/view/cdc/11997 (Accessed 15 Mar. 23).

Esang M, Ahmed S. A closer look at substance use and suicide. Am J Psychiatry Res J. 2018;13(6).

Favril L, Yu R, Uyar A, Sharpe M, Fazel S. Risk factors for suicide in adults: systematic review and meta-analysis of psychological autopsy studies. Evid Based Ment Health. 2022;25(4):148.

Stone DM, Crosby AE. Suicide Prevention: state of the Art Review. Am J Lifestyle Med. 2014;8(6):404–20.

PubMed   Google Scholar  

Turecki G, Brent DA. Suicide and suicidal behaviour. Lancet. 2016;387(10024):1227–39.

Diekstra R, Gulbinat W. The epidemiology of suicidal behaviour: a review of three continents. World Health Stat Q. 1993;46(1):52–68.

CAS   PubMed   Google Scholar  

Freeman A, Mergl R, Kohls E, Székely A, Gusmao R, Arensman E, et al. A cross-national study on gender differences in suicide intent. BMC Psychiatry. 2017;17(1):234.

Spillane A, Matvienko-Sikar K, Larkin C, Corcoran P, Arensman E. What are the physical and psychological health effects of suicide bereavement on family members? An observational and interview mixed-methods study in Ireland. BMJ Open. 2018;8(1):e019472.

Cerel J, Maple M, van de Venne J, Moore M, Flaherty C, Brown M. Exposure to suicide in the community: prevalence and correlates in one U.S. state. Public Health Rep. 2016;131(1):100–7.

McDaid C, Trowman R, Golder S, Hawton K, Sowden A. Interventions for people bereaved through suicide: systematic review. Br J Psychiatry. 2008;193(6):438–43.

Kennelly B. The economic cost of suicide in Ireland. Crisis. 2007;28(2):89–94.

Yang B, Lester D. Recalculating the economic cost of suicide. Death Stud. 2007;31(4):351–61.

World Health Organization. Comprehensive Mental Health Action Plan 2013–2030. Geneva: WHO. ; 2021. Available from: https://www.who.int/publications/i/item/9789240031029 (Accessed 15 Mar. 23).

Cantor CH, Baume PJ. Suicide prevention: a public health approach. Aust N Z J Ment Health Nurs. 1999;8(2):45–50.

Cavanagh JTO, Carson AJ, Sharpe M, Lawrie SM. Psychological autopsy studies of suicide: a systematic review. Psychol Med. 2003;33(3):395–405.

Yuodelis-Flores C, Ries RK. Addiction and suicide: a review. Am J Addict. 2015;24(2):98–104.

Hesse M, Thylstrup B, Seid AK, Skogen JC. Suicide among people treated for drug use disorders: a danish national record-linkage study. BMC Public Health. 2020;20(1):146.

Lynch FL, Peterson EL, Lu CY, Hu Y, Rossom RC, Waitzfelder BE, et al. Substance use disorders and risk of suicide in a general US population: a case control study. Addict Sci Clin Pract. 2020;15(1):14.

Harris EC, Barraclough B. Suicide as an outcome for mental disorders. A meta-analysis. Br J Psychiatry. 1997;170:205–28.

Wilcox HC, Conner KR, Caine ED. Association of alcohol and drug use disorders and completed suicide: an empirical review of cohort studies. Drug Alcohol Depend. 2004;76 Suppl:S11-19.

Bohnert KM, Ilgen MA, Louzon S, McCarthy JF, Katz IR. Substance use disorders and the risk of suicide mortality among men and women in the US Veterans Health Administration. Addiction. 2017;112(7):1193–201.

Darke S, Ross J. Suicide among heroin users: rates, risk factors and methods. Addiction. 2002;97(11):1383–94.

Schneider B. Substance use disorders and risk for completed suicide. Arch Suicide Res. 2009;13(4):303–16.

Degenhardt L, Singleton J, Calabria B, McLaren J, Kerr T, Mehta S, et al. Mortality among cocaine users: a systematic review of cohort studies. Drug Alcohol Depend. 2011;113(2–3):88–95.

Vijayakumar L, Kumar MS, Vijayakumar V. Substance use and suicide. Curr Opin Psychiatry. 2011;24(3):197–202.

Bohnert ASB, Roeder K, Ilgen MA. Unintentional overdose and suicide among substance users: a review of overlap and risk factors. Drug Alcohol Depend. 2010;110(3):183–92.

Degenhardt L, Bucello C, Mathers B, Briegleb C, Ali H, Hickman M, et al. Mortality among regular or dependent users of heroin and other opioids: a systematic review and meta-analysis of cohort studies. Addiction. 2011;106(1):32–51.

Poorolajal J, Haghtalab T, Farhadi M, Darvishi N. Substance use disorder and risk of suicidal ideation, suicide attempt and suicide death: a meta-analysis. J Public Health (Oxf). 2016;38(3):e282–91.

Mann JJ, Apter A, Bertolote J, Beautrais A, Currier D, Haas A, et al. Suicide Prevention Strategies: a systematic review. JAMA. 2005;294(16):2064–74.

Colquhoun HL, Levac D, O’Brien KK, Straus S, Tricco AC, Perrier L, et al. Scoping reviews: time for clarity in definition, methods, and reporting. J Clin Epidemiol. 2014;67(12):1291–4.

Peters MDJ. In no uncertain terms: the importance of a defined objective in scoping reviews. JBI Database System Rev Implement Rep. 2016;14(2):1–4.

Peters MDJ, Marnie C, Tricco AC, Pollock D, Munn Z, Alexander L, McInerney P, Godfrey CM, Khalil H. Updated methodological guidance for the conduct of scoping reviews. JBI Evid Synth. 2020;18(10):2119–26.

Arksey H, O’Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. 2005;8(1):19–32.

Google Scholar  

Tricco AC, Lillie E, Zarin W, O’Brien KK, Colquhoun H, Levac D, et al. PRISMA Extension for scoping reviews (PRISMA-ScR): Checklist and Explanation. Ann Intern Med. 2018;169(7):467–73.

Murphy L, Lyons S, O’Sullivan M, Lynn E. Risk factors for completed suicide among people who use drugs: a scoping review protocol [version 3; peer review: 2 approved, 1 approved with reservations]. HRB Open Res. 2021;3(45).

Peters MDJ, Godfrey CM, McInerney P, Munn Z, Tricco AC, Khalil H. Chapter 11: Scoping Reviews (2020 version). In: Aromataris E, Munn Z, editors. JBI Manual for Evidence Synthesis. JBI; 2020. Available from: https://synthesismanual.jbi.global (Accessed 15 Mar. 23).

Thomas J, Brunton J, Graziosi S. EPPI-Reviewer 4.0: software for research synthesis. London: Social Science Research Unit, Institute of Education, University of London; 2010.

Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71.

Hjorthoj C, Ostergaard MLD, Benros ME, Toftdahl NG, Erlangsen A, Andersen JT, et al. Association between alcohol and substance use disorders and all-cause and cause-specific mortality in schizophrenia, bipolar disorder, and unipolar depression: a nationwide, prospective, register-based study. Lancet Psychiatry. 2015;2(9):801–8.

Flynn S, Graney J, Nyathi T, Raphael J, Abraham S, Singh-Dernevik S, et al. Clinical characteristics and care pathways of patients with personality disorder who died by suicide. BJPsych Open. 2020;6(2):e29.

PubMed Central   Google Scholar  

Hentzien M, Cabie A, Pugliese P, Billaud E, Poizot-Martin I, Duvivier C, et al. Factors associated with deaths from suicide in a french nationwide HIV-infected cohort. HIV Med. 2018;19:551–8.

Sheehan CM, Rogers RG, Boardman JD. Postmortem Presence of drugs and method of violent suicide. J Drug Issues. 2015;45(3):249–62.

Zaheer J, Olfson M, Mallia E, Lam JSH, de Oliveira C, Rudoler D, et al. Predictors of suicide at time of diagnosis in schizophrenia spectrum disorder: a 20-year total population study in Ontario, Canada. Schizophr Res. 2020;222:382–8.

Kung HC, Pearson JL, Liu X. Risk factors for male and female suicide decedents ages 15–64 in the United States. Results from the 1993 National Mortality Followback Survey. Soc Psychiatry Psychiatr Epidemiol. 2003;38(8):419–26.

Mackenzie N, Oram C, Borrill J. Self-inflicted deaths of women in custody. Br J Forensic Pract. 2003;5:27–35.

Adams RS, Jiang T, Rosellini AJ, Horvath-Puho E, Street AE, Keyes KM, et al. Sex-specific risk profiles for suicide among persons with Substance Use Disorders in Denmark. Addiction. 2021;116(10):2882–92.

Myhre MO, Kildahl AT, Walby FA. Suicide after contact with substance misuse services: a national registry study. BJPsych Open. 2020;6(3):e45.

Feodor Nilsson S, Hjorthoj CR, Erlangsen A, Nordentoft M. Suicide and unintentional injury mortality among homeless people: a danish nationwide register-based cohort study. Eur J Public Health. 2014;24(1):50–6.

Willis LA, Coombs DW, Drentea P, Cockerham WC. Uncovering the mystery: factors of african american suicide. Suicide Life Threat Behav. 2003;33(4):412–29.

Arnautovska U, Sveticic J, De Leo D. What differentiates homeless persons who died by suicide from other suicides in Australia? A comparative analysis using a unique mortality register. Soc Psychiatry Psychiatr Epidemiol. 2014;49(4):583–9.

Darke S, Marel C, Mills KL, Ross J, Slade T, Tessson M. Years of potential life lost amongst heroin users in the australian treatment outcome study cohort, 2001–2015. Drug Alcohol Depend. 2016;162:206–10.

Zahra E, Darke S, Degenhardt L, Campbell G. Rates, characteristics and manner of cannabis-related deaths in Australia 2000–2018. Drug Alcohol Depend. 2020;212:108028.

Colell E, Domingo-Salvany A, Espelt A, Parés-Badell O, Brugal MT. Differences in mortality in a cohort of cocaine use disorder patients with concurrent alcohol or opiates disorder. Addiction. 2018;113(6):1045–55.

Darke S, Kaye S, Duflou J, Lappin J. Completed suicide among methamphetamine users: a National Study. Suicide Life Threat Behav. 2019;49(1):328–37.

Bartu A, Freeman NC, Gawthorne GS, Codde JP, Holman CDJ. Mortality in a cohort of opiate and amphetamine users in Perth, Western Australia. Addiction. 2004;99(1):53–60.

Elliott S, Evans J. A 3-year review of new psychoactive substances in casework. Forensic Sci Int. 2014;243:55–60.

Delaveris GJM, Teige B, Rogde S. Non-natural manners of death among users of illicit drugs: substance findings. Forensic Sci Int. 2014;238:16–21.

Merrall ELC, Bird SM, Hutchinson SJ. A record-linkage study of drug-related death and suicide after hospital discharge among drug-treatment clients in Scotland, 1996–2006. Addiction. 2013;108(2):377–84.

Stenbacka M, Leifman A, Romelsjo A. Mortality and cause of death among 1705 illicit drug users: a 37 year follow up. Drug Alcohol Rev. 2010;29(1):21–7.

Onyeka IN, Beynon CM, Vohlonen I, Tiihonen J, Fohr J, Ronkainen K, et al. Potential years of Life Lost due to premature mortality among treatment- seeking Illicit Drug users in Finland. J Community Health. 2015;40(6):1099–106.

Hayashi K, Dong H, Marshall BDL, Milloy MJ, Montaner JSG, Wood E, et al. Sex-based differences in Rates, causes, and predictors of death among injection drug users in Vancouver, Canada. Am J Epidemiol. 2016;183(6):544–52.

Pfeifer P, Nigg-Trawally N, Bartsch C, Reisch T. Characteristics of Suicides and Toxicology in a cohort of individuals with opioid Use Disorder. Arch Suicide Res. 2021;25(2):287–96.

Zamparutti G, Schifano F, Corkery JM, Oyefeso A, Ghodse AH. Deaths of opiate/opioid misusers involving dihydrocodeine, UK, 1997–2007. Br J Clin Pharmacol. 2011;72(2):330–7.

Riblet NB, Gottlieb DJ, Shiner B, Cornelius SL, Watts BV. Associations between Medication assisted Therapy Services Delivery and Mortality in a National Cohort of Veterans with posttraumatic stress disorder and opioid use disorder. J Dual Diagn. 2020;16(2):228–38.

Maxwell JC, Pullum TW, Tannert K. Deaths of clients in methadone treatment in Texas: 1994–2002. Drug Alcohol Depend. 2005;78(1):73–81.

Chang KC, Lu TH, Lee KY, Hwang JS, Cheng CM, Wang JD. Estimation of life expectancy and the expected years of life lost among heroin users in the era of opioid substitution treatment (OST) in Taiwan. Drug Alcohol Depend. 2015;153:152–8.

Mercedes L, Lovrecic B, Maremmani I, Maremmani AG. Excess suicide mortality in Heroin Use Disorder patients seeking opioid agonist treatment in Slovenia and risk factors for suicide. Heroin Addict Relat Clin Probl. 2018;20(2):35–40.

Degenhardt L, Randall D, Hall W, Law M, Butler T, Burns L. Mortality among clients of a state-wide opioid pharmacotherapy program over 20 years: risk factors and lives saved. Drug Alcohol Depend. 2009;105(1–2):9–15.

Cao X, Wu Z, Li L, Pang L, Rou K, Wang C, et al. Mortality among methadone maintenance clients in China: a six-year cohort study. PLoS ONE. 2013;8(12):e82476.

Larney S, Gisev N, Farrell M, Dobbins T, Burns L, Gibson A, et al. Opioid substitution therapy as a strategy to reduce deaths in prison: retrospective cohort study. BMJ Open. 2014;4(4):e004666.

Kelty E, Hulse G. Self-Injuring Behavior and Mental illness in opioid-dependent patients treated with Implant Naltrexone, Methadone, and Buprenorphine in Western Australia. Int J Ment Health Addict. 2018;16(1):187–98.

Lee CTC, Chen VCH, Tan HKL, Chou SY, Wu KH, Chan CH, et al. Suicide and other-cause mortality among heroin users in Taiwan: a prospective study. Addict Behav. 2013;38(10):2619–23.

Chen WT, Wang SC, Wang IA, Tsay JH, Chen CY. Suicide attempts and death among heroin-involved women seeking methadone treatment in Taiwan. Drug Alcohol Depend. 2020;217:108277.

Vajdic CM, Marashi Pour S, Olivier J, Swart A, O’Connell DL, Falster MO, et al. The impact of blood-borne viruses on cause-specific mortality among opioid dependent people: an australian population-based cohort study. Drug Alcohol Depend. 2015;152:264–71.

Gibson A, Randall D, Degenhardt L. The increasing mortality burden of liver disease among opioid-dependent people: cohort study. Addiction. 2011;106(12):2186–92.

Madadi P, Hildebrandt D, Lauwers AE, Koren G. Characteristics of opioid-users whose death was related to opioid- toxicity: a population-based study in Ontario, Canada. PLoS ONE. 2013;8(4):e60600.

CAS   PubMed   PubMed Central   Google Scholar  

Pan CH, Jhong JR, Tsai SY, Lin SK, Chen CC, Kuo CJ. Excessive suicide mortality and risk factors for suicide among patients with heroin dependence. Drug Alcohol Depend. 2014;145:224–30.

Degenhardt L, Larney S, Randall D, Burns L, Hall W. Causes of death in a cohort treated for opioid dependence between 1985 and 2005. Addiction. 2014;109(1):90–9.

Pavarin RM, Sanchini S, Marani S, Turino E, Tadonio L, Cantarelli B. Mortality risk among heroin users accessing treatment: natives and non- natives patients results of a longitudinal study. J Psychoact Drugs. 2020;52(2):176–85.

Pavarin RM, Fioritti A. Mortality Trends among Cocaine users treated between 1989 and 2013 in Northern Italy: results of a longitudinal study. J Psychoact Drugs. 2018;50(1):72–80.

Pavarin RM, Fioritti A, Sanchini S. Mortality trends among heroin users treated between 1975 and 2013 in Northern Italy: results of a longitudinal study. J Subst Abuse Treat. 2017;77:166–73.

Degenhardt L, Grebely J, Stone J, Hickman M, Vickerman P, Marshall BDL, et al. Global patterns of opioid use and dependence: harms to populations, interventions, and future action. Lancet. 2019;394(10208):1560–79.

Borges G, Bagge CL, Orozco R. A literature review and meta-analyses of cannabis use and suicidality. J Affect Disord. 2016;195:63–74.

European Monitoring Centre for Drugs and Drug Addiction. Mortality related to drug use in Europe: public health implications: EMCDDA Selected issues. Publications Office. ; 2011. Available from: https://data.europa.eu/doi/10.2810/49713 (Accessed 15 Mar. 23).

Bohnert ASB, Ilgen MA. Understanding links among opioid use, overdose, and suicide. N Engl J Med. 2019;380(1):71–9.

Appleby L. Drug misuse and suicide: a tale of two services. Addiction. 2000;95(2):175–7.

Kelly K, Holahan R, Dual Recovery. A qualitative exploration of the views of stakeholders working in mental health, substance use, and homelessness in Ireland on the barriers to recovery for individuals with a Dual Diagnosis. Dublin: Mental Health Reform; 2022. Available from: https://www.mentalhealthreform.ie/wp-content/uploads/2022/05/Dual-Recovery-Full-Report.pdf (Accessed 15 Mar. 23).

Ivers JH, Zgaga L, O’Donoghue-Hynes B, Heary A, Gallwey B, Barry J. Five-year standardised mortality ratios in a cohort of homeless people in Dublin. BMJ Open. 2019;9(1):e023010.

Baggett TP, Hwang SW, O’Connell JJ, Porneala BC, Stringfellow EJ, Orav EJ, et al. Mortality among homeless adults in Boston: shifts in causes of death over a 15-year period. JAMA Intern Med. 2013;173(3):189–95.

O’Connell JJ. Premature mortality in homeless populations: a review of the literature. Nashville: National Health Care for the Homeless Council, Inc.; 2005. Available from: http://sbdww.org/wp-content/uploads/2011/04/PrematureMortalityFinal.pdf (Accessed 15 Mar. 23).

Turecki G, Brent DA, Gunnell D, O’Connor RC, Oquendo MA, Pirkis J, et al. Suicide and suicide risk. Nat Rev Dis Primers. 2019;5(1):74.

United Nations. Department of Economic and Social Affairs: Sustainable Development Goal 5. Achieve gender equality and empower all women and girls. 2021. Avaiable from: https://sustainabledevelopment.un.org/sdg5 (Accessed 01 Jun. 2023).

Lynn E, Doyle A, Keane M, Bennett K, Cousins G. Drug poisoning deaths among women: a scoping review. J Stud Alcohol Drugs. 2020;81(5):543–55.

Morton S, Macdonald S, Christophers L. Responding to women with complex needs who use substances. Dublin: University College Dublin; 2020. Available from: https://researchrepository.ucd.ie/bitstream/10197/11712/2/Responding%20to%20women%20with%20complex%20needs%20who%20use%20substances.pdf (Accessed 15 Mar. 23).

United Nations Office on Drugs and Crime. World Drug Report 2018: Women and Drugs: Drug use, drug supply and their consequences. Vienna: UNODC. ; 2018. Available from: https://unodc.org/wdr2018/prelaunch/WDR18_Booklet_5_WOMEN.pdf (Accessed 15 Mar. 23).

Yur’yev A, Värnik P, Sisask M, Leppik L, Lumiste K, Värnik A. Some aspects of social exclusion: do they influence suicide mortality? Int J Soc Psychiatry. 2013;59(3):232–8.

McGinty EE, Daumit GL. Integrating Mental Health and Addiction Treatment Into General Medical Care: the role of policy. Psychiatr Serv. 2020;71(11):1163–9.

National Working Group for Dual Diagnosis. Model of Care for People with Mental Disorder and Co-existing Substance Use Disorder (Dual Diagnosis). Health Service Executive; 2023 May. Report No.: CDI006/2022. Available from: https://www.hse.ie/eng/about/who/cspd/ncps/mental-health/dual-diagnosis-ncp/dual-diagnosis-model-of-care.pdf .

Varnik A, Sisask M, Varnik P, Wu J, Kolves K, Arensman E, et al. Drug suicide: a sex-equal cause of death in 16 european countries. BMC Public Health. 2011;11(1):61.

Dumais A, Lesage AD, Alda M, Rouleau G, Dumont M, Chawky N, et al. Risk factors for suicide completion in Major Depression: a case-control study of impulsive and aggressive behaviors in men. Am J Psychiatry. 2005;162(11):2116–24.

Sallis JF, Owen N, Fisher EB. Ecological models of health behavior. In: Glanz K, Rimer BK, Viswanath K, editors. Health behavior and health education. 4th ed. San Francisco: John Wiley & Sons; 2008. pp. 465–85.

Madden A, Tanguay P, Chang J, Drug, Decriminalisation. Progress or Political Red Herring? International Network of People who Use Drugs. 2021. Available from: https://inpud.net/drug-decriminalisation-progress-or-political-red-herring/ (Accessed 01 Jun. 2023).

Walker I, Netherland J. Developing a transformative drug Policy Research Agenda in the United States. Contemp Drug Probl 201946(1):3–21.

Hoss A. Decriminalization as Substance Use Disorder Prevention. U Tol L Rev. 2019;51:477.

Download references

Acknowledgements

The authors would like to thank Ms Louise Farragher, Information Specialist with the HRB, and Dr Claire Erraught, for their assistance and expertise with database searching and information retrieval.

Author information

Authors and affiliations.

Health Research Board, Grattan House, 67–72 Lower Mount Street, Dublin 2, Ireland

Joan Devin, Suzi Lyons, Lisa Murphy, Michael O’Sullivan & Ena Lynn

School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland, 1st Floor Ardilaun House Block B, 111 St Stephen’s Green, Dublin 2, Ireland

You can also search for this author in PubMed   Google Scholar

Contributions

EL, LM, SL, and MOS conceptualised and designed the study. EL, LM, MOS, and SL constructed the search strategy and screening. JD and EL reviewed the full-text articles with input from the other authors. JD drafted the initial manuscript with input from the other authors. All authors contributed to and approved the final version.

Corresponding author

Correspondence to Ena Lynn .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Additional information, publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1: Population, concept and outcome definitions

Supplementary material 2: search terms for databases, supplementary material 3: prisma-scr checklist, supplementary material 4: charting form for included publications, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Devin, J., Lyons, S., Murphy, L. et al. Factors associated with suicide in people who use drugs: a scoping review. BMC Psychiatry 23 , 655 (2023). https://doi.org/10.1186/s12888-023-05131-x

Download citation

Received : 16 March 2023

Accepted : 23 August 2023

Published : 05 September 2023

DOI : https://doi.org/10.1186/s12888-023-05131-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Risk factors

BMC Psychiatry

ISSN: 1471-244X

descriptive research design about mental health

Europe PMC requires Javascript to function effectively.

Either your web browser doesn't support Javascript or it is currently turned off. In the latter case, please turn on Javascript support in your web browser and reload this page.

Search life-sciences literature (43,778,016 articles, preprints and more)

  • Free full text
  • Citations & impact
  • Similar Articles

An overview of the qualitative descriptive design within nursing research.

Author information, affiliations, orcids linked to this article.

  • Doyle L | 0000-0002-0153-8326
  • Brady A | 0000-0002-7112-6810
  • McCann M | 0000-0002-7925-6396

Journal of Research in Nursing : JRN , 18 Dec 2019 , 25(5): 443-455 https://doi.org/10.1177/1744987119880234   PMID: 34394658  PMCID: PMC7932381

Free full text in Europe PMC

Abstract 

Methods and results, conclusions, free full text .

Logo of jrn

An overview of the qualitative descriptive design within nursing research

Louise doyle.

Associate Professor in Mental Health Nursing, School of Nursing and Midwifery, Trinity College Dublin, Ireland

Catherine McCabe

Associate Professor in General Nursing, School of Nursing and Midwifery, Trinity College Dublin, Ireland

Brian Keogh

Assistant Professor in Mental Health Nursing, School of Nursing and Midwifery, Trinity College Dublin, Ireland

Annemarie Brady

Chair of Nursing and Chronic Illness, School of Nursing and Midwifery, Trinity College Dublin, Ireland

Qualitative descriptive designs are common in nursing and healthcare research due to their inherent simplicity, flexibility and utility in diverse healthcare contexts. However, the application of descriptive research is sometimes critiqued in terms of scientific rigor. Inconsistency in decision making within the research process coupled with a lack of transparency has created issues of credibility for this type of approach. It can be difficult to clearly differentiate what constitutes a descriptive research design from the range of other methodologies at the disposal of qualitative researchers.

This paper provides an overview of qualitative descriptive research, orientates to the underlying philosophical perspectives and key characteristics that define this approach and identifies the implications for healthcare practice and policy.

Using real-world examples from healthcare research, the paper provides insight to the practical application of descriptive research at all stages of the design process and identifies the critical elements that should be explicit when applying this approach.

By adding to the existing knowledge base, this paper enhances the information available to researchers who wish to use the qualitative descriptive approach, influencing the standard of how this approach is employed in healthcare research.

  • Introduction

Qualitative descriptive approaches to nursing and healthcare research provide a broad insight into particular phenomena and can be used in a variety of ways including as a standalone research design, as a precursor to larger qualitative studies and commonly as the qualitative component in mixed-methods studies. Despite the widespread use of descriptive approaches within nursing research, there is limited methodological guidance about this type of design in research texts or papers. The lack of adequate representation in research texts has at times resulted in novice researchers using other more complex qualitative designs including grounded theory or phenomenology without meeting the requirements of these approaches ( Lambert and Lambert, 2012 ), or having an appropriate rationale for use of these approaches. This suggests there is a need to have more discussion about how and why descriptive approaches to qualitative research are used. This serves to not only provide information and guidance for researchers, but to ensure acceptable standards in how this approach is applied in healthcare research.

  • Rationale for qualitative descriptive research

The selection of an appropriate approach to answer research questions is one of the most important stages of the research process; consequently, there is a requirement that researchers can clearly articulate and defend their selection. Those who wish to undertake qualitative research have a range of approaches available to them including grounded theory, phenomenology and ethnography. However, these designs may not be the most suitable for studies that do not require a deeply theoretical context and aim to stay close to and describe participants’ experiences. The most frequently proposed rationale for the use of a descriptive approach to is to provide straightforward descriptions of experiences and perceptions ( Sandelowski, 2010 ), particularly in areas where little is known about the topic under investigation. A qualitative descriptive design may be deemed most appropriate as it recognises the subjective nature of the problem, the different experiences participants have and will present the findings in a way that directly reflects or closely resembles the terminology used in the initial research question ( Bradshaw et al., 2017 ). This is particularly relevant in nursing and healthcare research, which is commonly concerned with how patients experience illness and associated healthcare interventions. The utilisation of a qualitative descriptive approach is often encouraged in Master’s level nurse education programmes as it enables novice clinical nurse researchers explore important healthcare questions that have direct implications and impact for their specific healthcare setting (Colorafi and Evans, 2016). As a Master’s level project is often the first piece of primary research undertaken by nurses, the use of a qualitative descriptive design provides an excellent method to address important clinical issues where the focus is not on increasing theoretical or conceptual understanding, but rather contributing to change and quality improvement in the practice setting ( Chafe, 2017 ).

This design is also frequently used within mixed-methods studies where qualitative data can explain quantitative findings in explanatory studies, be used for questionnaire development in exploratory studies and validate and corroborate findings in convergent studies ( Doyle et al., 2016 ). There has also been an increase in the use of qualitative descriptive research embedded in large-scale healthcare intervention studies, which can serve a number of purposes including identifying participants’ perceptions of why an intervention worked or, just as importantly, did not work and how the intervention might be improved ( Doyle et al., 2016 ). Using qualitative descriptive research in this manner can help to make the findings of intervention studies more clinically meaningful.

  • Philosophical and theoretical influences

Qualitative descriptive research generates data that describe the ‘who, what, and where of events or experiences’ from a subjective perspective ( Kim et al., 2017 , p. 23). From a philosophical perspective, this approach to research is best aligned with constructionism and critical theories that use interpretative and naturalistic methods ( Lincoln et al., 2017 ). These philosophical perspectives represent the view that reality exists within various contexts that are dynamic and perceived differently depending on the subject, therefore, reality is multiple and subjective ( Lincoln et al., 2017 ). In qualitative descriptive research, this translates into researchers being concerned with understanding the individual human experience in its unique context. This type of inquiry requires flexible research processes that are inductive and dynamic but do not transform the data beyond recognition from the phenomenon being studied ( Ormston et al., 2014 ; Sandelwoski 2010). Descriptive qualitative research has also been aligned with pragmatism ( Neergaard et al., 2009 ) where decisions are made about how the research should be conducted based on the aims or objectives and context of the study ( Ormston et al., 2014 ). The pragmatist researcher is not aligned to one particular view of knowledge generation or one particular methodology. Instead they look to the concepts or phenomena being studied to guide decision making in the research process, facilitating the selection of the most appropriate methods to answer the research question ( Bishop, 2015 ).

Perhaps linked to the practical application of pragmatism to research, that is, applying the best methods to answer the research question, is the classification of qualitative descriptive research by Sandelowski ( 2010 , p. 82) into a ‘distributed residual category’. This recognises and incorporates uncertainty about the phenomena being studied and the research methods used to study them. For researchers, it permits the use of one or more different types of inquiry, which is essential when acknowledging and exploring different realities and subjective experiences in relation to phenomena ( Long et al., 2018 ). Clarity, in terms of the rationale for the phenomenon being studied and the methods used by the researcher, emerges from the qualitative descriptive approach because the data gathered continue to remain close to the phenomenon throughout the study ( Sandelowski, 2010 ). For this to happen a flexible approach is required and this is evident in the practice of ‘borrowing’ elements of other qualitative methodologies such as grounded theory, phenomenology and ethnography ( Vaismoradi et al., 2013 ).

Regarded as a positive aspect by many researchers who are interested in studying human nature and phenomenon, others believe this flexibility leads to inconsistency across studies and in some cases complacency by researchers. This can result in vague or unexplained decision making around the research process and subsequent lack of credibility. Accordingly, nurse researchers need to be reflexive, that is, clear about their role and position in terms of the phenomena being studied, the context, the theoretical framework and all decision-making processes used in a qualitative descriptive study. This adds credibility to both the study and qualitative descriptive research.

  • Methods in qualitative descriptive research

As with any research study, the application of descriptive methods will emerge in response to the aims and objectives, which will influence the sampling, data collection and analysis phases of the study.

Most qualitative research aligns itself with non-probability sampling and descriptive research is no different. Descriptive research generally uses purposive sampling and a range of purposive sampling techniques have been described ( Palinkas et al., 2015 ). Many researchers use a combination of approaches such as convenience, opportunistic or snowball sampling as part of the sampling framework, which is determined by the desired sample and the phenomena being studied.

Purposive sampling refers to selecting research participants that can speak to the research aims and who have knowledge and experience of the phenomenon under scrutiny ( Ritchie et al., 2014 ). When purposive sampling is used in a study it delimits and narrows the study population; however, researchers need to remember that other characteristics of the sample will also affect the population, such as the location of the researcher and their flexibility to recruit participants from beyond their base. In addition, the heterogeneity of the population will need to be considered and how this might influence sampling and subsequent data collection and analysis ( Palinkas et al ., 2015 ). Take, for example, conducting research on the experience of caring for people with Alzheimer’s disease (AD). For the most part AD is a condition that affects older people and experiences of participants caring for older people will ultimately dominate the sample. However, AD also affects younger people and how this will impact on sampling needs to be considered before recruitment as both groups will have very different experiences, although there will be overlap. Teddlie and Fu (2007) suggest that although some purposive sampling techniques generate representative cases, most result in describing contrasting cases, which they argue are at the heart of qualitative analysis. To achieve this, Sandelowski (2010) suggests that maximum variation sampling is particularly useful in qualitative descriptive research, which may acknowledge the range of experiences that exist especially in healthcare research. Palinkas et al . (2015) describe maximum variation sampling as identifying shared patterns that emerge from heterogeneity. In other words, researchers attempt to include a wide range of participants and experiences when collecting data. This may be more difficult to achieve in areas where little is known about the substantive area and may depend on the researcher’s knowledge and immersion within the subject area.

Sample size will also need to be considered and although small sample sizes are common in qualitative descriptive research, researchers need to be careful they have enough data collected to meet the study aims ( Ritchie et al., 2014 ). Pre-determining the sample size prior to data collection may stifle the analytic process, resulting in too much or too little data. Traditionally, the gold standard for sample size in qualitative research is data saturation, which differs depending on the research design and the size of the population ( Fusch and Ness, 2015 ). Data saturation is reached ‘when there is enough information to replicate the study, when the ability to obtain additional new information has been attained, and when further coding is no longer feasible’ ( Fusch and Ness, 2015 , p. 1408). However, some argue that although saturation is often reported, it is rarely demonstrated in qualitative descriptive research reports ( Caelli et al., 2003 ; Malterud et al., 2016 ). If data saturation is used to determine sample size, it is suggested that greater emphasis be placed on demonstrating how saturation was reached and at what level to provide more credibility to sample sizes ( Caelli et al., 2003 ). Sample size calculation should be an estimate until saturation has been achieved through the concurrent processes of data collection and analysis. Where saturation has not been achieved, or where sample size has been predetermined for resource reasons, this should be clearly acknowledged. However, there is also a movement away from the reliance on data saturation as a measure of sample size in qualitative research ( Malterud et al., 2016 ). O’Reilly and Parker (2012) question the appropriateness of the rigid application of saturation as a sample size measure arguing that outside of Grounded Theory, its use is inconsistent and at times questionable. Malterud et al. (2016) focus instead on the concept of ‘information power’ to determine sample size. Here, they suggest sample size is determined by the amount of information the sample holds relevant to the actual study rather than the number of participants ( Malterud et al., 2016 ). Some guidance on specific sample size depending on research design has been provided in the literature; however, these are sometimes conflicting and in some cases lack evidence to support their claims ( Guest et al., 2006 ). This is further complicated by the range of qualitative designs and data collection approaches available.

Data collection

Data collection methods in qualitative descriptive research are diverse and aim to discover the who, what and where of phenomena ( Sandelowski, 2000 ). Although semi-structured individual face-to-face interviews are the most commonly used data collection approaches ( Kim et al ., 2017 ), focus groups, telephone interviews and online approaches are also used.

Focus groups involve people with similar characteristics coming together in a relaxed and permissive environment to share their thoughts, experiences and insights ( Krueger and Casey, 2009 ). Participants share their own views and experiences, but also listen to and reflect on the experiences of other group members. It is this synergistic process of interacting with other group members that refines individuals’ viewpoints to a deeper and more considered level and produces data and insights that would not be accessible without the interaction found in a group (Finch et al., 2014). Telephone interviews and online approaches are gaining more traction as they offer greater flexibility and reduced costs for researchers and ease of access for participants. In addition, they may help to achieve maximum variation sampling or examine experiences from a national or international perspective. Face-to-face interviews are often perceived as more appropriate than telephone interviews; however, this assumption has been challenged as evidence to support the use of telephone interviews emerges ( Ward et al., 2015 ). Online data collection also offers the opportunity to collect synchronous and asynchronous data using instant messaging and other online media ( Hooley et al., 2011 ). Online interviews or focus groups conducted via Skype or other media may overcome some of the limitations of telephone interviews, although observation of non-verbal communication may be more difficult to achieve ( Janghorban et al., 2014 ). Open-ended free-text responses in surveys have also been identified as useful data sources in qualitative descriptive studies ( Kim et al . , 2017 ) and in particular the use of online open-ended questions, which can have a large geographical reach ( Seixas et al., 2018 ). Observation is also cited as an approach to data collection in qualitative descriptive research ( Sandelowski, 2000 ; Lambert and Lambert, 2012 ); however, in a systematic review examining the characteristics of qualitative research studies, observation was cited as an additional source of data and was not used as a primary source of data collection ( Kim et al. , 2017 ).

Data analysis and interpretation

According to Lambert and Lambert (2012) , data analysis in qualitative descriptive research is data driven and does not use an approach that has emerged from a pre-existing philosophical or epistemological perspective. Within qualitative descriptive research, it is important analysis is kept at a level at which those to whom the research pertains are easily able to understand and so can use the findings in healthcare practice ( Chafe, 2017 ). The approach to analysis is dictated by the aims of the research and as qualitative descriptive research is generally explorative, inductive approaches will commonly need to be applied although deductive approaches can also be used ( Kim et al . , 2017 ).

Content and thematic analyses are the most commonly used data analysis techniques in qualitative descriptive research. Vaismoradi et al . (2013) argue that content and thematic analysis, although poorly understood and unevenly applied, offer legitimate ways of a lower level of interpretation that is often required in qualitative descriptive research. Sandelowski (2000) indicated that qualitative content analysis is the approach of choice in descriptive research; however, confusion exists between content and thematic analysis, which sometimes means researchers use a combination of the two. Vaismoradi et al. (2013) argue there are differences between the two and that content analysis allows the researchers to analyse the data qualitatively as well as being able to quantify the data whereas thematic analysis provides a purely qualitative account of the data that is richer and more detailed. Decisions to use one over the other will depend on the aims of the study, which will dictate the depth of analysis required. Although there is a range of analysis guidelines available, they share some characteristics and an overview of these, derived from some key texts ( Sandleowski, 2010 ; Braun and Clark, 2006 ; Newell and Burnard, 2006), is presented in Table 1 . Central to these guidelines is an attempt by the researcher to immerse themselves in the data and the ability to demonstrate a consistent and systematic approach to the analysis.

Common characteristics of descriptive qualitative analysis.

Coding in qualitative descriptive research can be inductive and emerge from the data, or a priori where they are based on a pre-determined template as in template analysis. Inductive codes can be ‘in vivo’ where the researcher uses the words or concepts as stated by the participants ( Howitt, 2019 ), or can be named by the researcher and grouped together to form emerging themes or categories through an iterative systematic process until the final themes emerge. Template analysis involves designing a coding template, which is designed inductively from a subset of the data and then applied to all the data and refined as appropriate ( King, 2012 ). It offers a standardised approach that may be useful when several researchers are involved in the analysis process.

Within qualitative research studies generally, the analysis of data and subsequent presentation of research findings can range from studies with a relatively minimal amount of interpretation to those with high levels of interpretation ( Sandelowski and Barroso, 2003 ). The degree of interpretation required in qualitative descriptive research is contentious. Sandelowski (2010) argues that although descriptive research produces findings that are ‘data-near’, they are nevertheless interpretative. Sandelowski (2010) reports that a common misconception in qualitative descriptive designs is that researchers do not need to include any level of analysis and interpretation and can rely solely on indiscriminately selecting direct quotations from participants to answer the research question(s). Although it is important to ensure those familiar with the topic under investigation can recognise their experiences in the description of it ( Kim et al . , 2017 ), this is not to say that there should be no transformation of data. Researchers using a qualitative descriptive design need to, through data analysis, move from un-interpreted participant quotations to interpreted research findings, which can still remain ‘data-near’ ( Sandeklwoski, 2010 ). Willis et al. (2016) suggest that researchers using the qualitative descriptive method might report a comprehensive thematic summary as findings, which moves beyond individual participant reports by developing an interpretation of a common theme. The extent of description and/or interpretation in a qualitative descriptive study is ultimately determined by the focus of the study (Neergard et al ., 2009).

As with any research design, ensuring the rigor or trustworthiness of findings from a qualitative descriptive study is crucial. For a more detailed consideration of the quality criteria in qualitative studies, readers are referred to the seminal work of Lincoln and Guba (1985) in which the four key criteria of credibility, dependability, confirmability and transferability are discussed. At the very least, researchers need to be clear about the methodological decisions taken during the study so readers can judge the trustworthiness of the study and ultimately the findings ( Hallberg, 2013 ). Being aware of personal assumptions and the role they play in the research process is also an important quality criterion (Colorafi and Evans, 2016) and these assumptions can be made explicit through the use of researcher reflexivity in the study ( Bradshaw et al., 2017 ).

  • Challenges in using a qualitative descriptive design

One of the challenges of utilising a qualitative descriptive design is responding to the charge that many qualitative designs have historically encountered, which is that qualitative designs lack the scientific rigor associated with quantitative approaches ( Vaismoradi et al . , 2013 ). The descriptive design faces further critique in this regard as, unlike other qualitative approaches such as phenomenology or grounded theory, it is not theory driven or oriented ( Neergaard et al ., 2009 ). However, it is suggested that this perceived limitation of qualitative descriptive research only holds true if it is used for the wrong purposes and not primarily for describing the phenomenon ( Neergaard et al ., 2009 ). Kahlke (2014) argues that rather than being atheoretical, qualitative descriptive approaches require researchers to consider to what extent theory will inform the study and are sufficiently flexible to leave space for researchers to utilise theoretical frameworks that are relevant and inform individual research studies. Kim et al. (2017) reported that most descriptive studies reviewed did not identify a theoretical or philosophical framework, but those that did used it to inform the development of either the interview guide or the data analysis framework, thereby identifying the potential use of theory in descriptive designs.

Another challenge around the use of qualitative descriptive research is that it can erroneously be seen as a ‘quick fix’ for researchers who want to employ qualitative methods, but perhaps lack the expertise or familiarity with qualitative research ( Sandelowski, 2010 ). Kim et al. (2017) report how in their review fewer than half of qualitative descriptive papers explicitly identified a rationale for choosing this design, suggesting that in some cases the rationale behind its use was ill considered. Providing a justification for choosing a particular research design is an important part of the research process and, in the case of qualitative descriptive research, a clear justification can offset concerns that a descriptive design was an expedient rather than a measured choice. For studies exploring participants’ experiences, which could be addressed using other qualitative designs, it also helps to clearly make a distinction as to why a descriptive design was the best choice for the research study ( Kim et al ., 2017 ). Similarly, there is a perception that the data analysis techniques most commonly associated with descriptive research – thematic and content analysis are the ‘easiest’ approaches to qualitative analysis; however, as Vaismoradi et al . (2013) suggest, this does not mean they produce low-quality research findings.

As previously identified, a further challenge with the use of qualitative descriptive methods is that as a research design it has limited visibility in research texts and methodological papers ( Kim et al ., 2017 ). This means that novice qualitative researchers have little guidance on how to design and implement a descriptive study as there is a lack of a ‘methodological rulebook’ to guide researchers ( Kahlke, 2014 ). It is also suggested that this lack of strict boundaries and rules around qualitative descriptive research also offers researchers flexibility to design a study using a variety of data collection and analysis approaches that best answer the research question ( Kahlke, 2014 ; Kim et al . , 2017 ). However, should researchers choose to integrate methods ‘borrowed’ from other qualitative designs such as phenomenology or grounded theory, they should do so with the caveat that they do not claim they are using designs they are not actually using ( Neergaard et al . , 2009 ).

  • Examples of the use of qualitative descriptive research in healthcare

Findings from qualitative descriptive studies within healthcare have the potential to describe the experiences of patients, families and health providers, inform the development of health interventions and policy and promote health and quality of life ( Neergaard et al ., 2009 ; Willis et al ., 2016 ). The examples provided here demonstrate different ways qualitative descriptive methods can be used in a range of healthcare settings.

Simon et al. (2015) used a qualitative descriptive design to identify the perspectives of seriously ill, older patients and their families on the barriers and facilitators to advance care planning. The authors provided a rationale for using a descriptive design, which was to gain a deeper understanding of the phenomenon under investigation. Data were gathered through nine open-ended questions on a researcher-administered questionnaire. Responses to all questions were recorded verbatim and transcribed. Using descriptive, interpretative and explanatory coding that transformed raw data recorded from 278 patients and 225 family members to more abstract ideas and concepts ( Simon et al. , 2015 ), a deeper understanding of the barriers and facilitators to advance care planning was developed. Three categories were developed that identified personal beliefs, access to doctors and interaction with doctors as the central barriers and facilitators to advance care planning. The use of a qualitative descriptive design facilitated the development of a schematic based on these three themes, which provides a framework for use by clinicians to guide improvement in advance care planning.

Focus group interviews are a common data collection method in qualitative descriptive studies and were the method of choice in a study by Pelentsov et al. (2015), which sought to identify the supportive care needs of parents whose child has a rare disease. The rationale provided for using a qualitative descriptive design was to obtain a ‘straight description of the phenomena’ and to provide analysis and interpretation of the findings that remained data-near and representative of the responses of participants. In this study, four semi-structured focus group interviews were conducted with 23 parents. The data from these focus groups were then subjected to a form of thematic analysis during which emerging theories and inferences were identified and organised into a series of thematic networks and ultimately into three global themes. These themes identified that a number of factors including social isolation and lack of knowledge on behalf of healthcare professionals significantly affected how supported parents felt. Identifying key areas of the supportive needs of parents using qualitative description provides direction to health professionals on how best to respond to and support parents of children with a rare disease.

The potential for findings from a qualitative descriptive study to impact on policy was identified in a study by Syme et al. (2016) , who noted a lack of guidance and policies around sexual expression management of residents in long-term care settings. In this study, 20 directors of nursing from long-term care settings were interviewed with a view to identifying challenges in addressing sexual expression in these settings and elicit their recommendations for addressing these challenges in practice and policy. Following thematic analysis, findings relating to what directors of nursing believed to be important components of policy to address sexual expression were identified. These included providing educational resources, having a person-centred care delivery model when responding to sexual expression and providing guidance when working with families. Findings from this qualitative descriptive study provide recommendations that can then feed in to a broader policy on sexual expression in long-term care settings.

The final example of the use of a qualitative descriptive study comes from a mixed-methods study comprising a randomised control trial and a qualitative process evaluation. He et al. (2015) sought to determine the effects of a play intervention for children on parental perioperative anxiety and to explore parents’ perceptions of the intervention. Parents who had children going for surgery were assigned to a control group or an intervention group. The intervention group took part in a 1-hour play therapy session with their child whereas the control group received usual care. Quantitative findings identified there was no difference in parents’ anxiety levels between the intervention and control group. However, qualitative findings identified that parents found the intervention helpful in preparing both themselves and their child for surgery and perceived a reduction in their anxiety about the procedure thereby capturing findings that were not captured by the quantitative measures. In addition, in the qualitative interviews, parents made suggestions about how the play group could be improved, which provides important data for the further development of the intervention.

These examples across a range of healthcare settings provide evidence of the way findings from qualitative descriptive research can be directly used to more fully understand the experiences and perspectives of patients, their families and healthcare providers in addition to guiding future healthcare practice and informing further research.

Qualitative research designs have made significant contributions to the development of nursing and healthcare practices and policy. The utilisation of qualitative descriptive research is common within nursing research and is gaining popularity with other healthcare professions. This paper has identified that the utilisation of this design can be particularly relevant to nursing and healthcare professionals undertaking a primary piece of research and provides an excellent method to address issues that are of real clinical significance to them and their practice setting. However, the conundrum facing researchers who wish to use this approach is its lack of visibility and transparency within methodological papers and texts, resulting in a deficit of available information to researchers when designing such studies. By adding to the existing knowledge base, this paper enhances the information available to researchers who wish to use the qualitative descriptive approach, thus influencing the standard in how this approach is employed in healthcare research. We highlight the need for researchers using this research approach to clearly outline the context, theoretical framework and concepts underpinning it and the decision-making process that informed the design of their qualitative descriptive study including chosen research methods, and how these contribute to the achievement of the study’s aims and objectives. Failure to describe these issues may have a negative impact on study credibility. As seen in our paper, qualitative descriptive studies have a role in healthcare research providing insight into service users and providers’ perceptions and experiences of a particular phenomenon, which can inform healthcare service provision.

  • Key points for policy, practice and/or research

Despite its widespread use, there is little methodological guidance to orientate novice nurse researchers when using the qualitative descriptive design. This paper provides this guidance and champions the qualitative descriptive design as appropriate to explore research questions that require accessible and understandable findings directly relevant to healthcare practice and policy.

This paper identifies how the use of a qualitative descriptive design gives direct voice to participants including patients and healthcare staff, allowing exploration of issues of real and immediate importance in the practice area.

This paper reports how within qualitative descriptive research, the analysis of data and presentation of findings in a way that is easily understood and recognised is important to contribute to the utilisation of research findings in nursing practice.

As this design is often overlooked in research texts despite its suitability to exploring many healthcare questions, this paper adds to the limited methodological guidance and has utility for researchers who wish to defend their rationale for the use of the qualitative descriptive design in nursing and healthcare research.

Louise Doyle (PhD, MSc, BNS, RNT, RPN) is an Associate Professor in Mental Health Nursing at the School of Nursing and Midwifery, Trinity College Dublin. Her research interests are in the area of self-harm and suicide and she has a particular interest and expertise in mixed-methods and qualitative research designs.

Catherine McCabe (PhD, MSc, BNS, RNT, RGN) is an Associate Professor in General Nursing at the School of Nursing and Midwifery, Trinity College Dublin. Her research interests and expertise are in the areas of digital health (chronic disease self-management and social/cultural wellbeing), cancer, dementia, arts and health and systematic reviews.

Brian Keogh (PhD, MSc, BNS, RNT, RPN) is an Assistant Professor in Mental Health Nursing at the School of Nursing and Midwifery, Trinity College Dublin. His main area of research interest is mental health recovery and he specialises in qualitative research approaches with a particular emphasis on grounded theory.

Annemarie Brady (PhD, MSc, BNS, RNT, RPN) is Chair of Nursing and Chronic Illness and Head of School of Nursing and Midwifery at Trinity College Dublin. Her research work has focused on the development of healthcare systems and workforce solutions to respond to increased chronic illness demands within healthcare. She has conducted a range of mixed-method research studies in collaboration with health service providers to examine issues around patient-related outcomes measures, workload measurement, work conditions, practice development, patient safety and competency among healthcare workers.

Margaret McCann (PhD, MSc, BNS, RNT, RGN) is an Assistant Professor in General Nursing at the School of Nursing and Midwifery, Trinity College Dublin. Research interests are focused on chronic illness management, the use of digital health and smart technology in supporting patient/client education, self-management and independence. Other research interests include conducting systematic reviews, infection prevention and control and exploring patient outcomes linked to chronic kidney disease.

  • Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Ethical approval was not required for this paper as it is a methodological paper and does not report on participant data.

The author(s) received no financial support for the research, authorship and/or publication of this article.

Louise Doyle https://orcid.org/0000-0002-0153-8326

Margaret McCann https://orcid.org/0000-0002-7925-6396

  • Bishop FL. (2015) Using mixed methods in health research: Benefits and challenges . British Journal of Health Psychology 20 : 1–4. [ Abstract ] [ Google Scholar ]
  • Bradshaw C, Atkinson S, Doody O. (2017) Employing a qualitative description approach in health care research . Global Qualitative Nursing Research 4 : 1–8. [ Europe PMC free article ] [ Abstract ] [ Google Scholar ]
  • Braun V, Clarke V. (2006) Using thematic analysis in psychology . Qualitative Research in Psychology 3 : 77–101. [ Google Scholar ]
  • Caelli K, Ray L, Mill J. (2003) ‘Clear as mud’: Toward greater clarity in generic qualitative research . International Journal of Qualitative Methods 2 : 1–13. [ Google Scholar ]
  • Chafe R. (2017) The Value of Qualitative Description in Health Services and Policy Research . Healthcare Policy 12 : 12–18. [ Europe PMC free article ] [ Abstract ] [ Google Scholar ]
  • Doyle L, Brady AM, Byrne G. (2016) An overview of mixed methods research–revisited . Journal of Research in Nursing 21 : 623–635. [ Google Scholar ]
  • Finch H, Lewis J, Turley C. Ritchie J, Lewis J, McNaughton Nicholls C, Ormston R, editors. Focus Groups . Qualitative Research Practice. A Guide for Social Science Students and Researchers , London: Sage, pp. 211–242. [ Google Scholar ]
  • Fusch PI, Ness LR. (2015) Are we there yet? Data saturation in qualitative research . The Qualitative Report 20 : 1408–1416. [ Google Scholar ]
  • Guest G, Bunce A, Johnson L. (2006) How many interviews are enough? An experiment with data saturation and variability . Field Methods 18 : 59–82. [ Google Scholar ]
  • Hallberg L. (2013) Quality criteria and generalization of results from qualitative studies . International Journal of Qualitative Studies in Health and Well-being 8 : 1. [ Europe PMC free article ] [ Abstract ] [ Google Scholar ]
  • He HG, Zhu LX, Chan WCS, et al.(2015) A mixed-method study of effects of a therapeutic play intervention for children on parental anxiety and parents’ perceptions of the intervention . Journal of Advanced Nursing 71 ( 7 ): 1539–1551. [ Abstract ] [ Google Scholar ]
  • Hooley T, Wellens J, Marriott J. (2011) What is Online research? Using the Internet for Social Science Research , London: Bloomsbury Academic. [ Google Scholar ]
  • Howitt D. (2019) Introduction to Qualitative Methods in Psychology: Putting Theory into Practice , (4th edition). Harlow: Pearson Education Limited. [ Google Scholar ]
  • Janghorban R, Roudsari RL, Taghipour A. (2014) Skype interviewing: The new generation of online synchronous interview in qualitative research . International Journal of Qualitative Studies on Health and Wellbeing 9 . [ Europe PMC free article ] [ Abstract ] [ Google Scholar ]
  • Kahlke RM. (2014) Generic qualitative approaches: Pitfalls and benefits of methodological mixology . International Journal of Qualitative Methods 13 : 37–52. [ Google Scholar ]
  • Kim H, Sefcik JS, Bradway C. (2017) Characteristics of qualitative descriptive studies: A systematic review . Research in Nursing & Health 40 : 23–42. [ Europe PMC free article ] [ Abstract ] [ Google Scholar ]
  • King N. (2012) Doing Template Analysis . In: Symon G, Cassell C, editors. (eds) Qualitative Organizational Research: Core Methods and Current Challenges , Los Angeles, CA: Sage. [ Google Scholar ]
  • Krueger RA, Casey MA. (2009) Focus Groups: A Practical Guide for Applied Research , 4th ed. Thousand Oaks, CA: Sage. [ Google Scholar ]
  • Lambert VA, Lambert CE. (2012) Qualitative descriptive research: An acceptable design . Pacific Rim International Journal of Nursing Research 16 : 255–256. [ Google Scholar ]
  • Lincoln YS, Guba EG. (1985) Naturalistic Inquiry , Newbury Park, CA: Sage. [ Google Scholar ]
  • Lincoln YS, Lynham SA, Guba EG. (2017) Paradigmatic Controversies, Contradictions and Emerging Confluences . In: NK Denzin, YS Guba, editors. (ed) The Sage Handbook of Qualitative Research , (5th edition). Thousand Oaks, CA: Sage. [ Google Scholar ]
  • Long KM, McDermott F, Meadows GN. (2018) Being pragmatic about healthcare complexity: Our experiences applying complexity theory and pragmatism to health services research . BMC Medicine 16 : 94. [ Europe PMC free article ] [ Abstract ] [ Google Scholar ]
  • Malterud K, Siersma VD, Guassora AD. (2016) Sample size in qualitative interview studies: Guided by information power . Qualitative Health Research 26 ( 13 ): 1753–1760. [ Abstract ] [ Google Scholar ]
  • Neergaard MA, Olesen F, Andersen RS, et al.(2009) Qualitative description – the poor cousin of health research? BMC Medical Research Methodology 9 . [ Europe PMC free article ] [ Abstract ] [ Google Scholar ]
  • Newell R, Burnard P. (2011) Research for Evidence Based Practice , Oxford: Blackwell Publishing. [ Google Scholar ]
  • O’Reilly M, Parker N. (2012) ‘Unsatisfactory Saturation’: A critical exploration of the notion of saturated sample sizes in qualitative research . Qualitative Research 13 ( 2 ): 190–197. [ Google Scholar ]
  • Ormston R, Spencer L, Barnard M, et al.(2014) The foundations of qualitative research . In: Ritchie J, Lewis J, McNaughton Nicholls C, Ormston R, editors. (eds) Qualitative Research Practice. A Guide for Social Science Students and Researchers , London: Sage, pp. 1–25. [ Google Scholar ]
  • Palinkas LA, Horwitz SM, Green CA, et al.(2015) Purposeful sampling for qualitative data collection and analysis in mixed method implementation research . Administration and Policy in Mental Health and Mental Health Services Research 42 : 533–544. [ Europe PMC free article ] [ Abstract ] [ Google Scholar ]
  • Pelentsov LL, Fielder AL, Esterman AJ. (2016) The supportive care needs of parents with a child with a rare disease: A qualitative descriptive study . Journal of Pediatric Nursing 31 ( 3 ): e207–e218. [ Abstract ] [ Google Scholar ]
  • Ritchie J, Lewis J, Elam G, et al.(2014) Designing and selecting samples . In: Ritchie J, Lewis J, McNaughton Nicholls C, Ormston R, editors. (eds) Qualitative Research Practice. A Guide for Social Science Students and Researchers , London: Sage, pp. 111–145. [ Google Scholar ]
  • Sandelowski M. (2000) Whatever happened to qualitative description? Research in Nursing & Health 23 : 334–340. [ Abstract ] [ Google Scholar ]
  • Sandelowski M. (2010) What’s in a name? Qualitative description revisited . Research in Nursing & Health 33 : 77–84. [ Abstract ] [ Google Scholar ]
  • Sandelowski M, Barroso J. (2003) Classifying the findings in qualitative studies . Qualitative Health Research 13 : 905–923. [ Abstract ] [ Google Scholar ]
  • Seixas BV, Smith N, Mitton C. (2018) The qualitative descriptive approach in international comparative studies: Using online qualitative surveys . International Journal of Health Policy Management 7 ( 9 ): 778–781. [ Europe PMC free article ] [ Abstract ] [ Google Scholar ]
  • Simon J, Porterfield P, Bouchal SR, et al.(2015) ‘Not yet’ and ‘just ask’: Barriers and facilitators to advance care planning – a qualitative descriptive study of the perspectives of seriously ill, older patients and their families . BMJ Supportive & Palliative Care 5 : 54–62. [ Abstract ] [ Google Scholar ]
  • Syme ML, Lichtenberg P, Moye J. (2016) Recommendations for sexual expression management in long-term care: A qualitative needs assessment . Journal of Advanced Nursing 72 ( 10 ): 2457–2467. [ Europe PMC free article ] [ Abstract ] [ Google Scholar ]
  • Teddlie C, Yu F. (2007) Mixed methods sampling: A typology with examples . Journal of Mixed Methods Research 1 : 77–100. [ Google Scholar ]
  • Vaismoradi M, Turunen H, Bondas T. (2013) Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study . Nursing & Health Sciences 15 : 398–405. [ Abstract ] [ Google Scholar ]
  • Ward K, Gott M, Hoare K. (2015) Participants’ views of telephone interviews within a grounded theory study . Journal of Advanced Nursing 71 : 2775–2785. [ Abstract ] [ Google Scholar ]
  • Willis DG, Sullivan-Bolyai S, Knafl K, et al.(2016) Distinguishing features and similarities between descriptive phenomenological and qualitative descriptive research . Western Journal of Nursing Research 38 : 1185–1204. [ Abstract ] [ Google Scholar ]

Full text links 

Read article at publisher's site: https://doi.org/10.1177/1744987119880234

Citations & impact 

Impact metrics, citations of article over time, alternative metrics.

Altmetric item for https://www.altmetric.com/details/72983517

Smart citations by scite.ai Smart citations by scite.ai include citation statements extracted from the full text of the citing article. The number of the statements may be higher than the number of citations provided by EuropePMC if one paper cites another multiple times or lower if scite has not yet processed some of the citing articles. Explore citation contexts and check if this article has been supported or disputed. https://scite.ai/reports/10.1177/1744987119880234

Article citations, in situ simulation training strengthened bachelor of nursing students' experienced learning and development process- a qualitative study..

Karlsen K , Nygård C , Johansen LG , Gjevjon ER

BMC Nurs , 23(1):121, 15 Feb 2024

Cited by: 0 articles | PMID: 38360599 | PMCID: PMC10870516

Awareness and knowledge of drug decriminalization among people who use drugs in British Columbia: a multi-method pre-implementation study.

Greer A , Xavier J , Loewen OK , Kinniburgh B , Crabtree A

BMC Public Health , 24(1):407, 08 Feb 2024

Cited by: 0 articles | PMID: 38331771 | PMCID: PMC10851533

Acceptability of the Long-Term In-Home Ventilator Engagement virtual intervention for home mechanical ventilation patients during the COVID-19 pandemic: A qualitative evaluation.

Dale CM , Ambreen M , Kang S , Buchanan F , Pizzuti R , Gershon AS , Rose L , Amin R

Digit Health , 10:20552076241228417, 27 Jan 2024

Cited by: 0 articles | PMID: 38282921 | PMCID: PMC10822085

Understanding adaptive tasks in cardiac rehabilitation among patients with acute myocardial infarction: a qualitative study.

Wang X , Chen D , Zou P , Zhang H , Qiu X , Xu L , Lee G

Ann Med , 56(1):2311227, 02 Feb 2024

Cited by: 0 articles | PMID: 38306095 | PMCID: PMC10840589

Men's experience of caring for a family member with cancer: a theory based on data.

Coppetti LC , Nietsche EA , Schimith MD , Radovanovic CAT , Lacerda MR , Girardon-Perlini NMO

Rev Lat Am Enfermagem , 32:e4095, 26 Jan 2024

Cited by: 0 articles | PMID: 38294054 | PMCID: PMC10825896

Similar Articles 

To arrive at the top five similar articles we use a word-weighted algorithm to compare words from the Title and Abstract of each citation.

Avoiding and identifying errors in health technology assessment models: qualitative study and methodological review.

Chilcott J , Tappenden P , Rawdin A , Johnson M , Kaltenthaler E , Paisley S , Papaioannou D , Shippam A

Health Technol Assess , 14(25):iii-iv, ix-xii, 1-107, 01 Jan 2010

Cited by: 29 articles | PMID: 20501062

Review Books & documents Free full text in Europe PMC

The Effectiveness of Integrated Care Pathways for Adults and Children in Health Care Settings: A Systematic Review.

Allen D , Gillen E , Rixson L

JBI Libr Syst Rev , 7(3):80-129, 01 Jan 2009

Cited by: 20 articles | PMID: 27820426

The future of Cochrane Neonatal.

Soll RF , Ovelman C , McGuire W

Early Hum Dev , 150:105191, 12 Sep 2020

Cited by: 5 articles | PMID: 33036834

Sampling issues in qualitative research.

Higginbottom GM

Nurse Res , 12(1):7-19, 01 Jan 2004

Cited by: 78 articles | PMID: 15493211

Using qualitative Health Research methods to improve patient and public involvement and engagement in research.

Rolfe DE , Ramsden VR , Banner D , Graham ID

Res Involv Engagem , 4:49, 13 Dec 2018

Cited by: 35 articles | PMID: 30564459 | PMCID: PMC6293564

Europe PMC is part of the ELIXIR infrastructure

U.S. flag

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

  • Publications
  • Account settings
  • Advanced Search
  • Journal List
  • SAGE Choice

The Study on Mental Health at Work: Design and sampling

1 Federal Institute for Occupational Safety and Health, Unit Mental Health and Cognitive Capacity, Berlin, Germany

Stefan Schiel

2 infas Institute for Applied Social Sciences, Bonn, Germany

Helmut Schröder

Martin kleudgen, silke tophoven.

3 Institute for Employment Research, Nuremberg, Germany

Angela Rauch

Gabriele freude, grit müller.

Aims: The Study on Mental Health at Work (S-MGA) generates the first nationwide representative survey enabling the exploration of the relationship between working conditions, mental health and functioning. This paper describes the study design, sampling procedures and data collection, and presents a summary of the sample characteristics. Methods: S-MGA is a representative study of German employees aged 31–60 years subject to social security contributions. The sample was drawn from the employment register based on a two-stage cluster sampling procedure. Firstly, 206 municipalities were randomly selected from a pool of 12,227 municipalities in Germany. Secondly, 13,590 addresses were drawn from the selected municipalities for the purpose of conducting 4500 face-to-face interviews. The questionnaire covers psychosocial working and employment conditions, measures of mental health, work ability and functioning. Data from personal interviews were combined with employment histories from register data. Descriptive statistics of socio-demographic characteristics and logistic regressions analyses were used for comparing population, gross sample and respondents. Results: In total, 4511 face-to-face interviews were conducted. A test for sampling bias revealed that individuals in older cohorts participated more often, while individuals with an unknown educational level, residing in major cities or with a non-German ethnic background were slightly underrepresented. Conclusions: There is no indication of major deviations in characteristics between the basic population and the sample of respondents. Hence, S-MGA provides representative data for research on work and health, designed as a cohort study with plans to rerun the survey 5 years after the first assessment.

Introduction

Systematic reviews of work environment and mental health indicators such as depressive symptoms [ 1 ] and depression [ 2 , 3 ] provide evidence of the impact of job strain, decision latitude or bullying. According to Theorell et al. [ 1 ] limited evidence is given by longitudinal studies with a high degree of methodological quality for working conditions such as effort reward imbalance, social support, psychological demands or job insecurity. As seen in the referenced literature within these reviews there is a strong orientation to studies from English-speaking or Scandinavian countries or the Netherlands and a lack of longitudinal studies based on a representative sample in several other countries, including Germany. Therefore, an independent reanalysis based on other samples and within a range of other national contexts is relevant for better understanding how widely and strongly the evidence applies.

A further indicator of mental health is burnout, with exhaustion as its core dimension. The associations between burnout and psychosocial working conditions have been analysed in a review by Seidler et al. [ 4 ]. In comparison with reviews of depressive symptoms they found even fewer longitudinal studies; precisely six studies were seen to be of sufficient quality and none of these were from Germany. A total of five of these studies considered selected occupational groups from the health sector or human services and not representative samples of all employees.

In epidemiological and public health research the investigation of mental health focusses on the negative spectrum of mental health such as burnout or depression. One reason for this focus is, that mental disorders lead to higher rates of absenteeism and constitute a leading cause of early retirement in Europe [ 5 ]. New developments in the field of positive psychology are moving towards positive attributes of mental health, thus highlighting aspects of well-being that have been neglected to date, such as the balance of positive and negative affects, life satisfaction, and subjective well-being [ 6 ]. Supporters of this move consider a view of mental health as reduced to its negative spectrum to be too narrow [ 7 ]. Even a broader view of mental health is still unidirectional and thus insufficient to describe the range of possible outcomes, as it does not reflect the impact of mental health on a person’s functioning.

This impact of mental health on a person’s functioning considers limitations in daily activities and participation restrictions, while considering environmental and personal factors. These components in conjunction with impairments in body functions or structures are key elements of the International Classification of Functioning, Disability, and Health (ICF) coordinated by the World Health Organization (WHO) [ 8 ]. The scope of functioning thus encompasses more than the assessment of symptomatology and the diagnosis of mental disorders. Therefore, it provides an important link between mental health and workforce participation. Functioning according to the ICF is not limited to a single life domain. Accordingly, the assessment of work ability is included as a related measurement of work-related functioning [ 9 ]. Work ability takes into account ’[…] health and functional capacity, but […] is also determined by professional knowledge and competence (skills), values, attitudes, and motivation, and work itself” [ 10 ]. The latter determinants such as motivation are part of the theoretical framework of work ability, but they are not included in the original assessment.

The foregoing discussion of the multiple dimensions of outcomes shows that an adequate analysis of psychosocial working conditions and mental health goes far beyond any simple association and that empirical studies need to account for this broad range of interrelated issues. This is the rationale behind the Study on Mental Health at Work (S-MGA) – a representative study of employees subjected to social security contributions in Germany – which was initiated by the German Federal Institute of Occupational Health and Safety and conducted in collaboration with the Institute for Employment Research (IAB) and the Infas Institute of Applied Social Sciences.

The following research aims are addressed within the S-MGA study:

  • Examining the impact of past employment experiences and current working conditions on positive (well-being) and negative (depressive symptoms and burnout) dimensions of mental health;
  • Analysing the association between mental health, functioning and work ability;
  • Investigating in a second wave the predictive value of working conditions, mental health, and functioning for the prediction of employment status five years later.

S-MGA addresses the lack of representative data on mental health, work ability and functioning for the working population in Germany. This study generates the first nationwide representative survey enabling the exploration of the relationship between working conditions, mental health and functioning. Hence, the distributions of indicators can be utilised for comparison with a norm sample or for using this sample as natural control group within intervention studies.

This present paper gives an overview on the study design, sampling procedures and method of data collection of the S-MGA. Socio-demographic and economic characteristics were used for detecting differences between the sample of respondents and the population from which it was drawn.

Design and measurement procedures

S-MGA is a nationwide representative study of employees subjected to social security contribution aged 31–60 years in Germany. This age range was selected as the vast majority of people in employment are between 31–60 (i.e. they have finished their vocational training or studies and have not yet reached retirement age). S-MGA is designed as a panel study with a second assessment occurring 5 years after the first data collection, which ran from November 2011 to June 2012. The second wave will be completed by the middle of 2017, when the oldest participants will have reached the statutory retirement age.

Sampling and data collection

The sampling was based on data from the Integrated Employment Biographies (IEB), a register of the German Federal Employment Agency held by the IAB. This register covers employees who are subject to social security contributions. This constitutes more than 80% of the German working population [ 11 ], with civil servants, self-employed individuals and freelancers not included by definition. Using these data allows the linkage of employment histories with the collected survey data and a comparison of sample characteristics with the register. Those eligible to participate were all employees subjected to social security contributions on the reference date of 31 December 2010 who were born between 1951 and 1980. In total, 4500 interviews were planned to be conducted. Due to the plans for conducting face-to-face interviews, a two-stage cluster sampling procedure was applied. First, municipalities in Germany were proportionately stratified by region and population size and 206 municipalities were randomly selected from the pool of 12,227. Second, a random gross sample of 13,590 addresses was drawn within selected municipalities.

In preparation for the field phase, a letter including information on the study purpose and data protection was sent to the addresses of the selected individuals 1 week prior to the first contact attempt. To increase the motivation to participate, the letter mentioned an incentive of EUR10 given for participating [ 12 ]. During the field phase all addresses were contacted by the interviewers up to a maximum of 31 times. The interviews were only conducted after respondents gave their informed consent to carry out the study. Data were collected face-to-face by computer-assisted personal interview (CAPI) by 243 trained interviewers at the homes of the respondents. Sensitive information on mental health was collected with a drop-off paper pencil questionnaire in an envelope handed out directly to the study participants. The respondents filled it out directly and handed it back in a closed envelope. All respondents were asked whether they would give their written consent for saving the address data for a second wave of assessment. Additionally, a total of 425 study participants from two major cities were asked for their willingness to attend an occupational medical examination on physical and mental functioning.

Integrated Employment Biographies (IEB)

When participants gave their written permission, the survey data were linked to the IEB [ 13 ]. Data from the IEB comprise information from the notifications sent to social insurance as well as from the administrative processes of the German Federal Employment Agency. The data contain detailed information on employment status on a daily basis [ 14 ]. When participants gave their written permission, S-MGA included computation of several individual indicators such as employment status and wage from the IEB data.

Measurements

The CAPI was evaluated in a pre-test with 200 interviews regarding the sequence and comprehension of questions in summer 2011. The sequence of the interview is depicted in Figure 1 .

An external file that holds a picture, illustration, etc.
Object name is 10.1177_1403494817707123-fig1.jpg

Structure of the interview programme [ 12 ] (modified version).

Drop-off questionnaires: well-being (A), burnout (B) and depressive symptoms (C).

Detailed information on instruments and indicators is listed in Table I . The first part of the interview was concerned with employment and working conditions including the type of contract and working hours. Physical working conditions such as heavy lifting and awkward body postures were assessed by seven questions. The main focus was on self-reported psychosocial working conditions, which were assessed by questions from the Copenhagen Psychosocial Questionnaire (COPSOQ) [ 15 ]. Information about work ability came from the Work Ability Index (WAI) [ 16 ], and the interviewee’s functioning was investigated by the Short-Form-12 Health Survey [ 17 ] and by a German translation of the Norwegian Functioning Assessment Scale (NFAS) [ 18 ]. Motiva-tional factors were covered by the General Self-Efficacy Scale (GSE) [ 19 ] and the Utrecht Work Engagement Scale (UWES) [ 20 ]. Additional motivational and volitional aspects such as the intention to leave the job and/or the employer or to apply for a pension were supplemented by single items. Positive attributes of mental health such as, life satisfaction [ 21 ] and job satisfaction were included, supplemented by items on personal co-factors (critical life events, health-related behaviour, social context), inability to relax due to work involvement assessed by a subscale from the German questionnaire FABA [ 22 ], and socio-demographic information.

Content of the computer-assisted personal interview (CAPI) and the drop-off questionnaires.

Drop-off paper questionnaire

Sensitive questions to emotional and psychological well-being [ 6 ] as well as depressive symptoms and burnout were addressed by a drop-off questionnaire handed out during the interview. Specifically, depressive symptoms were assessed by the Patient Health Questionnaire (PHQ-9) [ 23 ] and burnout was represented by the main dimension of exhaustion from the Oldenburg Burnout Inventory (OLBI) [ 24 ].

Non-respondents’ questionnaire

Additionally, a short questionnaire was given to non-respondents refusing an interview after the initial contact. These non-respondents were asked for information on socio-demographics, self-rated health and work ability.

Statistical analysis

The accuracy of the sampling process was checked by comparing socioeconomic and demographic characteristics between the basic population, the gross sample, and the sample of respondents. Percentage differences between the basic population and sample of respondents were calculated for these characteristics. Multivariate analysis was conducted by logistic regression with 14 socio-demographic and socioeconomic parameters as covariates. The analysis is based on the gross sample of n = 13,590 and the binary outcome is participation versus non-participation in the interview. A value of 1 is assigned if the individual belongs to sample of respondents.

Altogether 4511 interviews were conducted and each interview was checked for inconsistent responses. According to the standards of the American Association for Public Opinion Research (AAPOR) [ 25 ] there was a contact rate of 90.6% and a response rate of 35.7%. The refusal rate was 53.7%, in line with the trend of declining willingness to participate in surveys in Germany [ 26 ]. The addresses were contacted 3.5 times on average. The completion of an interview required an average of 3.7 contacts and the interview lasted an average of 65.6 minutes.

The acceptance of employees surveyed to support the study was very high: 87.4% declared their written consent to remain in the panel, 74.6% gave their written consent to merge occupational data from the IEB ( n = 3591), and 69.6% of respondents from Berlin and Dresden agreed to an occupational medical examination. The comparison between the basic population, the gross sample and the sample of respondents shows only slight differences in characteristics at the first and second level of sampling ( Tables II and III ). Individuals in cities with 100,000 to 500,000 residents are underrepresented (−2.8% points) and those from the State of Saxony are overrepresented (+4.8%). A minor underrepresentation is observed for individual characteristics such as sex (men: −1.4%), age (birth cohorts from 1975 to 1980: −3.0%), place of employment (western parts of Germany −5.6%), unknown education (−3.0%), nationality (non-German: −2.6%) and occupation (simple services: −3.2%).

Comparison of population ( N = 21,471,156), gross sample ( n = 13,590) and sample of respondents ( n = 4511); regional characteristics.

BIK: type of region according to a German classification system based on area size, population size and density.

Population ( N = 21,959,394) and sample of respondents ( n = 4511) compared by individual characteristics.

The results of the logistic regression analysis controlling for 14 regional and individual characteristics are displayed in Table IV . The multivariate analysis provides only a poor fit to the data: only 2% (pseudo R 2 = 0.02) of the variance is accounted for by the full model.

Logistic regression analysis with survey participation as outcome ( n = 13,573).

BIK: type of region according to a German classification system based on area size, population size and density; CI: confidence interval; X: reference category.

The short questionnaire for those, who refused to participate was filled out by 341 individuals. The information provided by non-respondents deviates slightly from that of respondents concerning subjectively-perceived health and work ability. Non-respondents consider their health status to be very good or good slightly more frequently (63.0% versus 57.4%). The assessment of perceived work ability exhibits the opposite trend: respondents attribute to themselves slightly higher work ability than non-respondents (84.2% versus 70.3%).

This present paper gives an overview on design, sampling and data collection of S-MGA, the first nationwide representative cohort study on psychosocial working conditions, mental health and functioning in Germany. A total of 4511 interviews were conducted with employees aged 31–60 years and subject to social security constituting a response rate of 35.7%. By comparing the basic population with the sample of respondents there are only minor deviations concerning the distribution of socio-demographic characteristics giving no indication for a sampling bias.

The response rate of 35.7% is in line with the trend of declining willingness to participate in surveys in Germany [ 26 ] and other epidemiologic studies [ 27 ]. Thus, questions of participation and refusal should be considered in this context. Additionally, the question of whether non-response is a serious issue regarding bias depends on both the proportion of non-responders as well as the difference between responders and non-responders according to the measured variables. Using data from the register enables the direct comparison of the population in the register with not only the gross sample but also the sample of respondents within the survey. The results of these comparisons reveal only minor differences for the observed variables. Furthermore, multivariate analysis shows that socio-demographic and socioeconomic parameters explain a mere 2% of the variance. Hence, these parameters are hardly useful in explaining participation in this study. Based on the assessment of representativeness as well as the two selectivity analyses mentioned, the quality of the sample can reasonably be rated as quite high. The results from the non-response questionnaire likewise give no indication of systematic bias due to individual health status. Some indications such as the underrepresentation of individuals with unknown education or occupations among simple services or regional differences may be valuable clues for the adjustment of possible confounders.

The current study is based on a sample which is to be prospectively followed as a cohort over a period of 5 years. The application of a longitudinal design is an important attribute of any analytical study aiming at causal associations. Hence, the primary focus of systematic reviews is on follow-up studies by filtering out cross-sectional studies [ 2 , 3 ], which yields reviews with only few original studies.

The second wave of the current study takes place in the first half of 2017. There is a realistic chance of a good response in the second wave of assessment, since 87% declared their willingness to remain within the panel. Additionally, attrition will likely be minimized by conducting panel maintenance, which includes regular contacts with respondents, and by an incentive of EUR20 for participation in the second assessment.

One of the main strengths of the current study is its use of the register of the German Federal Employment Agency as a sampling frame as well as additional linked information. The use of the register adheres to a clear and straightforward definition of the population studied and as such the limitations are known explicitly. This population-based register holds the complete records for all employees subjected to social security contributions in terms of employment history and several individual characteristics. By definition, this register is more a work-related than a community-based sampling frame, which would typically include, for instance, homeworkers or retired or non-employed individuals. Data concerning addresses are well maintained and linked to the register, which is valuable from the perspective of the interviewer in the field attempting to contact a sampled individual.

The database of the register covers more than 80% of the German working population. Civil servants, the self-employed and freelancers are not included. The focus on dependent employment is a limitation of the study and for the generalizability of conclusions based on it. Another limitation is given by the age of the participants, restricted to those between 31–60 years of age. The oldest participants in the first wave of assessment will have reached the statutory retirement age by the second wave. Therefore, older aged cohorts are still covered by this study, whereas those 30 years or younger are by definition excluded. This exclusion is grounded in practical reasons, such as excluding those not finished with their vocational training or studies. This strategy implies the loss of younger cohorts who may have different experiences of the changing labour market. However, especially in younger aged cohorts, long-term positioning in the labour market very often occurs at older and older ages due to longer phases of education. Even among the German baby boomers one finds a proportion of almost 10% who were older than 30 years at the first experience of employment subject to social security contribution [ 28 ].

New data are already available from the first cross-sectional assessment conducted among employees subjected to social security contributions in Germany. This population-based survey contains information about the distributions of psychosocial working conditions (COPSOQ), motivational determinants (UWES), negative and positive attributes of mental health (depressive symptoms, burnout, and well-being) and functioning. The assessment of psychosocial working conditions by the COPSOQ is well established within Danish cohort studies and adapted for the German working context [ 15 ] and outcomes like the PHQ [ 23 ] and SF-12 [ 17 ] have been applied to the general population in Germany. These distributions are useful as a means of comparison, as there is no other study available for Germany with a focus on this profile of exposure and outcome variables within a broad population of employees. Hence, the current study provides a national reference sample for the distribution of psychosocial working conditions and for exhaustion as the core dimension of burnout.

Another important opportunity offered by this sample is to utilise it as a reference for defining a minimum level of work functioning, especially when making comparisons within intervention studies and evaluation research. This opportunity arises as a result of the sampling procedure. The starting point is the status of being employed on the date of sampling within the register. By definition, this is an important difference to community or population-based studies, which include non-employed individuals, homeworkers or those who retired early. As a consequence, this introduces some level of positive bias towards individuals, who – despite possible impairments in health and functioning – are still employed. This means that the sample of respondents constitutes a reference level for working populations with at least a minimum level of work functioning. This interpretation also applies to the empirical distributions of indicators for mental health or working conditions which give a picture of individuals still in work. Studies focusing on individuals with impaired health (e.g. return-to-work studies) can use these distributions for means of comparison and as a goal level for functioning.

S-MGA provides information which is highly relevant for objectives of the WHO. The mental health action plan of the WHO [ 29 ] conceptualizes mental health as a state of well-being which includes positive indicators and components of functioning. The fourth objective is circumscribed as aiming “[…] to strengthen information systems, evidence and research for mental health” (p. 22). Furthermore it contributes to objectives of the WHO’s global plan for worker’s health [ 30 ], such as providing and communicating evidence for action and practice.

In conclusion: S-MGA is a nationwide study based on a longitudinal design deploying high quality sampling with a focus on employment and working conditions, mental health and functioning. The population-based sample constitutes a reference and provides useful information for means of comparisons. In addition, the longitudinal design is especially well-suited for assessing the determinants of mental health, functioning, and participation at work. To the best of our knowledge there is no nationwide study in Germany with this combination of study features. This gives S-MGA great potential for future enquiries, and valuable insights into the relationship between work and health.

Acknowledgments

The authors would like to thank the participants of the study. The authors would also like to thank Jon Scouten and Hermann Burr for critical review of the text.

Declaration of conflicting interests: The authors declare that there is no conflict of interest.

Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

This paper is in the following e-collection/theme issue:

Published on 14.3.2024 in Vol 8 (2024)

Novel Web-Based Drop-In Mindfulness Sessions (Pause-4-Providers) to Enhance Well-Being Among Health Care Workers During the COVID-19 Pandemic: Descriptive and Qualitative Study

Authors of this article:

Author Orcid Image

Original Paper

  • Mary Elliott 1, 2 , MD   ; 
  • Camille Khallouf 3 , BA   ; 
  • Jennifer Hirsch 2, 3 , MD   ; 
  • Diane de Camps Meschino 2, 4 , MD   ; 
  • Orit Zamir 2, 3, 5, 6 , MD   ; 
  • Paula Ravitz 2, 3, 7 , MD  

1 Department of Supportive Care, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada

2 Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada

3 Department of Psychiatry, Sinai Health System, Toronto, ON, Canada

4 Women's College Hospital, Toronto, ON, Canada

5 Toronto Academic Pain Medicine Institute, Women's College Hospital, Toronto, ON, Canada

6 Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada

7 Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada

Corresponding Author:

Mary Elliott, MD

Department of Supportive Care

Princess Margaret Cancer Centre

University Health Network

610 University Ave

Toronto, ON, M5G 2C1

Phone: 1 416 946 2000

Email: [email protected]

Background: The COVID-19 pandemic exerted extraordinary pressure on health care workers (HCWs), imperiling their well-being and mental health. In response to the urgent demand to provide barrier-free support for the health care workforce, Pause-4-Providers implemented 30-minute live web-based drop-in mindfulness sessions for HCWs.

Objective: This study aims to evaluate the use, feasibility, satisfaction, and acceptability of a novel mindfulness program aimed at enhancing the well-being of HCWs during the COVID-19 pandemic.

Methods: Accrual for the study continued throughout the first 3 pandemic waves, and attendees of ≥1 session were invited to participate. The evaluation framework included descriptive characteristics, including participant demographics, resilience at work, and single-item burnout scores; feedback questionnaires on reasons attended, benefits, and satisfaction; qualitative interviews to further understand participant experience, satisfaction, benefits, enablers, and barriers; and the number of participants in each session summarized according to the pandemic wave.

Results: We collected descriptive statistics from 50 consenting HCWs. Approximately half of the participants (24/50, 48%) attended >1 session. The study participants were predominantly female individuals (40/50, 80%) and comprised physicians (17/50, 34%), nurses (9/50, 18%), and other HCWs (24/50, 48%), who were largely from Ontario (41/50, 82%). Of 50 attendees, 26 (52%) endorsed feeling burned out. The highest attendance was in May 2020 and January 2021, corresponding to the first and second pandemic waves. The participants endorsed high levels of satisfaction (43/47, 92%). The most cited reasons for attending the program were to relax (38/48, 79%), manage stress or anxiety (36/48, 75%), wish for loving kindness or self-compassion (30/48, 64%), learn mindfulness (30/48, 64%), and seek help with emotional reactivity (25/48, 53%). Qualitative interviews with 15 out of 50 (30%) participants identified positive personal and professional impacts. Personal impacts revealed that participation helped HCWs to relax, manage stress, care for themselves, sleep better, reduce isolation, and feel recognized. Professional impacts included having a toolbox of mindfulness techniques, using mindfulness moments, and being calmer at work. Some participants noted that they shared techniques with their colleagues. The reported barriers included participants’ needing time to prioritize themselves, fatigue, forgetting to apply skills on the job, and finding a private place to participate.

Conclusions: The Pause-4-Providers participants reported that the web-based groups were accessible; appreciated the format, content, and faculty; and had high levels of satisfaction with the program. Both novel format (eg, drop-in, live, web-based, anonymous, brief, and shared activity with other HCWs) and content (eg, themed mindfulness practices including micropractices, with workplace applications) were enablers to participation. This study of HCW support sessions was limited by the low number of consenting participants and the rolling enrollment project design; however, the findings suggest that a drop-in web-based mindfulness program has the potential to support the well-being of HCWs.

Introduction

The COVID-19 pandemic has jeopardized the mental health and well-being of health care workers (HCWs). Rapidly shifting public health guidelines have been implemented in response to the emergent scientific findings. The uncertain landscape of this pandemic has produced a sense of uncertainty, fear, and psychological distress in HCWs [ 1 ]. This was compounded by the realities HCWs faced, including inequitable access to rationed resources such as personal protective equipment and needed acute care beds [ 2 ]. Changes in procedural guidelines and service priorities, ramping down of nonessential services, and shifting standards of care have contributed to moral distress [ 3 - 5 ]. Risk factors for HCWs’ burnout included heavy workload, shifting roles, need for additional training, redeployment, and hybrid models of web-based care with feeling disconnected from their usual support and community of practice [ 6 , 7 ]. Greater COVID-19 exposure risks forced many HCWs into isolation owing to fears of infecting family members [ 1 , 8 , 9 ]. Early in the pandemic, significant levels of fatigue, insomnia, anxiety, depression, and psychological distress among HCWs were reported [ 8 , 10 - 15 ]. Informed by the literature on previous pandemics, it was anticipated that as the pandemic endured, moral distress, posttraumatic stress, and burnout would become problematic [ 16 ]. All combined, the COVID-19 pandemic amplified the challenges faced by HCWs within an already-strained workforce and was thus critically important to address [ 1 , 3 , 9 , 17 - 22 ].

Before the pandemic, evidence-based mindfulness interventions for HCWs were found to enhance stress management, awareness, emotion regulation, connection, self-compassion, empathy, and resilience [ 23 - 27 ]. Research demonstrates that mindfulness training for HCWs can improve well-being by promoting self-care and cultivating self-compassion [ 28 ]. The term “mindfulness” is defined as the “awareness that arises through paying attention, on purpose, in the present moment, and nonjudgmentally” and implies the cultivating of compassion [ 29 ]. Most interventions for HCWs evolved from manualized formats of mindfulness-based stress reduction, mindfulness-based cognitive therapy, and mindful self-compassion, which require a large time commitment [ 29 - 31 ].

“Pause-4-Providers” was created during the first wave of the COVID-19 pandemic to support HCWs and be accessible using a web-based drop-in platform. This extended the program’s reach to underserved areas and those in quarantine, with adherence to physical distancing requirements [ 17 , 21 , 32 - 34 ]. To establish a safe space for weary HCWs, no registration was required, and anonymity was allowed as we did not require participants to turn on their cameras or introduce or disclose information about themselves [ 35 ]. Unique to this program was the flexible curriculum, making it adaptable to the varied and changing needs of HCWs with time [ 36 ]. We implemented Pause-4-Providers drop-in sessions at the beginning of the COVID-19 pandemic to provide momentary refuge and respite from the intensity associated with working in health care during the pandemic.

The objective of this study was to evaluate the implementation of Pause-4-Providers, a 30-minute evening web-based drop-in mindfulness program for HCWs during the COVID-19 pandemic. We designed a descriptive and qualitative study to examine the feasibility, satisfaction, and experiences of the participants. The research questions for the descriptive study were as follows:

  • What is the feasibility and acceptability of the web-based drop-in mindfulness program?
  • What is the level of burnout and resilience among the consenting participants?

Research questions for the qualitative study included the following: What were the experiences, enablers, and barriers to participating in the Pause-4-Providers program?

Program Development and Format

Within the first weeks of the COVID-19 pandemic in Canada, our team of university-affiliated psychiatrists (ME, JH, DdCM, and OZ) with expertise in mindfulness met and collaboratively decided to offer free, 30-minute live web-based drop-in mindfulness sessions for HCWs with the objective of supporting their well-being. We defined HCWs as anyone working in a health care or social care setting, including those providing direct patient-facing services and those performing indirect roles. Along with health care providers and trainees, the sessions were open to those providing administrative facilities, those working in support services, and research staff. Our sessions used a secure, privacy-compliant Zoom (Zoom Video Communication, Inc) platform multiple times per week, starting on March 24, 2020. We e-blasted Pause-4-Providers program announcements to >400 health care institutions, hospitals, long-term care homes, shelters, university departments, and associations (eg, Ontario Medical Association, Royal College of Physicians and Surgeons of Canada, Canadian Mental Health Association, and Registered Practical Nurses Association of Ontario) for distribution of session links to their HCWs.

Our group of faculty facilitators had extensive mindfulness training and clinical experience in leading manualized mindfulness group interventions in health care settings for HCWs and patients in an oncology health setting (ME) [ 21 , 35 , 37 ], patients with pain disorders (OZ), women with mental health concerns (DdCM and JH), and hospital-based health leaders and policy makers (DdCM). As mental health professionals working in hospital settings, we were also attuned to the psychological impacts the unfolding public health crisis had on HCWs. Notably, because we used the term “facilitators” when referring to the faculty who led the web-based drop-in sessions, we chose to use the term “enablers” when referring to factors in the qualitative analysis that facilitated or promoted participation. The themed agenda for each drop-in session was based on mindfulness, compassion, or resiliency skills to fit the emerging needs of HCWs, distressing local and global events and the time of the year or holidays. An evolving curriculum allowed for flexibility and responsiveness to the changing needs of HCWs [ 36 ]. We canvassed attendees using a situational needs assessment with routine quick check-ins at the start of each session to tailor the agenda accordingly. Given the time pressures and competing demands placed on HCWs, the sessions were intentionally designed to be of short duration. Each 30-minute session followed a semistructured agenda as presented in Figure 1 and Multimedia Appendix 1 [ 27 , 28 , 38 , 39 ]. The session themes evolved to reflect the immediate needs of HCWs, with a curricular structure of the sessions that was maintained. This structure included 2 short practices, including a micropractice and a closing. Maintaining a consistent format, the sessions introduced different practices and themes that were aligned with the objectives and principles of mindfulness and self-compassion. In small doses, with time, during the prolonged pandemic, faculty facilitators introduced a wide variety of mindfulness practices based on HCW attendees’ needs and levels of emotions (eg, hyperarousal vs emotional numbing). Drawing from positive psychology and resilience factors [ 40 - 45 ], the faculty facilitators used mindfulness techniques to promote positive emotions, compassion, and coping in the midst of challenges. Sessions included at least 1 guided micropractice (ie, a practice that was distilled into ≤1 minute meant for integration by participants throughout their workday) to emphasize how participants could apply aspects of the practices for self-care moments in the workplace [ 35 , 44 , 46 , 47 ]. Many sessions concluded with poems, followed by invited reflections and feedback. To support the program, we also created a website for Pause-4-Providers, where HCWs could find the schedule and session links, and access 4 prerecorded mindfulness practices for use at any time and participate in the research study.

descriptive research design about mental health

Ethical Considerations

This study was approved by the Sinai Health Research Ethics Board (20-0158-E). On the project website, participants were given a complete description of the study, and informed consent was obtained. The research assistant emailed the respondents who consented to be contacted for participation in a semistructured interview and obtained consent before the start of the interview. Participation in the study was voluntary and anonymous. The interviews were transcribed and deidentified to protect the identity of the study participants. The participants did not receive any compensation.

Research Methods

This study aimed to evaluate the feasibility and acceptability of a web-based drop-in mindfulness program. We assessed feasibility quantitatively with attendance and qualitatively by exploring participants’ experiences of barriers and facilitators or enablers of attending such a program. We assessed acceptability using a brief satisfaction questionnaire and semistructured interviews with a subset of participants to explore their experiences of the program sessions. The burnout and resilience measures characterized the sample to learn about the potential suitability or appropriateness of the Pause-4-Providers program [ 48 ].

The study was open to all HCWs who attended ≥1 Pause-4-Providers session. Faculty facilitators informed HCW attendees in the sessions that they could visit the project website if they wished to participate or learn more about the research study. On the website, a banner informed HCWs of the research study with a link to a consent form and the confidential questionnaire package. Study participants could choose to participate in the descriptive portion of the study or both the descriptive and qualitative studies. The descriptive measures were collected once at study enrollment and included a questionnaire package consisting of demographics (eg, profession, age, sex, province or country of origin, and primary care setting), burnout and resilience measures, and a self-report feedback questionnaire focused on the participants’ reasons for attending, satisfaction, and utility of the sessions. At the end of the questionnaire, respondents could consent to be contacted for participation in a semistructured interview about their experiences of the program. There were no exclusion criteria for this study.

Descriptive Measures

The Single-Item Burnout Measure [ 49 ] instructed respondents to define burnout for themselves with the following question: “Overall, based on your definition of burnout, how would you rate your level of burnout?” Participants scored their responses on a 5-category ordinal scale. The self-defined burnout measure has been useful as an abbreviated burnout assessment tool in medical professionals [ 50 , 51 ]. The self-defined burnout item correlates with the emotional exhaustion subscale of the Maslach Burnout Inventory ( r =0.64; P <.001), defining burnout as a score of ≥3, with a correlation of 0.79, sensitivity of 83.2%, specificity of 87.4%, and an area under the curve of 0.93 (SE 0.004) [ 49 ].

The Resilience at Work Scale consists of 25 items measuring 7 aspects of workplace resilience, focusing on everyday behaviors. Participants rated their responses on a Likert scale, ranging from 0 (strongly disagree) to 6 (strongly agree) [ 52 ]. The scale is a validated tool for measuring and developing resilience among HCWs, with 67% of variance and an acceptable confirmatory factor analysis model fit (goodness of fit 0.97, Tucker-Lewis Index 0.98).

The Participant Self-Report Feedback Questionnaire was developed by us and asked about the number of sessions attended, reasons and motivation to attend (eg, to relax, improve sleep, be in a community, and learn mindfulness), benefits of attending (eg, increased awareness of emotional states, enhanced coping skills, and improved capacity to work with your team on a day-to-day basis), and overall satisfaction with the web-based mindfulness sessions. There were several open-text questions where respondents could describe how Pause-4-Providers influenced their coping (eg, positive or negative), describe the impact the pandemic had on their role and job, and provide feedback on the Pause-4-Providers program as presented in Multimedia Appendix 2 .

Qualitative Methodology

To explore the participants’ experiences and views of the Pause-4-Providers program, we used a qualitative research design, which does not test or generate theory but instead gathers explicit insight into clinical or behavioral interventions [ 53 , 54 ]. Qualitative methods are able to gather detailed insights into what does and does not work well to reveal the impacts, enablers, and barriers of program participation [ 55 ]. This is widely used in health service research to evaluate the determinants and impacts of interventions. The study complied with the standards for reporting qualitative research in accordance with COREQ (Consolidated Criteria for Reporting Qualitative Research) [ 54 ]. All participants consented before the interviews. There was no prior relationship between the qualitative researcher (Anna R Gagliardi) and the participants.

Sampling and Recruitment

At the end of the web-based questionnaire, respondents were asked if they were willing to be contacted for subsequent participation in an interview. Using a convenience sampling technique, all interested participants were emailed and invited to be interviewed by the research assistant (CK). The study and recruitment continued until June 2021, coinciding with the first 3 waves of the COVID-19 pandemic as defined by Public Health Ontario and presented in Multimedia Appendix 3 . We sampled across 3 time frames corresponding to waves 1, 2, and 3 of the COVID-19 pandemic in Canada, with equal numbers of participants in each wave. We sampled concurrently with data collection and qualitative analysis and ceased when thematic saturation was achieved.

Data Collection

The audio-recorded (17-38 min), telephone-based, transcribed interviews conducted by the research assistant (CK) included questions about expectations, impacts, enablers, barriers, and recommendations to improve the program ( Multimedia Appendix 4 ). Participants were asked about their motivation to attend the program, their experience of the program sessions, associated benefits or challenges, and feedback or suggestions for the future. Interview transcripts were independently analyzed by Anna R Gagliardi (a PhD-trained consultant with expertise in qualitative research), following which the findings were reviewed by all members of the research team.

Data Analysis

Descriptive analysis.

The total weekly attendees at drop-in sessions were tallied from April 20, 2020, to June 21, 2021, as shown in Multimedia Appendix 3 ; a single participant would count multiple times in these tallies if multiple sessions were attended. These totals were plotted against time, with the ends of the first 3 pandemic waves on August 14, 2020; April 1, 2021; and July 6, 2021, respectively. The remaining analyses pertained only to survey respondents. Counts and percentages were used to summarize their demographic characteristics. Responses to questions on burnout, motivation, and experience were summarized, and the motivation and experience scales were collapsed into 3 levels (ie, very much [significantly or definitely], somewhat, and not at all or a bit). The 7 Resilience at Work subscale scores and the total score were each calculated according to the scoring guide, a 2-tailed t test was used to compare the mean overall score to that from a study on the psychological impact of COVID-19 on >500 hospital workers by Maunder et al [ 56 ] (email, August 13, 2021), and a 95% CI for the mean difference in overall scores was calculated. The relationship between the number of sessions attended (1 vs ≥2) and respondents’ feedback on the benefits of attending was assessed by cross-tabulating the 2 variables and calculating the P value using a Fisher exact test. Participants with a missing value for a variable were omitted from the analyses of that variable.

Qualitative Analysis

We used content analysis to identify themes for inductive coding in the qualitative interviews. This was done through constant comparison to develop a preliminary codebook of themes and exemplar quotes (first-level coding) [ 53 ]. We shared themes for discussion with all members of the research team to verify them. For subsequent interview transcripts, the qualitative expert researcher (Anna R Gagliardi) performed coding to expand or merge themes (second-level coding), tabulated participant characteristics and data (eg, themes and quotes), and examined similarities or differences by participant sampling characteristics. The research team reviewed and discussed the findings and further grouped them into categories related to motivation and facilitators, which we refer to as enablers, barriers, and impacts associated with participation. The qualitative findings were triangulated using descriptive findings.

Descriptive Results

Between April 20, 2020, and June 27, 2021, there were 1333 attendance entries at the drop-in sessions. Consent was obtained from 88 respondents, most of whom (66/88, 75%) were enrolled during the second wave of the pandemic. Of 88 respondents, we excluded 38 (43%) from the analysis because they did not submit the questionnaire, were not HCWs, or completed the questionnaire a second time to arrive at a total sample of 50 (57%) participants, as presented in Figure 2 . At the time of survey completion, 50% (25/50) had attended 1 session, 24% (12/50) 2 to 5 sessions, 8% (4/50) 6 to 10 sessions, and 16% (8/50) ≥11 sessions. If the participants indicated at the start of the questionnaire that they were completing it a second time, they were automatically taken to the end of the survey and only their first set of responses was included in the analysis.

descriptive research design about mental health

Of 88 participants, the demographics were similar between the 50 (57%) included and 38 (43%) excluded participants. There were 5 sections in the survey on motivation, experience, satisfaction, burnout, and resilience. Overall, 90% (45/50) of the participants filled out all 5 sections, 10% (5/50) did not report on their prior experiences with mindfulness, and 6% (3/50) did not report on satisfaction. Of the 50 participants who submitted the survey, not all items or sections of the survey were completed. We included participants in the analysis if they provided data on ≥1 section of the questions we examined. Of the 50 HCWs, 24 (48%) had participated in >1 session; 17 (34%) were physicians, 9 (18%) were nurses, and the remaining 24 (48%) were other HCWs (eg, administrative or education assistant, occupational therapist, pharmacist, physiotherapist, psychotherapist, social worker, and others). Most respondents (40/50, 80%) were female individuals, 43% (21/50) were aged 20 to 39 years, 45% (22/50) 40 to 59 years, and 12% (6/50) >60 years, with participation primarily from the province of Ontario (41/50, 82%) and other Canadian provinces (eg, Alberta, British Columbia, New Brunswick, Quebec, and Saskatchewan).

Half of the HCWs (26/50, 52%) endorsed feeling burned out (score ≥3). Regarding Resilience at Work scores, participants scored highly (mean score >70) on the subscales of "finding your calling" (mean score 78, SD 17), "building networks" (mean score 78, SD 17), "living authentically" (mean score 76, SD 12), and "interacting cooperatively" (mean score 75, SD 15). Participants also scored moderately (mean score 50-69) on the workplace resilience subscale items of “staying healthy” (mean score 73, SD 22) and “managing stress” (mean score 65, SD 19) and reported difficulty with the subscale item “maintaining perspective” (mean score 48, SD 17). The overall mean resilience score was 69.4 (SD 12.6) [ 56 ].

In the self-report feedback questionnaire, participants’ most frequently reported motivations to attend the program included relaxing, managing stress or anxiety, wishing for loving kindness or self-compassion, and learning mindfulness, as presented in Table 1 .

The most frequently endorsed benefits of attending included increased self-awareness of emotional states and reduced stress, as presented in Table 2 . Participants who attended ≥2 sessions reported more positive benefits with coping skills (Fisher exact test P <.001) and managing stress (Fisher exact test P =.008) than participants who only attended 1 session. Of the 47 participants who reported their overall program satisfaction, 92% (43/47) rated it with a score of ≥4 on a 5-point Likert scale, with a mean score of 4.6 (SD 0.7).

Qualitative Results

Participants.

A total of 21 participants agreed to be contacted for participation in an interview and received a standardized invitation letter via email. Qualitative interviews were conducted with 15 consenting participants who answered the email and agreed to be interviewed, including 5 physicians, 2 administrative assistants, 2 physiotherapists, 2 psychotherapists, and 1 each of nurse practitioner, social worker, executive manager, and a speech pathologist. By age, this included 9 (60%) persons aged between 40 and 59 years and 6 (40%) 20 and 39 years. A considerable number of qualitative study respondents were women (13/15, 87%) than men, reflecting the fact that, out of 15 participants, 40 (80%) women and 7 (14%) men completed the descriptive questionnaire. Participants were evenly divided in terms of when they were interviewed during the COVID-19 pandemic: 5 (33%) in the first wave, 5 (33%) in the second wave, and 5 (33%) in the third wave. Interview participants completed a mean of 7 sessions (median 10, range 1 to 11) at the time of completing the questionnaire. Most participants had some prior exposure to mindfulness (11/15, 73%).

Themes, experiences, enablers, and barriers to participation were related to respondents’ motivation, satisfaction, impact, and program design. Qualitative findings are described with select quotes and summarized below. Where participants’ quotes are used, we have specified their study number, role, age, number of sessions attended, whether they had applied the mindfulness skills taught, and the pandemic wave during which they were interviewed. A summary of findings is presented in Figure 3 and all data are included in Multimedia Appendix 5 .

descriptive research design about mental health

Motivation to Attend and Expectations

A variety of reasons motivated the participants to take part in the program. Most were looking for ways to relax and manage their stress:

Trying to help deal with the COVID and all the stress behind it. Dealing with the patients and their anxiety with it. I was kind of trying to be more relaxed. [#02 administrative assistant, aged 40-59 years, ≤5 sessions, applied learning, techniques, or tools in daily life, wave 1]

Some participants wanted to decrease their sense of isolation created by the pandemic and have a way to connect with other HCWs:

I had been looking all over the place just for some kind of event or experience or connection of some kind for healthcare staff, healthcare teams because I felt really isolated. [#46 psychotherapist, aged 20-39 years, ≤5 sessions, applied learning, techniques, or tools in daily life, wave 2]

Others said that they were curious about mindfulness, had been exposed to it in the past, saw this as an opportunity to pick it up again, and desired to gather with others and be a role model to encourage other staff to participate:

I am in a leadership position at the hospital and it was passed on to me as something that we could share with our staff. I wanted to encourage them to take it so I thought I should take it myself. [#14 manager, aged 40-59 years, ≤5 sessions, not applied learning, techniques, or tools in daily life, wave 1]

When asked about expectations, participants largely said that they had none and came with an open mind. Several participants anticipated that it was likely to be beneficial but did not specify how:

I didn’t honestly think about it that much other than I know, at least on some level, that mindfulness practice would be good for me, that just by showing up it would be a positive thing. [#10, physiotherapist, aged 20-39 years, 6-10 sessions, applied learning, techniques, or tools in daily life, wave 1]
Feeling quite unmotivated, just finding things at work difficult for the winter and the early part of spring, so it wasn’t necessarily fatigue, it was more feeling a bit overwhelmed with work. [#75, physician, aged 40-59 years, 6-10 sessions, applied learning, techniques, or tools in daily life, wave 3]

Satisfaction

All participants said that the sessions were helpful, and some said that they surpassed their expectations and felt it was essential for getting through the pandemic:

It was more than what I expected. I thought I would try, to help out with the burnout and with the pandemic. But it was a lot more relaxing than I thought it would be. I was able to get into a really deeply relaxed state. [#22, psychotherapist, aged 20-39 years, ≤5 sessions, applied learning, techniques, or tools in daily life, wave 2]
In order to keep working and go on in my life, it’s been one of the very important things for me. [#35, physician, aged 40-59 years, applied learning, techniques, or tools in daily life, wave 3, did not indicate the number of sessions they attended]

When asked to rate the importance of the program to them on a scale from 1 to 10, in which 10 was very important, most participants articulated a moderately high score (mean 7.7, SD 1.48; median 8.0, range 5.0-10.0). Some participants commented on how this program was one of the several resources or supports, such as family, and that they were new to the program and could not yet fully appreciate how important the sessions may be:

I needed multiple things to help me through this time and so it was very important to me to have that regular time twice a week, where I would check-in and do these techniques to make sense of what’s going on, being able to deal with the difficult situation. In order to keep working and go on in my life, it’s been one of the very important things for me. [#35, physician, aged 40-59 years, applied learning, techniques, or tools in daily life, wave 3, did not indicate the number of sessions they attended; level of importance in life: score=10]
I’ve barely scratched the surface... it’s the beginning of a learning. I’m hoping that if and when it ends, I will be able to continue this. A 10 out of 10 would be a sort of life-changing, I don’t think it’s life-changing. I would call it life-enhancing. [#78, physician, aged 40-59 years, >11 sessions, applied learning, techniques, or tools in daily life, wave 3; level of importance in life: score=8]
I can’t say yet. I think I’m still pretty new. I’ve only done two sessions. Yes and no. In the sense that I think it’s nice to have that put in to your schedule a little bit but I can’t say that it’s translated into anything else in my life yet. [#44, physician, aged 40-59 years, ≤5 sessions, not applied learning, techniques, or tools in daily life, wave 2; level of importance in life: score=5]

The participants articulated the numerous positive benefits of the mindfulness program. Most participants said that it prompted them to disconnect from work responsibilities and take time for self-care. As a result, they were able to unwind and relax at the end of the day and sleep better:

It helps me to realize it’s not all about going, going, going and bringing home your work and thinking about it 24/7. I think it’s a good way to almost detach a little bit from that stuff. [#44, physician, aged 40-59 years, ≤5 sessions, not applied learning, techniques, or tools in daily life, wave 2]
It’s definitely easier to get into that relaxed state to go to sleep... I definitely feel more relaxed those nights when we have the session. [#22, psychotherapist, aged 20-39 years, ≤5 sessions, applied learning, techniques, or tools in daily life, wave 2]

Most participants said that participation in the program helped them to be more present and calm and to better manage stress or anxiety. Many participants applied mindfulness techniques in their daily lives, including at work:

Being present, being consistent and calm when you are working in very high stress environments...I did try that out when I was at work, and especially when you’re feeling overwhelmed or just tired. And so, I think just being able to use those skills can help you think more clearly, tackle things in a calmer manner. [#01, physician, aged 20-39 years, >11 sessions, applied learning, techniques, or tools in daily life, wave 1]
I’m much more productive with my time...and when you start to get more things done you don’t stress as much about it. It’s still pretty intense and it’s been a year and half...it just made me more level and able to work. [#78, physician, aged 40-59 years, >11 sessions, applied learning, techniques, or tools in daily life, wave 3]
I found it a very useful tool to use, in my personal toolbox, to help me be more grounded, to be more productive and actually slow down and listen to others. [#78, physician, aged 40-59 years, >11 sessions, applied learning, techniques, or tools in daily life, wave 3]

Engaging in a shared activity with other HCWs reduced feelings of isolation and loneliness, with gratitude for acknowledging HCWs as those who needed help to combat the undue stress of the pandemic:

I didn’t know any of the other people but you still kind of felt, even if you don’t know them everyone is facing similar challenges and probably having similar worries. That was nice to sit together. [#01, physician, aged 20-39 years, ≤5 sessions, applied learning, techniques, or tools in daily life, wave 2]
It’s really comforting to see the same people coming, even if I don’t see them, sometimes I see their comments...I always like the idea of a community so feeling included or part of the group, where I’m not lost in a big system, so that helps. [#35, physician, aged 40-59 years, applied learning, techniques, or tools in daily life, wave 3, did not indicate the number of sessions they attended]

A few participants mentioned additional positive impacts, such as sharing mindfulness techniques with patients whom they thought might benefit.

When asked about the program design and format, participants appreciated the web-based, drop-in nature requiring no advance registration, the flow and variety of activities during each session, and the interactive components. Participants also appreciated the soothing voices, reassurances and reminders offered by faculty facilitators, the timing of the evening sessions, and the short 30-minute session length:

I love that it’s drop-in, you don’t have to register or sign up or make a plan. [#04, nurse practitioner, aged 20-39 years, 6-10 sessions, applied learning, techniques, or tools in daily life, wave 1]
I joined a couple sessions where it seemed to flow really nicely. I thought that there was kind of an initial activity and then a little interlude moment and then a second activity. [#04, nurse practitioner, aged 20-39 years, 6-10 sessions, applied learning, techniques, or tools in daily life, wave 1]
I really also enjoyed that there was a little bit of dialogue at the end, and I thought that was so nice for other people to share their comments, to be able to share mine. [#14, manager, aged 40-59 years, ≤5 sessions, not applied learning, techniques, or tools in daily life, wave 1]

Furthermore, the participants noted specific aspects of the content they found helpful. In most cases, this referred to mindfulness exercises or techniques, for example, breathing exercises or body scans. In other cases, this referred to a concept, such as the need for self-care:

Self-compassion practices are probably the ones that stick out most. [#10, physiotherapist, aged 20-39 years, 6-10 sessions, applied learning, techniques, or tools in daily life, wave 1]
The whole practice was around being kind to yourself and kind to others even though we may differ in our opinions or views etcetera. [...] And that was really impactful given the social-political state the world is in right now, so much divide and social injustice and political divide. It was really refreshing to talk about community and generosity and focus on that, when we’re bombarded everyday with the news and tv about what’s different about us right now. [#22, psychotherapist, aged 20-39 years, ≤5 sessions, applied learning, techniques, or tools in daily life, wave 2]
My personality is that I always helped other people, family. That’s me. That’s my job and that’s also my personality. I always put everybody in front of me instead of taking care of myself. Which I think I do have to change a little bit as I am getting older [...] if I am forced to get into a place where I am the center and not everybody else but just me only, I think that would help me tremendously. [#48, physiotherapist, aged 20-39 years, ≤5 sessions, not applied learning, techniques, or tools in daily life, wave 2]

Participants noted multiple factors that enabled or challenged participation in Pause-4-Providers and the application of mindfulness outside the scheduled sessions.

These included a well-designed website and facilitated, web-based drop-in sessions. Although most participants appreciated the group nature of the sessions, they also valued their anonymity:

It’s convenient because it’s online, you don’t have to go somewhere, you can just Zoom in. It’s hard to get myself going somewhere to an actual place, but it is good to be with people. You kind of feel like you are with them, even if you don’t see them, so for me, the virtual format was perfect. [#35, physician, aged 40-59 years, applied learning, techniques, or tools in daily life, wave 3, did not indicate the number of sessions they attended]
I think that’s a really powerful aspect of the program that invites more people to attend because you can change your screen name and be anonymous, so I thought that was cool. I think that anonymity aspect is really important so that everybody can just feel safe to access support and not have to reveal their identity from fear of judgement from coworkers. [#76, administrative assistant, aged 20-39 years, ≤5 sessions, applied learning, techniques, or tools in daily life, wave 3]

Enablers to adopt or use mindfulness included faculty facilitators giving advice and examples on how to integrate practice into daily life, demonstrating techniques that were easy to adopt, and offering self-directed resources on the website to enable practice outside the sessions:

The way the facilitators are able to link the practices to real, realistic, day-to-day moments where the skills might come in handy [...] the suggestions, gentle reminders of where these skills can be useful in daily life. [#10, physiotherapist, aged 20-39 years, 6-10 sessions, applied learning, techniques, or tools in daily life, wave 1]
Even throughout the day I think of some of the exercises. I’m seeing that start to change in a positive way. I’m taking a break from work at my desk, I stand up and I’ll take a moment with the practices in mind. [#46, psychotherapist, aged 20-39 years, ≤5 sessions, applied learning, techniques, or tools in daily life, wave 2]

Barriers to participation included competing demands that made it difficult to be a priority, being tired and feeling easily distracted, difficulty finding a quiet and private space at home, internet connection issues, and being seen by others in a susceptible state:

I guess the time of day. Although it is very convenient for me to attend, I do have to make a choice to do. Either I fit in time with my husband, or I prep for tomorrow or clean up. It’s a choice. You have to make a choice to go cause there’s always something else that you could be doing. [#04, nurse practitioner, aged <40 years, 6-10 sessions, applied learning, techniques, or tools in daily life, wave 1]
Finding a quiet space in the house. I have to be really intentional about that part of things. I really need to set that up. [they compare to in-person] But now, even if I get in the room, even if I close the door and set it up, there’s still this possibility of other sounds in the house or somebody coming in. I think that’s a barrier to full participation, a distraction. [#46, psychotherapist, aged <40 years, ≤5 sessions, applied learning, techniques, or tools in daily life, wave 2]

Some of the participants expressed a concern about appearing susceptible:

The one thing did cross my mind, this is a time I was hoping to be in my pajamas, wash my face, maybe lying down, and I wondered am I going to have to be on camera? I don’t want other people to see me in this kind of vulnerable state but that was quickly cleared up at the beginning of the Zoom call. [#22, psychotherapist, aged <40 years, ≤5 sessions, applied learning, techniques, or tools in daily life, wave 2]

Barriers to adopting, applying, or using mindfulness outside of the sessions included forgetting or feeling unable to invoke learned skills and finding a quiet place at work to practice mindfulness:

It hasn’t been something that I have been trained to do so it takes a lot more effort and add-on to implement these new learned behaviors. [#22, psychotherapist, aged <40 years, ≤5 sessions, applied learning, techniques, or tools in daily life, wave 2]

Participants variably preferred some practices over others, with none of the different practices being universally favored or disliked by the respondents. Participants offered 2 suggestions for promoting and supporting the adoption of mindfulness: offering quiet spaces at work and providing or referring participants to other resources that support mindfulness practice. The sessions were open to all HCWs, and some saw this as a barrier to feeling comfortable, with several participants offering the opinion that to create a safe space, consideration should be given to restricting the sessions to licensed clinical health care providers:

If one of the goals of the intervention was more engagement or discussion, or people sharing their stories, keeping it to the regulated professionals might have been more of a safe space, I guess. Not knowing who was on the call. I think at times kind of kept me from speaking up or asking questions or participating in discussions or feedback. Whereas, if it was just my peers, then it may have felt more of a safer space to talk. [#04, nurse practitioner, aged 20-39 years, 6-10 sessions, applied learning, techniques, or tools in daily life, wave 1]

Principal Findings

The strain placed on HCWs was evident from the start of the COVID-19 pandemic and persisted as the pandemic endured. This newly conceived well-being support program, Pause-4-Providers, consisted of synchronous, web-based, brief, drop-in mindfulness sessions for HCWs. It was feasible to implement as evidenced by its rapid deployment early in the first phase of the pandemic, with good use and continued session attendance during the first 3 waves of the pandemic (total attendance=1333). This program reached a wide range of HCWs, including physicians, a group typically more reluctant to attend well-being sessions, and more so during the pandemic [ 57 ]. It was acceptable to participants, with a large majority endorsing overall satisfaction of 5 out of 5 (32/47, 68%) and 4 out of 5 (11/47, 23%).

The Pause-4-Providers program was intentionally planned for implementation for HCWs with competing demands, time pressures, and exhaustion during the COVID-19 pandemic. Participants corroborated that they valued the program content and format that did not require registration, took place on the internet in the evening, was a drop-in session, and was of short duration (30 min) with the option of anonymity (eg, cameras could be switched off). The nonprescriptive nature of drop-in sessions allowed participants the choice to attend any number of sessions, unlike other structured mindfulness programs. Consistent with mindfulness literature, we observed a potential dose effect [ 31 ]. Participants who attended ≥2 sessions reported more positive benefits in coping skills ( P <.001) and reduced perceived stress ( P =.008).

Half of the participants attending Pause-4-Providers had moderate to high levels of burnout, as measured by the Single-Item Burnout Measure (26/50, 52%), similar to what others had during the COVID-19 pandemic [ 56 ]. This highlights the fact that some participants were in need of well-being interventions. In other words, some may have been motivated to alleviate burnout symptoms, while others sought to cultivate their well-being. We observed that resilience and burnout coexisted in this sample of HCWs during the COVID-19 pandemic.

The Pause-4-Providers study participants scored moderately high overall on the Resilience at Work Scale, with high subscale scores of “building networks, interacting cooperatively, finding your calling, and living authentically.” This may reflect HCWs’ need to pull together teams, with a shared purpose and a “calling”—resiliency factors that are essential during a pandemic. There is no ceiling on resilience, which can continue to grow. However, participants endorsed difficulty with the “maintaining perspective” subscale, scoring 48.1 (difficulty <50). This subscale represents an ability for flexible thinking and optimism. The pandemic has challenged HCWs to be adaptable and maintain positivity. The use of mindfulness training can help stressed individuals maintain perspective and shift from primitive survival stress responses (eg, fight, flight, freeze, or fold) to adaptive coping with mindful and reflective problem solving skills. The participants scored moderately on the subscale of “managing stress” aligned with their endorsed reasons for taking the course to relax and manage stress or anxiety. This is consistent with areas that mindfulness sessions can address by helping individuals to keep calm and reduce perceived stress [ 23 , 24 , 29 - 31 ]. These findings on the Resilience at Work measure were similar to those in a study by Maunder et al [ 56 ] with Canadian HCWs that evaluated the psychological impact of COVID-19.

The reported benefits of the program in the qualitative study included being better able to disconnect and decompress after work, seeing a need to prioritize self-care, and an improved ability to manage stress at work. This aligned with the survey findings of increased self-awareness of emotional states (25/45, 56%) and reduced stress (24/45, 53%). By providing a toolbox of mindfulness strategies and skills, participants were empowered to be calmer and more present. Brief mindfulness micropractices provided a potential mechanism for HCWs to navigate stressful and demanding workplace environments, as demonstrated in previous work done by one of the authors (ME) [ 13 , 35 , 36 ]. The themed agendas of each session focused on workplace applications of mindfulness practices. Respondents described how the particular use of micropractices allowed them to be more present, calmer, and more balanced at work. Some participants shared these mindfulness tools with their coworkers and patients. Participants also valued the faculty facilitators’ encouragement, tips, and examples of ways to use practices in the workplace, on the go.

Many participants did not turn on their cameras, although many did offer their thoughts and feedback (often gratitude) in the chat at the end of each session. Without their cameras turned on and in their homes in the evenings, the participants reported feeling less susceptible and more relaxed. Despite the anonymity of participation, the attendees endorsed a decreased sense of isolation in the context of the pandemic and felt connected to the group. We speculate that the combination of the live format, the commonality of being with HCWs during the pandemic, and the shared experience of practicing self-care in a group setting was sufficient to promote a sense of connection. This is similar to other mindfulness skills–based groups in which participants do not talk about their life experiences and yet endorse an increased sense of connectedness [ 37 ].

The use of an evolving curriculum allowed the team of faculty facilitators to perform practical ongoing needs assessment by checking in with attendees at the start of each session and flexibly adapting the session in response to the relevant needs of the attendees [ 36 ]. This was important as HCWs’ needs changed with the course of the pandemic. In the first wave, HCWs were frightened and needed to find ways to cope with uncertainty and change, whereas, with time, participants shared experiences of moral distress, exhaustion, and elements of posttraumatic stress [ 6 , 22 ]. The faculty facilitators could garner an iterative understanding of challenges and burnout factors with time as mental health experts, mindfulness specialists, and HCWs.

Limitations

We largely relied on a top-down approach to invite HCWs to Pause-4-Providers sessions, contacting leadership in a wide array of institutions and health care settings. This dissemination strategy included outreach to interprofessional stakeholder organizations at the provincial, university, and hospital health care system levels. We did not track how or if they disseminated the information, and we did not have a consistent strategy to follow up with these organizations. Although this session recruitment strategy supported an expedient deployment strategy, it may have affected attendee recruitment.

Prioritizing anonymity and open access to drop-in web-based sessions with no required registration meant that we were not able to provide attendance reminders and relied on participant engagement and institutions to notify and remind potential attendees. This likely limited session attendance, retention, and study recruitment. Nonetheless, the study design was pragmatic for the drop-in nature of the program, with rolling recruitment during the first 3 waves of the pandemic. Approximately half (24/50, 48%) of the participants attended >2 sessions at the time of survey completion. Participants’ reports on resilience and burnout could have been affected by how many sessions they had attended before study enrollment and how far into the pandemic they started to attend sessions. We do not know if the consenting study participants were representative of the entire Pause-4-Providers attendee population or the HCWs’ population at large, limiting generalizability.

When the program was developed, we did not expect the pandemic to endure and have multiple waves. Attendance in the program was well distributed across the first 3 waves of the pandemic, and survey responses were concentrated between the end of wave 1 and the end of wave 2. It is possible that HCWs became more accustomed to the COVID-19 pandemic, with reduced stress and improved coping with time. Alternatively, the cumulative effect of the pandemic may have adversely affected the well-being of HCWs (eg, with increased levels of moral distress). The sample size was too small to determine how the motivations, benefits, satisfaction, and experiences of the participants may have differed across time points. Consistent with qualitative research standards, saturation of the findings was identified, and our sample size was consistent with the qualitative methodology [ 55 , 58 ].

It is unknown how representative the 50 study HCW participants were in relation to the larger sample of all attendees. The demographics did not include data on race, ethnicity, or intersectional identity, nor did they distinguish between work practice settings (eg, intensive care unit vs outpatient clinics) or whether HCWs were in COVID-19 patient-facing practice settings. Any of these factors could have affected or moderated the findings on burnout, workplace resilience, and pandemic-related stresses. The faculty facilitators in this project were White women psychiatrists. Future iterations of this program would benefit from a more culturally diverse and larger group of interprofessional faculty facilitators and participants. With respect to generalizability, qualitative findings were obtained from participants in the province of Ontario, Canada, and thus may not represent other health settings in other locations. Nurses represent approximately half of the health care workforce in Canada, and yet only 18% of the study participants were nurses. This low level of nurse participation may have been because of long, 12-hour shifts and competing priorities, such as family or childcare during the pandemic. This may also be related to free alternative support provided through their professional organizations (eg, individual psychotherapy) [ 6 ].

The format of live web-based mindfulness sessions is resource intensive as it relies on faculty facilitators; therefore, it may not be sustainable without funding or a dedicated team. Early in the COVID-19 pandemic, with heightened uncertainty and major changes in health care, faculty facilitated 8 evening sessions per week. As the pandemic continued, to reduce the burden on the faculty facilitators, the frequency of sessions was decreased to once a week.

Conclusions

This descriptive, qualitative study and program evaluation demonstrated that the Pause-4-Providers program was feasible, acceptable, and appropriate, with high levels of satisfaction. Half of the participants endorsed moderate to high burnout, which may have motivated their attendance. Most participants endorsed positive benefits enabled by the curriculum, the faculty facilitators and the drop-in, low-dose, open-access format of the program. Importantly, participants reported feeling more relaxed after the sessions and using mindfulness tools at work and in their daily lives.

As Dana Faulds, an American poet, writes, “It only takes a reminder to breathe, a moment to be still, and just like that, something in me settles, softens, makes space for imperfection...I can make the choice to stop, to breathe, and be, and walk slowly into the mystery” [ 38 ]. The Pause-4-Providers program reminded HCWs to breathe, create space to be still, reflect on mindful self-compassion, and use microskills in the workplace and at home. To address the unprecedented negative psychological effects and burnout during the COVID-19 pandemic and support the well-being of HCWs beyond the pandemic, this program of brief web-based drop-in mindfulness merits further study.

Acknowledgments

The Pause-4-Providers program was supported by the Innovation Fund of the Alternative Funding Plan for the Academic Health Sciences Centres of Ontario. The authors gratefully acknowledge the Sinai Health System, University Health Network, Women’s College Hospital and University of Toronto, Department of Psychiatry, the Lunenfeld-Tanenbaum Research Institute, and Drs Jon Hunter and Robert Maunder for their mentorship; the Ontario Medical Association; and the contributions of Anna Gagliardi for the qualitative analysis, George Tomlinson and Fuzo Yosh for descriptive analyses in this study, and Natalie Heeney for the design of study figures.

Data Availability

The data sets generated and analyzed during this study are not publicly available because participants’ approval for public data sharing was not explicitly requested in the consent form approved by the research ethics board.

Conflicts of Interest

None declared.

Definitions of mindfulness concepts.

Pause-4-Providers questionnaire package.

Weekly number of attendees during the first 3 waves of the COVID-19 pandemic.

Pause-4-Providers qualitative interview guide.

Themes and exemplar quotes on motivation, expectations, design, and impact.

  • Shanafelt T, Ripp J, Trockel M. Understanding and addressing sources of anxiety among health care professionals during the COVID-19 pandemic. JAMA. Jun 02, 2020;323(21):2133-2134. [ CrossRef ] [ Medline ]
  • Wilbiks JM, Best LA, Law MA, Roach SP. Evaluating the mental health and well-being of Canadian healthcare workers during the COVID-19 outbreak. Healthc Manage Forum. Jul 08, 2021;34(4):205-210. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Greenberg N, Docherty M, Gnanapragasam S, Wessely S. Managing mental health challenges faced by healthcare workers during covid-19 pandemic. BMJ. Mar 26, 2020;368:m1211. [ CrossRef ] [ Medline ]
  • Smallwood N, Pascoe A, Karimi L, Willis K. Moral distress and perceived community views are associated with mental health symptoms in frontline health workers during the COVID-19 pandemic. Int J Environ Res Public Health. Aug 18, 2021;18(16):8723. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Lamb D, Gnanapragasam S, Greenberg N, Bhundia R, Carr E, Hotopf M, et al. Psychosocial impact of the COVID-19 pandemic on 4378 UK healthcare workers and ancillary staff: initial baseline data from a cohort study collected during the first wave of the pandemic. Occup Environ Med. Nov 28, 2021;78(11):801-808. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Maunder RG, Heeney ND, Kiss A, Hunter JJ, Jeffs LP, Ginty L, et al. Psychological impact of the COVID-19 pandemic on hospital workers over time: relationship to occupational role, living with children and elders, and modifiable factors. Gen Hosp Psychiatry. Jul 2021;71:88-94. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Physician burnout nearly doubles during pandemic. PR Newswire. Mar 23, 2022. URL: https://www.proquest.com/docview/2641763114?sourcetype=Wire%20Feeds [accessed 2024-02-28]
  • Pappa S, Ntella V, Giannakas T, Giannakoulis VG, Papoutsi E, Katsaounou P. Prevalence of depression, anxiety, and insomnia among healthcare workers during the COVID-19 pandemic: a systematic review and meta-analysis. Brain Behav Immun. Aug 2020;88:901-907. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Berkhout SG, Sheehan KA, Abbey SE. Individual- and institutional-level concerns of health care workers in Canada during the COVID-19 pandemic: a qualitative analysis. JAMA Netw Open. Jul 01, 2021;4(7):e2118425. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Trumello C, Bramanti SM, Ballarotto G, Candelori C, Cerniglia L, Cimino S, et al. Psychological adjustment of healthcare workers in Italy during the COVID-19 pandemic: differences in stress, anxiety, depression, burnout, secondary trauma, and compassion satisfaction between frontline and non-frontline professionals. Int J Environ Res Public Health. Nov 12, 2020;17(22):8358. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Gainer DM, Nahhas RW, Bhatt NV, Merrill A, McCormack J. Association between proportion of workday treating COVID-19 and depression, anxiety, and PTSD outcomes in US physicians. J Occup Environ Med. Feb 01, 2021;63(2):89-97. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Kang L, Ma S, Chen M, Yang J, Wang Y, Li R, et al. Impact on mental health and perceptions of psychological care among medical and nursing staff in Wuhan during the 2019 novel coronavirus disease outbreak: a cross-sectional study. Brain Behav Immun. Jul 2020;87:11-17. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Evanoff BA, Strickland JR, Dale AM, Hayibor L, Page E, Duncan JG, et al. Work-related and personal factors associated with mental well-being during the COVID-19 response: survey of health care and other workers. J Med Internet Res. Aug 25, 2020;22(8):e21366. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Lixia W, Xiaoming X, Lei S, Su H, Wo W, Xin F, et al. A cross-sectional study of the psychological status of 33,706 hospital workers at the late stage of the COVID-19 outbreak. J Affect Disord. Jan 15, 2022;297:156-168. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Greenberg N, Weston D, Hall C, Caulfield T, Williamson V, Fong K. Mental health of staff working in intensive care during Covid-19. Occup Med (Lond). Apr 09, 2021;71(2):62-67. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Maunder RG, Leszcz M, Savage D, Adam MA, Peladeau N, Romano D, et al. Applying the lessons of SARS to pandemic influenza. Can J Public Health. Nov 1, 2008;99(6):486-488. [ CrossRef ]
  • Rosen B, Preisman M, Read H, Chaukos D, Greenberg RA, Jeffs L, et al. Resilience coaching for healthcare workers: experiences of receiving collegial support during the COVID-19 pandemic. Gen Hosp Psychiatry. Mar 2022;75:83-87. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Wallace JE, Lemaire JB, Ghali WA. Physician wellness: a missing quality indicator. Lancet. Nov 14, 2009;374(9702):1714-1721. [ CrossRef ] [ Medline ]
  • Walton M, Murray E, Christian MD. Mental health care for medical staff and affiliated healthcare workers during the COVID-19 pandemic. Eur Heart J Acute Cardiovasc Care. Apr 28, 2020;9(3):241-247. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Gajjar J, Pullen N, Laxer D, Wright J. Healing the healers: system-level solutions to physician burnout recommendations of the Ontario Medical Association burnout task force. Ontario Medical Association. Aug 18, 2021. URL: https:/​/www.​oma.org/​uploadedfiles/​oma/​media/​pagetree/​advocacy/​health-policy-recommendations/​burnout-paper.​pdf [accessed 2024-02-28]
  • Shapiro GK, Schulz-Quach C, Matthew A, Mosher P, Rodin G, de Vries F, et al. An institutional model for health care workers’ mental health during Covid-19. NEJM Catalyst. Mar 12, 2021. [ FREE Full text ] [ CrossRef ]
  • Plouffe RA, Nazarov A, Forchuk CA, Gargala D, Deda E, Le T, et al. Impacts of morally distressing experiences on the mental health of Canadian health care workers during the COVID-19 pandemic. Eur J Psychotraumatol. 2021;12(1):1984667. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Spinelli C, Wisener M, Khoury B. Corrigendum to 'mindfulness training for healthcare professionals and trainees: a meta-analysis of randomized controlled trials' [Journal of Psychosomatic Research 120 (2019) 29-38]. J Psychosom Res. Aug 2019;123:109733. [ CrossRef ] [ Medline ]
  • Scheepers RA, Emke H, Epstein RM, Lombarts KM. The impact of mindfulness-based interventions on doctors' well-being and performance: a systematic review. Med Educ. Feb 22, 2020;54(2):138-149. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Guillaumie L, Boiral O, Champagne J. A mixed-methods systematic review of the effects of mindfulness on nurses. J Adv Nurs. May 03, 2017;73(5):1017-1034. [ CrossRef ] [ Medline ]
  • West CP, Dyrbye LN, Erwin PJ, Shanafelt TD. Interventions to prevent and reduce physician burnout: a systematic review and meta-analysis. Lancet. Nov 2016;388(10057):2272-2281. [ CrossRef ]
  • Regehr C, Glancy D, Pitts A, LeBlanc VR. Interventions to reduce the consequences of stress in physicians: a review and meta-analysis. J Nerv Ment Dis. May 2014;202(5):353-359. [ CrossRef ] [ Medline ]
  • Shapiro SL, Brown KW, Biegel GM. Teaching self-care to caregivers: effects of mindfulness-based stress reduction on the mental health of therapists in training. Train Educ Prof Psychol. May 2007;1(2):105-115. [ CrossRef ]
  • Kabat-Zinn J, Hanh TN. Full Catastrophe Living: Using the Wisdom of Your Body and Mind to Face Stress, Pain, and Illness. New York, NY. Random House Publishing Group; 2009.
  • Germer C, Germer CK, Neff K. Teaching the Mindful Self-Compassion Program: A Guide for Professionals. New York, NY. The Guilford Press; 2019.
  • Segal Z, Williams JM, Williams M, Teasdale J. Mindfulness-Based Cognitive Therapy for Depression. New York, NY. Guilford Publications; 2012.
  • Zhang H, Zhang A, Liu C, Xiao J, Wang K. A brief online mindfulness-based group intervention for psychological distress among Chinese residents during COVID-19: a pilot randomized controlled trial. Mindfulness (N Y). 2021;12(6):1502-1512. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Drissi N, Ouhbi S, Marques G, de la Torre Díez I, Ghogho M, Janati Idrissi MA. A systematic literature review on e-mental health solutions to assist health care workers during COVID-19. Telemed J E Health. Jun 22, 2021;27(6):594-602. [ CrossRef ] [ Medline ]
  • Castillo-Sánchez G, Sacristán-Martín O, Hernández MA, Muñoz I, de la Torre I, Franco-Martín M. Online mindfulness experience for emotional support to healthcare staff in times of Covid-19. J Med Syst. Jan 26, 2022;46(3):14. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Nissim R, Malfitano C, Coleman M, Rodin G, Elliott M. A qualitative study of a compassion, presence, and resilience training for oncology interprofessional teams. J Holist Nurs. Mar 29, 2019;37(1):30-44. [ CrossRef ] [ Medline ]
  • Lieff SJ. Evolving curriculum design: a novel framework for continuous, timely, and relevant curriculum adaptation in faculty development. Acad Med. 2009;84(1):127-134. [ CrossRef ]
  • Nissim RS, Roth A, Gupta AA, Elliott M. Mindfulness-based cognitive therapy intervention for young adults with cancer: a pilot mixed-method study. J Adolesc Young Adult Oncol. Apr 01, 2020;9(2):256-261. [ CrossRef ] [ Medline ]
  • Faulds D. Go In and In: Poems From the Heart of Yoga. Berkeley, CA. Peaceable Kingdom Books; Jul 31, 2002.
  • Bloom R. Cloudy with a Fire in the Basement. St John’s, NL. Pedlar Press; 2012.
  • Porges SW, Dana D. Clinical Applications of the Polyvagal Theory: The Emergence of Polyvagal-Informed Therapies. New York, NY. W. W. Norton & Company; 2018.
  • Raab K. Mindfulness, self-compassion, and empathy among health care professionals: a review of the literature. J Health Care Chaplain. Jun 13, 2014;20(3):95-108. [ CrossRef ] [ Medline ]
  • Fredrickson BL, Boulton AJ, Firestine AM, Van Cappellen P, Algoe SB, Brantley MM, et al. Positive emotion correlates of meditation practice: a comparison of mindfulness meditation and loving-kindness meditation. Mindfulness (N Y). Dec 29, 2017;8(6):1623-1633. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Southwick SM, Charney DS. Resilience: The Science of Mastering Life's Greatest Challenges. Cambridge, MA. Cambridge University Press; 2012.
  • Elliott M, Macedo A, Escaf M. Building Resilience within Institutions Together with Employees (BRITE): preliminary experience with implementation in an academic cancer centre. Healthc Manage Forum. Mar 22, 2021;34(2):107-114. [ CrossRef ] [ Medline ]
  • Seligman ME. Positive psychology: a personal history. Annu Rev Clin Psychol. May 07, 2019;15(1):1-23. [ CrossRef ] [ Medline ]
  • Fessell D, Cherniss C. Coronavirus disease 2019 (COVID-19) and beyond: micropractices for burnout prevention and emotional wellness. J Am Coll Radiol. Jun 2020;17(6):746-748. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Hedderman E, O'Doherty V, O'Connor S. Mindfulness moments for clinicians in the midst of a pandemic. Ir J Psychol Med. Jun 21, 2021;38(2):154-157. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, et al. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health. Mar 19, 2011;38(2):65-76. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Dolan ED, Mohr D, Lempa M, Joos S, Fihn SD, Nelson KM, et al. Using a single item to measure burnout in primary care staff: a psychometric evaluation. J Gen Intern Med. May 2, 2015;30(5):582-587. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Rabatin J, Williams E, Baier Manwell L, Schwartz MD, Brown RL, Linzer M. Predictors and outcomes of burnout in primary care physicians. J Prim Care Community Health. Jan 28, 2016;7(1):41-43. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Rohland BM, Kruse GR, Rohrer JE. Validation of a single‐item measure of burnout against the Maslach Burnout Inventory among physicians. Stress Health. Apr 07, 2004;20(2):75-79. [ CrossRef ]
  • Winwood PC, Colon R, McEwen K. A practical measure of workplace resilience: developing the resilience at work scale. J Occup Environ Med. Oct 2013;55(10):1205-1212. [ CrossRef ] [ Medline ]
  • Auerbach C, Silverstein LB. Qualitative Data: An Introduction to Coding and Analysis. New York, NY. New York University Press; 2003.
  • Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. Dec 2007;19(6):349-357. [ CrossRef ] [ Medline ]
  • Sandelowski M. Whatever happened to qualitative description? Res Nurs Health. Aug 2000;23(4):334-340. [ CrossRef ] [ Medline ]
  • Maunder RG, Heeney ND, Hunter JJ. Adult attachment insecurity and responses to prolonged severe occupational stress in hospital workers during the COVID-19 pandemic. Health Psychol Behav Med. Sep 15, 2022;10(1):871-887. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Shanafelt TD, Dyrbye LN, West CP, Sinsky C, Tutty M, Carlasare LE, et al. Suicidal ideation and attitudes regarding help seeking in US physicians relative to the US working population. Mayo Clin Proc. Aug 2021;96(8):2067-2080. [ FREE Full text ] [ CrossRef ] [ Medline ]
  • Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. Jan 2006;3(2):77-101. [ CrossRef ]

Abbreviations

Edited by G Eysenbach; submitted 31.10.22; peer-reviewed by J Xiao, S Dijk; comments to author 21.02.23; revised version received 02.06.23; accepted 17.11.23; published 14.03.24.

©Mary Elliott, Camille Khallouf, Jennifer Hirsch, Diane de Camps Meschino, Orit Zamir, Paula Ravitz. Originally published in JMIR Formative Research (https://formative.jmir.org), 14.03.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.

COMMENTS

  1. The Social Determinants of Mental Health: A Descriptive Study of State Mental Health Agencies' Priorities

    Introduction. Almost 80 years ago, the Constitution of the World Health Organization (WHO) recognized that "health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity" (WHO Constitution, 1946).Some 40 years later, Engel, in describing the "biopsychosocial" approach to addressing mental illnesses, wrote, "to best serve the ...

  2. An overview of the qualitative descriptive design within nursing research

    Administration and Policy in Mental Health and Mental Health Services Research 42: 533-544. [PMC free article] [Google Scholar] Pelentsov LL, Fielder AL, Esterman AJ. (2016) The supportive care needs of parents with a child with a rare disease: A qualitative descriptive study. Journal of Pediatric Nursing 31 (3): e207-e218.

  3. Study designs: Part 2

    INTRODUCTION. In our previous article in this series, [ 1] we introduced the concept of "study designs"- as "the set of methods and procedures used to collect and analyze data on variables specified in a particular research question.". Study designs are primarily of two types - observational and interventional, with the former being ...

  4. The 3 Descriptive Research Methods of Psychology

    Types of descriptive research. Observational method. Case studies. Surveys. Recap. Descriptive research methods are used to define the who, what, and where of human behavior and other ...

  5. An integrative review on methodological considerations in mental health

    Background Several typologies and guidelines are available to address the methodological and practical considerations required in mental health research. However, few studies have actually attempted to systematically identify and synthesise these considerations. This paper provides an integrative review that identifies and synthesises the available research evidence on mental health research ...

  6. Exploring the relationship between mental health ...

    About the research design, the scope is descriptive since the objective is to specify the characteristics of a phenomenon the dropout rates to determine tendencies in a study group. Also, the research is non-experimental. ... Mental health-related reasons were the most common motives for dropout addressed by the students, as reported by similar ...

  7. Full article: Design for mental health: can design promote human

    A growing number of projects apply design and design research in different areas of mental health care. Design input ranges from improving mental health care for young people through design (Nakarada-Kordic et al. Citation 2017; Johansson, Vink, and Wetter-Edman Citation 2017; Scholten and Granic Citation 2019) to the (co-)design of psychiatric ...

  8. A descriptive study of mental health and wellbeing among medical

    The CAGE questionnaire was positive in 10% of students. Future research is required to confirm these results, assess and monitor local and global trends and investigate interventions at both local and national level to improve the mental wellbeing of medical students.

  9. Mixed-Methods Designs in Mental Health Services Research: A Review

    The number of published mental health services research studies with mixed-methods designs increased by 67% between 2005 and 2006, by 80% between 2006 and 2007, and by 155% between 2007 and 2008. Furthermore, 21 of the 50 published studies (42%) that we reviewed appeared in journals with 2008 IFs of 2.0 or higher, including ten articles ...

  10. A Descriptive Mixed-Methods Study Examining Resilience and

    experience more than average disease burden on physical health (M = 43.9), experience an average disease burden on mental health (M = 50.1), are generally satisfied with their lives (M = 23.6), are future orientated (M = 3.7), and have social support resources (M = 2.9). No correlation was noted between the variables resilience and physical health

  11. An overview of the qualitative descriptive design within nursing research

    Louise Doyle (PhD, MSc, BNS, RNT, RPN) is an Associate Professor in Mental Health Nursing at the School of Nursing and Midwifery, Trinity College Dublin. Her research interests are in the area of self-harm and suicide and she has a particular interest and expertise in mixed-methods and qualitative research designs.

  12. Employing a Qualitative Description Approach in Health Care Research

    It is essential that the sampling techniques selected within a research study are reflective of the research design and research question. The sampling process best able to achieve this within qualitative studies and in particular qualitative description designs is a nonprobability technique of convenience or purposive sampling (Parahoo, 2014 ...

  13. (PDF) Design for mental health: can design promote human-centred

    Design and design research hold the potential to drive these incremental and iterative changes in traditional mental health care services, as it builds on creative thinking and doing [5]. Over the ...

  14. Descriptive research and the mental health counselor

    This article makes the case that is is usually inappropriate for management to require mental health counselors to be data-takers from their clients on descriptive research projects that pose as necessary evaluative research. This is true because the goals of descriptive research and those of clinical treatment differ. Group methodology and exhaustive descriptive questioning are unhelpful and ...

  15. Qualitative Methods in Mental Health Services Research

    Qualitative methods are also used in combination with quantitative methods in mixed method designs for convergence, complementarity, expansion, development, and sampling. Rigorously applied qualitative methods offer great potential in contributing to the scientific foundation of mental health services research.

  16. Descriptive Research Design and Its Myriad Uses

    In qualitative descriptive research: A cross-sectional study exploring the cultural perceptions of mental health across different communities. Ecological studies : Descriptive research design is also well-suited for studies that seek to understand relationships between variables and outcomes in specific populations.

  17. PDF Conceptualization, Design, and Methods

    Quality mental health research in the Philippines is a comprehensive guidebook that provides an overview of the current state, challenges, and opportunities for mental health research in the country. It also outlines the conceptual framework, research agenda, and ethical principles for conducting mental health research in the Philippine context. This pdf document is a valuable resource for ...

  18. PDF Mental health of young adults: A descriptive study

    Mental health of young adults: A descriptive study ... Exploratory research design was utilized in current research. mind which guide, shape and regulate communication, conduct and

  19. Understanding the Experiences of COVID-19 Public Health Measures and

    This interpretative descriptive study explores how public health measures implemented during the first wave of the COVID-19 pandemic in Quebec, Canada, affected the well-being of older adults. ... Research Design. ... in discussing the mental health impacts of the confinement, some participants revealed that the social isolation imposed by ...

  20. (PDF) A Correlational Study: Quality of Life and Mental Health of

    The aim of this study was to see if there was a correlation between the selected individuals' Quality of Life and their Demographic Profile (Age, Sex, Year Level, and Family Socio Economic Status ...

  21. Exploring work‐related stressors experienced by mental health nurses: A

    The challenging work environments mental health nurses (MHNs) encounter can negatively impact their mental health, psychological well-being and physical health. While these impacts have been investigated in quantitative research, little is known about work-related stress from the perspective of MHNs.

  22. A scoping review of the barriers and facilitators to accessing and

    Inadequate healthcare access and utilisation are implicated in the mental health burden experienced by those living in regional, rural, and remote Australia. Facilitators that better enable access and utilisation are also reported in the literature. To date, a synthesis on both the barriers and facilitators to accessing and utilising mental health services within the rural Australian context ...

  23. Evidence linking COVID-19 and the health/well-being of children and

    The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been spreading globally for more than 3 years [1, 2].As of April 20, 2023, there have been over 765 million confirmed cases and over 6.9 million deaths reported worldwide [].COVID-19 has had varied effects on the health of children and adolescents, both directly and indirectly.

  24. An integrative review on methodological considerations in mental health

    Six studies explain the function of conducting mixed methods design in mental health research. ... and also require having specific content such as descriptive and interpretive data. Three studies in this section suggested that in-depth interviews are used to collect data from consumers of mental health services [19, 30, 34].

  25. Factors associated with suicide in people who use drugs: a scoping

    Previous research has suggested that drug use may exacerbate underlying risk of suicide, or interact with mental illness to increase risk of engaging in suicidal behaviours . Darke and Ross [ 25 ] suggest that between a quarter and a third of people who use heroin meet the criteria for a life-time diagnosis of major depression, a figure much ...

  26. Understanding mental health in the research environment

    The aim of this study was to assess what is known about mental health in research environments through a literature review, and it focused on the UK and comparable research systems. A better understanding of researchers' mental health needs will enable the design of more effective interventions to address them, while a better understanding of ...

  27. Impact effects of COVID‐19 pandemic on chronic disease patients: A

    The Journal of Clinical Nursing publishes research and developments relevant to all areas of nursing practice- community, geriatric, mental health, pediatric & more. Abstract Aims To assess the effects of COVID-19 pandemic on clinical variables as part of the routine clinical monitoring of patients with chronic diseases in primary care.

  28. An overview of the qualitative descriptive design within nursing research

    It can be difficult to clearly differentiate what constitutes a descriptive research design from the range of other methodologies at the disposal of qualitative researchers. ... Administration and Policy in Mental Health and Mental Health Services Research 42: 533-544. [Europe PMC free article] [Google Scholar]

  29. The Study on Mental Health at Work: Design and sampling

    Aims: The Study on Mental Health at Work (S-MGA) generates the first nationwide representative survey enabling the exploration of the relationship between working conditions, mental health and functioning. This paper describes the study design, sampling procedures and data collection, and presents a summary of the sample characteristics. Methods: S-MGA is a representative study of German ...

  30. JMIR Formative Research

    Background: The COVID-19 pandemic exerted extraordinary pressure on health care workers (HCWs), imperiling their well-being and mental health. In response to the urgent demand to provide barrier-free support for the health care workforce, Pause-4-Providers implemented 30-minute live web-based drop-in mindfulness sessions for HCWs. Objective: This study aims to evaluate the use, feasibility ...