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  • What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on June 19, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analyzing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.

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Table of contents

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, other interesting articles, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography , action research , phenomenological research, and narrative research. They share some similarities, but emphasize different aims and perspectives.

Note that qualitative research is at risk for certain research biases including the Hawthorne effect , observer bias , recall bias , and social desirability bias . While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.

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qualitative research 2

Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

  • Observations: recording what you have seen, heard, or encountered in detailed field notes.
  • Interviews:  personally asking people questions in one-on-one conversations.
  • Focus groups: asking questions and generating discussion among a group of people.
  • Surveys : distributing questionnaires with open-ended questions.
  • Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
  • You take field notes with observations and reflect on your own experiences of the company culture.
  • You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
  • You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves “instruments” in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analyzing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

  • Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
  • Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
  • Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
  • Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
  • Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

  • Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

  • Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

  • Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

  • Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

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Researchers must consider practical and theoretical limitations in analyzing and interpreting their data. Qualitative research suffers from:

  • Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

  • Subjectivity

Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

  • Limited generalizability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions because the data may be biased and unrepresentative of the wider population .

  • Labor-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

  • Chi square goodness of fit test
  • Degrees of freedom
  • Null hypothesis
  • Discourse analysis
  • Control groups
  • Mixed methods research
  • Non-probability sampling
  • Quantitative research
  • Inclusion and exclusion criteria

Research bias

  • Rosenthal effect
  • Implicit bias
  • Cognitive bias
  • Selection bias
  • Negativity bias
  • Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

There are five common approaches to qualitative research :

  • Grounded theory involves collecting data in order to develop new theories.
  • Ethnography involves immersing yourself in a group or organization to understand its culture.
  • Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
  • Phenomenological research involves investigating phenomena through people’s lived experiences.
  • Action research links theory and practice in several cycles to drive innovative changes.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

  • Prepare and organize your data.
  • Review and explore your data.
  • Develop a data coding system.
  • Assign codes to the data.
  • Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

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  • Published: 27 May 2020

How to use and assess qualitative research methods

  • Loraine Busetto   ORCID: orcid.org/0000-0002-9228-7875 1 ,
  • Wolfgang Wick 1 , 2 &
  • Christoph Gumbinger 1  

Neurological Research and Practice volume  2 , Article number:  14 ( 2020 ) Cite this article

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This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions, and focussing on intervention improvement. The most common methods of data collection are document study, (non-) participant observations, semi-structured interviews and focus groups. For data analysis, field-notes and audio-recordings are transcribed into protocols and transcripts, and coded using qualitative data management software. Criteria such as checklists, reflexivity, sampling strategies, piloting, co-coding, member-checking and stakeholder involvement can be used to enhance and assess the quality of the research conducted. Using qualitative in addition to quantitative designs will equip us with better tools to address a greater range of research problems, and to fill in blind spots in current neurological research and practice.

The aim of this paper is to provide an overview of qualitative research methods, including hands-on information on how they can be used, reported and assessed. This article is intended for beginning qualitative researchers in the health sciences as well as experienced quantitative researchers who wish to broaden their understanding of qualitative research.

What is qualitative research?

Qualitative research is defined as “the study of the nature of phenomena”, including “their quality, different manifestations, the context in which they appear or the perspectives from which they can be perceived” , but excluding “their range, frequency and place in an objectively determined chain of cause and effect” [ 1 ]. This formal definition can be complemented with a more pragmatic rule of thumb: qualitative research generally includes data in form of words rather than numbers [ 2 ].

Why conduct qualitative research?

Because some research questions cannot be answered using (only) quantitative methods. For example, one Australian study addressed the issue of why patients from Aboriginal communities often present late or not at all to specialist services offered by tertiary care hospitals. Using qualitative interviews with patients and staff, it found one of the most significant access barriers to be transportation problems, including some towns and communities simply not having a bus service to the hospital [ 3 ]. A quantitative study could have measured the number of patients over time or even looked at possible explanatory factors – but only those previously known or suspected to be of relevance. To discover reasons for observed patterns, especially the invisible or surprising ones, qualitative designs are needed.

While qualitative research is common in other fields, it is still relatively underrepresented in health services research. The latter field is more traditionally rooted in the evidence-based-medicine paradigm, as seen in " research that involves testing the effectiveness of various strategies to achieve changes in clinical practice, preferably applying randomised controlled trial study designs (...) " [ 4 ]. This focus on quantitative research and specifically randomised controlled trials (RCT) is visible in the idea of a hierarchy of research evidence which assumes that some research designs are objectively better than others, and that choosing a "lesser" design is only acceptable when the better ones are not practically or ethically feasible [ 5 , 6 ]. Others, however, argue that an objective hierarchy does not exist, and that, instead, the research design and methods should be chosen to fit the specific research question at hand – "questions before methods" [ 2 , 7 , 8 , 9 ]. This means that even when an RCT is possible, some research problems require a different design that is better suited to addressing them. Arguing in JAMA, Berwick uses the example of rapid response teams in hospitals, which he describes as " a complex, multicomponent intervention – essentially a process of social change" susceptible to a range of different context factors including leadership or organisation history. According to him, "[in] such complex terrain, the RCT is an impoverished way to learn. Critics who use it as a truth standard in this context are incorrect" [ 8 ] . Instead of limiting oneself to RCTs, Berwick recommends embracing a wider range of methods , including qualitative ones, which for "these specific applications, (...) are not compromises in learning how to improve; they are superior" [ 8 ].

Research problems that can be approached particularly well using qualitative methods include assessing complex multi-component interventions or systems (of change), addressing questions beyond “what works”, towards “what works for whom when, how and why”, and focussing on intervention improvement rather than accreditation [ 7 , 9 , 10 , 11 , 12 ]. Using qualitative methods can also help shed light on the “softer” side of medical treatment. For example, while quantitative trials can measure the costs and benefits of neuro-oncological treatment in terms of survival rates or adverse effects, qualitative research can help provide a better understanding of patient or caregiver stress, visibility of illness or out-of-pocket expenses.

How to conduct qualitative research?

Given that qualitative research is characterised by flexibility, openness and responsivity to context, the steps of data collection and analysis are not as separate and consecutive as they tend to be in quantitative research [ 13 , 14 ]. As Fossey puts it : “sampling, data collection, analysis and interpretation are related to each other in a cyclical (iterative) manner, rather than following one after another in a stepwise approach” [ 15 ]. The researcher can make educated decisions with regard to the choice of method, how they are implemented, and to which and how many units they are applied [ 13 ]. As shown in Fig.  1 , this can involve several back-and-forth steps between data collection and analysis where new insights and experiences can lead to adaption and expansion of the original plan. Some insights may also necessitate a revision of the research question and/or the research design as a whole. The process ends when saturation is achieved, i.e. when no relevant new information can be found (see also below: sampling and saturation). For reasons of transparency, it is essential for all decisions as well as the underlying reasoning to be well-documented.

figure 1

Iterative research process

While it is not always explicitly addressed, qualitative methods reflect a different underlying research paradigm than quantitative research (e.g. constructivism or interpretivism as opposed to positivism). The choice of methods can be based on the respective underlying substantive theory or theoretical framework used by the researcher [ 2 ].

Data collection

The methods of qualitative data collection most commonly used in health research are document study, observations, semi-structured interviews and focus groups [ 1 , 14 , 16 , 17 ].

Document study

Document study (also called document analysis) refers to the review by the researcher of written materials [ 14 ]. These can include personal and non-personal documents such as archives, annual reports, guidelines, policy documents, diaries or letters.

Observations

Observations are particularly useful to gain insights into a certain setting and actual behaviour – as opposed to reported behaviour or opinions [ 13 ]. Qualitative observations can be either participant or non-participant in nature. In participant observations, the observer is part of the observed setting, for example a nurse working in an intensive care unit [ 18 ]. In non-participant observations, the observer is “on the outside looking in”, i.e. present in but not part of the situation, trying not to influence the setting by their presence. Observations can be planned (e.g. for 3 h during the day or night shift) or ad hoc (e.g. as soon as a stroke patient arrives at the emergency room). During the observation, the observer takes notes on everything or certain pre-determined parts of what is happening around them, for example focusing on physician-patient interactions or communication between different professional groups. Written notes can be taken during or after the observations, depending on feasibility (which is usually lower during participant observations) and acceptability (e.g. when the observer is perceived to be judging the observed). Afterwards, these field notes are transcribed into observation protocols. If more than one observer was involved, field notes are taken independently, but notes can be consolidated into one protocol after discussions. Advantages of conducting observations include minimising the distance between the researcher and the researched, the potential discovery of topics that the researcher did not realise were relevant and gaining deeper insights into the real-world dimensions of the research problem at hand [ 18 ].

Semi-structured interviews

Hijmans & Kuyper describe qualitative interviews as “an exchange with an informal character, a conversation with a goal” [ 19 ]. Interviews are used to gain insights into a person’s subjective experiences, opinions and motivations – as opposed to facts or behaviours [ 13 ]. Interviews can be distinguished by the degree to which they are structured (i.e. a questionnaire), open (e.g. free conversation or autobiographical interviews) or semi-structured [ 2 , 13 ]. Semi-structured interviews are characterized by open-ended questions and the use of an interview guide (or topic guide/list) in which the broad areas of interest, sometimes including sub-questions, are defined [ 19 ]. The pre-defined topics in the interview guide can be derived from the literature, previous research or a preliminary method of data collection, e.g. document study or observations. The topic list is usually adapted and improved at the start of the data collection process as the interviewer learns more about the field [ 20 ]. Across interviews the focus on the different (blocks of) questions may differ and some questions may be skipped altogether (e.g. if the interviewee is not able or willing to answer the questions or for concerns about the total length of the interview) [ 20 ]. Qualitative interviews are usually not conducted in written format as it impedes on the interactive component of the method [ 20 ]. In comparison to written surveys, qualitative interviews have the advantage of being interactive and allowing for unexpected topics to emerge and to be taken up by the researcher. This can also help overcome a provider or researcher-centred bias often found in written surveys, which by nature, can only measure what is already known or expected to be of relevance to the researcher. Interviews can be audio- or video-taped; but sometimes it is only feasible or acceptable for the interviewer to take written notes [ 14 , 16 , 20 ].

Focus groups

Focus groups are group interviews to explore participants’ expertise and experiences, including explorations of how and why people behave in certain ways [ 1 ]. Focus groups usually consist of 6–8 people and are led by an experienced moderator following a topic guide or “script” [ 21 ]. They can involve an observer who takes note of the non-verbal aspects of the situation, possibly using an observation guide [ 21 ]. Depending on researchers’ and participants’ preferences, the discussions can be audio- or video-taped and transcribed afterwards [ 21 ]. Focus groups are useful for bringing together homogeneous (to a lesser extent heterogeneous) groups of participants with relevant expertise and experience on a given topic on which they can share detailed information [ 21 ]. Focus groups are a relatively easy, fast and inexpensive method to gain access to information on interactions in a given group, i.e. “the sharing and comparing” among participants [ 21 ]. Disadvantages include less control over the process and a lesser extent to which each individual may participate. Moreover, focus group moderators need experience, as do those tasked with the analysis of the resulting data. Focus groups can be less appropriate for discussing sensitive topics that participants might be reluctant to disclose in a group setting [ 13 ]. Moreover, attention must be paid to the emergence of “groupthink” as well as possible power dynamics within the group, e.g. when patients are awed or intimidated by health professionals.

Choosing the “right” method

As explained above, the school of thought underlying qualitative research assumes no objective hierarchy of evidence and methods. This means that each choice of single or combined methods has to be based on the research question that needs to be answered and a critical assessment with regard to whether or to what extent the chosen method can accomplish this – i.e. the “fit” between question and method [ 14 ]. It is necessary for these decisions to be documented when they are being made, and to be critically discussed when reporting methods and results.

Let us assume that our research aim is to examine the (clinical) processes around acute endovascular treatment (EVT), from the patient’s arrival at the emergency room to recanalization, with the aim to identify possible causes for delay and/or other causes for sub-optimal treatment outcome. As a first step, we could conduct a document study of the relevant standard operating procedures (SOPs) for this phase of care – are they up-to-date and in line with current guidelines? Do they contain any mistakes, irregularities or uncertainties that could cause delays or other problems? Regardless of the answers to these questions, the results have to be interpreted based on what they are: a written outline of what care processes in this hospital should look like. If we want to know what they actually look like in practice, we can conduct observations of the processes described in the SOPs. These results can (and should) be analysed in themselves, but also in comparison to the results of the document analysis, especially as regards relevant discrepancies. Do the SOPs outline specific tests for which no equipment can be observed or tasks to be performed by specialized nurses who are not present during the observation? It might also be possible that the written SOP is outdated, but the actual care provided is in line with current best practice. In order to find out why these discrepancies exist, it can be useful to conduct interviews. Are the physicians simply not aware of the SOPs (because their existence is limited to the hospital’s intranet) or do they actively disagree with them or does the infrastructure make it impossible to provide the care as described? Another rationale for adding interviews is that some situations (or all of their possible variations for different patient groups or the day, night or weekend shift) cannot practically or ethically be observed. In this case, it is possible to ask those involved to report on their actions – being aware that this is not the same as the actual observation. A senior physician’s or hospital manager’s description of certain situations might differ from a nurse’s or junior physician’s one, maybe because they intentionally misrepresent facts or maybe because different aspects of the process are visible or important to them. In some cases, it can also be relevant to consider to whom the interviewee is disclosing this information – someone they trust, someone they are otherwise not connected to, or someone they suspect or are aware of being in a potentially “dangerous” power relationship to them. Lastly, a focus group could be conducted with representatives of the relevant professional groups to explore how and why exactly they provide care around EVT. The discussion might reveal discrepancies (between SOPs and actual care or between different physicians) and motivations to the researchers as well as to the focus group members that they might not have been aware of themselves. For the focus group to deliver relevant information, attention has to be paid to its composition and conduct, for example, to make sure that all participants feel safe to disclose sensitive or potentially problematic information or that the discussion is not dominated by (senior) physicians only. The resulting combination of data collection methods is shown in Fig.  2 .

figure 2

Possible combination of data collection methods

Attributions for icons: “Book” by Serhii Smirnov, “Interview” by Adrien Coquet, FR, “Magnifying Glass” by anggun, ID, “Business communication” by Vectors Market; all from the Noun Project

The combination of multiple data source as described for this example can be referred to as “triangulation”, in which multiple measurements are carried out from different angles to achieve a more comprehensive understanding of the phenomenon under study [ 22 , 23 ].

Data analysis

To analyse the data collected through observations, interviews and focus groups these need to be transcribed into protocols and transcripts (see Fig.  3 ). Interviews and focus groups can be transcribed verbatim , with or without annotations for behaviour (e.g. laughing, crying, pausing) and with or without phonetic transcription of dialects and filler words, depending on what is expected or known to be relevant for the analysis. In the next step, the protocols and transcripts are coded , that is, marked (or tagged, labelled) with one or more short descriptors of the content of a sentence or paragraph [ 2 , 15 , 23 ]. Jansen describes coding as “connecting the raw data with “theoretical” terms” [ 20 ]. In a more practical sense, coding makes raw data sortable. This makes it possible to extract and examine all segments describing, say, a tele-neurology consultation from multiple data sources (e.g. SOPs, emergency room observations, staff and patient interview). In a process of synthesis and abstraction, the codes are then grouped, summarised and/or categorised [ 15 , 20 ]. The end product of the coding or analysis process is a descriptive theory of the behavioural pattern under investigation [ 20 ]. The coding process is performed using qualitative data management software, the most common ones being InVivo, MaxQDA and Atlas.ti. It should be noted that these are data management tools which support the analysis performed by the researcher(s) [ 14 ].

figure 3

From data collection to data analysis

Attributions for icons: see Fig. 2 , also “Speech to text” by Trevor Dsouza, “Field Notes” by Mike O’Brien, US, “Voice Record” by ProSymbols, US, “Inspection” by Made, AU, and “Cloud” by Graphic Tigers; all from the Noun Project

How to report qualitative research?

Protocols of qualitative research can be published separately and in advance of the study results. However, the aim is not the same as in RCT protocols, i.e. to pre-define and set in stone the research questions and primary or secondary endpoints. Rather, it is a way to describe the research methods in detail, which might not be possible in the results paper given journals’ word limits. Qualitative research papers are usually longer than their quantitative counterparts to allow for deep understanding and so-called “thick description”. In the methods section, the focus is on transparency of the methods used, including why, how and by whom they were implemented in the specific study setting, so as to enable a discussion of whether and how this may have influenced data collection, analysis and interpretation. The results section usually starts with a paragraph outlining the main findings, followed by more detailed descriptions of, for example, the commonalities, discrepancies or exceptions per category [ 20 ]. Here it is important to support main findings by relevant quotations, which may add information, context, emphasis or real-life examples [ 20 , 23 ]. It is subject to debate in the field whether it is relevant to state the exact number or percentage of respondents supporting a certain statement (e.g. “Five interviewees expressed negative feelings towards XYZ”) [ 21 ].

How to combine qualitative with quantitative research?

Qualitative methods can be combined with other methods in multi- or mixed methods designs, which “[employ] two or more different methods [ …] within the same study or research program rather than confining the research to one single method” [ 24 ]. Reasons for combining methods can be diverse, including triangulation for corroboration of findings, complementarity for illustration and clarification of results, expansion to extend the breadth and range of the study, explanation of (unexpected) results generated with one method with the help of another, or offsetting the weakness of one method with the strength of another [ 1 , 17 , 24 , 25 , 26 ]. The resulting designs can be classified according to when, why and how the different quantitative and/or qualitative data strands are combined. The three most common types of mixed method designs are the convergent parallel design , the explanatory sequential design and the exploratory sequential design. The designs with examples are shown in Fig.  4 .

figure 4

Three common mixed methods designs

In the convergent parallel design, a qualitative study is conducted in parallel to and independently of a quantitative study, and the results of both studies are compared and combined at the stage of interpretation of results. Using the above example of EVT provision, this could entail setting up a quantitative EVT registry to measure process times and patient outcomes in parallel to conducting the qualitative research outlined above, and then comparing results. Amongst other things, this would make it possible to assess whether interview respondents’ subjective impressions of patients receiving good care match modified Rankin Scores at follow-up, or whether observed delays in care provision are exceptions or the rule when compared to door-to-needle times as documented in the registry. In the explanatory sequential design, a quantitative study is carried out first, followed by a qualitative study to help explain the results from the quantitative study. This would be an appropriate design if the registry alone had revealed relevant delays in door-to-needle times and the qualitative study would be used to understand where and why these occurred, and how they could be improved. In the exploratory design, the qualitative study is carried out first and its results help informing and building the quantitative study in the next step [ 26 ]. If the qualitative study around EVT provision had shown a high level of dissatisfaction among the staff members involved, a quantitative questionnaire investigating staff satisfaction could be set up in the next step, informed by the qualitative study on which topics dissatisfaction had been expressed. Amongst other things, the questionnaire design would make it possible to widen the reach of the research to more respondents from different (types of) hospitals, regions, countries or settings, and to conduct sub-group analyses for different professional groups.

How to assess qualitative research?

A variety of assessment criteria and lists have been developed for qualitative research, ranging in their focus and comprehensiveness [ 14 , 17 , 27 ]. However, none of these has been elevated to the “gold standard” in the field. In the following, we therefore focus on a set of commonly used assessment criteria that, from a practical standpoint, a researcher can look for when assessing a qualitative research report or paper.

Assessors should check the authors’ use of and adherence to the relevant reporting checklists (e.g. Standards for Reporting Qualitative Research (SRQR)) to make sure all items that are relevant for this type of research are addressed [ 23 , 28 ]. Discussions of quantitative measures in addition to or instead of these qualitative measures can be a sign of lower quality of the research (paper). Providing and adhering to a checklist for qualitative research contributes to an important quality criterion for qualitative research, namely transparency [ 15 , 17 , 23 ].

Reflexivity

While methodological transparency and complete reporting is relevant for all types of research, some additional criteria must be taken into account for qualitative research. This includes what is called reflexivity, i.e. sensitivity to the relationship between the researcher and the researched, including how contact was established and maintained, or the background and experience of the researcher(s) involved in data collection and analysis. Depending on the research question and population to be researched this can be limited to professional experience, but it may also include gender, age or ethnicity [ 17 , 27 ]. These details are relevant because in qualitative research, as opposed to quantitative research, the researcher as a person cannot be isolated from the research process [ 23 ]. It may influence the conversation when an interviewed patient speaks to an interviewer who is a physician, or when an interviewee is asked to discuss a gynaecological procedure with a male interviewer, and therefore the reader must be made aware of these details [ 19 ].

Sampling and saturation

The aim of qualitative sampling is for all variants of the objects of observation that are deemed relevant for the study to be present in the sample “ to see the issue and its meanings from as many angles as possible” [ 1 , 16 , 19 , 20 , 27 ] , and to ensure “information-richness [ 15 ]. An iterative sampling approach is advised, in which data collection (e.g. five interviews) is followed by data analysis, followed by more data collection to find variants that are lacking in the current sample. This process continues until no new (relevant) information can be found and further sampling becomes redundant – which is called saturation [ 1 , 15 ] . In other words: qualitative data collection finds its end point not a priori , but when the research team determines that saturation has been reached [ 29 , 30 ].

This is also the reason why most qualitative studies use deliberate instead of random sampling strategies. This is generally referred to as “ purposive sampling” , in which researchers pre-define which types of participants or cases they need to include so as to cover all variations that are expected to be of relevance, based on the literature, previous experience or theory (i.e. theoretical sampling) [ 14 , 20 ]. Other types of purposive sampling include (but are not limited to) maximum variation sampling, critical case sampling or extreme or deviant case sampling [ 2 ]. In the above EVT example, a purposive sample could include all relevant professional groups and/or all relevant stakeholders (patients, relatives) and/or all relevant times of observation (day, night and weekend shift).

Assessors of qualitative research should check whether the considerations underlying the sampling strategy were sound and whether or how researchers tried to adapt and improve their strategies in stepwise or cyclical approaches between data collection and analysis to achieve saturation [ 14 ].

Good qualitative research is iterative in nature, i.e. it goes back and forth between data collection and analysis, revising and improving the approach where necessary. One example of this are pilot interviews, where different aspects of the interview (especially the interview guide, but also, for example, the site of the interview or whether the interview can be audio-recorded) are tested with a small number of respondents, evaluated and revised [ 19 ]. In doing so, the interviewer learns which wording or types of questions work best, or which is the best length of an interview with patients who have trouble concentrating for an extended time. Of course, the same reasoning applies to observations or focus groups which can also be piloted.

Ideally, coding should be performed by at least two researchers, especially at the beginning of the coding process when a common approach must be defined, including the establishment of a useful coding list (or tree), and when a common meaning of individual codes must be established [ 23 ]. An initial sub-set or all transcripts can be coded independently by the coders and then compared and consolidated after regular discussions in the research team. This is to make sure that codes are applied consistently to the research data.

Member checking

Member checking, also called respondent validation , refers to the practice of checking back with study respondents to see if the research is in line with their views [ 14 , 27 ]. This can happen after data collection or analysis or when first results are available [ 23 ]. For example, interviewees can be provided with (summaries of) their transcripts and asked whether they believe this to be a complete representation of their views or whether they would like to clarify or elaborate on their responses [ 17 ]. Respondents’ feedback on these issues then becomes part of the data collection and analysis [ 27 ].

Stakeholder involvement

In those niches where qualitative approaches have been able to evolve and grow, a new trend has seen the inclusion of patients and their representatives not only as study participants (i.e. “members”, see above) but as consultants to and active participants in the broader research process [ 31 , 32 , 33 ]. The underlying assumption is that patients and other stakeholders hold unique perspectives and experiences that add value beyond their own single story, making the research more relevant and beneficial to researchers, study participants and (future) patients alike [ 34 , 35 ]. Using the example of patients on or nearing dialysis, a recent scoping review found that 80% of clinical research did not address the top 10 research priorities identified by patients and caregivers [ 32 , 36 ]. In this sense, the involvement of the relevant stakeholders, especially patients and relatives, is increasingly being seen as a quality indicator in and of itself.

How not to assess qualitative research

The above overview does not include certain items that are routine in assessments of quantitative research. What follows is a non-exhaustive, non-representative, experience-based list of the quantitative criteria often applied to the assessment of qualitative research, as well as an explanation of the limited usefulness of these endeavours.

Protocol adherence

Given the openness and flexibility of qualitative research, it should not be assessed by how well it adheres to pre-determined and fixed strategies – in other words: its rigidity. Instead, the assessor should look for signs of adaptation and refinement based on lessons learned from earlier steps in the research process.

Sample size

For the reasons explained above, qualitative research does not require specific sample sizes, nor does it require that the sample size be determined a priori [ 1 , 14 , 27 , 37 , 38 , 39 ]. Sample size can only be a useful quality indicator when related to the research purpose, the chosen methodology and the composition of the sample, i.e. who was included and why.

Randomisation

While some authors argue that randomisation can be used in qualitative research, this is not commonly the case, as neither its feasibility nor its necessity or usefulness has been convincingly established for qualitative research [ 13 , 27 ]. Relevant disadvantages include the negative impact of a too large sample size as well as the possibility (or probability) of selecting “ quiet, uncooperative or inarticulate individuals ” [ 17 ]. Qualitative studies do not use control groups, either.

Interrater reliability, variability and other “objectivity checks”

The concept of “interrater reliability” is sometimes used in qualitative research to assess to which extent the coding approach overlaps between the two co-coders. However, it is not clear what this measure tells us about the quality of the analysis [ 23 ]. This means that these scores can be included in qualitative research reports, preferably with some additional information on what the score means for the analysis, but it is not a requirement. Relatedly, it is not relevant for the quality or “objectivity” of qualitative research to separate those who recruited the study participants and collected and analysed the data. Experiences even show that it might be better to have the same person or team perform all of these tasks [ 20 ]. First, when researchers introduce themselves during recruitment this can enhance trust when the interview takes place days or weeks later with the same researcher. Second, when the audio-recording is transcribed for analysis, the researcher conducting the interviews will usually remember the interviewee and the specific interview situation during data analysis. This might be helpful in providing additional context information for interpretation of data, e.g. on whether something might have been meant as a joke [ 18 ].

Not being quantitative research

Being qualitative research instead of quantitative research should not be used as an assessment criterion if it is used irrespectively of the research problem at hand. Similarly, qualitative research should not be required to be combined with quantitative research per se – unless mixed methods research is judged as inherently better than single-method research. In this case, the same criterion should be applied for quantitative studies without a qualitative component.

The main take-away points of this paper are summarised in Table 1 . We aimed to show that, if conducted well, qualitative research can answer specific research questions that cannot to be adequately answered using (only) quantitative designs. Seeing qualitative and quantitative methods as equal will help us become more aware and critical of the “fit” between the research problem and our chosen methods: I can conduct an RCT to determine the reasons for transportation delays of acute stroke patients – but should I? It also provides us with a greater range of tools to tackle a greater range of research problems more appropriately and successfully, filling in the blind spots on one half of the methodological spectrum to better address the whole complexity of neurological research and practice.

Availability of data and materials

Not applicable.

Abbreviations

Endovascular treatment

Randomised Controlled Trial

Standard Operating Procedure

Standards for Reporting Qualitative Research

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Busetto, L., Wick, W. & Gumbinger, C. How to use and assess qualitative research methods. Neurol. Res. Pract. 2 , 14 (2020). https://doi.org/10.1186/s42466-020-00059-z

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The Oxford Handbook of Qualitative Research (2nd edn)

The Oxford Handbook of Qualitative Research (2nd edn)

The Oxford Handbook of Qualitative Research (2nd edn)

Patricia Leavy Independent Scholar Kennebunk, ME, USA

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The Oxford Handbook of Qualitative Research, second edition, presents a comprehensive retrospective and prospective review of the field of qualitative research. Original, accessible chapters written by interdisciplinary leaders in the field make this a critical reference work. Filled with robust examples from real-world research; ample discussion of the historical, theoretical, and methodological foundations of the field; and coverage of key issues including data collection, interpretation, representation, assessment, and teaching, this handbook aims to be a valuable text for students, professors, and researchers. This newly revised and expanded edition features up-to-date examples and topics, including seven new chapters on duoethnography, team research, writing ethnographically, creative approaches to writing, writing for performance, writing for the public, and teaching qualitative research.

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  • What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on 4 April 2022 by Pritha Bhandari . Revised on 30 January 2023.

Qualitative research involves collecting and analysing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analysing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, and history.

  • How does social media shape body image in teenagers?
  • How do children and adults interpret healthy eating in the UK?
  • What factors influence employee retention in a large organisation?
  • How is anxiety experienced around the world?
  • How can teachers integrate social issues into science curriculums?

Table of contents

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography, action research, phenomenological research, and narrative research. They share some similarities, but emphasise different aims and perspectives.

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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

  • Observations: recording what you have seen, heard, or encountered in detailed field notes.
  • Interviews:  personally asking people questions in one-on-one conversations.
  • Focus groups: asking questions and generating discussion among a group of people.
  • Surveys : distributing questionnaires with open-ended questions.
  • Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
  • You take field notes with observations and reflect on your own experiences of the company culture.
  • You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
  • You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves ‘instruments’ in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analysing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

  • Prepare and organise your data. This may mean transcribing interviews or typing up fieldnotes.
  • Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
  • Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorise your data.
  • Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
  • Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analysing qualitative data. Although these methods share similar processes, they emphasise different concepts.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

  • Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

  • Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

  • Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

  • Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

Researchers must consider practical and theoretical limitations in analysing and interpreting their data. Qualitative research suffers from:

  • Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

  • Subjectivity

Due to the researcher’s primary role in analysing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

  • Limited generalisability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalisable conclusions because the data may be biased and unrepresentative of the wider population .

  • Labour-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

There are five common approaches to qualitative research :

  • Grounded theory involves collecting data in order to develop new theories.
  • Ethnography involves immersing yourself in a group or organisation to understand its culture.
  • Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
  • Phenomenological research involves investigating phenomena through people’s lived experiences.
  • Action research links theory and practice in several cycles to drive innovative changes.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

  • Prepare and organise your data.
  • Review and explore your data.
  • Develop a data coding system.
  • Assign codes to the data.
  • Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

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Bhandari, P. (2023, January 30). What Is Qualitative Research? | Methods & Examples. Scribbr. Retrieved 12 March 2024, from https://www.scribbr.co.uk/research-methods/introduction-to-qualitative-research/

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Qualitative Research : Definition

Qualitative research is the naturalistic study of social meanings and processes, using interviews, observations, and the analysis of texts and images.  In contrast to quantitative researchers, whose statistical methods enable broad generalizations about populations (for example, comparisons of the percentages of U.S. demographic groups who vote in particular ways), qualitative researchers use in-depth studies of the social world to analyze how and why groups think and act in particular ways (for instance, case studies of the experiences that shape political views).   

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Home » Qualitative Research – Methods, Analysis Types and Guide

Qualitative Research – Methods, Analysis Types and Guide

Table of Contents

Qualitative Research

Qualitative Research

Qualitative research is a type of research methodology that focuses on exploring and understanding people’s beliefs, attitudes, behaviors, and experiences through the collection and analysis of non-numerical data. It seeks to answer research questions through the examination of subjective data, such as interviews, focus groups, observations, and textual analysis.

Qualitative research aims to uncover the meaning and significance of social phenomena, and it typically involves a more flexible and iterative approach to data collection and analysis compared to quantitative research. Qualitative research is often used in fields such as sociology, anthropology, psychology, and education.

Qualitative Research Methods

Types of Qualitative Research

Qualitative Research Methods are as follows:

One-to-One Interview

This method involves conducting an interview with a single participant to gain a detailed understanding of their experiences, attitudes, and beliefs. One-to-one interviews can be conducted in-person, over the phone, or through video conferencing. The interviewer typically uses open-ended questions to encourage the participant to share their thoughts and feelings. One-to-one interviews are useful for gaining detailed insights into individual experiences.

Focus Groups

This method involves bringing together a group of people to discuss a specific topic in a structured setting. The focus group is led by a moderator who guides the discussion and encourages participants to share their thoughts and opinions. Focus groups are useful for generating ideas and insights, exploring social norms and attitudes, and understanding group dynamics.

Ethnographic Studies

This method involves immersing oneself in a culture or community to gain a deep understanding of its norms, beliefs, and practices. Ethnographic studies typically involve long-term fieldwork and observation, as well as interviews and document analysis. Ethnographic studies are useful for understanding the cultural context of social phenomena and for gaining a holistic understanding of complex social processes.

Text Analysis

This method involves analyzing written or spoken language to identify patterns and themes. Text analysis can be quantitative or qualitative. Qualitative text analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns. Text analysis is useful for understanding media messages, public discourse, and cultural trends.

This method involves an in-depth examination of a single person, group, or event to gain an understanding of complex phenomena. Case studies typically involve a combination of data collection methods, such as interviews, observations, and document analysis, to provide a comprehensive understanding of the case. Case studies are useful for exploring unique or rare cases, and for generating hypotheses for further research.

Process of Observation

This method involves systematically observing and recording behaviors and interactions in natural settings. The observer may take notes, use audio or video recordings, or use other methods to document what they see. Process of observation is useful for understanding social interactions, cultural practices, and the context in which behaviors occur.

Record Keeping

This method involves keeping detailed records of observations, interviews, and other data collected during the research process. Record keeping is essential for ensuring the accuracy and reliability of the data, and for providing a basis for analysis and interpretation.

This method involves collecting data from a large sample of participants through a structured questionnaire. Surveys can be conducted in person, over the phone, through mail, or online. Surveys are useful for collecting data on attitudes, beliefs, and behaviors, and for identifying patterns and trends in a population.

Qualitative data analysis is a process of turning unstructured data into meaningful insights. It involves extracting and organizing information from sources like interviews, focus groups, and surveys. The goal is to understand people’s attitudes, behaviors, and motivations

Qualitative Research Analysis Methods

Qualitative Research analysis methods involve a systematic approach to interpreting and making sense of the data collected in qualitative research. Here are some common qualitative data analysis methods:

Thematic Analysis

This method involves identifying patterns or themes in the data that are relevant to the research question. The researcher reviews the data, identifies keywords or phrases, and groups them into categories or themes. Thematic analysis is useful for identifying patterns across multiple data sources and for generating new insights into the research topic.

Content Analysis

This method involves analyzing the content of written or spoken language to identify key themes or concepts. Content analysis can be quantitative or qualitative. Qualitative content analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns. Content analysis is useful for identifying patterns in media messages, public discourse, and cultural trends.

Discourse Analysis

This method involves analyzing language to understand how it constructs meaning and shapes social interactions. Discourse analysis can involve a variety of methods, such as conversation analysis, critical discourse analysis, and narrative analysis. Discourse analysis is useful for understanding how language shapes social interactions, cultural norms, and power relationships.

Grounded Theory Analysis

This method involves developing a theory or explanation based on the data collected. Grounded theory analysis starts with the data and uses an iterative process of coding and analysis to identify patterns and themes in the data. The theory or explanation that emerges is grounded in the data, rather than preconceived hypotheses. Grounded theory analysis is useful for understanding complex social phenomena and for generating new theoretical insights.

Narrative Analysis

This method involves analyzing the stories or narratives that participants share to gain insights into their experiences, attitudes, and beliefs. Narrative analysis can involve a variety of methods, such as structural analysis, thematic analysis, and discourse analysis. Narrative analysis is useful for understanding how individuals construct their identities, make sense of their experiences, and communicate their values and beliefs.

Phenomenological Analysis

This method involves analyzing how individuals make sense of their experiences and the meanings they attach to them. Phenomenological analysis typically involves in-depth interviews with participants to explore their experiences in detail. Phenomenological analysis is useful for understanding subjective experiences and for developing a rich understanding of human consciousness.

Comparative Analysis

This method involves comparing and contrasting data across different cases or groups to identify similarities and differences. Comparative analysis can be used to identify patterns or themes that are common across multiple cases, as well as to identify unique or distinctive features of individual cases. Comparative analysis is useful for understanding how social phenomena vary across different contexts and groups.

Applications of Qualitative Research

Qualitative research has many applications across different fields and industries. Here are some examples of how qualitative research is used:

  • Market Research: Qualitative research is often used in market research to understand consumer attitudes, behaviors, and preferences. Researchers conduct focus groups and one-on-one interviews with consumers to gather insights into their experiences and perceptions of products and services.
  • Health Care: Qualitative research is used in health care to explore patient experiences and perspectives on health and illness. Researchers conduct in-depth interviews with patients and their families to gather information on their experiences with different health care providers and treatments.
  • Education: Qualitative research is used in education to understand student experiences and to develop effective teaching strategies. Researchers conduct classroom observations and interviews with students and teachers to gather insights into classroom dynamics and instructional practices.
  • Social Work : Qualitative research is used in social work to explore social problems and to develop interventions to address them. Researchers conduct in-depth interviews with individuals and families to understand their experiences with poverty, discrimination, and other social problems.
  • Anthropology : Qualitative research is used in anthropology to understand different cultures and societies. Researchers conduct ethnographic studies and observe and interview members of different cultural groups to gain insights into their beliefs, practices, and social structures.
  • Psychology : Qualitative research is used in psychology to understand human behavior and mental processes. Researchers conduct in-depth interviews with individuals to explore their thoughts, feelings, and experiences.
  • Public Policy : Qualitative research is used in public policy to explore public attitudes and to inform policy decisions. Researchers conduct focus groups and one-on-one interviews with members of the public to gather insights into their perspectives on different policy issues.

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

  • Identify your research question: Qualitative research starts with a research question or set of questions that you want to explore. This question should be focused and specific, but also broad enough to allow for exploration and discovery.
  • Select your research design: There are different types of qualitative research designs, including ethnography, case study, grounded theory, and phenomenology. You should select a design that aligns with your research question and that will allow you to gather the data you need to answer your research question.
  • Recruit participants: Once you have your research question and design, you need to recruit participants. The number of participants you need will depend on your research design and the scope of your research. You can recruit participants through advertisements, social media, or through personal networks.
  • Collect data: There are different methods for collecting qualitative data, including interviews, focus groups, observation, and document analysis. You should select the method or methods that align with your research design and that will allow you to gather the data you need to answer your research question.
  • Analyze data: Once you have collected your data, you need to analyze it. This involves reviewing your data, identifying patterns and themes, and developing codes to organize your data. You can use different software programs to help you analyze your data, or you can do it manually.
  • Interpret data: Once you have analyzed your data, you need to interpret it. This involves making sense of the patterns and themes you have identified, and developing insights and conclusions that answer your research question. You should be guided by your research question and use your data to support your conclusions.
  • Communicate results: Once you have interpreted your data, you need to communicate your results. This can be done through academic papers, presentations, or reports. You should be clear and concise in your communication, and use examples and quotes from your data to support your findings.

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

  • Customer Feedback: A company may conduct qualitative research to understand the feedback and experiences of its customers. This may involve conducting focus groups or one-on-one interviews with customers to gather insights into their attitudes, behaviors, and preferences.
  • Healthcare : A healthcare provider may conduct qualitative research to explore patient experiences and perspectives on health and illness. This may involve conducting in-depth interviews with patients and their families to gather information on their experiences with different health care providers and treatments.
  • Education : An educational institution may conduct qualitative research to understand student experiences and to develop effective teaching strategies. This may involve conducting classroom observations and interviews with students and teachers to gather insights into classroom dynamics and instructional practices.
  • Social Work: A social worker may conduct qualitative research to explore social problems and to develop interventions to address them. This may involve conducting in-depth interviews with individuals and families to understand their experiences with poverty, discrimination, and other social problems.
  • Anthropology : An anthropologist may conduct qualitative research to understand different cultures and societies. This may involve conducting ethnographic studies and observing and interviewing members of different cultural groups to gain insights into their beliefs, practices, and social structures.
  • Psychology : A psychologist may conduct qualitative research to understand human behavior and mental processes. This may involve conducting in-depth interviews with individuals to explore their thoughts, feelings, and experiences.
  • Public Policy: A government agency or non-profit organization may conduct qualitative research to explore public attitudes and to inform policy decisions. This may involve conducting focus groups and one-on-one interviews with members of the public to gather insights into their perspectives on different policy issues.

Purpose of Qualitative Research

The purpose of qualitative research is to explore and understand the subjective experiences, behaviors, and perspectives of individuals or groups in a particular context. Unlike quantitative research, which focuses on numerical data and statistical analysis, qualitative research aims to provide in-depth, descriptive information that can help researchers develop insights and theories about complex social phenomena.

Qualitative research can serve multiple purposes, including:

  • Exploring new or emerging phenomena : Qualitative research can be useful for exploring new or emerging phenomena, such as new technologies or social trends. This type of research can help researchers develop a deeper understanding of these phenomena and identify potential areas for further study.
  • Understanding complex social phenomena : Qualitative research can be useful for exploring complex social phenomena, such as cultural beliefs, social norms, or political processes. This type of research can help researchers develop a more nuanced understanding of these phenomena and identify factors that may influence them.
  • Generating new theories or hypotheses: Qualitative research can be useful for generating new theories or hypotheses about social phenomena. By gathering rich, detailed data about individuals’ experiences and perspectives, researchers can develop insights that may challenge existing theories or lead to new lines of inquiry.
  • Providing context for quantitative data: Qualitative research can be useful for providing context for quantitative data. By gathering qualitative data alongside quantitative data, researchers can develop a more complete understanding of complex social phenomena and identify potential explanations for quantitative findings.

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

  • Exploring a new area: If little is known about a particular topic, qualitative research can help to identify key issues, generate hypotheses, and develop new theories.
  • Understanding complex phenomena: Qualitative research can be used to investigate complex social, cultural, or organizational phenomena that are difficult to measure quantitatively.
  • Investigating subjective experiences: Qualitative research is particularly useful for investigating the subjective experiences of individuals or groups, such as their attitudes, beliefs, values, or emotions.
  • Conducting formative research: Qualitative research can be used in the early stages of a research project to develop research questions, identify potential research participants, and refine research methods.
  • Evaluating interventions or programs: Qualitative research can be used to evaluate the effectiveness of interventions or programs by collecting data on participants’ experiences, attitudes, and behaviors.

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

  • Focus on subjective experience: Qualitative research is concerned with understanding the subjective experiences, beliefs, and perspectives of individuals or groups in a particular context. Researchers aim to explore the meanings that people attach to their experiences and to understand the social and cultural factors that shape these meanings.
  • Use of open-ended questions: Qualitative research relies on open-ended questions that allow participants to provide detailed, in-depth responses. Researchers seek to elicit rich, descriptive data that can provide insights into participants’ experiences and perspectives.
  • Sampling-based on purpose and diversity: Qualitative research often involves purposive sampling, in which participants are selected based on specific criteria related to the research question. Researchers may also seek to include participants with diverse experiences and perspectives to capture a range of viewpoints.
  • Data collection through multiple methods: Qualitative research typically involves the use of multiple data collection methods, such as in-depth interviews, focus groups, and observation. This allows researchers to gather rich, detailed data from multiple sources, which can provide a more complete picture of participants’ experiences and perspectives.
  • Inductive data analysis: Qualitative research relies on inductive data analysis, in which researchers develop theories and insights based on the data rather than testing pre-existing hypotheses. Researchers use coding and thematic analysis to identify patterns and themes in the data and to develop theories and explanations based on these patterns.
  • Emphasis on researcher reflexivity: Qualitative research recognizes the importance of the researcher’s role in shaping the research process and outcomes. Researchers are encouraged to reflect on their own biases and assumptions and to be transparent about their role in the research process.

Advantages of Qualitative Research

Qualitative research offers several advantages over other research methods, including:

  • Depth and detail: Qualitative research allows researchers to gather rich, detailed data that provides a deeper understanding of complex social phenomena. Through in-depth interviews, focus groups, and observation, researchers can gather detailed information about participants’ experiences and perspectives that may be missed by other research methods.
  • Flexibility : Qualitative research is a flexible approach that allows researchers to adapt their methods to the research question and context. Researchers can adjust their research methods in real-time to gather more information or explore unexpected findings.
  • Contextual understanding: Qualitative research is well-suited to exploring the social and cultural context in which individuals or groups are situated. Researchers can gather information about cultural norms, social structures, and historical events that may influence participants’ experiences and perspectives.
  • Participant perspective : Qualitative research prioritizes the perspective of participants, allowing researchers to explore subjective experiences and understand the meanings that participants attach to their experiences.
  • Theory development: Qualitative research can contribute to the development of new theories and insights about complex social phenomena. By gathering rich, detailed data and using inductive data analysis, researchers can develop new theories and explanations that may challenge existing understandings.
  • Validity : Qualitative research can offer high validity by using multiple data collection methods, purposive and diverse sampling, and researcher reflexivity. This can help ensure that findings are credible and trustworthy.

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

  • Subjectivity : Qualitative research relies on the subjective interpretation of researchers, which can introduce bias into the research process. The researcher’s perspective, beliefs, and experiences can influence the way data is collected, analyzed, and interpreted.
  • Limited generalizability: Qualitative research typically involves small, purposive samples that may not be representative of larger populations. This limits the generalizability of findings to other contexts or populations.
  • Time-consuming: Qualitative research can be a time-consuming process, requiring significant resources for data collection, analysis, and interpretation.
  • Resource-intensive: Qualitative research may require more resources than other research methods, including specialized training for researchers, specialized software for data analysis, and transcription services.
  • Limited reliability: Qualitative research may be less reliable than quantitative research, as it relies on the subjective interpretation of researchers. This can make it difficult to replicate findings or compare results across different studies.
  • Ethics and confidentiality: Qualitative research involves collecting sensitive information from participants, which raises ethical concerns about confidentiality and informed consent. Researchers must take care to protect the privacy and confidentiality of participants and obtain informed consent.

Also see Research Methods

About the author

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Muhammad Hassan

Researcher, Academic Writer, Web developer

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Chapter 2. Research Design

Getting started.

When I teach undergraduates qualitative research methods, the final product of the course is a “research proposal” that incorporates all they have learned and enlists the knowledge they have learned about qualitative research methods in an original design that addresses a particular research question. I highly recommend you think about designing your own research study as you progress through this textbook. Even if you don’t have a study in mind yet, it can be a helpful exercise as you progress through the course. But how to start? How can one design a research study before they even know what research looks like? This chapter will serve as a brief overview of the research design process to orient you to what will be coming in later chapters. Think of it as a “skeleton” of what you will read in more detail in later chapters. Ideally, you will read this chapter both now (in sequence) and later during your reading of the remainder of the text. Do not worry if you have questions the first time you read this chapter. Many things will become clearer as the text advances and as you gain a deeper understanding of all the components of good qualitative research. This is just a preliminary map to get you on the right road.

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Research Design Steps

Before you even get started, you will need to have a broad topic of interest in mind. [1] . In my experience, students can confuse this broad topic with the actual research question, so it is important to clearly distinguish the two. And the place to start is the broad topic. It might be, as was the case with me, working-class college students. But what about working-class college students? What’s it like to be one? Why are there so few compared to others? How do colleges assist (or fail to assist) them? What interested me was something I could barely articulate at first and went something like this: “Why was it so difficult and lonely to be me?” And by extension, “Did others share this experience?”

Once you have a general topic, reflect on why this is important to you. Sometimes we connect with a topic and we don’t really know why. Even if you are not willing to share the real underlying reason you are interested in a topic, it is important that you know the deeper reasons that motivate you. Otherwise, it is quite possible that at some point during the research, you will find yourself turned around facing the wrong direction. I have seen it happen many times. The reason is that the research question is not the same thing as the general topic of interest, and if you don’t know the reasons for your interest, you are likely to design a study answering a research question that is beside the point—to you, at least. And this means you will be much less motivated to carry your research to completion.

Researcher Note

Why do you employ qualitative research methods in your area of study? What are the advantages of qualitative research methods for studying mentorship?

Qualitative research methods are a huge opportunity to increase access, equity, inclusion, and social justice. Qualitative research allows us to engage and examine the uniquenesses/nuances within minoritized and dominant identities and our experiences with these identities. Qualitative research allows us to explore a specific topic, and through that exploration, we can link history to experiences and look for patterns or offer up a unique phenomenon. There’s such beauty in being able to tell a particular story, and qualitative research is a great mode for that! For our work, we examined the relationships we typically use the term mentorship for but didn’t feel that was quite the right word. Qualitative research allowed us to pick apart what we did and how we engaged in our relationships, which then allowed us to more accurately describe what was unique about our mentorship relationships, which we ultimately named liberationships ( McAloney and Long 2021) . Qualitative research gave us the means to explore, process, and name our experiences; what a powerful tool!

How do you come up with ideas for what to study (and how to study it)? Where did you get the idea for studying mentorship?

Coming up with ideas for research, for me, is kind of like Googling a question I have, not finding enough information, and then deciding to dig a little deeper to get the answer. The idea to study mentorship actually came up in conversation with my mentorship triad. We were talking in one of our meetings about our relationship—kind of meta, huh? We discussed how we felt that mentorship was not quite the right term for the relationships we had built. One of us asked what was different about our relationships and mentorship. This all happened when I was taking an ethnography course. During the next session of class, we were discussing auto- and duoethnography, and it hit me—let’s explore our version of mentorship, which we later went on to name liberationships ( McAloney and Long 2021 ). The idea and questions came out of being curious and wanting to find an answer. As I continue to research, I see opportunities in questions I have about my work or during conversations that, in our search for answers, end up exposing gaps in the literature. If I can’t find the answer already out there, I can study it.

—Kim McAloney, PhD, College Student Services Administration Ecampus coordinator and instructor

When you have a better idea of why you are interested in what it is that interests you, you may be surprised to learn that the obvious approaches to the topic are not the only ones. For example, let’s say you think you are interested in preserving coastal wildlife. And as a social scientist, you are interested in policies and practices that affect the long-term viability of coastal wildlife, especially around fishing communities. It would be natural then to consider designing a research study around fishing communities and how they manage their ecosystems. But when you really think about it, you realize that what interests you the most is how people whose livelihoods depend on a particular resource act in ways that deplete that resource. Or, even deeper, you contemplate the puzzle, “How do people justify actions that damage their surroundings?” Now, there are many ways to design a study that gets at that broader question, and not all of them are about fishing communities, although that is certainly one way to go. Maybe you could design an interview-based study that includes and compares loggers, fishers, and desert golfers (those who golf in arid lands that require a great deal of wasteful irrigation). Or design a case study around one particular example where resources were completely used up by a community. Without knowing what it is you are really interested in, what motivates your interest in a surface phenomenon, you are unlikely to come up with the appropriate research design.

These first stages of research design are often the most difficult, but have patience . Taking the time to consider why you are going to go through a lot of trouble to get answers will prevent a lot of wasted energy in the future.

There are distinct reasons for pursuing particular research questions, and it is helpful to distinguish between them.  First, you may be personally motivated.  This is probably the most important and the most often overlooked.   What is it about the social world that sparks your curiosity? What bothers you? What answers do you need in order to keep living? For me, I knew I needed to get a handle on what higher education was for before I kept going at it. I needed to understand why I felt so different from my peers and whether this whole “higher education” thing was “for the likes of me” before I could complete my degree. That is the personal motivation question. Your personal motivation might also be political in nature, in that you want to change the world in a particular way. It’s all right to acknowledge this. In fact, it is better to acknowledge it than to hide it.

There are also academic and professional motivations for a particular study.  If you are an absolute beginner, these may be difficult to find. We’ll talk more about this when we discuss reviewing the literature. Simply put, you are probably not the only person in the world to have thought about this question or issue and those related to it. So how does your interest area fit into what others have studied? Perhaps there is a good study out there of fishing communities, but no one has quite asked the “justification” question. You are motivated to address this to “fill the gap” in our collective knowledge. And maybe you are really not at all sure of what interests you, but you do know that [insert your topic] interests a lot of people, so you would like to work in this area too. You want to be involved in the academic conversation. That is a professional motivation and a very important one to articulate.

Practical and strategic motivations are a third kind. Perhaps you want to encourage people to take better care of the natural resources around them. If this is also part of your motivation, you will want to design your research project in a way that might have an impact on how people behave in the future. There are many ways to do this, one of which is using qualitative research methods rather than quantitative research methods, as the findings of qualitative research are often easier to communicate to a broader audience than the results of quantitative research. You might even be able to engage the community you are studying in the collecting and analyzing of data, something taboo in quantitative research but actively embraced and encouraged by qualitative researchers. But there are other practical reasons, such as getting “done” with your research in a certain amount of time or having access (or no access) to certain information. There is nothing wrong with considering constraints and opportunities when designing your study. Or maybe one of the practical or strategic goals is about learning competence in this area so that you can demonstrate the ability to conduct interviews and focus groups with future employers. Keeping that in mind will help shape your study and prevent you from getting sidetracked using a technique that you are less invested in learning about.

STOP HERE for a moment

I recommend you write a paragraph (at least) explaining your aims and goals. Include a sentence about each of the following: personal/political goals, practical or professional/academic goals, and practical/strategic goals. Think through how all of the goals are related and can be achieved by this particular research study . If they can’t, have a rethink. Perhaps this is not the best way to go about it.

You will also want to be clear about the purpose of your study. “Wait, didn’t we just do this?” you might ask. No! Your goals are not the same as the purpose of the study, although they are related. You can think about purpose lying on a continuum from “ theory ” to “action” (figure 2.1). Sometimes you are doing research to discover new knowledge about the world, while other times you are doing a study because you want to measure an impact or make a difference in the world.

Purpose types: Basic Research, Applied Research, Summative Evaluation, Formative Evaluation, Action Research

Basic research involves research that is done for the sake of “pure” knowledge—that is, knowledge that, at least at this moment in time, may not have any apparent use or application. Often, and this is very important, knowledge of this kind is later found to be extremely helpful in solving problems. So one way of thinking about basic research is that it is knowledge for which no use is yet known but will probably one day prove to be extremely useful. If you are doing basic research, you do not need to argue its usefulness, as the whole point is that we just don’t know yet what this might be.

Researchers engaged in basic research want to understand how the world operates. They are interested in investigating a phenomenon to get at the nature of reality with regard to that phenomenon. The basic researcher’s purpose is to understand and explain ( Patton 2002:215 ).

Basic research is interested in generating and testing hypotheses about how the world works. Grounded Theory is one approach to qualitative research methods that exemplifies basic research (see chapter 4). Most academic journal articles publish basic research findings. If you are working in academia (e.g., writing your dissertation), the default expectation is that you are conducting basic research.

Applied research in the social sciences is research that addresses human and social problems. Unlike basic research, the researcher has expectations that the research will help contribute to resolving a problem, if only by identifying its contours, history, or context. From my experience, most students have this as their baseline assumption about research. Why do a study if not to make things better? But this is a common mistake. Students and their committee members are often working with default assumptions here—the former thinking about applied research as their purpose, the latter thinking about basic research: “The purpose of applied research is to contribute knowledge that will help people to understand the nature of a problem in order to intervene, thereby allowing human beings to more effectively control their environment. While in basic research the source of questions is the tradition within a scholarly discipline, in applied research the source of questions is in the problems and concerns experienced by people and by policymakers” ( Patton 2002:217 ).

Applied research is less geared toward theory in two ways. First, its questions do not derive from previous literature. For this reason, applied research studies have much more limited literature reviews than those found in basic research (although they make up for this by having much more “background” about the problem). Second, it does not generate theory in the same way as basic research does. The findings of an applied research project may not be generalizable beyond the boundaries of this particular problem or context. The findings are more limited. They are useful now but may be less useful later. This is why basic research remains the default “gold standard” of academic research.

Evaluation research is research that is designed to evaluate or test the effectiveness of specific solutions and programs addressing specific social problems. We already know the problems, and someone has already come up with solutions. There might be a program, say, for first-generation college students on your campus. Does this program work? Are first-generation students who participate in the program more likely to graduate than those who do not? These are the types of questions addressed by evaluation research. There are two types of research within this broader frame; however, one more action-oriented than the next. In summative evaluation , an overall judgment about the effectiveness of a program or policy is made. Should we continue our first-gen program? Is it a good model for other campuses? Because the purpose of such summative evaluation is to measure success and to determine whether this success is scalable (capable of being generalized beyond the specific case), quantitative data is more often used than qualitative data. In our example, we might have “outcomes” data for thousands of students, and we might run various tests to determine if the better outcomes of those in the program are statistically significant so that we can generalize the findings and recommend similar programs elsewhere. Qualitative data in the form of focus groups or interviews can then be used for illustrative purposes, providing more depth to the quantitative analyses. In contrast, formative evaluation attempts to improve a program or policy (to help “form” or shape its effectiveness). Formative evaluations rely more heavily on qualitative data—case studies, interviews, focus groups. The findings are meant not to generalize beyond the particular but to improve this program. If you are a student seeking to improve your qualitative research skills and you do not care about generating basic research, formative evaluation studies might be an attractive option for you to pursue, as there are always local programs that need evaluation and suggestions for improvement. Again, be very clear about your purpose when talking through your research proposal with your committee.

Action research takes a further step beyond evaluation, even formative evaluation, to being part of the solution itself. This is about as far from basic research as one could get and definitely falls beyond the scope of “science,” as conventionally defined. The distinction between action and research is blurry, the research methods are often in constant flux, and the only “findings” are specific to the problem or case at hand and often are findings about the process of intervention itself. Rather than evaluate a program as a whole, action research often seeks to change and improve some particular aspect that may not be working—maybe there is not enough diversity in an organization or maybe women’s voices are muted during meetings and the organization wonders why and would like to change this. In a further step, participatory action research , those women would become part of the research team, attempting to amplify their voices in the organization through participation in the action research. As action research employs methods that involve people in the process, focus groups are quite common.

If you are working on a thesis or dissertation, chances are your committee will expect you to be contributing to fundamental knowledge and theory ( basic research ). If your interests lie more toward the action end of the continuum, however, it is helpful to talk to your committee about this before you get started. Knowing your purpose in advance will help avoid misunderstandings during the later stages of the research process!

The Research Question

Once you have written your paragraph and clarified your purpose and truly know that this study is the best study for you to be doing right now , you are ready to write and refine your actual research question. Know that research questions are often moving targets in qualitative research, that they can be refined up to the very end of data collection and analysis. But you do have to have a working research question at all stages. This is your “anchor” when you get lost in the data. What are you addressing? What are you looking at and why? Your research question guides you through the thicket. It is common to have a whole host of questions about a phenomenon or case, both at the outset and throughout the study, but you should be able to pare it down to no more than two or three sentences when asked. These sentences should both clarify the intent of the research and explain why this is an important question to answer. More on refining your research question can be found in chapter 4.

Chances are, you will have already done some prior reading before coming up with your interest and your questions, but you may not have conducted a systematic literature review. This is the next crucial stage to be completed before venturing further. You don’t want to start collecting data and then realize that someone has already beaten you to the punch. A review of the literature that is already out there will let you know (1) if others have already done the study you are envisioning; (2) if others have done similar studies, which can help you out; and (3) what ideas or concepts are out there that can help you frame your study and make sense of your findings. More on literature reviews can be found in chapter 9.

In addition to reviewing the literature for similar studies to what you are proposing, it can be extremely helpful to find a study that inspires you. This may have absolutely nothing to do with the topic you are interested in but is written so beautifully or organized so interestingly or otherwise speaks to you in such a way that you want to post it somewhere to remind you of what you want to be doing. You might not understand this in the early stages—why would you find a study that has nothing to do with the one you are doing helpful? But trust me, when you are deep into analysis and writing, having an inspirational model in view can help you push through. If you are motivated to do something that might change the world, you probably have read something somewhere that inspired you. Go back to that original inspiration and read it carefully and see how they managed to convey the passion that you so appreciate.

At this stage, you are still just getting started. There are a lot of things to do before setting forth to collect data! You’ll want to consider and choose a research tradition and a set of data-collection techniques that both help you answer your research question and match all your aims and goals. For example, if you really want to help migrant workers speak for themselves, you might draw on feminist theory and participatory action research models. Chapters 3 and 4 will provide you with more information on epistemologies and approaches.

Next, you have to clarify your “units of analysis.” What is the level at which you are focusing your study? Often, the unit in qualitative research methods is individual people, or “human subjects.” But your units of analysis could just as well be organizations (colleges, hospitals) or programs or even whole nations. Think about what it is you want to be saying at the end of your study—are the insights you are hoping to make about people or about organizations or about something else entirely? A unit of analysis can even be a historical period! Every unit of analysis will call for a different kind of data collection and analysis and will produce different kinds of “findings” at the conclusion of your study. [2]

Regardless of what unit of analysis you select, you will probably have to consider the “human subjects” involved in your research. [3] Who are they? What interactions will you have with them—that is, what kind of data will you be collecting? Before answering these questions, define your population of interest and your research setting. Use your research question to help guide you.

Let’s use an example from a real study. In Geographies of Campus Inequality , Benson and Lee ( 2020 ) list three related research questions: “(1) What are the different ways that first-generation students organize their social, extracurricular, and academic activities at selective and highly selective colleges? (2) how do first-generation students sort themselves and get sorted into these different types of campus lives; and (3) how do these different patterns of campus engagement prepare first-generation students for their post-college lives?” (3).

Note that we are jumping into this a bit late, after Benson and Lee have described previous studies (the literature review) and what is known about first-generation college students and what is not known. They want to know about differences within this group, and they are interested in ones attending certain kinds of colleges because those colleges will be sites where academic and extracurricular pressures compete. That is the context for their three related research questions. What is the population of interest here? First-generation college students . What is the research setting? Selective and highly selective colleges . But a host of questions remain. Which students in the real world, which colleges? What about gender, race, and other identity markers? Will the students be asked questions? Are the students still in college, or will they be asked about what college was like for them? Will they be observed? Will they be shadowed? Will they be surveyed? Will they be asked to keep diaries of their time in college? How many students? How many colleges? For how long will they be observed?

Recommendation

Take a moment and write down suggestions for Benson and Lee before continuing on to what they actually did.

Have you written down your own suggestions? Good. Now let’s compare those with what they actually did. Benson and Lee drew on two sources of data: in-depth interviews with sixty-four first-generation students and survey data from a preexisting national survey of students at twenty-eight selective colleges. Let’s ignore the survey for our purposes here and focus on those interviews. The interviews were conducted between 2014 and 2016 at a single selective college, “Hilltop” (a pseudonym ). They employed a “purposive” sampling strategy to ensure an equal number of male-identifying and female-identifying students as well as equal numbers of White, Black, and Latinx students. Each student was interviewed once. Hilltop is a selective liberal arts college in the northeast that enrolls about three thousand students.

How did your suggestions match up to those actually used by the researchers in this study? It is possible your suggestions were too ambitious? Beginning qualitative researchers can often make that mistake. You want a research design that is both effective (it matches your question and goals) and doable. You will never be able to collect data from your entire population of interest (unless your research question is really so narrow to be relevant to very few people!), so you will need to come up with a good sample. Define the criteria for this sample, as Benson and Lee did when deciding to interview an equal number of students by gender and race categories. Define the criteria for your sample setting too. Hilltop is typical for selective colleges. That was a research choice made by Benson and Lee. For more on sampling and sampling choices, see chapter 5.

Benson and Lee chose to employ interviews. If you also would like to include interviews, you have to think about what will be asked in them. Most interview-based research involves an interview guide, a set of questions or question areas that will be asked of each participant. The research question helps you create a relevant interview guide. You want to ask questions whose answers will provide insight into your research question. Again, your research question is the anchor you will continually come back to as you plan for and conduct your study. It may be that once you begin interviewing, you find that people are telling you something totally unexpected, and this makes you rethink your research question. That is fine. Then you have a new anchor. But you always have an anchor. More on interviewing can be found in chapter 11.

Let’s imagine Benson and Lee also observed college students as they went about doing the things college students do, both in the classroom and in the clubs and social activities in which they participate. They would have needed a plan for this. Would they sit in on classes? Which ones and how many? Would they attend club meetings and sports events? Which ones and how many? Would they participate themselves? How would they record their observations? More on observation techniques can be found in both chapters 13 and 14.

At this point, the design is almost complete. You know why you are doing this study, you have a clear research question to guide you, you have identified your population of interest and research setting, and you have a reasonable sample of each. You also have put together a plan for data collection, which might include drafting an interview guide or making plans for observations. And so you know exactly what you will be doing for the next several months (or years!). To put the project into action, there are a few more things necessary before actually going into the field.

First, you will need to make sure you have any necessary supplies, including recording technology. These days, many researchers use their phones to record interviews. Second, you will need to draft a few documents for your participants. These include informed consent forms and recruiting materials, such as posters or email texts, that explain what this study is in clear language. Third, you will draft a research protocol to submit to your institutional review board (IRB) ; this research protocol will include the interview guide (if you are using one), the consent form template, and all examples of recruiting material. Depending on your institution and the details of your study design, it may take weeks or even, in some unfortunate cases, months before you secure IRB approval. Make sure you plan on this time in your project timeline. While you wait, you can continue to review the literature and possibly begin drafting a section on the literature review for your eventual presentation/publication. More on IRB procedures can be found in chapter 8 and more general ethical considerations in chapter 7.

Once you have approval, you can begin!

Research Design Checklist

Before data collection begins, do the following:

  • Write a paragraph explaining your aims and goals (personal/political, practical/strategic, professional/academic).
  • Define your research question; write two to three sentences that clarify the intent of the research and why this is an important question to answer.
  • Review the literature for similar studies that address your research question or similar research questions; think laterally about some literature that might be helpful or illuminating but is not exactly about the same topic.
  • Find a written study that inspires you—it may or may not be on the research question you have chosen.
  • Consider and choose a research tradition and set of data-collection techniques that (1) help answer your research question and (2) match your aims and goals.
  • Define your population of interest and your research setting.
  • Define the criteria for your sample (How many? Why these? How will you find them, gain access, and acquire consent?).
  • If you are conducting interviews, draft an interview guide.
  •  If you are making observations, create a plan for observations (sites, times, recording, access).
  • Acquire any necessary technology (recording devices/software).
  • Draft consent forms that clearly identify the research focus and selection process.
  • Create recruiting materials (posters, email, texts).
  • Apply for IRB approval (proposal plus consent form plus recruiting materials).
  • Block out time for collecting data.
  • At the end of the chapter, you will find a " Research Design Checklist " that summarizes the main recommendations made here ↵
  • For example, if your focus is society and culture , you might collect data through observation or a case study. If your focus is individual lived experience , you are probably going to be interviewing some people. And if your focus is language and communication , you will probably be analyzing text (written or visual). ( Marshall and Rossman 2016:16 ). ↵
  • You may not have any "live" human subjects. There are qualitative research methods that do not require interactions with live human beings - see chapter 16 , "Archival and Historical Sources." But for the most part, you are probably reading this textbook because you are interested in doing research with people. The rest of the chapter will assume this is the case. ↵

One of the primary methodological traditions of inquiry in qualitative research, ethnography is the study of a group or group culture, largely through observational fieldwork supplemented by interviews. It is a form of fieldwork that may include participant-observation data collection. See chapter 14 for a discussion of deep ethnography. 

A methodological tradition of inquiry and research design that focuses on an individual case (e.g., setting, institution, or sometimes an individual) in order to explore its complexity, history, and interactive parts.  As an approach, it is particularly useful for obtaining a deep appreciation of an issue, event, or phenomenon of interest in its particular context.

The controlling force in research; can be understood as lying on a continuum from basic research (knowledge production) to action research (effecting change).

In its most basic sense, a theory is a story we tell about how the world works that can be tested with empirical evidence.  In qualitative research, we use the term in a variety of ways, many of which are different from how they are used by quantitative researchers.  Although some qualitative research can be described as “testing theory,” it is more common to “build theory” from the data using inductive reasoning , as done in Grounded Theory .  There are so-called “grand theories” that seek to integrate a whole series of findings and stories into an overarching paradigm about how the world works, and much smaller theories or concepts about particular processes and relationships.  Theory can even be used to explain particular methodological perspectives or approaches, as in Institutional Ethnography , which is both a way of doing research and a theory about how the world works.

Research that is interested in generating and testing hypotheses about how the world works.

A methodological tradition of inquiry and approach to analyzing qualitative data in which theories emerge from a rigorous and systematic process of induction.  This approach was pioneered by the sociologists Glaser and Strauss (1967).  The elements of theory generated from comparative analysis of data are, first, conceptual categories and their properties and, second, hypotheses or generalized relations among the categories and their properties – “The constant comparing of many groups draws the [researcher’s] attention to their many similarities and differences.  Considering these leads [the researcher] to generate abstract categories and their properties, which, since they emerge from the data, will clearly be important to a theory explaining the kind of behavior under observation.” (36).

An approach to research that is “multimethod in focus, involving an interpretative, naturalistic approach to its subject matter.  This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them.  Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives." ( Denzin and Lincoln 2005:2 ). Contrast with quantitative research .

Research that contributes knowledge that will help people to understand the nature of a problem in order to intervene, thereby allowing human beings to more effectively control their environment.

Research that is designed to evaluate or test the effectiveness of specific solutions and programs addressing specific social problems.  There are two kinds: summative and formative .

Research in which an overall judgment about the effectiveness of a program or policy is made, often for the purpose of generalizing to other cases or programs.  Generally uses qualitative research as a supplement to primary quantitative data analyses.  Contrast formative evaluation research .

Research designed to improve a program or policy (to help “form” or shape its effectiveness); relies heavily on qualitative research methods.  Contrast summative evaluation research

Research carried out at a particular organizational or community site with the intention of affecting change; often involves research subjects as participants of the study.  See also participatory action research .

Research in which both researchers and participants work together to understand a problematic situation and change it for the better.

The level of the focus of analysis (e.g., individual people, organizations, programs, neighborhoods).

The large group of interest to the researcher.  Although it will likely be impossible to design a study that incorporates or reaches all members of the population of interest, this should be clearly defined at the outset of a study so that a reasonable sample of the population can be taken.  For example, if one is studying working-class college students, the sample may include twenty such students attending a particular college, while the population is “working-class college students.”  In quantitative research, clearly defining the general population of interest is a necessary step in generalizing results from a sample.  In qualitative research, defining the population is conceptually important for clarity.

A fictional name assigned to give anonymity to a person, group, or place.  Pseudonyms are important ways of protecting the identity of research participants while still providing a “human element” in the presentation of qualitative data.  There are ethical considerations to be made in selecting pseudonyms; some researchers allow research participants to choose their own.

A requirement for research involving human participants; the documentation of informed consent.  In some cases, oral consent or assent may be sufficient, but the default standard is a single-page easy-to-understand form that both the researcher and the participant sign and date.   Under federal guidelines, all researchers "shall seek such consent only under circumstances that provide the prospective subject or the representative sufficient opportunity to consider whether or not to participate and that minimize the possibility of coercion or undue influence. The information that is given to the subject or the representative shall be in language understandable to the subject or the representative.  No informed consent, whether oral or written, may include any exculpatory language through which the subject or the representative is made to waive or appear to waive any of the subject's rights or releases or appears to release the investigator, the sponsor, the institution, or its agents from liability for negligence" (21 CFR 50.20).  Your IRB office will be able to provide a template for use in your study .

An administrative body established to protect the rights and welfare of human research subjects recruited to participate in research activities conducted under the auspices of the institution with which it is affiliated. The IRB is charged with the responsibility of reviewing all research involving human participants. The IRB is concerned with protecting the welfare, rights, and privacy of human subjects. The IRB has the authority to approve, disapprove, monitor, and require modifications in all research activities that fall within its jurisdiction as specified by both the federal regulations and institutional policy.

Introduction to Qualitative Research Methods Copyright © 2023 by Allison Hurst is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

What is Qualitative in Qualitative Research

Affiliations.

  • 1 1Department of Sociology, Uppsala University, Uppsala, Sweden.
  • 2 2Seminar for Sociology, Universität St. Gallen, St. Gallen, Switzerland.
  • 3 3Department of Media and Social Sciences, University of Stavanger, Stavanger, Norway.
  • PMID: 31105362
  • PMCID: PMC6494783
  • DOI: 10.1007/s11133-019-9413-7

What is qualitative research? If we look for a precise definition of qualitative research, and specifically for one that addresses its distinctive feature of being "qualitative," the literature is meager. In this article we systematically search, identify and analyze a sample of 89 sources using or attempting to define the term "qualitative." Then, drawing on ideas we find scattered across existing work, and based on Becker's classic study of marijuana consumption, we formulate and illustrate a definition that tries to capture its core elements. We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. This formulation is developed as a tool to help improve research designs while stressing that a qualitative dimension is present in quantitative work as well. Additionally, it can facilitate teaching, communication between researchers, diminish the gap between qualitative and quantitative researchers, help to address critiques of qualitative methods, and be used as a standard of evaluation of qualitative research.

Keywords: Epistemology; Methods; Phenomenology; Philosophy of science; Qualitative research.

  • Research article
  • Open access
  • Published: 25 November 2021

Mental health professionals’ perceived barriers and enablers to shared decision-making in risk assessment and risk management: a qualitative systematic review

  • Nafiso Ahmed   ORCID: orcid.org/0000-0001-6732-1317 1 ,
  • Sally Barlow 1 ,
  • Lisa Reynolds 2 ,
  • Nicholas Drey 3 ,
  • Fareha Begum 1 ,
  • Elizabeth Tuudah 4 &
  • Alan Simpson 4 , 5 , 6  

BMC Psychiatry volume  21 , Article number:  594 ( 2021 ) Cite this article

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Risk assessment and risk management are fundamental processes in the delivery of safe and effective mental health care, yet studies have shown that service users are often not directly involved or are unaware that an assessment has taken place. Shared decision-making in mental health systems is supported by research and advocated in policy. This systematic review (PROSPERO: CRD42016050457) aimed to explore the perceived barriers and enablers to implementing shared decision-making in risk assessment and risk management from mental health professionals’ perspectives.

PRISMA guidelines were followed in the conduct and reporting of this review. Medline, CINAHL, EMBASE, PsycINFO, AMED and Internurse were systematically searched from inception to December 2019. Data were mapped directly into the Theoretical Domains Framework (TDF), a psychological framework that includes 14 domains relevant to behaviour change. Thematic synthesis was used to identify potential barriers and enablers within each domain. Data were then matched to the three components of the COM-B model: Capability, Opportunity, and Motivation.

Twenty studies met the eligibility criteria. The findings of this review indicate that shared decision-making is not a concept commonly used in mental health services when exploring processes of risk assessment and risk management. The key barriers identified were ‘power and best interest’ (social influences) and ‘my professional role and responsibility’ (social/professional role and identity). Key enablers were ‘therapeutic relationship’ (social influences) and ‘value collaboration’ (reinforcement). The salient barriers, enablers and linked TDF domains matched COM-B components ‘opportunity’ and ‘motivation’.

The review highlights the need for further empirical research to better understand current practice and mental health professionals’ experiences and attitudes towards shared decision-making in risk assessment and risk management.

Peer Review reports

In mental health services, Shared Decision Making (SDM) is a means of delivering recovery orientated care through involving individuals in decisions about their care. For a decision to be ‘shared’ it must involve: at least two participants, the sharing of information, and a decision that is made and agreed upon by all parties [ 1 ]. These criteria are reflected in a shared decision model [ 2 ], which proposes that SDM occurs when all participants are informed, involved, and influential in the decision-making process. It is, however, emphasised that the three SDM components are on a sliding scale of influence that is dependent on context, capacity and desire to influence [ 2 ].

In shared decision-making, the aim is to recognise and utilise the unique expertise of healthcare professionals and services users to produce better decisions, and potentially better outcomes. While healthcare professionals may be experts in diagnosis, aetiology, prognosis, treatment options, and outcome probabilities [ 3 ]; service users are experts about the impact of the condition on their lives, their preferences, their personal attitudes towards risks, and often know what works best for them regarding their condition and treatment [ 4 ].

Studies report positive effects of SDM interventions on patient outcomes within different mental health populations. A randomised control trial (RCT) for people with depression reported a positive impact on patient participation in treatment decision-making and patient satisfaction [ 5 ]. Another RCT of an intervention for people with schizophrenia found SDM improved social recovery [ 6 ]. A pilot trial of a SDM intervention with veterans with post-traumatic stress disorder (PTSD) found positive impacts on patients’ receptivity to evidence-based treatment [ 7 ]. In contrast, some studies report no significant effect of SDM on clinical outcomes for people with severe mental illness [ 8 ] and depression [ 9 ], although they acknowledge that further long-term work may be needed to detect an effect.

Shared decision-making is endorsed and advocated in international healthcare policy [ 10 , 11 ]. Research has found that both service users and professionals support SDM. A qualitative research synthesis examining stakeholders’ attitudes towards SDM in mental health reported that service users valued their voice being heard, listened to, and supported to express themselves in encounters with professionals [ 12 ]. Several barriers to SDM were identified from the service user’s perspective, including feelings of perceived inadequacy, fear of being judged and a lack of trust. Barriers to SDM for professionals included: the service user lacking cognitive capacity or insight; where stigma negatively influenced the service user’s attitude towards SDM; and the professional’s own attitudes, motivation, willingness, empathy, and ability to engage and implement SDM. Professionals also highlighted challenges surrounding the competing priorities of their role, mainly them being accountable and responsible for managing risk.

Implementing SDM may pose challenges when there are concerns about the potential risks to self or others [ 13 , 14 ]. In these circumstances, mental health professionals (MHP) may not feel able to engage service users in decisions about their care. Potential barriers cited in the literature include inadequate training in suicide prevention [ 15 ]; fears about negative adverse reaction from individuals who pose a risk to other [ 16 ] and the ‘blame culture’ observed in mental health care [ 17 ], whereby MHPs are increasingly fearful of culpability and litigation. It has been suggested that this has resulted in more defensive or risk-averse practice intended to prevent harm [ 18 , 19 ].

Risk in mental health care is often used to refer to the possibility of an adverse event, outcome or behaviour arising from the unwanted actions of the service user [ 20 , 21 ]: notably risk of harm to self, others, or both, and may include self-harm, suicide, or violence. Risk also signifies the vulnerabilities that a person with mental illness may be exposed to, such as side effects from medication, exploitation, victimisation, bullying, and discrimination [ 22 , 23 ]. These risks occur frequently but are considered less in the assessment and management of risks [ 24 ].

Risk Assessment (RA) and Risk Management (RM) are the mechanisms used by MHPs to identify and minimise risk. There are three main approaches to assessing risk in mental health care: unstructured clinical judgement, actuarial methods and structured clinical judgement [ 25 ]. Unstructured clinical judgement typically involves professionals making judgements based on their clinical experience, opinion, intuition or ‘gut feeling’. Actuarial methods provide the assessor with a statistical means to combine information and calculate risk [ 26 ]. The subjective nature and poor predictive accuracy of these approaches have resulted in recommendations for them not to be used on their own in clinical practice [ 27 ]. Structured clinical judgement is considered the best approach to assessing risk [ 28 ]; this involves the use of a standardised RA tool to aid a professional in their clinical judgement [ 25 ].

Nonetheless, studies have found wide variability in the methods used to assess risk in UK mental health services [ 29 ] and forensic services in Australia and New Zealand [ 30 ]. These studies agree that a more consistent approach to RA is needed in mental health services. A multitude of evidence-based guidance is available to help standardise the process and support professionals in their assessment of risk [ 28 , 31 , 32 , 33 ]. A model for assessing suicidality, for example, provides guidance on the importance of language, the structure of the clinical interview, questioning, actuarial tools and risk categorisation [ 31 ].

Risk management is informed by the RA and includes the key actions or strategies that are designed to prevent or limit undesirable outcomes. Strategies may include treatment, supervision (i.e. help with planning daily activities), or monitoring (i.e. identifying and looking out for early warning signs) [ 28 ]. Several RM and safety planning interventions have been developed that can be used to mitigate, contain or improve RM [ 34 , 35 , 36 ].

The need to involve service users in the RA and RM process has been advocated in current professional guidance, policy, and research [ 28 , 33 , 37 ]. Involving service users is a means of minimising the gap between professionals and service users’ perspectives of risk [ 38 , 39 ] and thus, ensuring that the plan developed meets the individual’s needs [ 33 ]. This can lead to more accurate prediction and management of risk. Another potential benefit of involvement is that the individual is empowered to take responsibility for their choices, which can be a motivator for change [ 40 ]. It has been suggested that service user involvement can improve confidence and self-management skills, which may have long term impacts on reducing dependency on services, thereby increasing cost-effectiveness [ 37 ].

The UK Department of Health (DH) best practice guideline, specifically recommends SDM. Studies have shown, however, that service users are often unaware that a RA has taken place [ 41 , 42 ].

Although Higgins, Doyle [ 24 ] found that more than three-quarters of MHPs reported ‘always’ involving service users in risk assessment (77.8%) and safety planning (78.4%), only 50% of the respondents reported that they ‘always’ informed service users about their risk level, while only 43% of the respondents reported that they ‘always’ developed a shared responsibility with the service user for safety. Despite professionals reporting a high rate of service user involvement, these findings suggest that SDM is not routinely nor fully implemented.

A recent systematic review of mixed methods studies explored the service users’ perspective of helpful RM practices within mental health services [ 43 ]. Two categories of beneficial RM practices were identified: interpersonal relationships and communication; and agency and autonomy. A key finding was that trust fosters openness in relationships and enables discussion of risks, especially when service users felt that their distress was understood or their accounts were validated by professionals. Service users preferred professionals to maintain responsibility for RM initially but that eventually (at their own pace) they wished to regain control.

Other systematic reviews in this field have focused on interventions that promote SDM in RA and RM in forensic mental health settings [ 36 , 44 ]. A qualitative synthesis of research examining professionals attitudes towards SDM in the broader field of mental health exists [ 12 ], however, the authors acknowledge that the rigour of a full systematic review was not adopted. There is currently no systematic review of MHPs’ experiences and attitudes towards implementing SDM in the assessment and management of risk. A synthesis of studies will improve our understanding of the discrepancies in reported practice and identify factors that may help or hinder its implementation. The specific review question was:

What do mental health professionals perceive as the barriers and enablers to SDM in RA and RM?

This review was conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 45 ]. The protocol is registered on PROSPERO (CRD42016050457).

Eligibility criteria

The SPIDER framework (sample, phenomenon of interest, design, evaluation, research type) was used to specify eligibility criteria [ 46 ]. An additional S was added to capture the ‘setting’ criterion of adult mental health services. The SPIDER framework is a tool for developing a search strategy that has been designed from the PICO tool, specifically for reviews that aim to synthesise qualitative and mixed-method research studies. Due to limited resources, only studies written in English were included in the review. Table  1 lists the inclusion and exclusion criteria.

Search strategy

The EBSCOhost and Ovid Online platforms were used to search six electronic bibliographic databases: MEDLINE; EMBASE; PsycINFO; CINAHL; AMED and Internurse. Databases were searched from inception. The last search was completed on the 4th December 2019.

The search strategy used a combination of medical subject headings (MeSH) and free text key terms related to concepts of ‘mental health’, ‘health professionals’, ‘experiences’, ‘shared decision making’, ‘risk assessment’ and ‘risk management’. A full electronic search strategy is presented in Additional file 1 .

Two grey literature databases were also searched for relevant unpublished empirical research studies; Bielefeld Academic Search Engine (BASE) and Open Grey. Citation chaining was performed on all articles selected for inclusion to identify further studies of interest, and this involved searching the reference lists (backward chaining) and using Google Scholar to identify and review papers that had cited the included articles (forward chaining).

Study selection

Search results were imported into a systematic review management software EPPI-reviewer 4 [ 47 ] and duplicates removed. Two-stage screening was undertaken: stage 1 screened the titles and abstracts of studies against the eligibility criteria; stage 2, further assessed full-text of potential studies against the eligibility criteria. Study authors were contacted if more information was needed.

To minimise risk of bias, two authors (NA and FB) independently assessed titles and abstracts, and subsequently, full-text articles. A full-text review was carried out if at least one of the reviewers believed that the study met the inclusion criteria at the title and abstract screening stage. At full-text review, any discrepancies regarding eligibility were resolved by consensus and in consultation with a third author (AS/LR). Also, studies were included only once if they had multiple articles. The original or most relevant to the review question was used as the primary article for the study’s results.

The ‘Three I’s Scale of Influence Model’ [ 2 ] was used as a framework for study selection. Studies that reported on a least one of the three components (informed, involved and influential) of SDM in RA and RM were included. Stacey, Felton [ 2 ] definitions of the SDM components can be found in Additional file 2 .

Data extraction

An electronic data extraction form was devised and piloted on two of the included studies. The following data items were extracted: author(s), publication year, research question/aim, geographical location, sample size, setting, data collection, and method of analysis. The entire results sections, including direct quotations and author interpretations were imported directly into NVivo 11 software [ 48 ]. For studies with multiple publications, results were extracted and collated from all the linked reports but only one publication was used as the source of study results. Data extraction was carried out by the first author (NA) and cross-checked by a second author (SB): disagreements were resolved through discussion.

Quality appraisal

Dixon-Woods, Shaw [ 49 ] prompts were used to assess the quality and relevance of individual studies within this review. These prompts focus on the universal features of qualitative research and have been devised to ‘sensitise appraisers to the various dimensions of articles that require evaluation’ (p224). Two reviewers (NA and AJ or UF – see acknowledgements) read the papers independently and answered a series of questions on the quality appraisal checklist (e.g., Are the research questions clear?). They recorded their response as Yes (Y), No (N), Can’t tell (−). A rating system was then used to categorise the papers: Key paper (meets all quality criteria and clearly fits with review question); Satisfactory (meets most quality criteria and fits well to review question); Unsure (mixed responses to quality criteria and lack of clarity regarding relevance to review question); and Poor (does not meet quality criteria) [ 50 ]. No studies were excluded based on methodological quality; however, a sensitivity analysis (described below) was conducted to see the impact of removing lower-rated studies on the review findings. Any disagreements were discussed in full, and a rating was agreed (Additional file 3 ).

Data synthesis

The Theoretical Domains Framework (TDF) was used to explore the factors that influence the implementation of SDM in RA and RM with individuals with mental illness. The TDF is a behaviour change framework developed by a group of experts to simplify and integrate the large number of psychological theories relevant to behaviour change [ 51 ]. The TDF has been used by researchers across a range of healthcare settings to identify determinants of behaviour, namely the barriers and enablers to implementation, and to inform intervention design [ 52 ]. The original TDF has 12 domains derived from 33 health and social psychology theories and 128 key theoretical constructs. The framework was later validated and refined by Cane, O’Connor [ 52 ] to include 14 theoretical domains. The revised version of the framework was used in this review, Cane et al. (2012) definition of each domain is presented in (Additional file 2 ).

The Capability, Opportunity, and Motivation (COM-B) model was then used to condense the relevant TDF domains into three components that interact to predict behaviour. The model was developed as part of the broader framework of the behaviour change wheel [ 53 ] and provides a basis for intervention design. Each component of the COM-B model is divided into sub-components that capture important distinctions. Capability can be physical (e.g. skills) or psychological (e.g. interpersonal skills and knowledge) and represents an individual’s capacity to carry out the behaviour. Opportunity can be physical (e.g. environmental factors) and social (e.g. social influences) and is defined as all the factors that lie outside the individual that influence the behaviour. Motivation can be reflective (e.g. beliefs, intentions) or automatic (e.g. emotions) and characterises the brain processes that drive behaviour [ 53 ]. The most relevant TDF domains and linked components that are likely important to changing behaviour were identified [ 52 ].

The data synthesis process drew on established analysis methods recommended in the TDF guidelines [ 54 ], and used in previous studies applying the TDF [ 55 , 56 , 57 ]. Data synthesis involved the following six stages:

Step 1: developing a coding manual

A coding guide was developed based on the definitions of the three components of SDM [ 2 ], and the 14 domains and 84 constructs from Cane, O’Connor [ 52 ]. To provide guidance and confidence that a piece of text represents a domain, statements of how the domain applies to the research context were also included in the coding guide.

Step 2: pilot coding exercise

To ensure consistency between coders and refine the coding guideline, two coders (NA and ET) jointly coded the extracted findings from two randomly selected included papers. Any disagreements were discussed until consensus was reached; where consensus could not be reached a third researcher was consulted. The final version of the coding guide is included in Additional file 2 .

Step 3: coding papers and assessing reliability

Two researchers (NA and ET) independently coded the extracted findings from the remaining included papers using the coding guideline and via NVivo 11 software [ 48 ]. Findings relating to the target behaviour were coded to the SDM components [ 2 ], whereas potential barriers and enablers identified within the included papers were coded to the 14 domains of the TDF [ 52 ]. For example, the statement ‘“[the risk assessment is] one thing … you never discuss with service users just in case it alarms them”’ was coded to the ‘informed’ component and the ‘beliefs about consequences’ domain. If the participant’s response or the author’s interpretation represented more than one TDF domain, the text was coded to multiple domains. For example, “You know that you’re going to have suicide risk but you think well, the psychologists will deal with that bit … so to want to deal with it, even as part of the overall care, I think you’d want some type of supervision” was coded to both “social professionals’ role and identity” and “social influences”.

Inter-coder reliability was assessed by calculating the percentage agreement/disagreement (prior to consensus being reached), to measure consistency in coding within and across domains [ 58 ]. Reliability between two coders is considered acceptable if percentage agreement > 60% is achieved [ 54 ]. Discrepancies in coding were addressed by NA and ET with a consensus reached by discussion. AS was available to resolve any disputes over discrepancies; however, this was not required.

Step 4: developing overarching themes

Data within the domains were further analysed by the lead researcher (NA) using thematic synthesis [ 59 ]. Text coded into each domain were compared across papers, and findings representing similar ideas were grouped together. An overarching theme was then generated to categorise the initial themes. The overarching themes represent the specific factor perceived to influence SDM in RA and RM. For example, findings that suggest rapport, alliance or connection facilitate discussion about risk with service users were categorised as ‘therapeutic relationship’.

Step 5: mapping the COM-B model to the TDF domains

The relevant TDF domains were matched to the COM-B components [ 53 ]. The lead researcher (NA) drew on the links between the TDF domains and COM-B components identified by a group of experts in a consensus exercise reported in Cane, O’Connor [ 52 ]. The most relevant TDF domains (and themes within) were identified based on a frequency count of studies by domain. The TDF domains (and themes within) identified in at least 60% ( n  = 11) of the included studies were considered salient in understanding the target behaviour.

Step 6: sensitivity analysis

A sensitivity analysis was carried out to determine whether the methodological quality of studies impacted on the findings of the review. The results from the lowest-rated studies were removed from the synthesis to see if this influenced the key themes originally identified. No studies were excluded based on methodological quality.

A total of 8211 papers were yielded in the databases searches; and 1420 additional papers were included from other sources. After the removal of duplicates, a total of 8652 papers were eligible for screening. Following title and abstract screening, 8491 papers were excluded, and 161 full text papers were reviewed; 134 papers were excluded at full-text, and 20 studies (reported in 27 papers) met the inclusion criteria for this review. The PRISMA diagram of study selection can be seen in Fig.  1 .

figure 1

A PRISMA flow diagram detailing the search strategy and results (Moher et al., 2009) [ 45 ]

All papers gained the rating of either key paper ( n  = 9) or satisfactory ( n  = 11). Papers were rated satisfactory if they did not meet all of the quality criteria and/or did not clearly fit with the review question. For example, papers that reported on specific risk decisions i.e. decision-making regarding neuroleptic medication [ 60 ]; specific RM practices i.e. clinician-patient alliance during mechanical restraint [ 61 ]; or contained very limited findings relevant to the review question [ 62 ] were rated satisfactory. Quality appraisal of the included studies can be seen in Additional file 3 .

Study characteristics

Over half of the included studies were conducted in the UK ( n  = 11), two in Belgium and the remaining studies in Australia, Canada, Taiwan, Denmark, Sweden, Italy, and Norway. The papers were published between 1999 and 2019 and were predominantly qualitative in design ( n  = 18). Semi-structured interviews were the most common data collection method ( n  = 15); four studies utilised focus groups [ 61 , 63 , 64 , 65 ]; and one used in-depth interviews [ 60 ]. Three studies used unstructured observation in addition to semi-structured interviews [ 66 , 67 , 68 ]. One study surveyed participants before conducting the qualitative interviews [ 69 ], and one described using a mixed-methods approach [ 65 ] comprising of focus groups and a quantitative analysis technique (i.e., inductive content analysis). Their findings, however, included several illustrative quotes that were deemed relevant to the review question.

Over half of the studies gathered data from adult psychiatric/forensic inpatient settings. ( n  = 12). Other settings included adult community mental health teams ( n  = 4) or both inpatient and community mental health settings ( n  = 4).

The included studies focused on a range of risk issues including suicidality ( n  = 7); risk to others [ 16 ]; self-neglect [ 70 ] and violence [ 64 ]. Two of the studies explored safety and risk within the broader topic of care-planning [ 20 , 62 ]. Other studies explored specific RM practices [ 61 , 65 , 68 , 71 ]; the tension between promoting recovery and managing risk [ 66 , 72 ]; and risk-minimisation and risk-taking [ 73 ]. One study examined clinicians’ perspectives of supporting service users who wished to discontinue from medication, which is a form of risk-taking [ 60 ]. Several of the included studies [ 16 , 20 , 66 , 71 , 74 ] had multiple publications from the same study [ 42 , 75 , 76 , 77 , 78 , 79 , 80 ]. The characteristics of the included studies are summarised in Table  2 .

Coder reliability and sensitivity analysis

Interrater agreement between the two coders across the three SDM components and 14 TDF domains ranged from 83.1 to 100%. For the sensitivity analysis, removing all the studies that gained an overall ‘satisfactory’ rating [ 60 , 61 , 62 , 63 , 64 , 67 , 68 , 69 , 70 , 73 , 74 ] resulted in one domain (knowledge) no longer being relevant. The same salient TDF domains were identified, with the addition of ‘beliefs about consequences’ and ‘emotions’. The findings of the sensitivity analysis demonstrated that the exclusion of these studies would have had a small impact on the overall findings.

The following section begins by summarising study findings relating to the components of SDM. Then, the key barriers and enablers within each of the TDF domains and COM-B components are summarised.

SDM components

None of the included studies directly referred to the term SDM in RA and RM with individuals with mental illness. However, all studies reported on at least one component of the ‘Three Is of Influence’ SDM model [ 2 ].

The ‘informed’ component was identified in several of the included studies. Professionals spoke openly about not discussing risk with service users; that RA was undertaken without the service user’s knowledge; and that the content of the RA was not always shared with the individual [ 16 , 20 , 62 , 63 , 66 , 81 ]. Conversely, in describing RM practices, professionals emphasised the importance of providing information to service users during observation and mechanical restraint [ 61 , 71 , 82 ]. In a study about forensic mental health services, professionals believed that keeping the service user informed and prepared before meetings, as well as discussing risk factors contributed to forming a trusting relationship [ 64 ].

In other studies, professionals acknowledged that they do not generally involve service users in the RA process [ 16 , 20 , 63 , 64 ], some reported involving service users for obligatory, and information gathering purposes [ 20 , 67 , 70 , 82 ]. Others believed it was important to involve and collaborate with service users in RM planning [ 64 , 65 , 83 ] for reasons discussed later.

The ‘influence’ component was also mapped to findings within this review. Some professionals described the need to make decisions on behalf of the service user [ 66 , 70 , 72 , 83 ], thus inhibiting the service user’s influence in the RA and RM process. Other professionals valued collaborating with service users and supporting their choice in decisions that involved risk [ 60 , 64 ]. Positive risk-taking was encouraged to support service users’ influence in decision-making [ 66 , 71 , 72 , 73 ].

Barriers and enablers

Through the use of the TDF [ 52 ], potential barriers and enablers to the SDM components in RA and RM were identified. Barriers and enablers ranged across twelve domains: knowledge, skills; social/professional role and identity; beliefs about capabilities; beliefs about consequences; reinforcement; intentions; goals; memory, attention and decision processes; environmental context and resources; social influences; and emotions . Relevant domains, and the how they relate to barriers and enablers are presented in Table  3 .

TDF domains (and the themes within) were then mapped to COM-B components and sub-components (Fig.  2 ). Based on a frequency count of studies by domain (Table 3 ), the most relevant domains were: social influences ( n  = 18); social/professional role and identity ( n  = 16); reinforcement ( n  = 14); goal ( n  = 13); environmental context and resources ( n  = 12) and beliefs about capabilities ( n  = 11). The key barriers were ‘power and best interest’ ( n  = 11) and ‘my professional role and responsibility’ ( n  = 12). The key enablers were ‘therapeutic relationship’ ( n  = 12), and ‘value collaboration’ ( n  = 11). The key barriers and enablers linked with TDF domains: ‘social influences’, ‘social/professional role and identity’ and ‘reinforcement’. The salient TDF domains (and barriers and enablers within) matched COM-B components: ‘opportunity’ and ‘motivation’.

figure 2

TDF domains mapped to COM-B components and sub-components

Below, is a summary of the review findings of the barriers and enablers matched to TDF domain and COM-B component. Both first-order (direct quotations) and second-order (authors interpretation) themes are presented using illustrative quotations. Direct quotes have been presented in italics.

Professionals referred to policy and legislation in guiding them in supporting service users’ influence in decision-making or risk-taking [ 73 ]. In a study about service users who wish to discontinue taking neuroleptic medication [ 60 ], professionals working in early intervention services demonstrated openness towards supporting discontinuation and said that this was guided by their understanding of the National Institute for Health and Care Excellence (NICE) guidelines and research:

“The evidence we have is that it is worth giving most people a trial off the medication in order to see if their illness would be a relapsing recurring one” [ 60 ] p244)

Memory, attention and decision processes

Professionals’ implementation behaviours may have been influenced by the type of risk identified. In Langan [ 16 ], professionals believed that service users were less involved in a discussion about risk to others than risk to self:

“I think risk to other people tends to be thought of as being...You know, look at it historically and see what has happened before. Whereas, risk of suicide, although that’s important as well, tends to be more on how the patient feels, in terms of harming themselves, at that time. So, probably, risk to self is more centred on the patient” [ 16 ] p476)

In other studies, individual factors were key in determining service users’ readiness to be released from mechanical restraint [ 61 ]; and if risk-taking could be supported [ 60 , 73 ].

Some professionals attributed their reluctance to discussing suicide with service users to lack of formal training [ 69 , 74 , 81 , 83 ] . Limited training was also considered a barrier to engaging service users in RM:

“I have never done any training on this topic. I know that I may change my attitude towards the patients, but I don’t know how to do it” [ 65 ] p7)

Some professionals’ believed that additional training in risk would enhance their practice in caring for suicidal service users [ 69 ]. In a study about risk to others [ 16 ], a psychiatrist explained how training in RA and RM enabled him to discuss risk openly with a service user:

Professionals described adapting the language of risk to aid them in communicating with service users. In Langan and Lindow [ 42 ], professionals questioned the helpfulness in using the term risk: “I mean, I don’t like to use terms like ‘risk’ in that sense, but I mean I think he does accept that there are concerns about his behaviour” [ 42 ] p16). Instead, they reported using terms such as “early warning signs” or “relapse indicators” to facilitate discussion about risk with service users.

In a study about suicidal ideation, nurses reported adapting their communication to align with the service user’s communication preferences [ 82 ]:

“I ask patients how they feel about it when I talk to them about suicidality and how they prefer to have these interactions” [ 82 ] p2870)

Professionals also reported adapting their communication style with individuals who wished to discontinue taking neuroleptic medication [ 60 ]. The communication style that they adopted, i.e. collaborative or coercive, was based on their judgement of the risk factors and perceived outcome. Other professionals were reported to have used euphemistic language to avoid open dialogue about suicide with service users, : “oh, well, you know, if you’re not feeling right” [ 81 ] p105)).

Opportunity

Social influences.

The tension between managing risk and promoting recovery resulted in professionals experiencing role conflict [ 20 , 64 , 72 , 73 , 74 , 83 ]. Findings indicate that RM practices influence other aspects of care including therapeutic relationships, decision-making, and recovery [ 64 , 65 , 72 , 74 , 78 ]. In a study about continuous observation [ 71 , 77 ], a professional explained that while developing a therapeutic relationship with the service user was important, the utmost priority was maintaining safety:

“Every encounter with a patient should be made therapeutic … but it isn’t the primary purpose. The primary purpose is safety. I think the policy makes it very clear that safety trumps everything else” [ 77 ] p553)

Findings suggest that the pressure of managing risk could lead to power imbalances that inhibit service users’ involvement or influence in the decision-making process:

‘ … risk dominated the decision-making of professionals to such an extent that it defined how service users were understood and treated with limited evidence of power-sharing and involvement of service users in decisions’ [ 66 ] p1142).

Some professionals reported using coercion [ 68 ] to maintain the service users safety:

“If we indicate to patients that we are going to the seclusion room, then few patients say they’d “rather not”. But even when they say they’d “rather not”, we do it anyway, and then we emphasise, “Look, we want to protect you against your thoughts” [ 83 ] p1129)

Decisions about risk are sometimes made by professionals in what they believe to be the service user’s best interest [ 16 , 20 , 60 , 65 , 66 , 70 , 71 , 72 , 74 ]:

“Of course it can get difficult if the service user says no, “I want, I want to do it my way now,“ Um, and then you have to have a very different conversation and you need to say that we feel collectively as a team that at this stage it’s still a risk” [ 72 ] p4)

Factors relating directly to the service user, such as insight or mental capacity impede on the SDM components in RA and RM [ 42 , 60 , 61 , 65 , 70 , 71 , 72 , 73 , 83 ]:

“We can share the responsibility with the patient only when he has totally understood and accepted what is happening to himself, otherwise it is very difficult … ” [ 65 ] p7)

A risk-averse team culture was highlighted as a barrier to positive risk-taking [ 72 , 73 ] and the sharing of risk information with service users:

“To my shame, there are cases that I follow that culture, that I hide that risk assessment or secret. Why? Because I want to protect the individual from the knowledge of that.., their illness that they have can be a risk to themselves or to the others. It’s a practice that I’m not very comfortable but nevertheless, I raise my hand and say I have” [ 20 ] p6)

Some professionals’ reluctance to talk openly about suicide or trauma was reinforced in team culture [ 81 , 83 ]. In a study about service users who wished to discontinue from neuroleptic medication, professionals spoke about the change in service culture [ 60 ]. With the ‘old’ culture described as less acceptant of discontinuation and service users influence in the decision-making process.

Developing a therapeutic relationship and trust enabled professionals to facilitate discussion about risk with service users [ 16 , 69 , 82 ], as well to collaborate in RM [ 71 ] and gather information for RA purposes [ 67 ]:

“Rapport is key . .. it means I can get the information I need and that they’re more likely to actually tell me whether they’re still suicidal or not, and then from there we can work out what they need together” [ 69 ] p310)

Others felt that knowing the service user enabled them to support positive risk-taking:

“If you’re beginning to know a bit more about who they are, you might feel able to take greater therapeutic risks, in the hope of encouraging them to take responsibility” [ 71 ] p478)

A good therapeutic relationship was reported to be beneficial in challenging situation, for example, communicating negative decisions to service users [ 64 ]. Therapeutic trust and alliance were also viewed as critical strategies in engaging service users in RM [ 61 , 65 ].

Conversely, where the quality of the therapeutic relationship was less than ideal, it was considered a barrier to involving service users in RA and RM. Staff acknowledged that they were more likely to err on the side of caution with RM with service users that were less well known [ 71 ]. In other studies, professionals recognised that the therapeutic relationship may be better with one professional compared to another and that this could impact on the service user’s openness about risk and engagement in RM [ 61 , 77 ]. Authors concluded that professionals lack of interaction with service users and distance from their subjective experience suggest a relational distance [ 66 ]. In a study about the risk to others, professional’s tentativeness in language, for example, “I try to discuss risk with him” , was attributed to the quality of therapeutic relationship [ 42 ].

Supervision was considered essential and beneficial to support discussing risk, such as suicidality, with service users [ 69 , 81 , 83 ]; and perceived as an enabler to engaging service users in RM [ 71 , 77 ]:

Environmental context and resources

Professionals reported that they did not have the time or opportunity to get to know or directly relate to service users [ 65 , 66 , 71 ]. High caseloads, staff shortages, lack of training and resources were highlighted as factors that impede practice [ 63 , 66 , 69 ]. For example, in Forsberg, Tai [ 60 ], the pressure of increased caseloads, administration and service targets were reported as barriers to supporting service users to discontinue from medication. In a study about suicidal ideation, a nurse reported:

“Sometimes I spend more time reporting than being present with the person. That is a shame! I sometimes wonder what is most important, “What I write down or what I really do with that person?”. Of course, I believe it is important that you write down things in case something happens, but I also believe that there are too many administrative tasks” [ 83 ] p1130)

In Felton, Repper [ 66 ], professionals recognised that most of their time was spent in an office and that this caused a spatial distance between themselves and service users. Professionals were critical of organisational requirements to persistently document risks [ 82 ] and the amount of screening and assessments they needed to do for service users at risk of suicide. Instead, they questioned the value of these tasks as they believed it limited their time to meaningfully engage with service users.

Findings indicate that the setting or meeting structure used to discuss and make decisions about risk may impede on the service user’s involvement or influence in the process [ 62 , 66 ].

“Formal ward round-based review meetings were named as a place for risks to be discussed although not necessarily in the presence of service users” [ 62 ] p12).

Nurses reported the difficulty in communicating risk with service users when they were not invited to the RA meeting or not directly involved in developing the RA [ 64 ], and they believed that this hindered their ability to promote the service users participation in decisions. Professionals also highlighted that if the environment or setting was inappropriate, for example unsafe, noisy and distracting, this could impact on the service users’ involvement in RM [ 65 , 77 ].

Local policies and procedures were considered an aid to communication about risk with service users. In Langan [ 16 ], a voluntary sector organisation reported that their local policies encourage openness between professionals and service users about risk. Specifically, it was a requirement for professionals to complete RA forms jointly with service users, or the voluntary organisation operated an open access policy where individuals could freely access any information about their risks.

Social/professional role and identity

Findings indicate that professionals retain responsibility for managing risk [ 16 , 20 , 63 , 65 , 66 , 70 , 71 , 72 , 74 ], which may be influencing the service users involvement in the RA and RM process.

Findings mapped to this domain were associated with data within the ‘social influences’ domain, for example, professionals making decisions in the best interest of the service user or conforming to their teams’ risk averse culture. In Holley, Chambers [ 72 ], professionals described making decisions on behalf of service users by drawing on their professional knowledge and expertise for managing risk.

In many of the included studies, decision-making regarding risk was described as a team responsibility with little mention of the service user’s input [ 66 , 67 , 70 , 72 ]. In a study about service users who self-neglect, the author concluded that:

“it was not clear how often the teams made decisions based on what they thought was appropriate for the client, rather than on the client’s personal and informed choice” [ 70 ].

Professionals’ responsibility for reducing risk of harm to the individual and others conflicted with their intention to work collaboratively with the service user:

“You know they [meaning colleagues] have a duty to protect the populous from risk. Sometimes that may not chime with the personal interest of the patient ...” [ 60 ] p243)

Findings indicate that therapeutic engagement with individuals at risk of suicide was not always prioritised by nurses or realised by other MHP’s as part of their role [ 69 , 81 ]. For some, facilitating discussion about suicidality or trauma was considered the responsibility of the psychologist or psychiatrist [ 81 , 83 ] . For others, the service user was responsible for initiating discussion about suicidality:

“Basically, it’s down to them to tell us … we’ve no other way really unless they already told their relative so they’re gonna have to be speaking about it” [ 81 ] p105)

Beliefs about capabilities

Conversations with service users about risk and therapeutic risk-taking were described as difficult [ 16 , 66 , 81 ]. Some professionals lacked confidence in approaching the topic of ‘risk to others’ with service users [ 16 ], whereas others expressed a lack of confidence about how to talk with service users about suicide [ 81 ]. Professionals highlighted the need for more training on suicidality in their education:

‘ … although all participants are specialized in mental health nursing, one of them stated that she does not feel educated or confident enough to talk with patients about suicide, and another informant stated that there should be much more focus on caring for suicidal persons in the education’ [ 80 ] p33).

They acknowledged that risk information might not be shared with service users because of potential disagreements [ 20 ]. In a study about the risk to others, reaching a mutual agreement with an individual who disagreed with their identified risks was described as challenging:

“Very difficult. Very difficult. He’ll deny many of the incidents that I’ve told you about. He’ll say that the police are wrong, that they were harassing him. That he didn’t do these things. That he’s not a risk to other people …. So it’s very, very difficult, yeah, to find any middle ground there really” [ 42 ] p18)

When the service user and professional had conflicting viewpoints about discontinuation from medication, this impeded on the service user’s influence in the process [ 60 ]. The professional, instead, attempted to increase the service user’s agreement with their perspective.

On the other hand, the level of agreement about risk was highlighted as an enabler to involving service users in RM:

“Obviously, if they can acknowledge that there is a problem then we’re in a much better position to ensure that they put something in place which works” [ 42 ] p17)

Beliefs about consequences

Professionals expressed a range of views about the potential consequences of involving service users in the RA and RM process. Many were concerned that discussing risk with a service user or involving them in RM would cause the individual distress or harm [ 16 , 20 , 81 , 82 ]:

“Sometimes we avoid involving patients in order to preserve his saneness. In the psychiatric field is difficult to evaluate how much information the patient may tolerate” [ 65 ] p7)

Some professionals believed that discussing risk with others could be damaging to their therapeutic relationship with the service user and lead to disengagement [ 16 ] . Others were worried that involving service users in RA would reinforce stigma:

“the stigma of the mental health is still very prevalent in our society so by doing a risk assessment you more or less emphasise that stigma. .. You are a very risky person, you’re dangerous to yourself, and you’re dangerous to society, whereas this doesn’t go well with the recovery that we try to achieve for that person” [ 20 ] p8)

Professionals also feared negative consequences for themselves by discussing risk with service users. In Awenat, Peters [ 81 ], following a suicide, professionals were worried about being blamed for negligence. This resulted in them recording detailed information to clear themselves of blame should a suicide occur, as well as cautious discussions with service users in case they disclosed suicidal ideation. Similarly, in other studies, professionals highlighted the need to document decisions accurately and follow protocol to protect themselves from blame should their decision be questioned [ 74 , 83 ]. Professionals who encouraged risk-taking [ 73 ] or supported a service user’s wish to discontinue from medication [ 60 ] were also fearful of being blamed if negative outcomes occurred as a result of their decision.

“Risk-taking and promoting an individual’s freedom is encouraged but you’re conscious of the fact that if someone gets hurt, it’s not just them. .. criticism will be levelled at each level within the authority” [ 73 ] p180)

In other studies, fear of being blamed influenced the decision-making process and resulted in professionals adopting defensive or restrictive approaches [ 71 , 83 ].

Professionals’ concern for their personal safety acted as a barrier to both discussing ‘risk to others’ with service users [ 16 ] and involving service users in RM [ 65 ].

Some professionals were resigned to their current practice of not involving service users in the RA and RM process [ 20 ]. Others were willing to move towards involving service user more in the process:

“I’m quite open to change and including the person more in it, rather than it just being professionals talking about the risks” [ 16 ] p477)

Nonetheless, professionals’ aspirations for greater service user involvement in RA and RM did not necessarily reflect practice [ 72 ]:

‘Whilst everyone considered openness a good idea in principle, practice had not always caught up with aspirations’ [ 16 ].

The extent to which professionals consider the SDM components important in the RA and RM process influenced their implementation behaviour. For example, involving service users in RA and RM was not considered a priority for some professionals:

‘… they had given little consideration to how they could directly and actively involve clients in the assessment and management of risk’ [ 63 ] p810).

For others, interpersonal engagement with service users at risk of suicide was not prioritised [ 69 ] and discussion about suicidal ideation was considered counterproductive [ 68 ]. Obligatory reasons for involving service users in RA and RM practices, i.e. for assessment and information gathering purposes, were provided by professionals in several studies [ 20 , 61 , 63 , 65 , 67 , 70 , 74 , 82 , 83 ]:

“In order to take care of these suicidal patients, I try to build a trusting relationship with them. If I can build a good trusting relationship with them, they will trust me. They will give me the information I need and then we can explore their problems and try to help them to prevent future suicide attempts” [ 67 ] p687)

Forming agreements with service users (or a shared-decision) was considered an important step in the RM process [ 61 , 82 , 83 ]. In several studies, professionals emphasised the importance in openly communicating about risk, as well as providing the service user with knowledge and information about their risk [ 16 , 65 , 71 , 83 ]:

‘These nurses avoid imposing instant protection and instead engage in dialogue with patients that facilitates understanding of risks and potentially risky situations (e.g. taking a bath), the meaning that patients attach to risks and potentially risky situations, and what can be done to address risks’ [ 83 ] p1126).

Professionals acknowledged that RM was more likely to be helpful or effective if the service user was involved in the RA process [ 16 , 61 , 65 , 67 , 69 , 71 , 82 , 83 ]:

“I think it’s more of a risk if it’s other people talking about them behind their back. I think the more that things can be out in the open, the less of a risk it is” [ 42 ] p14)

Reinforcement

Professionals emphasised the importance in communicating to service users about their risk [ 72 ], as well as encouraging service users to talk about their distress or suicidality [ 81 , 82 , 83 ].

“The opportunity to interact is the ultimate. .. it’s a really important interaction.. . It can be the difference between life and death” [ 69 ] p309)

Some believed that RM was more likely helpful if service users were involved in decision-making [ 71 ]. Others valued supporting choice and collaboration, and this guided their interaction with service users who wished to discontinue from medication [ 60 ]. Positive risk-taking encouraged some professionals to support the service user’s choice or influence [ 61 , 62 , 71 , 72 , 73 ].

Professionals were motivated to support service users’ influence and positive risk-taking as this favoured autonomy, empowerment, and recovery [ 65 , 66 , 72 , 73 , 82 ]:

“if it is her wish to look after her finances then actually she is entitled and that needs to be explored very slowly with her [. . .] You can give her advice whether it’s a good decision or a bad decision but it’s her decision to take control of it” [ 72 ] p3)

Professionals stressed the importance in demonstrating empathy, compassion and instilling hope [ 67 , 69 , 77 , 82 , 83 ]. They believed that empathy supported service user to work through their distress and talk about suicidal feelings:

“I feel it’s important to feel and show empathy. If you don’t have empathy, you have no way of realising the patients’ torment and discomfort, or how serious or how strongly they feel about attempting suicide” [ 67 ] p687)

Professionals expressed negative emotions that impact on the assessment and management of risk with individuals with mental illness. In Barnicot, Insua-Summerhayes [ 71 ], anxiety in preventing harm and about being blamed may have influenced decision-making around continuous observation and led to restrictive practices. The possibility of a negative outcome from supporting a service user to discontinue from medication triggered anxiety in professionals [ 60 ]. While approaching the issue of risk created anxiety for some professionals [ 20 , 66 , 80 ], others expressed fear in approaching sensitive topics such as risk to others [ 16 ] or suicidal risk [ 69 , 80 , 81 ]. For example, a professional described their concern about possibly being the last person to have spoken to someone who takes their own life:

“I think it’s scary because you don’t want to be the last person having that conversation and they do something. You don’t want to think you’ve done anything that could have erm, actually aggravated them or tipped them over the edge or you’ve said something that has made them think about something” [ 81 ] p106)

The findings of this review indicate that SDM is not a term commonly used in mental health services when exploring processes of RA and RM. The components of SDM (i.e. informed, involved and influential) are referred to but are not being implemented consistently in the RA and RM process. MHPs spoke openly about not discussing risk with service users, involving service users in the process, or supporting their influence in decision-making about risk. This is in line with studies of service user accounts of RA and RM [ 20 , 38 , 42 ], where it was found that service users were often unaware of the RA and RM plan.

Through the use of the TDF [ 52 ], this systematic review has provided a comprehensive understanding of the perceived barriers and enablers to the SDM components in RA and RM from the literature. The salient COM-B components (and linked TDF domains) identified from the findings of this review were social and physical opportunity (i.e. ‘social influences’ and ‘environmental context and resources’), which refer to the social, cultural, and environmental influences on behaviour; and reflective and automatic motivation (i.e. ‘social/professional role and identity’, ‘beliefs about capabilities’, ‘goals’ and ‘reinforcement’), which characterise the cognitive processes that drive behaviour.

Mental health policy at an international level recommends that the processes of RA and RM are collaborative, person-centered and based on SDM [ 28 , 33 , 84 ]; however, there were many factors identified in this review that potentially impede on practice.

Managing risk and delivering recovery-orientated care were experienced as competing priorities that led to practice dilemma. The tension was believed to arise from organisational expectations, legal responsibilities, and contradictory frameworks of practice. Policy guidelines emphasise protection, harm minimisation, public safety, and duty of care. At the same time, they recommend recovery-orientated care based upon the components of SDM, positive risk-taking, therapeutic relationships, and empowerment. Our findings show professionals acknowledged the primacy of RM and the impact this had on other aspects of care including therapeutic relationships, and positive risk-taking. Boardman and Roberts [ 37 ] argue that it is possible to strike a balance between managing risk and delivering recovery-orientated care. They propose shifting towards a ‘person-centred’ approach to assessing and managing risk, based on SDM and collaborative safety planning.

Reluctance to talk about suicidality with service users or to support positive risk-taking were believed to be reinforced in a risk-averse team culture. Simpson [ 85 ] reported similar findings and highlighted the need for a ‘safe’ environment for professionals to openly discuss and disclose uncertainties, challenges, and alternative treatment options within the team. In addition, the findings of this review suggest that professionals tried to make decisions about risk with the service users’ best interests in mind, but at times this was the professionals’ interpretation of best interests and not necessarily the service users’. This is problematic as a capacitous service user is the expert on their own best interests, and even when not capacitous their wishes and views ought to be taken into account. Factors relating directly to the service user, such as capacity and insight, were considered barriers to discussing risk and collaborating with the service user in RM planning, thus impeding best interest decisions. It has been argued that paternalistic approaches to decision-making can cause practice conflicts between the ethical principles of autonomy on the one hand, and beneficence and non-maleficence on the other [ 86 ]. In mental health care, decision-making can be justified in terms of respecting the service user’s choice (autonomy), the professional’s duty to promote good (beneficence) or to prevent harm (non-maleficence) [ 86 ]. Paternalistic approaches may conflict with the autonomy of a non-capacitous service user, when decisions are made based on the professional’s interpretation of the best interests of the service user [ 87 ]. Experiencing a mental health crisis can lead to diminished capacity and competency to make a decision and in these circumstances, paternalistic interventions have been justified on the basis of the requirements of beneficence or non-maleficence [ 88 ]. Breeze [ 87 ] argues that the assessment of rationality or competency has the potential to be subjective and value-laden and although paternalism maybe justified in some situations, it should be exercised with caution. For example, where there is a disagreement between the professional and service user about what is considered ‘best interest’, it should not be assumed that the service user’s view is irrational or wrong, indeed S. 1 [ 4 ] Mental Capacity Act (2005) states that ‘A person is not to be treated as unable to make a decision merely because he makes an unwise decision’ [ 89 ].

Developing a therapeutic relationship and gaining trust enabled professionals to engage service users in a discussion about suicidality, as well as promote positive risk-taking and collaboration in RM. A recent review of service users’ perspectives of helpful RM practices [ 43 ] found that interpersonal relationship and communication aided RM to be inclusive for service users, and trust was considered to nurture open discussion about risk. In a study about risk-taking and recovery [ 90 ], service users also reported that therapeutic relationships developed trust, and this led to more collaborative discussion and decision-making.

Study findings suggest that professionals may be retaining responsibility for assessing and managing risk and thus limiting the extent to which service users are genuinely informed, involved or influential in the process. Negative beliefs about consequences inhibited professionals from implementing SDM in RA and RM. On the one hand, professionals were concerned that discussing risk could cause the service user distress, to disengage from services or to feel stigmatised. On the other hand, professionals were fearful of being blamed or investigated for negative outcomes from supporting risk-taking, i.e. service user who wished to discontinue taking medication, or discussing suicidality. Fear of blame led professionals to accurately document decision-making to protect themselves should their decision later be questioned, as well as cautious discussion with service users about suicidal thoughts. A culture of blame and risk aversion continues to pervade mental health services [ 91 ] that is said to derive from bureaucratic management styles, perception of failure, political pressures and media influences [ 17 , 92 ]. In a qualitative study, professionals expressed concern about restrictive practices potentially being eliminated as they felt that this would make it difficult to maintain safety [ 93 ], they were also concerned about being blamed when a negative event occurred.

Beliefs about consequences provoked negative emotions for some professionals who expressed fear and anxiety about preventing harm. Supervision was highlighted as a potential aid in discussing suicidal thoughts with service users. Tragic incidents can occur even after careful decision-making and thus professionals can expect to be accountable for decision-making and its implementation but not outcomes that they have no control over [ 94 ]. For MHPs to move away from paternalism and towards promoting SDM, change needs to occur at an organisational level [ 37 ]. Professionals need to know that they have managerial and institutional support, especially in situations where negative beliefs about consequences occur. It has been suggested that developing therapeutic risk-taking in practice requires organisations to support professionals by creating safe spaces to hold uncertainty, multidisciplinary working, shared responsibility, and supervision [ 88 ]. Institutional fear of things ‘going wrong’ is perhaps not helped by anxieties over the hyperbolic media coverage that can emerge when tragedies do occur [ 95 ]. The media’s negative portrayal of mental illness and misleading association with violence [ 96 , 97 ] may contribute to the continuing stigma of mental illness; the preoccupation with RM in mental health care; and misconstrued perceptions of the actual risk posed towards others by individuals with mental illness. In reality, 11% of all homicide convictions in the UK, during 2007–2017, were patient homicides, i.e. people in contact with mental health services in the 12 months prior to the offence [ 98 ].

A lack of confidence in discussing certain types of risks with service users was reported. For example, professionals expressed concern about approaching the topic of ‘risk to others’, and uncertainty in how to initiate discussions about suicide with service users. In mental health care, it is recognised that RA and RM practices focus on ‘dramatic risks’ that involve harm to self or others [ 37 ], however, these extreme harms relate to a minority of people in contact with mental health services [ 98 ]. Dixon [ 38 ] compared service users’ and professionals’ ratings of risk and found that service users identified more risks in relation to their vulnerability, such as self-neglect and suicide, than professionals did. In contrast, professionals identified more risks than service users in relation to risk of harm to others. A collaborative safety planning approach would broaden the focus on risk to include the service users perspectives and consideration of everyday risks that are common but less considered in the assessment and management of risk [ 37 ]. Changing the language of risk and basing discussions on safety-concerns offer an alternative way of involving service users’ in managing their own safety and opens discussion about risk [ 99 ].

In the current review, professionals questioned their ability to resolve disagreements with service users about risk to others. Consequently, conversations about risk with service users were described as difficult. A systematic review of services users’ perceptions of RM found that people’s desire for honesty and collaboration was fulfilled when they felt listened to, despite disagreements. Furthermore, some services users recognised disagreements as an authentic part of therapeutic relationships [ 43 ].

As found in the broader recovery-focused care-planning and coordination literature [ 75 ], high caseloads, staff shortages and a lack of resource were highlighted as factors that impede on practice. Professionals reported limited time or opportunity to support positive risk-taking or to meaningfully engage with service users. Also, insufficient training on RA and RM negatively impacted on professionals’ ability to talk openly about risk. In one of the included studies, a professional who had received RA training reported that it enabled him to face his fear in discussing risk openly with an individual who had previously damaged his office [ 16 ]. Higgins, Doyle [ 24 ] research findings indicate the need for training to enable professionals to adopt a collaborative RA and safety planning approach. They propose training delivered at undergraduate and postgraduate level that includes the skills necessary to engage service users and carers in the RA and safety planning process [ 24 ].

Professionals’ behaviours were guided by their perceived outcomes of implementing the SDM components in RA and RM. For some professionals, involving service users in RA and RM was not always a priority. Others, however, were motivated to involve service users for obligatory reasons, as well as to provide the service users with knowledge and understanding of risks and to collaborate in reducing risks. Similar to the findings of Kaminskiy, Senner [ 12 ] qualitative synthesis, this review found support from MHPs for the idea of implementing SDM or working in collaboration with service users. Professionals’ emphasised the importance in communicating risk with service users, promoting empowerment and demonstrating empathy. Some described adjusting their language to facilitate discussions about risk, while others expressed aspiration towards involving service users in future RA and RM practices, though it was recognised that aspiration may have not yet influenced practice.

Strengths and limitations

This is the first systematic review of evidence reporting MHPs’ experiences and attitudes towards SDM in RA and RM, which uses both the TDF and COM-B model to synthesise findings. The synthesis was informed by several psychological theories of behaviour change and empirical findings of included studies. However, this review is not without limitation. First, the review focused on MHPs’ experiences of SDM in RA and RM: thus, the service users’ perspective was not examined, however, a recent mixed-studies systematic review explored helpful RM practices from the service users’ viewpoint [ 43 ]. Secondly, despite conducting systematic searches, SDM is not a well-indexed term, and researchers have varying interpretations of the concept: therefore, our search strategy may have inadvertently missed relevant studies. To capture relevant studies in our searches, we used MeSH terms for SDM and included additional free text key terms related to the concept of SDM (e.g., service user involvement, patient-centred and recovery). Thirdly, it is important to note that the decision to conduct a qualitative systematic review was derived from the findings of a scoping search, which indicated that qualitative methods dominated this field of research. A quantitative survey study [ 24 ] was identified, however, but excluded on the review’s eligibility criteria. Although the key focus of Higgins, Doyle [ 24 ] study was to explore mental health nurses’ practices and confidence in RA and safety planning, there was a small amount of data relevant to the findings of this review (i.e. stakeholders’ involvement in the RA and RM process). Lastly, the wide variation in methods employed in qualitative research poses challenges in the assessment of quality and synthesis of findings for the purpose of a review [ 49 , 100 ]. Indeed, the present review included studies that differed significantly in design, data collection, and analysis method. Also, qualitative research is often criticised for lack of generalisability. Therefore, the strength of recommendation that can be made from the evidence included in this review is limited. Future reviews may wish to further develop the themes identified in this review by sourcing data from quantitative work.

The findings of this review indicate that there may be limited SDM in RA and RM with individuals with mental health problems. Langan and Lindow [ 42 ] reported this over 15 years ago, and despite policies endorsing SDM it, largely, is not happening. This review identifies some of the key issues that may be underpinning this lack of action and warrant further intervention and investigation.

Through the use of the TDF and COM-B model, this review explored MHPs’ perceived barriers and enablers to SDM in RA and RM. Key barriers were ‘power and best interest’ and ‘my professional role and responsibility’, whereas key enablers were ‘therapeutic relationship’ and ‘value collaboration’. These barriers, enablers and TDF domains matched COM-B components ‘opportunity’ and ‘motivation’.

The finding from the present study contributes to existing knowledge of SDM by providing insight into MHPs’ perceived barriers and enablers to implementing SDM in RA and RM. Consistent with a qualitative synthesis study that examined attitudes towards SDM in the broader field of mental health [ 12 ], a lack of capacity was identified as a barrier to SDM in RA and RM. Although justified in some situations, mental capacity fluctuates with time and research indicates that most psychiatric in-patients are capable of making key treatment decisions [ 101 ]. There are also methods that can be used to incorporate service users’ views, such as decision aids, advance directives and advocacy. Therefore, diminished capacity alone should not be reason to exclude the service user from the RA and RM process, as the service user may still be able to offer valuable insight into their perspective and experiences with risk that can inform the RM plan. The present study also highlights the importance of the therapeutic relationship in facilitating discussions about risk with service users, which corroborates findings from a previous systematic review of service users’ perspectives of RM [ 43 ]. Therefore, increasing professionals’ opportunity to develop the therapeutic relationship may influence their motivation to implement SDM in RA and RM.

The findings of this review highlight a complex range of social, cultural and environmental factors that together influence SDM in RA and RM. This information will be relevant to policymakers and practitioners and can also be used to develop targeted interventions aimed at changing practice in this challenging area. However, these findings are based on a small number of studies that are heterogeneous in aim and objective. Furthermore, none of the included studies directly investigated SDM in RA and RM with individuals with mental illness. Therefore, further extensive work is needed to better understand how best to implement SDM in RA and RM so that all parties feel comfortable. A qualitative study by the lead author, directly investigating the barriers and enablers to SDM in RA and RM, is currently underway and has been developed from the findings of this review. The benefits of implementing SDM in RA and RM planning is also insufficiently researched. It is important to build an evidence base on the impact, as well as the acceptability and feasibility of a collaborative approach.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

Abbreviations

Shared Decision Making

Mental Health Professional

Risk Assessment

Risk Management

Department of Health

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

International prospective register of systematic reviews

Sample, Phenomenon of Interest, Design, Evaluation, Research type

Bielefeld Academic Search Engine

Theoretical Domains Framework

Capability, Opportunity, Motivation to Behaviour

United Kingdom

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Acknowledgements

I would like to thank Dr. Afnan Aljaffary, and Dr. Una Foye for their support with appraising the quality of studies within this review.

This research was part of a PhD funded by City, University of London, and East London NHS Foundation Trust. Neither funding body had a role in the design of the study, data collection, analysis, interpretation of data or writing the manuscript.

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NA contributed to the design of study, conducted the searches, screening, quality appraisal, data extraction, analysis, synthesis, drafted and edited the manuscript. AS contributed to the design of the study, supported screening, analysis, synthesis, and revised the manuscript. SB contributed to the design of the study, supported data extraction, screening and revised the manuscript. LR contributed to the design of the study, supported screening, and revised the manuscript. ND advised and revised the manuscript. FB supported title and abstract, and full text screening. ET contributed to the analysis and interpretation of data. All authors have read and approved the final version of the manuscript.

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Ahmed, N., Barlow, S., Reynolds, L. et al. Mental health professionals’ perceived barriers and enablers to shared decision-making in risk assessment and risk management: a qualitative systematic review. BMC Psychiatry 21 , 594 (2021). https://doi.org/10.1186/s12888-021-03304-0

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How is trauma-focused therapy experienced by adults with PTSD? A systematic review of qualitative studies

  • Solveig Flem Gjerstad 1 , 5 ,
  • Linda Nordin 2 , 3 ,
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  • Erminio Francesco Antares Spadaro 1 &
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Trauma-focused therapies (TFTs) are first-line treatments for posttraumatic stress disorder (PTSD). However, TFTs are under-utilised, partly due to clinicians’ and patients' fear that TFT is too challenging or harmful. We review the qualitative studies on how adults with PTSD experience TFTs to enhance the understanding of user perspectives, therapeutic processes, and outcomes.

PubMed, PsychINFO and PTSDPubs were searched between October 1st and November 30th, 2021. Study quality assessments were undertaken, and studies were analysed using a descriptive-interpretative approach. Nine studies were included.

The analysis resulted in the identification of four key domains, representing a temporal sequence of TFT stages: Overcoming ambivalence towards TFT, Experience of treatment elements, Motivation for dropout/retention, and Perceived changes post-treatment.

Although many participants reported high levels of distress and considered dropping out, only a minority did eventually drop out and most patients expressed that the hardships in therapy were necessary for PTSD improvement. Establishing a safe therapeutic environment and working with the ambivalence towards treatment was essential for retention. This review serves a dual purpose, to shed light on diverse TFT experiences found to be important for treatment satisfaction, and to elucidate common treatment patterns. The results can be used in preparing patients for therapy and in training TFT therapists. Studies had moderate to high quality, and more studies of experiences of TFT non-responders and dropouts in a non-veteran population are needed to further our understanding of the utility and limitations of TFTs.

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Posttraumatic Stress Disorder (PTSD) is a highly prevalent psychological disorder characterised by symptoms of re-experiencing trauma-related memories, avoidance, and elevated arousal [ 1 ]. The disorder is more commonly reported in high-income countries; however, the symptoms, personal and socioeconomic consequences are consistent globally [ 2 ]. Several types of therapies have been developed with various degrees of proven efficacy. Trauma-focused therapies (TFTs) are suggested as the first-line treatment for PTSD [ 3 ]. In a summary of the major Clinical Practice Guidelines (CPGs), Hamblen et al. [ 4 ] found that all guidelines [ 5 , 6 , 7 , 8 , 9 ] strongly recommended trauma-focused cognitive behavioural therapy (TF-CBT), including cognitive processing therapy (CPT) [ 10 ] and prolonged exposure (PE) [ 11 ]. Eye movement desensitisation and reprocessing (EMDR) [ 12 ] was strongly recommended by all except one guideline [ 5 ].

For this review, TFT is defined as “any therapy that uses cognitive, emotional or behavioural techniques to facilitate the processing of a traumatic experience and in which the trauma focus is a central component of the therapeutic process” [ 13 ]. Specific types of TFT include, but are not limited to, cognitive-behavioural therapies such as PE, CPT, cognitive therapy for PTSD (CT-PTSD) [ 14 ], and narrative exposure therapy (NET) [ 15 ], as well as EMDR, an alternative format of delivering exposure therapy in association with cognitive and emotional components [ 13 ]. In the literature, TF-CBT has both been described as a category encompassing the various cognitive-behavioural therapies mentioned above, or as a specific type of TFT [ 16 ]. In this review, TF-CBT will be referred to as an overarching category of cognitive-behavioural treatments, and TFT will be used as a broader category including TF-CBTs and EMDR.

The distinctive TFTs utilise different interventions. However, they are thought to create change in the same underlying mechanisms, targeting emotion, cognitions, and avoidance of trauma memories [ 17 ]. The cognitive model of PTSD [ 18 ] explains exposure, i.e., imaginal or written reliving and in-vivo exposure, as essential because it modifies negative trauma appraisals. The emotional processing theory [ 19 ] further posits that inhibition of the exaggerated fear response occurs when the patient experiences an optimal emotional activation while experiencing information contradicting their fears. Thus, TFT is theorised and expected to be challenging, as it requires high levels of activation of negative emotions during exposure.

Despite TFTs being the recommended first-line treatments for PTSD, they are often not utilised in clinical practice [ 20 ]. A review by Finch et al. [ 21 ] found that three of the most important clinician-related barriers to the use of the evidence-informed interventions are fear of re-traumatising patients, fear of increasing patients’ symptoms, and a disliking of the inflexibility of the manualized approaches. Therapists further often believed TFT to be unsuitable for patients in case of comorbidity or more complex trauma histories [ 21 ]. However, evidence does not support the concerns regarding the retraumatization and un-suitability of TFTs in cases with comorbidity, for example for psychosis [ 22 ], dissociative symptoms [ 23 ] and major depressive disorder [ 24 ]; see also Ennis et al. [ 25 ] and Voorendonk et al. [ 26 ].

Smith et al. [ 27 ] reviewed barriers to help-seeking in adults with PTSD, including barriers to initiating TFT. The findings revealed complex patterns, where some participants reported not being emotionally ready to talk about trauma or believing PE or CPT to be ineffective or harmful [ 28 , 29 , 30 ], and others having a strong preference for exposure therapy [ 31 ]. Importantly, the patients’ treatment preferences impacted therapists’ willingness to offer TFT [ 21 ]. Hence, systematic reviews [ 21 , 27 ] find that fear of negative experiences and reactions to TFT in both patients and therapists alike is a central barrier to its application.

Finally, TFT has been associated with higher drop-out rates than non-TFT [ 32 , 33 ], and the non-response rate to TFTs is often reported around 50% percent. This has been unchanged over the last two decades [ 33 , 34 ] despite extensive quantitative research into predictors and moderators of outcome as well as therapy effectiveness and dismantling studies. Therefore, a qualitative review of TFT users’ experiences may inform us on how to more efficiently approach the TFT concerns of therapists and patients, as well as the questions of drop-out and nonresponse. Further, users’ experiences with TFTs may lead to new research questions and designs, which can not be deduced from quantitative associations between variables.

Hence, investigating similarities and discrepancies in how patients experience the TFTs might be essential in understanding how to close the gap between current clinical practice and treatment guidelines for PTSD. While reviews studying this question have been conducted for populations of children and youths [ 35 ] and patients’ experience with EMDR [ 36 ], as of today, no review has investigated adult patient experiences with TFTs.

This qualitative review aims to synthesise adult patients’ reported experiences of TFTs to broaden the understanding of common and relevant treatment experiences, themes and trajectories in the therapeutic processes that can inform ways to more efficient and successful delivery of TFT.

Eligibility criteria

The study inclusion and exclusion criteria for this analysis were defined a priori, using the SPIDER mnemonic: Sample, Phenomenon of Interest, Design, Evaluation and Research type [ 37 ]. The final inclusion criteria were: English-language, published, peer-reviewed, qualitative and mixed-method studies reporting on the experience of receiving TFT for patients aged 17 or above with a primary diagnosis of PTSD. The inclusion age was modified from 18 to 17 years during the screening process since one identified article [ 38 *] with participants aged 17– 25 years (M = 20.0, SD = 2.61) was assessed to provide important qualitative information. Since the mean age was 20 and only a few participants were below the age of 18, it was decided that the study should be included. Studies describing both positive and negative experiences of receiving TFT were included to ensure variation in the phenomenon and strengthen the fidelity to the subject matter [ 39 ]. Some studies were excluded from the analysis because they had been discussed in a prior systematic review, exploring patients’ experiences with EMDR [ 36 ]. Their findings are included in the discussion of the current review. However, as the review by Whitehouse [ 36 ] only included studies with clients identified as potentially benefiting from EMDR, older studies that did not meet the inclusion criteria for the review by Whitehouse [ 36 ] were considered for the current review. Therefore, studies involving EMDR published before Whitehouse’s review were also included.

Search strategy

The systematic search consisted of three phases. The first phase involved a preliminary search in PubMed and Google Scholar to identify keywords within the abstract of relevant articles. The SPIDER [ 37 ] tool was applied to define search terms from the review question and develop a standardised search strategy. The second phase consisted of systematic searches using the identified keywords. The searches were conducted in three databases: Pubmed (Medline), PsycINFO (EBSCOHost) and PTSDPubs (Proquest) between October 1st and November 30th, 2021. Some of the search terms were modified to fit the different databases (e.g., using truncation and wildcards). The final phase consisted of hand searches in the chosen studies’ reference lists. The key search terms are presented in Table  1 . For a comprehensive presentation of the search process for each database, see Additional file 1 .

Study selection

Studies were screened and reviewed by the first author with the aid of Covidence. First, duplicates were removed. Titles and abstracts were then screened for inclusion. Studies were retrieved and full-text assessed for eligibility. To limit the possibility of excluding relevant articles, credibility checks were conducted by auditing [ 40 ], meaning that the inclusion of some articles was discussed by three of the authors.

Quality assessment

The quality of the included studies was ensured by including published, peer-reviewed studies [ 39 ]. Further quality assessment was undertaken using the Critical Appraisal Skills Programme [ 41 ], the most used quality checklist in health-related qualitative synthesis [ 42 ]. CASP does not provide a scoring system but allows for a systematic quality assessment through 10 questions with elaborative prompts. To summarise the quality assessment, questions 1 through 9 were evaluated with the following score: Yes/clearly described = 1; Partially described = 0.5; No/insufficient information = 0 (adapted from Neelakantan et al. [ 35 ]). The total scores were categorised as low quality (scores 0 – 3), moderate quality (scores 4 – 8) and high quality (scores 8—9). Studies identified as lower quality by the checklist were not excluded. The quality assessments were used to assess potential biases, reliability, and value in the review’s findings [ 43 ].

Data analysis and synthesis

Descriptive-interpretative qualitative analysis [ 40 ] was applied to provide a comprehensive description of patients’ experience of receiving TFT, including ambiguities and differences found in the primary studies. This approach is suggested for qualitative meta-analyses because it minimises two opposite types of risks that qualitative studies face. One risk is being too relativistic but with insightful findings, meaning that the findings are relative to the interpreter of the analysis and cannot lead to a generalizable framework. Another risk is that the studies are too realistic but with superficial results, because the results simply reproduce the participants’ words true to their original form but lack essential comparisons and interpretation of importance across different studies [ 44 , 45 ]. A qualitative systematic review not only provides a synthesis but also an interpretation of experiences, enabling the presentation of shared, divergent, or significant themes across various modalities of Trauma-Focused Therapies (TFT), group or individual settings, and spanning different types of trauma.

The analysis consisted of four steps, described by Timulak [ 40 ]. First, the collected data were assigned into domains, informed and adjusted by the data of the primary studies. The identified domains created a conceptual framework and represented a temporal sequence of participants’ experiences of trauma-focused therapy. Second, meaning units (the smallest units of the data that conveyed a clear meaning) were identified. Third, meaning units were clustered based on similarities, generating categories and sub-categories. Lastly, the main findings were abstracted in narratives, exemplified through direct quotes.

The analysis was guided by a realist epistemology, assuming a unidirectional relationship between patients’ reports and experiences [ 46 ]. Categories were identified at a semantic level, that is the explicit meaning of the data was identified and organised into patterns [ 46 ]. The patterns were interpreted in terms of their significance and broader meaning. The interpretation included assessing how the methodology in the primary studies may have influenced the results.

All contextual information, including direct quotes, descriptions, and discussions, were considered data. The rationale for including contextual information was to retain the meaning of the results and minimise the risk of overlooking the context of the primary studies, to which qualitative research is sensitive [ 40 ]. Only accounts available in the published versions were included. In mixed methods studies, only qualitative information was used as data. To minimise the risk of overgeneralizing findings, means were taken to address the representativeness of the results in the final review by reporting: (i) how many primary studies were included in each domain, category, sub-category and (ii) how many categories were identified in each study, to account for the degree that each study was represented in the final review [ 47 ].

The analysis and synthesis were initially conducted by the primary author. The fourth author then conducted a separate analysis and synthesis. The process of reaching consensus included making sure that the synthesis represented both analyses and that the final synthesis was adjusted to fit the categories of the independent analysis. Consensus of the domains, categories, meaning units and extracted data were reached in collaboration [ 48 ].

The database search identified 163 studies, where 57 duplicates were removed. The resulting 106 records were screened based on title and abstract. After excluding 95 studies, 11 studies were retrieved and assessed for eligibility. Five studies were excluded during full-text screening, resulting in six studies identified from database-search. Three additional studies were identified through hand searches. All three studies were kept during the screening of title and abstract and the full-text eligibility assessment. The process resulted in nine included studies, three identified through hand-search and six from database searches. Details of the screening process are provided in a PRISMA Flow Diagram (Fig.  1 ).

figure 1

PRISMA flow diagram. Note: Articles excluded based on full-text assessment: Hundt et al. [ 28 ], König et al. [ 49 ], Sherril et al. [ 50 ], Tong et al. [ 51 ] and Wise & Marich [ 52 ]. From: Page, M. J. et al. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372 , n71. https://doi.org/10.1136/bmj.n71

The reasons for exclusion were wrong population ( n  = 1) and wrong objective ( n  = 4), i.e., not meeting the criteria for PTSD [ 51 ], investigating pre-treatment criteria [ 28 ], comparing the importance of treatment elements in two treatments without describing the experience [ 49 ], and not including qualitative information about how the patients’ experienced the treatment [ 50 , 52 ]. For a more detailed description of the in- and exclusion process, see Additional file 2 .

Study characteristics

Table 2 provides details of study characteristics. The service contexts included trauma outpatient treatment services, a centre for anxiety disorders, veteran PTSD clinics, a youth mental health service and a primary care service. The studies described using TF-CBT, PE, CPT, Imaginary Rescripting (ImRs), EMDR, reliving, on-site-visits, Imaginal Reliving and/or Adapted Testimony within a TF-CBT framework. Two studies included group CPT, while the rest were delivered as individual therapy. Eight studies used qualitative interviews and one study used a questionnaire with free-text items. All samples consisted of adults, with one study focusing on young adults between 17 and 25 years. Reported traumatic events varied: physical and sexual assault or abuse, gang rape, road traffic accidents, medical trauma, military trauma, witnessing a murder, witnessing others or family members being killed, harmed or captured, finding a child murdered, physical torture, imprisonment, physical threat, domestic and childhood abuse, acts of terrorism, assaults with a weapon. The nine studies comprised 174 participants, with 38 dropping out of treatment (21.8%). Three studies reported interviews with dropouts. The rest of the studies recruited participants that had completed therapy.

Synthesis of the results

The analysis resulted in a conceptual framework representing a temporal sequence of experiences and dilemmas in different stages of TFT. There were four key domains: Overcoming ambivalence towards TFT , Experience of treatment elements , Motivation for dropout or retention and Perceived changes post-treatment , with three categories for each domain. Each category was represented by several sub-categories (see Fig.  2 for a visual representation of experiences and dilemmas in different stages of TFT and Table  3 for a comprehensive summary of the distribution of the articles within each category and which studies are represented by the themes described below).

figure 2

Experiences and dilemmas in different stages of TFT

Overcoming ambivalence towards TFT

Overcoming ambivalence towards TFT was identified as a major theme for all participants. This domain was further divided into three categories: Concerns about engaging in TFT, Desperation and hope facilitated engagement and The therapist’s role.

Concerns about engaging in TFT: fear and scepticism

Participants described experiencing ambivalence about engaging in TFT. More specifically, participants expressed fear, anxiety, and avoidance. “I’d been avoiding it for ages and ages and ages, […]. And it wasn’t until I’d spoken, I’d thought it through, that I realised that I was scared of things, it was just kind of instinctive reaction of like horror, not wanting to go there” [ 53 *] and “I am absolutely afraid I will get depressed again. In fact, I expect it” [ 60 *].

Desperation and hope facilitated engagement

Most of the studies described motivating factors that facilitated initiating TFT. Being desperate and hitting rock bottom was identified as a central factor for encountering the anticipated distress. Conversely, one study [ 53 *] also identified being in a good place as essential for choosing to engage in TFT. Many highlighted the importance of having positive attitudes towards TFT. Three sub-groups emerged. One group reported feelings of hope, determination, commitment and being intrinsically motivated. A second group described emotional doubt but intellectual confidence in the effectiveness of therapy, which was promoted through the understanding of the treatment rationale and therapy process. The last group experienced scepticism and belief simultaneously.

The therapist’s role

Most of the studies highlighted the therapists’ role in helping the patients overcome anticipatory anxiety and engage in trauma-focused interventions. Many studies emphasised the importance of the collaborative relationship, for example feeling that the therapist “facilitated” rather than “directed” the patients [ 55 *] and experiencing being both pushed and respected [ 54 *]. Furthermore, trusting the therapist was considered a significant factor in both empowering patients to manage complicated feelings [ 53 *], expressing concerns about treatment [ 60 *] and gaining a sense of self-efficacy [ 54 *]. Participants identified several valuable characteristics of the therapist that facilitated trust: transparency regarding the content [ 38 *], flexibility within therapy sessions [ 55 *], attentive listening [ 54 *], and empathy, understanding and non-judgement [ 58 *].

Experience of treatment elements

All the studies described patients’ positive or negative experiences of specific elements of TFT, including perceptions of what aspects of therapy they valued or disliked. Despite some differences between the various types of interventions (TF-CBT, PE, CPT, reliving and site-visits as part of TF-CBT, ImRs and EMDR), most participants expressed they had changed their thoughts/beliefs (cognitive-behavioural element) and learned affective coping skills (affective modulation strategies). They also valued exposure and experiencing habituation (trauma-focused elements) and felt that homework generalised learning (homework assignments).

General experience of treatment

Most of the studies included positive reports regarding cognitive-behavioural elements. Cognitive techniques such as questioning one’s thought processes and identifying cognitive biases were emphasised by participants as valuable in gaining a greater understanding of themselves, their triggers, symptoms, traumatic experiences, and were experienced as contributing to positive changes in thoughts/beliefs and better coping skills. In addition to cognitive strategies, affective modulation strategies and psychoeducation were both described as vital for change and helped the participants gain a sense of control. Regarding the length of therapy, there are mixed results. Some participants reported wanting more sessions, some were satisfied, and others were reported as finishing treatment early. See Table  3 for an overview of what articles report which of the reported themes.

Ambivalence and disagreement about trauma-focused elements

Trauma-focused interventions received the most negative evaluation, but were also described as the most essential and critical parts of recovery. Since this category accounted for a large part of the analysis, it was separated into conflicting but complementary subcategories. The following subthemes show a disagreement in how the participants experienced trauma-focused interventions.

Harder than expected versus unfounded fears

Participants’ encounters with trauma-focused interventions varied and were categorised into three groups: (i) easier than anticipated, (ii) more challenging than expected, and (iii) difficult, as expected. Those individuals who perceived trauma-focused interventions as easier than anticipated described them as painful yet manageable, as their worst fears were proven unfounded. In the words of a participant, “Although it was very, very painful to relive it, I didn’t lose control, I didn’t scream, cry, or lash out” [ 53 *]. A few studies reported experiences where treatment proved more challenging than expected, as expressed by a participant in Doran et al. [ 60 *]: “I simply didn’t anticipate my reactions. I didn’t expect it to be this difficult”. In contrast, a majority experienced distress during the trauma processing, but recognized it as an expected and necessary part of the recovery process.

Difficulty tolerating trauma work versus importance of hardship

All studies consistently reported emotional distress among patients undergoing trauma-focused therapy (TFT), emphasising its demanding nature in addressing negative emotions and content. Common adverse reactions included initial symptom worsening, including nightmares, flashbacks, intrusive thoughts, and increased substance use [ 38 *, 53 *, 54 *, 56 , 57 ,*– 58 *].

Feeling overwhelmed during trauma-related exposures and re-experiencing the events was also frequently reported. Notably, one participant described the resurfacing of trauma-related emotions as “even more traumatic” than the original event, attributing this distress to an inability to disengage from the traumatic memories [ 38 *]. Another participant conveyed a sense of dissociation during trauma work, stating, “… I was actually back when it was, all the stuff [the trauma] was happening. So I was like actually, I was scared and I’d leave, like obviously we’d stop because [the therapist] could see that I was not in the room” [ 38 *].

Nonetheless, despite the distress experienced, discussing the trauma was described as “cathartic” and deemed essential [ 54 *]. A majority of participants credited therapeutic progress to trauma work, emphasizing that the short-term pain was outweighed by the eventual benefits. One participant continued therapy even after relapsing into substance use during trauma narration, regarding it as a necessary part of their healing journey [ 58 *]. However, it is important to note that not all participants shared this perspective, and dropout from treatment was often linked to an inability to manage the emotional distress associated with trauma work, which will be discussed separately.

Life-consuming versus habituation

Several participants reported that trauma work consumed every facet of their lives. This immersion manifested itself as persistent rumination and enduring low mood in the intervals between therapy sessions, which had adverse effects on their social, occupational, and academic aspects of life. For instance, one participant articulated their experience, stating, “I was very dark and depressed… constantly thinking about it, bringing up suppressed memories…” [ 38 *]. Nonetheless, a prevalent pattern surfaced where participants progressively found the trauma-work more manageable over time, experiencing habituation and improved coping. They likened it to desensitisation, making it easier to discuss and express their experiences.

Piecing together traumatic experiences versus wanting less repetition

Participants generally had positive concluding remarks on trauma processing. Repeatedly discussing the “original event” facilitated memory reconstruction, changed beliefs [ 57 *], memory vividness [ 56 *], and “moving forward” [ 59 *]. However, some wanted to address multiple events, patients who dropped out cited feeling overwhelmed by the repetitive sessions [ 60 *], and some viewed discussing trauma as “dwelling on the past” and potentially hindering recovery [ 38 *].

Experience with homework

Most participants found homework beneficial for practice and generalised learning [ 55 *]. Positive experiences with homework served as positive feedback that the therapy was working [ 57 *]. Challenges included finding the homework assignments confusing or having problems completing it due to other commitments [ 57 *, 60 *].

Motivation for dropout or retention

The third domain that emerged from the analysis was “Motivation for dropout or retention”. Although a minority of participants dropped out, many participants described wanting to drop out at some point. The domain was divided into the categories “Reasons for considering dropping out”, “Factors contributing to retention”, and “Reasons for dropout”.

Reasons for considering dropping out

The primary reason for considering ending therapy was unresolved ambivalence about treatment, primarily rooted in doubts regarding therapy effectiveness, difficulty tolerating treatment, and avoidance behaviours, as indicated by one participant: “I thought about quitting because I was avoiding writing about my traumatic experience” [ 57 *]. Stigma and cultural stereotypes surrounding seeking mental health prevailed and were a central theme for participants’ ambivalence about treatment. Concerns about treatment duration, especially its brevity, added to ambivalence, as participants questioned the adequacy of the allocated time. Uncertainty about the future, notably among asylum seekers awaiting decisions on their asylum claim, also led to doubts about the worth of continuing therapy. Furthermore, participants cited practical barriers, including transportation challenges and family responsibilities, as hindrances to therapy.

Factors contributing to retention

Despite considering discontinuing treatment, most participants chose to continue therapy. Support from family and friends was mentioned by many as a primary reason for retention. For those lacking social support, the therapeutic relationship held great importance and openly discussing concerns with the therapist reinforced commitment. Additionally, perceived early progress, symptom improvement, relief and shifts in perspectives, inspired the patients’ persistence. Lastly, dedication to the therapy process, oneself, and the therapist was recognized as crucial during challenging phases, with some participants attributing their decision to continue to their “commitment” [ 57 *].

Reasons for dropout

Participants dropped out of therapy for four main reasons: external barriers, therapy-related difficulties, therapeutic alliance issues and lack of social support.

External barriers such as therapists lacking dedicated offices, scheduling conflicts, and limited health plan coverage, often led to disengagement. Therapy-related difficulties mirrored the concerns of those considering dropout. Many quit when they didn't see improvement or had doubts about the therapy approach, finding it too formal or preferring to learn coping skills. Some started therapies recommended by their therapists despite reservations [ 58 *]. Interestingly, some dropped out despite believing in the benefits of trauma work due to an inner conflict between avoidance and recognizing the need for therapy [ 60 *].

Participants expressed their willingness to consider returning to therapy if it were possible to develop a stronger therapeutic relationship, acquire enhanced coping skills, or resolve practical barriers [ 54 *, 58 *]. Importantly, those facing therapy-related challenges often cited issues with the therapist-patient relationship and a lack of social support [ 38 *, 58 *].

Perceived changes post-treatment

Participants reported noteworthy positive changes: reduction in symptoms, changed beliefs about the trauma, themselves and the future and better functioning. A few reported negative outcomes, which will be discussed within these categories.

Perceived symptom changes

Positive symptom changes included reduced re-experiencing symptoms, improved sleep, mood, concentration, fewer nightmares, and less avoidance and hyperarousal. Most commonly, participants reported mood and functional improvements, a reduction in symptom intensity and frequency, while also acquiring coping skills to better manage residual symptoms. Yet, some saw no improvements, and a few felt worse, experiencing symptom exacerbation, nightmares, and substance abuse relapses [ 60 *].

Changed beliefs

Participants experienced profound shifts in their beliefs about trauma, themselves, and the future. These changes involved developing a new relationship with traumatic memories, reinterpreting the traumatic experiences, and gaining insights into their impact on life challenges. The changes extended to participants regaining a sense of agency, and experiencing bolstered confidence in handling trauma and reduced self-blame, exemplified by a participant recognizing they were allowed to be angry about what was done to them [ 53 *]. This transformation indicated a profound shift in self-identity [ 38 *, 57 *].

Notably, asylum-seekers differed in their responses. They expressed feelings of weakness and illness due to their therapy needs, contrary to the more common experience of relief from shame and guilt. Accepting new perspectives was challenging for some asylum-seekers, leading to negative changes in self-understanding and beliefs about others [ 54 *].

Despite these variations, most participants adopted a positive outlook on life following therapy. They expressed renewed hope for a meaningful future and a preference for life over death, representing a significant shift in their perspective.

Better functioning

Symptom improvements, increased hope, and enhanced symptom management had a positive effect on various aspects of participants’ lives. They reported improved social relationships, occupational functioning, and a rekindled interest in previously enjoyed activities. For instance, one participant mentioned increased participation in family events [ 57 *]. Another credited therapy with helping them open up about their experiences, which allowed for a sense of connection and social support [ 38 *].

Representativeness of findings

The representativeness of the findings in the review is presented in Table  3 . Representativeness was assessed as (a) how many studies were represented in each category and sub-category, and (b) how many categories were identified in each study. Assessing the representativeness of each study in the findings was conducted by calculating the total amount of categories each study identified.

Critical appraisal

The quality of the included studies was high and moderate, with six studies rated as high quality and three studies rated as moderate quality according to CASP. All studies gave a clear statement of the research aims, and qualitative research was justified and considered to be the suitable methodology for addressing the research goal. Recruitment bias was widespread throughout all the studies. For instance, two of the studies did not provide sufficient information about how the participants were selected [ 56 *, 57 *], and one study used self-selecting recruitment but did not discuss the implications of this method [ 53 *]. Despite the presence of recruitment bias, most authors discussed their recruitment strategy (e.g., recruiting participants from one treatment facility or choosing participants who were thought to benefit from the treatment), which demonstrated systematic appraisal of study limitations. All the studies described and justified the data collection procedures. Five studies did not discuss the relationship between researcher and participants. This was mostly not considered to create a high risk of bias, as different individuals conducted the therapy, data collection and analysis. However, in two studies, participants might have been reluctant to disclose negative therapy experiences due to the nature of the data collection [ 54 *, 55 *]. Three studies did not provide sufficient details to assess whether ethical standards were maintained [ 53 *, 55 *, 56 *]. All studies described data analysis rigorously. All except one study [ 56 *] offered a comprehensive statement of findings. See Additional file 3 for a detailed description of the quality assessments.

The purpose of the present review was to understand and summarise patients’ experiences and dilemmas in trauma-focused therapy. The synthesis across patients with different trauma and six different types of TFT resulted in a common pattern, which provides insight into common experiences likely to occur throughout TFT. Comparing the experiences reported by those who considered dropping out but chose to stay and those who did drop out may help to illuminate, which aspects of TFT that are experienced as too challenging for patients [ 21 , 27 ].

Trajectories of treatment experiences

Different trajectories of how patients experienced the process of TFT emerged. Patients’ concerns about starting therapy, described in this review, concur with the common characteristics of PTSD, including avoidance and negative beliefs about the self, future, and trauma [ 18 ]. At the beginning of therapy, most participants experienced scepticism and fear of talking about the trauma. Despite the commonly held belief in both patients and therapists that the patients’ should be in “a good place in life” in order to engage in TFT, the most prevalently reported patient-experience in the study was that desperation (i.e., “hitting rock bottom”) was important for deciding to engage in TFT in the first place. Thus, apparently a combination of desperation and hope might compel patients to begin treatment.

Next, patients’ experiences with trauma-focused interventions were mixed. Importantly, most considered dropping out at some point, due to the hardship of trauma-focused interventions and doubts about its efficacy. This finding has important clinical implications, because while most TFT manuals prescribe motivational strategies before the initiation of trauma-focused exposure, to the best of our knowledge, none deal explicitly with retention strategies once exposure has begun (NET (15); CT-PTSD (14); CPT (10); PE (11)). Thus, therapists are currently left to devise their own retention strategies to the best of their ability.

Despite the high distress levels involved, difficulty tolerating treatment and overcoming the discomfort was found to be essential for recovery. Furthermore, overall the patient experiences did not support patients’ and therapists’ concerns that TFT might be ineffective or harmful. To the contrary, some described TFT to be effective, despite dropping out of therapy.

Factors associated with retention

Factors associated with retention included buy-in to treatment, symptom improvement, fewer external barriers, social support, and a strong therapeutic relationship. Buy-in to treatment was crucial, often achieved through psychoeducation and therapist support.

The results indicated that buy-in to treatment can be divided into a rational, emotional and desperate buy-in. A rational buy-in was accomplished through thorough psychoeducation. An emotional buy-in was described as based on a trust in the therapists, facilitated by feeling both respected and pushed. When respected, patients were allowed time to understand the treatment rationale and take breaks, due to emotional limits. The experience of being pushed in a constructive way encompassed being exposed to trauma-interventions even when they did not believe they could tolerate it. The last group of clients, characterised by what we have termed desperate buy-in, preferred starting trauma intervention as soon as possible to limit the risk of them backing out. Despite not necessarily understanding the treatment approach, early trauma interventions allowed them to experience early symptom improvement. This exemplifies the complexities of trauma treatment and the all-important balancing of providing psychoeducation, ensuring “buy-in to treatment”, and early introduction of trauma-focused interventions. Hence, if we are to get better at preventing drop-out from TFT, designing explicit manualized strategies, which help therapists to recognize and address the above patterns, might be a way forward.

Patients perceived certain aspects of TFT as too inflexible, including the treatment content and process, consistent with concerns raised by therapists [ 21 ]. However, participants experiencing both being pushed and respected reported positive sentiments about its flexibility. Thus, although flexible sessions that adapt to individual needs while staying true to treatment goals may be beneficial, trusting the therapist might result in a more positive attitude towards the treatment manual. Overall, in order to improve retention, the expectations of treatment services regarding the pace and length of TFTs need to be flexible enough to allow for adaptations and good enough working alliances between therapists and patients, as well as good enough working conditions for those providing the treatments.

Social issues such as external stressors, logistical barriers and unstable living conditions often interfered with treatment. However, those reporting external barriers who simultaneously had a strong therapeutic relationship or good social support were more inclined to stay in therapy. Moreover, participants reporting both external barriers and lack of social support specifically emphasised the therapist’s support as a central factor in their decision to stay in therapy. For those experiencing alliance issues, discussing concerns about the treatment with their therapist often facilitated retention. This is in line with prior research that points to the significance of acknowledging factors related to the therapeutic alliance (i.e., the therapeutic relationship, empathy, support, and shared goals) as potential mediators of symptom change [ 61 ]. Finally, an important dynamic is demonstrated in the trajectory from the initial need to be in a place desperate enough to consider starting TFT, to the finding that those same social issues may become a hindrance in later phases of treatment. A clinical implication of this sequence might be that we should not wait for patients’ lives to become more “stable” before initiating TFT as has been suggested to reduce patients’ fear [ 62 ], but rather provide effective social counselling in parallel with TFT to alleviate the worst social stressors and improve retention during the exposure phase.

The findings shared similarities with the qualitative review of EMDR experiences among patients identified as benefiting from EMDR [ 36 ]. Similarities included the significance of a trusting therapeutic relationship to create a sense of safety and alleviate doubts and scepticism about therapy. Additionally, a common theme that emerged included experiencing a broader transformation through therapy, leading to an enhanced quality of life and changed beliefs about oneself.

Treatment rationale of trauma-focused therapies

Patients’ experiences both aligned with and challenged the assumptions about common mechanisms promoting change in TFT through the targeting of emotion, cognition and avoidance, i.e., psychoeducation, exposure, memory processing and habituation [ 17 ].

Psychoeducation not only seemed to increase participants’ commitment to treatment but also positively influenced most patients’ self-perceptions and how they viewed their symptoms. These shifts in how they appraised their traumatic experiences were mainly attributed to cognitive techniques, while exposure interventions played a crucial role in memory modification and discrimination. Although a minority of patients did not experience habituation to their trauma memories or symptom improvement despite completing treatment, many still reported significant improvements representing an increase in quality of life [ 63 ], including better symptom management, increased sense of control, improved social relationships, and enhanced work and daily functioning.

While the positive outcomes might be attributed to or moderated by non-specific therapeutic factors, such as the therapeutic relationship [ 64 ], patients attributed the changes to the process of addressing their trauma. The key elements that patients valued in therapy included experiencing catharsis and relief through discussing their trauma, transforming their beliefs about trauma, the world, and themselves, and having a trustworthy and genuine therapist to facilitate these changes. In accordance with the theoretical framework proposed by Ehlers and Clark [ 18 ], the results indicate that from a patient perspective, trauma-focused work was essential for regaining trauma memory, achieving a new perspective on the trauma, and managing their symptoms.

Diverse experiences within subgroups

The findings of the study indicate that Trauma-Focused Therapy (TFT) was experienced as beneficial for veterans and asylum seekers; however, the results suggest that these groups exhibit distinct and somewhat less favourable responses to TFT when compared to other populations. Notably, despite Clinical Practice Guidelines recommending TFT as the primary treatment for PTSD, recent research has uncovered inconsistent findings with regard to its superiority, particularly in the context of military-related PTSD [ 65 , 66 , 67 , 68 ].

These variations in treatment outcomes may stem from various external, cultural, or trauma-specific factors and the results underscore the imperative of cultural sensitivity when working with trauma survivors [ 69 , 70 ]. Both veteran and asylum seeker groups encountered significant challenges related to stigma, shame, and guilt. Stigma could exacerbate negative appraisals of trauma and self-perception, subsequently impeding help-seeking behaviour. This, in turn, could contribute to the persistence and severity of symptoms, as noted in prior research [ 71 ]. Moreover, limited help-seeking behaviour among these groups may lead to reduced social support, a factor which has been identified as crucial for maintaining engagement and retention in treatment.

Asylum seekers’ difficulties in acknowledging past traumas and altering their beliefs about themselves and the world pose a crucial challenge in the context of most TFTs. Among the other study samples, gaining a new perception of the trauma memory appeared as essential for improving symptom management, aligning with existing studies demonstrating that alterations in appraisals mediate the change of PTSD symptoms [ 72 ]. This observed subgroup difference might reflect significant cultural variations in the perception of psychiatric diagnoses and trauma experiences. However, it might be that current threats moderate this relationship. Notably, the fear of repatriation emerged as a significant barrier hindering engagement for asylum seekers. This aligns with theoretical models suggesting that the perception of current threats sustains PTSD symptoms [ 18 ]. Despite evidence supporting the effectiveness of TFT for individuals at high risk of re-exposure [ 25 ], the results suggest that the coexistence of cultural stigma and current threats may increase the likelihood of treatment dropout among these patient populations. More qualitative studies of refugee-patients’ experiences with TFT are needed to better understand the obstacles to effective implementation of TFT in this group.

Clinical implications

Creating a safe therapeutic environment is crucial to enhance the effectiveness and tolerability of Trauma-Focused Therapy (TFT). Addressing and working through ambivalence plays a central role in building trust in treatment and influencing patient engagement and retention. Trust encompasses both a rational understanding of the treatment rationale and an emotional reliance on the therapeutic process and therapist.

Therapists should prioritise building trust, considering the client's unique subjective and cultural perspectives. It is particularly important to inform the patient about the treatment principles, to present a clear rationale for the exposure component that acknowledges that revisiting the trauma memories may seem counterintuitive, and to provide realistic expectations for both positive and negative experiences throughout therapy. It is important to anticipate and openly discuss common reactions like fear, ambivalence, and symptom exacerbation, reassuring clients that these are typical and not indicative of treatment failure. Finally, anticipating patients’ ambivalence during treatment and manualizing retention strategies in TFTs might be a way of improving their effectiveness.

For individuals hesitant to engage in treatment due to apprehension, the awareness of shared experiences or the recognition that encountering challenges like relapse and symptom worsening has been reported as worthwhile by others may be reassuring. Follow-up sessions aimed at discussing re-engagement are recommended, as most dropouts express a willingness to retry TFT.

Some participants, particularly refugees and veterans, express a desire to move on from traumatic events, which contrasts with TFT's core element of revisiting trauma for processing. Therapists should explain this counterintuitive approach and address client scepticism through education and preparation, both in sessions and through written or online materials. Patients across the studies emphasised the importance of understanding the treatment rationale, suggesting a need for adaptations like translated materials or culturally relevant language for minority groups [ 73 ].

Clinicians should address the potential stigma and increased sense of guilt associated with psychiatric diagnosis for multiple marginalised groups. Challenges including shame, isolation and cultural stereotypes suggest that a group-oriented approach focusing on these aspects as part of psychoeducation, could be beneficial. Recognizing that cultural context shapes trauma experiences, the results suggest that the treatment should address the perception of current stressors alongside past trauma, rather than exclusively concentrating on a single traumatic event. The findings suggest that patients with many social stressors might benefit from more short-term intensive treatment [ 74 , 75 ], or/and treatments that focus on alleviating social stressors in parallel with provision of TFT.

This review informs psychoeducation by shedding light on TFT experiences and elucidating common treatment patterns. Referring to how other patients respond can assist clinicians and patients in developing trust in TFT. Recognizing that ambivalence and fear can deter both patients and therapists, this review may mitigate treatment dropouts and enhance willingness to engage in TFT.

Strengths and limitations

A strength of this review is the pre-defined inclusion and exclusion criteria. The wide range of search terms and the inclusion of hand-searched articles enhanced the likelihood to detect a large proportion of existing papers relating to patients’ experiences of TFT. The studies represented both positive and negative experiences, providing a nuanced picture of patients’ experiences. The studies included a diversity of sub-groups (veterans, asylum seekers, youths, and patients with various index traumas), allowing for a more comprehensive understanding of typical and distinct experiences seen across these groups, e.g., difficulties with completing TFT. The studies reviewed were conducted in the US, UK, Australia, Germany and Netherlands, with a wide range of ethnicities represented.

The included studies covered a variety of therapeutic methods (imaginal reliving, site-visits, PE, CPT, Adapted Testimony, ImRe and EMDR). Furthermore, the quality of this systematic review was strengthened through credibility checks. The authors amongst themselves encompassed a broad range of therapeutic experiences and preferences, including both TFT-practitioners and non-TFT practitioners. Lastly, the representativeness of the findings in this systematic review was assessed [ 47 ].

Nonetheless, certain limitations affect the generalizability of the findings. Participants with a positive experience could have been more inclined to participate in the research. Also, the use of purposive sampling might have contributed to sampling bias, resulting in overly optimistic reports about TFT experiences. For example, certain studies included patients who completed at least eight sessions of therapy [ 57 *], who found the treatment to be a positive experience [ 55 *], or who were believed to benefit from exposure interventions [ 56 *, 60 *]. Furthermore, interviews conducted in the setting where the participants received therapy might have impacted to what degree the participants were willing to disclose negative experiences [ 54 *]. Finally, the included studies do not represent the perspectives of patients who have refused to start in TFT. It is likely that studies investigating the expectations and concerns of patients who are not willing to enter into a therapy including an exposure component would have further added to the understanding of patient perspectives on TFT.

Despite the possibility that some studies contributed to disproportionately positive results, it was also evident in the studies that most participants shared both negative and positive experiences. Furthermore, certain of the included studies actively reduced the possibility of overgeneralizing positive findings in the review by focusing on those who had dropped out of TFT [ 38 *, 58 *, 60 *]. Even when bearing in mind the impact of the potential methodological biases, the themes reflecting positive and negative experiences were similar across different types of study populations. Moreover, dropouts from all three studies reported positive feelings about TFT, and many were willing to try TFT again.

Despite the inclusion of several therapeutic interventions, most studies examined therapies related to TF-CBT and no studies examined the experience of narrative exposure therapy. Approximately half of the sample and 70% of the dropouts were veterans. The exclusion criteria could have biased the reported results, as non-English language studies and studies not published in peer-reviewed publications were excluded. The exclusion of grey literature could have contributed to a publication bias of the reported experiences. Furthermore, the reporting of the results (a few, some, many, several and most) might represent a bias. Due to a lack of accurate descriptions in some of the studies, it was impossible to provide a precise number of participants reporting different experiences. Two authors selected relevant “quotations” from the original studies, and although means were taken to stay close to the language of the original studies when describing the results, both the original researchers of the primary studies and the authors of the current review might have overlooked some information. Nevertheless, by conducting rigorous and systematic analysis, the findings are likely to offer a comprehensive and in-depth picture of patients’ experiences.

Future research

First, it is evident that there is a lack of studies involving TFT experiences of multiply marginalised groups. Future research should prioritise investigating how these specific populations experience TFTs. Given that most existing studies focus on TF-CBT, it is crucial to expand our understanding by exploring how patients experience Narrative Exposure Therapy (NET). It would be relevant to focus such studies on refugees or asylum seekers, as this group did not experience the common trajectory of altered beliefs about themselves, the trauma and the world, and because NET was developed to treat trauma within this population and has demonstrated effectiveness [ 76 ]. The literature search also identified a lack of studies investigating therapists’ experience with conducting TFTs. Further research should investigate both patients’ and therapists’ experiences, making it possible to compare their experiences and to what extent they align.

Overall, participants reported high levels of distress and re-emergence of symptoms during trauma work. Still, despite negative experiences, most patients were grateful and perceived the hardship as essential for improvement. At the beginning of therapy, most participants experienced scepticism and fear of talking about the trauma. Most participants expressed a reduction in ambivalence throughout therapy due to experiencing symptom improvement, understanding the treatment rationale, and trusting the therapist’s empathy and expertise. Some expressed persistent ambivalence about the effectiveness of the treatment as an essential factor for dropping out. Also, it seems that it is vital for participants to be informed about the treatment principles and the rationale for the exposure component of the therapy. Clinicians should emphasise that therapy will be challenging and that symptom exacerbations may occur during trauma exposure, but that these experiences do not imply that treatment does not work. Instead, experiencing difficulties with the treatment and overcoming these could be essential for recovery. Most participants experienced significant improvements in symptoms and quality of life. Realistic expectations of symptom improvements post-therapy should be emphasised, as many still experienced some symptoms post-treatment. However, therapy helped them gain coping skills, a sense of control, agency and a better outlook on life. The results also emphasised that participants’ appreciated hearing about other people’s experiences, as it helped them overcome their ambivalence about staying in therapy.

Availability of data and materials

All data generated or analysed during this study are included in this published article and its supplementary information files.

Abbreviations

Cognitive processing therapy

Cognitive therapy for post-traumatic stress disorder

Eye movement desensitisation and reprocessing

Narrative exposure therapy

Prolonged exposure

Post-traumatic stress disorder

Trauma-focused cognitive behaviour therapy

  • Trauma-focused therapy

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Acknowledgements

The authors would like to thank the participants from the primary studies for their contribution.

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Contributions

SFG completed the systematic search, reviewed, analysed and synthesised the data. SaPa designed the study and LN and SaPa screened articles for inclusion for credibility checks. StPo reviewed the manuscript through the initial preparation. EFAS conducted an independent analysis and synthesis of the data. All authors read, made amendments to, and approved the final manuscript.

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Solveig Flem Gjerstad is a clinical psychologist. She earned her Master's degree in clinical psychology at University of Copenhagen and her Bachelor’s degree in General Psychology at University of Bergen, including a scholarship semester at University of Sydney. Currently she practises Dialectical Behavioural Therapy in a treatment facility for eating disorders. ORCID: 0000-0001-6744-8262.

Linda Nordin is a clinical psychologist and a researcher at DIGNITY - Danish Institute Against Torture with an affiliation at Lund University, Department of Psychology. Her main focuses of research are trauma, PTSD, refugees, and pain. ORCID: 0000-0002-8533-520X.

Stig Poulsen is Professor in Clinical Psychology and Psychotherapy at the Department of Psychology, University of Copenhagen. His main area of research is the process and outcome of psychotherapy and he has a particular focus on qualitative research in client experiences of psychotherapy. ORCID: 0000-0002-0536-1820.

Erminio Francesco Antares Spadaro graduated in Psychology at Università degli Studi di Messina (IT) (Bachelor program) and in Clinical Psychology at Università degli Studi di Palermo (IT) (Master program). He was trained as a Counselor in Family Constellations with Ad Vitam Geminos Association. He currently works as a research assistant at the Department of Psychology, University of Copenhagen.

Sabina Palic is a clinical psychologist and senior researcher at DIGNITY - Danish Institute against Torture and at Department for Treatment of Borderline Personality Disorder and Self-harm, Psychiatric Centre Glostrup. Her main areas of clinical and research interest is treatment of trauma and complex PTSD. She practises trauma-focused therapy, namely Prolonged Exposure (PE) and Narrative Exposure Therapy (NET). ORCID: 0000-0002-9686-9370.

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Correspondence to Stig Poulsen .

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Gjerstad, S.F., Nordin, L., Poulsen, S. et al. How is trauma-focused therapy experienced by adults with PTSD? A systematic review of qualitative studies. BMC Psychol 12 , 135 (2024). https://doi.org/10.1186/s40359-024-01588-x

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What is Qualitative in Qualitative Research

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What is qualitative research? If we look for a precise definition of qualitative research, and specifically for one that addresses its distinctive feature of being “qualitative,” the literature is meager. In this article we systematically search, identify and analyze a sample of 89 sources using or attempting to define the term “qualitative.” Then, drawing on ideas we find scattered across existing work, and based on Becker’s classic study of marijuana consumption, we formulate and illustrate a definition that tries to capture its core elements. We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. This formulation is developed as a tool to help improve research designs while stressing that a qualitative dimension is present in quantitative work as well. Additionally, it can facilitate teaching, communication between researchers, diminish the gap between qualitative and quantitative researchers, help to address critiques of qualitative methods, and be used as a standard of evaluation of qualitative research.

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If we assume that there is something called qualitative research, what exactly is this qualitative feature? And how could we evaluate qualitative research as good or not? Is it fundamentally different from quantitative research? In practice, most active qualitative researchers working with empirical material intuitively know what is involved in doing qualitative research, yet perhaps surprisingly, a clear definition addressing its key feature is still missing.

To address the question of what is qualitative we turn to the accounts of “qualitative research” in textbooks and also in empirical work. In his classic, explorative, interview study of deviance Howard Becker ( 1963 ) asks ‘How does one become a marijuana user?’ In contrast to pre-dispositional and psychological-individualistic theories of deviant behavior, Becker’s inherently social explanation contends that becoming a user of this substance is the result of a three-phase sequential learning process. First, potential users need to learn how to smoke it properly to produce the “correct” effects. If not, they are likely to stop experimenting with it. Second, they need to discover the effects associated with it; in other words, to get “high,” individuals not only have to experience what the drug does, but also to become aware that those sensations are related to using it. Third, they require learning to savor the feelings related to its consumption – to develop an acquired taste. Becker, who played music himself, gets close to the phenomenon by observing, taking part, and by talking to people consuming the drug: “half of the fifty interviews were conducted with musicians, the other half covered a wide range of people, including laborers, machinists, and people in the professions” (Becker 1963 :56).

Another central aspect derived through the common-to-all-research interplay between induction and deduction (Becker 2017 ), is that during the course of his research Becker adds scientifically meaningful new distinctions in the form of three phases—distinctions, or findings if you will, that strongly affect the course of his research: its focus, the material that he collects, and which eventually impact his findings. Each phase typically unfolds through social interaction, and often with input from experienced users in “a sequence of social experiences during which the person acquires a conception of the meaning of the behavior, and perceptions and judgments of objects and situations, all of which make the activity possible and desirable” (Becker 1963 :235). In this study the increased understanding of smoking dope is a result of a combination of the meaning of the actors, and the conceptual distinctions that Becker introduces based on the views expressed by his respondents. Understanding is the result of research and is due to an iterative process in which data, concepts and evidence are connected with one another (Becker 2017 ).

Indeed, there are many definitions of qualitative research, but if we look for a definition that addresses its distinctive feature of being “qualitative,” the literature across the broad field of social science is meager. The main reason behind this article lies in the paradox, which, to put it bluntly, is that researchers act as if they know what it is, but they cannot formulate a coherent definition. Sociologists and others will of course continue to conduct good studies that show the relevance and value of qualitative research addressing scientific and practical problems in society. However, our paper is grounded in the idea that providing a clear definition will help us improve the work that we do. Among researchers who practice qualitative research there is clearly much knowledge. We suggest that a definition makes this knowledge more explicit. If the first rationale for writing this paper refers to the “internal” aim of improving qualitative research, the second refers to the increased “external” pressure that especially many qualitative researchers feel; pressure that comes both from society as well as from other scientific approaches. There is a strong core in qualitative research, and leading researchers tend to agree on what it is and how it is done. Our critique is not directed at the practice of qualitative research, but we do claim that the type of systematic work we do has not yet been done, and that it is useful to improve the field and its status in relation to quantitative research.

The literature on the “internal” aim of improving, or at least clarifying qualitative research is large, and we do not claim to be the first to notice the vagueness of the term “qualitative” (Strauss and Corbin 1998 ). Also, others have noted that there is no single definition of it (Long and Godfrey 2004 :182), that there are many different views on qualitative research (Denzin and Lincoln 2003 :11; Jovanović 2011 :3), and that more generally, we need to define its meaning (Best 2004 :54). Strauss and Corbin ( 1998 ), for example, as well as Nelson et al. (1992:2 cited in Denzin and Lincoln 2003 :11), and Flick ( 2007 :ix–x), have recognized that the term is problematic: “Actually, the term ‘qualitative research’ is confusing because it can mean different things to different people” (Strauss and Corbin 1998 :10–11). Hammersley has discussed the possibility of addressing the problem, but states that “the task of providing an account of the distinctive features of qualitative research is far from straightforward” ( 2013 :2). This confusion, as he has recently further argued (Hammersley 2018 ), is also salient in relation to ethnography where different philosophical and methodological approaches lead to a lack of agreement about what it means.

Others (e.g. Hammersley 2018 ; Fine and Hancock 2017 ) have also identified the treat to qualitative research that comes from external forces, seen from the point of view of “qualitative research.” This threat can be further divided into that which comes from inside academia, such as the critique voiced by “quantitative research” and outside of academia, including, for example, New Public Management. Hammersley ( 2018 ), zooming in on one type of qualitative research, ethnography, has argued that it is under treat. Similarly to Fine ( 2003 ), and before him Gans ( 1999 ), he writes that ethnography’ has acquired a range of meanings, and comes in many different versions, these often reflecting sharply divergent epistemological orientations. And already more than twenty years ago while reviewing Denzin and Lincoln’ s Handbook of Qualitative Methods Fine argued:

While this increasing centrality [of qualitative research] might lead one to believe that consensual standards have developed, this belief would be misleading. As the methodology becomes more widely accepted, querulous challengers have raised fundamental questions that collectively have undercut the traditional models of how qualitative research is to be fashioned and presented (1995:417).

According to Hammersley, there are today “serious treats to the practice of ethnographic work, on almost any definition” ( 2018 :1). He lists five external treats: (1) that social research must be accountable and able to show its impact on society; (2) the current emphasis on “big data” and the emphasis on quantitative data and evidence; (3) the labor market pressure in academia that leaves less time for fieldwork (see also Fine and Hancock 2017 ); (4) problems of access to fields; and (5) the increased ethical scrutiny of projects, to which ethnography is particularly exposed. Hammersley discusses some more or less insufficient existing definitions of ethnography.

The current situation, as Hammersley and others note—and in relation not only to ethnography but also qualitative research in general, and as our empirical study shows—is not just unsatisfactory, it may even be harmful for the entire field of qualitative research, and does not help social science at large. We suggest that the lack of clarity of qualitative research is a real problem that must be addressed.

Towards a Definition of Qualitative Research

Seen in an historical light, what is today called qualitative, or sometimes ethnographic, interpretative research – or a number of other terms – has more or less always existed. At the time the founders of sociology – Simmel, Weber, Durkheim and, before them, Marx – were writing, and during the era of the Methodenstreit (“dispute about methods”) in which the German historical school emphasized scientific methods (cf. Swedberg 1990 ), we can at least speak of qualitative forerunners.

Perhaps the most extended discussion of what later became known as qualitative methods in a classic work is Bronisław Malinowski’s ( 1922 ) Argonauts in the Western Pacific , although even this study does not explicitly address the meaning of “qualitative.” In Weber’s ([1921–-22] 1978) work we find a tension between scientific explanations that are based on observation and quantification and interpretative research (see also Lazarsfeld and Barton 1982 ).

If we look through major sociology journals like the American Sociological Review , American Journal of Sociology , or Social Forces we will not find the term qualitative sociology before the 1970s. And certainly before then much of what we consider qualitative classics in sociology, like Becker’ study ( 1963 ), had already been produced. Indeed, the Chicago School often combined qualitative and quantitative data within the same study (Fine 1995 ). Our point being that before a disciplinary self-awareness the term quantitative preceded qualitative, and the articulation of the former was a political move to claim scientific status (Denzin and Lincoln 2005 ). In the US the World War II seem to have sparked a critique of sociological work, including “qualitative work,” that did not follow the scientific canon (Rawls 2018 ), which was underpinned by a scientifically oriented and value free philosophy of science. As a result the attempts and practice of integrating qualitative and quantitative sociology at Chicago lost ground to sociology that was more oriented to surveys and quantitative work at Columbia under Merton-Lazarsfeld. The quantitative tradition was also able to present textbooks (Lundberg 1951 ) that facilitated the use this approach and its “methods.” The practices of the qualitative tradition, by and large, remained tacit or was part of the mentoring transferred from the renowned masters to their students.

This glimpse into history leads us back to the lack of a coherent account condensed in a definition of qualitative research. Many of the attempts to define the term do not meet the requirements of a proper definition: A definition should be clear, avoid tautology, demarcate its domain in relation to the environment, and ideally only use words in its definiens that themselves are not in need of definition (Hempel 1966 ). A definition can enhance precision and thus clarity by identifying the core of the phenomenon. Preferably, a definition should be short. The typical definition we have found, however, is an ostensive definition, which indicates what qualitative research is about without informing us about what it actually is :

Qualitative research is multimethod in focus, involving an interpretative, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives. (Denzin and Lincoln 2005 :2)

Flick claims that the label “qualitative research” is indeed used as an umbrella for a number of approaches ( 2007 :2–4; 2002 :6), and it is not difficult to identify research fitting this designation. Moreover, whatever it is, it has grown dramatically over the past five decades. In addition, courses have been developed, methods have flourished, arguments about its future have been advanced (for example, Denzin and Lincoln 1994) and criticized (for example, Snow and Morrill 1995 ), and dedicated journals and books have mushroomed. Most social scientists have a clear idea of research and how it differs from journalism, politics and other activities. But the question of what is qualitative in qualitative research is either eluded or eschewed.

We maintain that this lacuna hinders systematic knowledge production based on qualitative research. Paul Lazarsfeld noted the lack of “codification” as early as 1955 when he reviewed 100 qualitative studies in order to offer a codification of the practices (Lazarsfeld and Barton 1982 :239). Since then many texts on “qualitative research” and its methods have been published, including recent attempts (Goertz and Mahoney 2012 ) similar to Lazarsfeld’s. These studies have tried to extract what is qualitative by looking at the large number of empirical “qualitative” studies. Our novel strategy complements these endeavors by taking another approach and looking at the attempts to codify these practices in the form of a definition, as well as to a minor extent take Becker’s study as an exemplar of what qualitative researchers actually do, and what the characteristic of being ‘qualitative’ denotes and implies. We claim that qualitative researchers, if there is such a thing as “qualitative research,” should be able to codify their practices in a condensed, yet general way expressed in language.

Lingering problems of “generalizability” and “how many cases do I need” (Small 2009 ) are blocking advancement – in this line of work qualitative approaches are said to differ considerably from quantitative ones, while some of the former unsuccessfully mimic principles related to the latter (Small 2009 ). Additionally, quantitative researchers sometimes unfairly criticize the first based on their own quality criteria. Scholars like Goertz and Mahoney ( 2012 ) have successfully focused on the different norms and practices beyond what they argue are essentially two different cultures: those working with either qualitative or quantitative methods. Instead, similarly to Becker ( 2017 ) who has recently questioned the usefulness of the distinction between qualitative and quantitative research, we focus on similarities.

The current situation also impedes both students and researchers in focusing their studies and understanding each other’s work (Lazarsfeld and Barton 1982 :239). A third consequence is providing an opening for critiques by scholars operating within different traditions (Valsiner 2000 :101). A fourth issue is that the “implicit use of methods in qualitative research makes the field far less standardized than the quantitative paradigm” (Goertz and Mahoney 2012 :9). Relatedly, the National Science Foundation in the US organized two workshops in 2004 and 2005 to address the scientific foundations of qualitative research involving strategies to improve it and to develop standards of evaluation in qualitative research. However, a specific focus on its distinguishing feature of being “qualitative” while being implicitly acknowledged, was discussed only briefly (for example, Best 2004 ).

In 2014 a theme issue was published in this journal on “Methods, Materials, and Meanings: Designing Cultural Analysis,” discussing central issues in (cultural) qualitative research (Berezin 2014 ; Biernacki 2014 ; Glaeser 2014 ; Lamont and Swidler 2014 ; Spillman 2014). We agree with many of the arguments put forward, such as the risk of methodological tribalism, and that we should not waste energy on debating methods separated from research questions. Nonetheless, a clarification of the relation to what is called “quantitative research” is of outmost importance to avoid misunderstandings and misguided debates between “qualitative” and “quantitative” researchers. Our strategy means that researchers, “qualitative” or “quantitative” they may be, in their actual practice may combine qualitative work and quantitative work.

In this article we accomplish three tasks. First, we systematically survey the literature for meanings of qualitative research by looking at how researchers have defined it. Drawing upon existing knowledge we find that the different meanings and ideas of qualitative research are not yet coherently integrated into one satisfactory definition. Next, we advance our contribution by offering a definition of qualitative research and illustrate its meaning and use partially by expanding on the brief example introduced earlier related to Becker’s work ( 1963 ). We offer a systematic analysis of central themes of what researchers consider to be the core of “qualitative,” regardless of style of work. These themes – which we summarize in terms of four keywords: distinction, process, closeness, improved understanding – constitute part of our literature review, in which each one appears, sometimes with others, but never all in the same definition. They serve as the foundation of our contribution. Our categories are overlapping. Their use is primarily to organize the large amount of definitions we have identified and analyzed, and not necessarily to draw a clear distinction between them. Finally, we continue the elaboration discussed above on the advantages of a clear definition of qualitative research.

In a hermeneutic fashion we propose that there is something meaningful that deserves to be labelled “qualitative research” (Gadamer 1990 ). To approach the question “What is qualitative in qualitative research?” we have surveyed the literature. In conducting our survey we first traced the word’s etymology in dictionaries, encyclopedias, handbooks of the social sciences and of methods and textbooks, mainly in English, which is common to methodology courses. It should be noted that we have zoomed in on sociology and its literature. This discipline has been the site of the largest debate and development of methods that can be called “qualitative,” which suggests that this field should be examined in great detail.

In an ideal situation we should expect that one good definition, or at least some common ideas, would have emerged over the years. This common core of qualitative research should be so accepted that it would appear in at least some textbooks. Since this is not what we found, we decided to pursue an inductive approach to capture maximal variation in the field of qualitative research; we searched in a selection of handbooks, textbooks, book chapters, and books, to which we added the analysis of journal articles. Our sample comprises a total of 89 references.

In practice we focused on the discipline that has had a clear discussion of methods, namely sociology. We also conducted a broad search in the JSTOR database to identify scholarly sociology articles published between 1998 and 2017 in English with a focus on defining or explaining qualitative research. We specifically zoom in on this time frame because we would have expect that this more mature period would have produced clear discussions on the meaning of qualitative research. To find these articles we combined a number of keywords to search the content and/or the title: qualitative (which was always included), definition, empirical, research, methodology, studies, fieldwork, interview and observation .

As a second phase of our research we searched within nine major sociological journals ( American Journal of Sociology , Sociological Theory , American Sociological Review , Contemporary Sociology , Sociological Forum , Sociological Theory , Qualitative Research , Qualitative Sociology and Qualitative Sociology Review ) for articles also published during the past 19 years (1998–2017) that had the term “qualitative” in the title and attempted to define qualitative research.

Lastly we picked two additional journals, Qualitative Research and Qualitative Sociology , in which we could expect to find texts addressing the notion of “qualitative.” From Qualitative Research we chose Volume 14, Issue 6, December 2014, and from Qualitative Sociology we chose Volume 36, Issue 2, June 2017. Within each of these we selected the first article; then we picked the second article of three prior issues. Again we went back another three issues and investigated article number three. Finally we went back another three issues and perused article number four. This selection criteria was used to get a manageable sample for the analysis.

The coding process of the 89 references we gathered in our selected review began soon after the first round of material was gathered, and we reduced the complexity created by our maximum variation sampling (Snow and Anderson 1993 :22) to four different categories within which questions on the nature and properties of qualitative research were discussed. We call them: Qualitative and Quantitative Research, Qualitative Research, Fieldwork, and Grounded Theory. This – which may appear as an illogical grouping – merely reflects the “context” in which the matter of “qualitative” is discussed. If the selection process of the material – books and articles – was informed by pre-knowledge, we used an inductive strategy to code the material. When studying our material, we identified four central notions related to “qualitative” that appear in various combinations in the literature which indicate what is the core of qualitative research. We have labeled them: “distinctions”, “process,” “closeness,” and “improved understanding.” During the research process the categories and notions were improved, refined, changed, and reordered. The coding ended when a sense of saturation in the material arose. In the presentation below all quotations and references come from our empirical material of texts on qualitative research.

Analysis – What is Qualitative Research?

In this section we describe the four categories we identified in the coding, how they differently discuss qualitative research, as well as their overall content. Some salient quotations are selected to represent the type of text sorted under each of the four categories. What we present are examples from the literature.

Qualitative and Quantitative

This analytic category comprises quotations comparing qualitative and quantitative research, a distinction that is frequently used (Brown 2010 :231); in effect this is a conceptual pair that structures the discussion and that may be associated with opposing interests. While the general goal of quantitative and qualitative research is the same – to understand the world better – their methodologies and focus in certain respects differ substantially (Becker 1966 :55). Quantity refers to that property of something that can be determined by measurement. In a dictionary of Statistics and Methodology we find that “(a) When referring to *variables, ‘qualitative’ is another term for *categorical or *nominal. (b) When speaking of kinds of research, ‘qualitative’ refers to studies of subjects that are hard to quantify, such as art history. Qualitative research tends to be a residual category for almost any kind of non-quantitative research” (Stiles 1998:183). But it should be obvious that one could employ a quantitative approach when studying, for example, art history.

The same dictionary states that quantitative is “said of variables or research that can be handled numerically, usually (too sharply) contrasted with *qualitative variables and research” (Stiles 1998:184). From a qualitative perspective “quantitative research” is about numbers and counting, and from a quantitative perspective qualitative research is everything that is not about numbers. But this does not say much about what is “qualitative.” If we turn to encyclopedias we find that in the 1932 edition of the Encyclopedia of the Social Sciences there is no mention of “qualitative.” In the Encyclopedia from 1968 we can read:

Qualitative Analysis. For methods of obtaining, analyzing, and describing data, see [the various entries:] CONTENT ANALYSIS; COUNTED DATA; EVALUATION RESEARCH, FIELD WORK; GRAPHIC PRESENTATION; HISTORIOGRAPHY, especially the article on THE RHETORIC OF HISTORY; INTERVIEWING; OBSERVATION; PERSONALITY MEASUREMENT; PROJECTIVE METHODS; PSYCHOANALYSIS, article on EXPERIMENTAL METHODS; SURVEY ANALYSIS, TABULAR PRESENTATION; TYPOLOGIES. (Vol. 13:225)

Some, like Alford, divide researchers into methodologists or, in his words, “quantitative and qualitative specialists” (Alford 1998 :12). Qualitative research uses a variety of methods, such as intensive interviews or in-depth analysis of historical materials, and it is concerned with a comprehensive account of some event or unit (King et al. 1994 :4). Like quantitative research it can be utilized to study a variety of issues, but it tends to focus on meanings and motivations that underlie cultural symbols, personal experiences, phenomena and detailed understanding of processes in the social world. In short, qualitative research centers on understanding processes, experiences, and the meanings people assign to things (Kalof et al. 2008 :79).

Others simply say that qualitative methods are inherently unscientific (Jovanović 2011 :19). Hood, for instance, argues that words are intrinsically less precise than numbers, and that they are therefore more prone to subjective analysis, leading to biased results (Hood 2006 :219). Qualitative methodologies have raised concerns over the limitations of quantitative templates (Brady et al. 2004 :4). Scholars such as King et al. ( 1994 ), for instance, argue that non-statistical research can produce more reliable results if researchers pay attention to the rules of scientific inference commonly stated in quantitative research. Also, researchers such as Becker ( 1966 :59; 1970 :42–43) have asserted that, if conducted properly, qualitative research and in particular ethnographic field methods, can lead to more accurate results than quantitative studies, in particular, survey research and laboratory experiments.

Some researchers, such as Kalof, Dan, and Dietz ( 2008 :79) claim that the boundaries between the two approaches are becoming blurred, and Small ( 2009 ) argues that currently much qualitative research (especially in North America) tries unsuccessfully and unnecessarily to emulate quantitative standards. For others, qualitative research tends to be more humanistic and discursive (King et al. 1994 :4). Ragin ( 1994 ), and similarly also Becker, ( 1996 :53), Marchel and Owens ( 2007 :303) think that the main distinction between the two styles is overstated and does not rest on the simple dichotomy of “numbers versus words” (Ragin 1994 :xii). Some claim that quantitative data can be utilized to discover associations, but in order to unveil cause and effect a complex research design involving the use of qualitative approaches needs to be devised (Gilbert 2009 :35). Consequently, qualitative data are useful for understanding the nuances lying beyond those processes as they unfold (Gilbert 2009 :35). Others contend that qualitative research is particularly well suited both to identify causality and to uncover fine descriptive distinctions (Fine and Hallett 2014 ; Lichterman and Isaac Reed 2014 ; Katz 2015 ).

There are other ways to separate these two traditions, including normative statements about what qualitative research should be (that is, better or worse than quantitative approaches, concerned with scientific approaches to societal change or vice versa; Snow and Morrill 1995 ; Denzin and Lincoln 2005 ), or whether it should develop falsifiable statements; Best 2004 ).

We propose that quantitative research is largely concerned with pre-determined variables (Small 2008 ); the analysis concerns the relations between variables. These categories are primarily not questioned in the study, only their frequency or degree, or the correlations between them (cf. Franzosi 2016 ). If a researcher studies wage differences between women and men, he or she works with given categories: x number of men are compared with y number of women, with a certain wage attributed to each person. The idea is not to move beyond the given categories of wage, men and women; they are the starting point as well as the end point, and undergo no “qualitative change.” Qualitative research, in contrast, investigates relations between categories that are themselves subject to change in the research process. Returning to Becker’s study ( 1963 ), we see that he questioned pre-dispositional theories of deviant behavior working with pre-determined variables such as an individual’s combination of personal qualities or emotional problems. His take, in contrast, was to understand marijuana consumption by developing “variables” as part of the investigation. Thereby he presented new variables, or as we would say today, theoretical concepts, but which are grounded in the empirical material.

Qualitative Research

This category contains quotations that refer to descriptions of qualitative research without making comparisons with quantitative research. Researchers such as Denzin and Lincoln, who have written a series of influential handbooks on qualitative methods (1994; Denzin and Lincoln 2003 ; 2005 ), citing Nelson et al. (1992:4), argue that because qualitative research is “interdisciplinary, transdisciplinary, and sometimes counterdisciplinary” it is difficult to derive one single definition of it (Jovanović 2011 :3). According to them, in fact, “the field” is “many things at the same time,” involving contradictions, tensions over its focus, methods, and how to derive interpretations and findings ( 2003 : 11). Similarly, others, such as Flick ( 2007 :ix–x) contend that agreeing on an accepted definition has increasingly become problematic, and that qualitative research has possibly matured different identities. However, Best holds that “the proliferation of many sorts of activities under the label of qualitative sociology threatens to confuse our discussions” ( 2004 :54). Atkinson’s position is more definite: “the current state of qualitative research and research methods is confused” ( 2005 :3–4).

Qualitative research is about interpretation (Blumer 1969 ; Strauss and Corbin 1998 ; Denzin and Lincoln 2003 ), or Verstehen [understanding] (Frankfort-Nachmias and Nachmias 1996 ). It is “multi-method,” involving the collection and use of a variety of empirical materials (Denzin and Lincoln 1998; Silverman 2013 ) and approaches (Silverman 2005 ; Flick 2007 ). It focuses not only on the objective nature of behavior but also on its subjective meanings: individuals’ own accounts of their attitudes, motivations, behavior (McIntyre 2005 :127; Creswell 2009 ), events and situations (Bryman 1989) – what people say and do in specific places and institutions (Goodwin and Horowitz 2002 :35–36) in social and temporal contexts (Morrill and Fine 1997). For this reason, following Weber ([1921-22] 1978), it can be described as an interpretative science (McIntyre 2005 :127). But could quantitative research also be concerned with these questions? Also, as pointed out below, does all qualitative research focus on subjective meaning, as some scholars suggest?

Others also distinguish qualitative research by claiming that it collects data using a naturalistic approach (Denzin and Lincoln 2005 :2; Creswell 2009 ), focusing on the meaning actors ascribe to their actions. But again, does all qualitative research need to be collected in situ? And does qualitative research have to be inherently concerned with meaning? Flick ( 2007 ), referring to Denzin and Lincoln ( 2005 ), mentions conversation analysis as an example of qualitative research that is not concerned with the meanings people bring to a situation, but rather with the formal organization of talk. Still others, such as Ragin ( 1994 :85), note that qualitative research is often (especially early on in the project, we would add) less structured than other kinds of social research – a characteristic connected to its flexibility and that can lead both to potentially better, but also worse results. But is this not a feature of this type of research, rather than a defining description of its essence? Wouldn’t this comment also apply, albeit to varying degrees, to quantitative research?

In addition, Strauss ( 2003 ), along with others, such as Alvesson and Kärreman ( 2011 :10–76), argue that qualitative researchers struggle to capture and represent complex phenomena partially because they tend to collect a large amount of data. While his analysis is correct at some points – “It is necessary to do detailed, intensive, microscopic examination of the data in order to bring out the amazing complexity of what lies in, behind, and beyond those data” (Strauss 2003 :10) – much of his analysis concerns the supposed focus of qualitative research and its challenges, rather than exactly what it is about. But even in this instance we would make a weak case arguing that these are strictly the defining features of qualitative research. Some researchers seem to focus on the approach or the methods used, or even on the way material is analyzed. Several researchers stress the naturalistic assumption of investigating the world, suggesting that meaning and interpretation appear to be a core matter of qualitative research.

We can also see that in this category there is no consensus about specific qualitative methods nor about qualitative data. Many emphasize interpretation, but quantitative research, too, involves interpretation; the results of a regression analysis, for example, certainly have to be interpreted, and the form of meta-analysis that factor analysis provides indeed requires interpretation However, there is no interpretation of quantitative raw data, i.e., numbers in tables. One common thread is that qualitative researchers have to get to grips with their data in order to understand what is being studied in great detail, irrespective of the type of empirical material that is being analyzed. This observation is connected to the fact that qualitative researchers routinely make several adjustments of focus and research design as their studies progress, in many cases until the very end of the project (Kalof et al. 2008 ). If you, like Becker, do not start out with a detailed theory, adjustments such as the emergence and refinement of research questions will occur during the research process. We have thus found a number of useful reflections about qualitative research scattered across different sources, but none of them effectively describe the defining characteristics of this approach.

Although qualitative research does not appear to be defined in terms of a specific method, it is certainly common that fieldwork, i.e., research that entails that the researcher spends considerable time in the field that is studied and use the knowledge gained as data, is seen as emblematic of or even identical to qualitative research. But because we understand that fieldwork tends to focus primarily on the collection and analysis of qualitative data, we expected to find within it discussions on the meaning of “qualitative.” But, again, this was not the case.

Instead, we found material on the history of this approach (for example, Frankfort-Nachmias and Nachmias 1996 ; Atkinson et al. 2001), including how it has changed; for example, by adopting a more self-reflexive practice (Heyl 2001), as well as the different nomenclature that has been adopted, such as fieldwork, ethnography, qualitative research, naturalistic research, participant observation and so on (for example, Lofland et al. 2006 ; Gans 1999 ).

We retrieved definitions of ethnography, such as “the study of people acting in the natural courses of their daily lives,” involving a “resocialization of the researcher” (Emerson 1988 :1) through intense immersion in others’ social worlds (see also examples in Hammersley 2018 ). This may be accomplished by direct observation and also participation (Neuman 2007 :276), although others, such as Denzin ( 1970 :185), have long recognized other types of observation, including non-participant (“fly on the wall”). In this category we have also isolated claims and opposing views, arguing that this type of research is distinguished primarily by where it is conducted (natural settings) (Hughes 1971:496), and how it is carried out (a variety of methods are applied) or, for some most importantly, by involving an active, empathetic immersion in those being studied (Emerson 1988 :2). We also retrieved descriptions of the goals it attends in relation to how it is taught (understanding subjective meanings of the people studied, primarily develop theory, or contribute to social change) (see for example, Corte and Irwin 2017 ; Frankfort-Nachmias and Nachmias 1996 :281; Trier-Bieniek 2012 :639) by collecting the richest possible data (Lofland et al. 2006 ) to derive “thick descriptions” (Geertz 1973 ), and/or to aim at theoretical statements of general scope and applicability (for example, Emerson 1988 ; Fine 2003 ). We have identified guidelines on how to evaluate it (for example Becker 1996 ; Lamont 2004 ) and have retrieved instructions on how it should be conducted (for example, Lofland et al. 2006 ). For instance, analysis should take place while the data gathering unfolds (Emerson 1988 ; Hammersley and Atkinson 2007 ; Lofland et al. 2006 ), observations should be of long duration (Becker 1970 :54; Goffman 1989 ), and data should be of high quantity (Becker 1970 :52–53), as well as other questionable distinctions between fieldwork and other methods:

Field studies differ from other methods of research in that the researcher performs the task of selecting topics, decides what questions to ask, and forges interest in the course of the research itself . This is in sharp contrast to many ‘theory-driven’ and ‘hypothesis-testing’ methods. (Lofland and Lofland 1995 :5)

But could not, for example, a strictly interview-based study be carried out with the same amount of flexibility, such as sequential interviewing (for example, Small 2009 )? Once again, are quantitative approaches really as inflexible as some qualitative researchers think? Moreover, this category stresses the role of the actors’ meaning, which requires knowledge and close interaction with people, their practices and their lifeworld.

It is clear that field studies – which are seen by some as the “gold standard” of qualitative research – are nonetheless only one way of doing qualitative research. There are other methods, but it is not clear why some are more qualitative than others, or why they are better or worse. Fieldwork is characterized by interaction with the field (the material) and understanding of the phenomenon that is being studied. In Becker’s case, he had general experience from fields in which marihuana was used, based on which he did interviews with actual users in several fields.

Grounded Theory

Another major category we identified in our sample is Grounded Theory. We found descriptions of it most clearly in Glaser and Strauss’ ([1967] 2010 ) original articulation, Strauss and Corbin ( 1998 ) and Charmaz ( 2006 ), as well as many other accounts of what it is for: generating and testing theory (Strauss 2003 :xi). We identified explanations of how this task can be accomplished – such as through two main procedures: constant comparison and theoretical sampling (Emerson 1998:96), and how using it has helped researchers to “think differently” (for example, Strauss and Corbin 1998 :1). We also read descriptions of its main traits, what it entails and fosters – for instance, an exceptional flexibility, an inductive approach (Strauss and Corbin 1998 :31–33; 1990; Esterberg 2002 :7), an ability to step back and critically analyze situations, recognize tendencies towards bias, think abstractly and be open to criticism, enhance sensitivity towards the words and actions of respondents, and develop a sense of absorption and devotion to the research process (Strauss and Corbin 1998 :5–6). Accordingly, we identified discussions of the value of triangulating different methods (both using and not using grounded theory), including quantitative ones, and theories to achieve theoretical development (most comprehensively in Denzin 1970 ; Strauss and Corbin 1998 ; Timmermans and Tavory 2012 ). We have also located arguments about how its practice helps to systematize data collection, analysis and presentation of results (Glaser and Strauss [1967] 2010 :16).

Grounded theory offers a systematic approach which requires researchers to get close to the field; closeness is a requirement of identifying questions and developing new concepts or making further distinctions with regard to old concepts. In contrast to other qualitative approaches, grounded theory emphasizes the detailed coding process, and the numerous fine-tuned distinctions that the researcher makes during the process. Within this category, too, we could not find a satisfying discussion of the meaning of qualitative research.

Defining Qualitative Research

In sum, our analysis shows that some notions reappear in the discussion of qualitative research, such as understanding, interpretation, “getting close” and making distinctions. These notions capture aspects of what we think is “qualitative.” However, a comprehensive definition that is useful and that can further develop the field is lacking, and not even a clear picture of its essential elements appears. In other words no definition emerges from our data, and in our research process we have moved back and forth between our empirical data and the attempt to present a definition. Our concrete strategy, as stated above, is to relate qualitative and quantitative research, or more specifically, qualitative and quantitative work. We use an ideal-typical notion of quantitative research which relies on taken for granted and numbered variables. This means that the data consists of variables on different scales, such as ordinal, but frequently ratio and absolute scales, and the representation of the numbers to the variables, i.e. the justification of the assignment of numbers to object or phenomenon, are not questioned, though the validity may be questioned. In this section we return to the notion of quality and try to clarify it while presenting our contribution.

Broadly, research refers to the activity performed by people trained to obtain knowledge through systematic procedures. Notions such as “objectivity” and “reflexivity,” “systematic,” “theory,” “evidence” and “openness” are here taken for granted in any type of research. Next, building on our empirical analysis we explain the four notions that we have identified as central to qualitative work: distinctions, process, closeness, and improved understanding. In discussing them, ultimately in relation to one another, we make their meaning even more precise. Our idea, in short, is that only when these ideas that we present separately for analytic purposes are brought together can we speak of qualitative research.

Distinctions

We believe that the possibility of making new distinctions is one the defining characteristics of qualitative research. It clearly sets it apart from quantitative analysis which works with taken-for-granted variables, albeit as mentioned, meta-analyses, for example, factor analysis may result in new variables. “Quality” refers essentially to distinctions, as already pointed out by Aristotle. He discusses the term “qualitative” commenting: “By a quality I mean that in virtue of which things are said to be qualified somehow” (Aristotle 1984:14). Quality is about what something is or has, which means that the distinction from its environment is crucial. We see qualitative research as a process in which significant new distinctions are made to the scholarly community; to make distinctions is a key aspect of obtaining new knowledge; a point, as we will see, that also has implications for “quantitative research.” The notion of being “significant” is paramount. New distinctions by themselves are not enough; just adding concepts only increases complexity without furthering our knowledge. The significance of new distinctions is judged against the communal knowledge of the research community. To enable this discussion and judgements central elements of rational discussion are required (cf. Habermas [1981] 1987 ; Davidsson [ 1988 ] 2001) to identify what is new and relevant scientific knowledge. Relatedly, Ragin alludes to the idea of new and useful knowledge at a more concrete level: “Qualitative methods are appropriate for in-depth examination of cases because they aid the identification of key features of cases. Most qualitative methods enhance data” (1994:79). When Becker ( 1963 ) studied deviant behavior and investigated how people became marihuana smokers, he made distinctions between the ways in which people learned how to smoke. This is a classic example of how the strategy of “getting close” to the material, for example the text, people or pictures that are subject to analysis, may enable researchers to obtain deeper insight and new knowledge by making distinctions – in this instance on the initial notion of learning how to smoke. Others have stressed the making of distinctions in relation to coding or theorizing. Emerson et al. ( 1995 ), for example, hold that “qualitative coding is a way of opening up avenues of inquiry,” meaning that the researcher identifies and develops concepts and analytic insights through close examination of and reflection on data (Emerson et al. 1995 :151). Goodwin and Horowitz highlight making distinctions in relation to theory-building writing: “Close engagement with their cases typically requires qualitative researchers to adapt existing theories or to make new conceptual distinctions or theoretical arguments to accommodate new data” ( 2002 : 37). In the ideal-typical quantitative research only existing and so to speak, given, variables would be used. If this is the case no new distinction are made. But, would not also many “quantitative” researchers make new distinctions?

Process does not merely suggest that research takes time. It mainly implies that qualitative new knowledge results from a process that involves several phases, and above all iteration. Qualitative research is about oscillation between theory and evidence, analysis and generating material, between first- and second -order constructs (Schütz 1962 :59), between getting in contact with something, finding sources, becoming deeply familiar with a topic, and then distilling and communicating some of its essential features. The main point is that the categories that the researcher uses, and perhaps takes for granted at the beginning of the research process, usually undergo qualitative changes resulting from what is found. Becker describes how he tested hypotheses and let the jargon of the users develop into theoretical concepts. This happens over time while the study is being conducted, exemplifying what we mean by process.

In the research process, a pilot-study may be used to get a first glance of, for example, the field, how to approach it, and what methods can be used, after which the method and theory are chosen or refined before the main study begins. Thus, the empirical material is often central from the start of the project and frequently leads to adjustments by the researcher. Likewise, during the main study categories are not fixed; the empirical material is seen in light of the theory used, but it is also given the opportunity to kick back, thereby resisting attempts to apply theoretical straightjackets (Becker 1970 :43). In this process, coding and analysis are interwoven, and thus are often important steps for getting closer to the phenomenon and deciding what to focus on next. Becker began his research by interviewing musicians close to him, then asking them to refer him to other musicians, and later on doubling his original sample of about 25 to include individuals in other professions (Becker 1973:46). Additionally, he made use of some participant observation, documents, and interviews with opiate users made available to him by colleagues. As his inductive theory of deviance evolved, Becker expanded his sample in order to fine tune it, and test the accuracy and generality of his hypotheses. In addition, he introduced a negative case and discussed the null hypothesis ( 1963 :44). His phasic career model is thus based on a research design that embraces processual work. Typically, process means to move between “theory” and “material” but also to deal with negative cases, and Becker ( 1998 ) describes how discovering these negative cases impacted his research design and ultimately its findings.

Obviously, all research is process-oriented to some degree. The point is that the ideal-typical quantitative process does not imply change of the data, and iteration between data, evidence, hypotheses, empirical work, and theory. The data, quantified variables, are, in most cases fixed. Merging of data, which of course can be done in a quantitative research process, does not mean new data. New hypotheses are frequently tested, but the “raw data is often the “the same.” Obviously, over time new datasets are made available and put into use.

Another characteristic that is emphasized in our sample is that qualitative researchers – and in particular ethnographers – can, or as Goffman put it, ought to ( 1989 ), get closer to the phenomenon being studied and their data than quantitative researchers (for example, Silverman 2009 :85). Put differently, essentially because of their methods qualitative researchers get into direct close contact with those being investigated and/or the material, such as texts, being analyzed. Becker started out his interview study, as we noted, by talking to those he knew in the field of music to get closer to the phenomenon he was studying. By conducting interviews he got even closer. Had he done more observations, he would undoubtedly have got even closer to the field.

Additionally, ethnographers’ design enables researchers to follow the field over time, and the research they do is almost by definition longitudinal, though the time in the field is studied obviously differs between studies. The general characteristic of closeness over time maximizes the chances of unexpected events, new data (related, for example, to archival research as additional sources, and for ethnography for situations not necessarily previously thought of as instrumental – what Mannay and Morgan ( 2015 ) term the “waiting field”), serendipity (Merton and Barber 2004 ; Åkerström 2013 ), and possibly reactivity, as well as the opportunity to observe disrupted patterns that translate into exemplars of negative cases. Two classic examples of this are Becker’s finding of what medical students call “crocks” (Becker et al. 1961 :317), and Geertz’s ( 1973 ) study of “deep play” in Balinese society.

By getting and staying so close to their data – be it pictures, text or humans interacting (Becker was himself a musician) – for a long time, as the research progressively focuses, qualitative researchers are prompted to continually test their hunches, presuppositions and hypotheses. They test them against a reality that often (but certainly not always), and practically, as well as metaphorically, talks back, whether by validating them, or disqualifying their premises – correctly, as well as incorrectly (Fine 2003 ; Becker 1970 ). This testing nonetheless often leads to new directions for the research. Becker, for example, says that he was initially reading psychological theories, but when facing the data he develops a theory that looks at, you may say, everything but psychological dispositions to explain the use of marihuana. Especially researchers involved with ethnographic methods have a fairly unique opportunity to dig up and then test (in a circular, continuous and temporal way) new research questions and findings as the research progresses, and thereby to derive previously unimagined and uncharted distinctions by getting closer to the phenomenon under study.

Let us stress that getting close is by no means restricted to ethnography. The notion of hermeneutic circle and hermeneutics as a general way of understanding implies that we must get close to the details in order to get the big picture. This also means that qualitative researchers can literally also make use of details of pictures as evidence (cf. Harper 2002). Thus, researchers may get closer both when generating the material or when analyzing it.

Quantitative research, we maintain, in the ideal-typical representation cannot get closer to the data. The data is essentially numbers in tables making up the variables (Franzosi 2016 :138). The data may originally have been “qualitative,” but once reduced to numbers there can only be a type of “hermeneutics” about what the number may stand for. The numbers themselves, however, are non-ambiguous. Thus, in quantitative research, interpretation, if done, is not about the data itself—the numbers—but what the numbers stand for. It follows that the interpretation is essentially done in a more “speculative” mode without direct empirical evidence (cf. Becker 2017 ).

Improved Understanding

While distinction, process and getting closer refer to the qualitative work of the researcher, improved understanding refers to its conditions and outcome of this work. Understanding cuts deeper than explanation, which to some may mean a causally verified correlation between variables. The notion of explanation presupposes the notion of understanding since explanation does not include an idea of how knowledge is gained (Manicas 2006 : 15). Understanding, we argue, is the core concept of what we call the outcome of the process when research has made use of all the other elements that were integrated in the research. Understanding, then, has a special status in qualitative research since it refers both to the conditions of knowledge and the outcome of the process. Understanding can to some extent be seen as the condition of explanation and occurs in a process of interpretation, which naturally refers to meaning (Gadamer 1990 ). It is fundamentally connected to knowing, and to the knowing of how to do things (Heidegger [1927] 2001 ). Conceptually the term hermeneutics is used to account for this process. Heidegger ties hermeneutics to human being and not possible to separate from the understanding of being ( 1988 ). Here we use it in a broader sense, and more connected to method in general (cf. Seiffert 1992 ). The abovementioned aspects – for example, “objectivity” and “reflexivity” – of the approach are conditions of scientific understanding. Understanding is the result of a circular process and means that the parts are understood in light of the whole, and vice versa. Understanding presupposes pre-understanding, or in other words, some knowledge of the phenomenon studied. The pre-understanding, even in the form of prejudices, are in qualitative research process, which we see as iterative, questioned, which gradually or suddenly change due to the iteration of data, evidence and concepts. However, qualitative research generates understanding in the iterative process when the researcher gets closer to the data, e.g., by going back and forth between field and analysis in a process that generates new data that changes the evidence, and, ultimately, the findings. Questioning, to ask questions, and put what one assumes—prejudices and presumption—in question, is central to understand something (Heidegger [1927] 2001 ; Gadamer 1990 :368–384). We propose that this iterative process in which the process of understanding occurs is characteristic of qualitative research.

Improved understanding means that we obtain scientific knowledge of something that we as a scholarly community did not know before, or that we get to know something better. It means that we understand more about how parts are related to one another, and to other things we already understand (see also Fine and Hallett 2014 ). Understanding is an important condition for qualitative research. It is not enough to identify correlations, make distinctions, and work in a process in which one gets close to the field or phenomena. Understanding is accomplished when the elements are integrated in an iterative process.

It is, moreover, possible to understand many things, and researchers, just like children, may come to understand new things every day as they engage with the world. This subjective condition of understanding – namely, that a person gains a better understanding of something –is easily met. To be qualified as “scientific,” the understanding must be general and useful to many; it must be public. But even this generally accessible understanding is not enough in order to speak of “scientific understanding.” Though we as a collective can increase understanding of everything in virtually all potential directions as a result also of qualitative work, we refrain from this “objective” way of understanding, which has no means of discriminating between what we gain in understanding. Scientific understanding means that it is deemed relevant from the scientific horizon (compare Schütz 1962 : 35–38, 46, 63), and that it rests on the pre-understanding that the scientists have and must have in order to understand. In other words, the understanding gained must be deemed useful by other researchers, so that they can build on it. We thus see understanding from a pragmatic, rather than a subjective or objective perspective. Improved understanding is related to the question(s) at hand. Understanding, in order to represent an improvement, must be an improvement in relation to the existing body of knowledge of the scientific community (James [ 1907 ] 1955). Scientific understanding is, by definition, collective, as expressed in Weber’s famous note on objectivity, namely that scientific work aims at truths “which … can claim, even for a Chinese, the validity appropriate to an empirical analysis” ([1904] 1949 :59). By qualifying “improved understanding” we argue that it is a general defining characteristic of qualitative research. Becker‘s ( 1966 ) study and other research of deviant behavior increased our understanding of the social learning processes of how individuals start a behavior. And it also added new knowledge about the labeling of deviant behavior as a social process. Few studies, of course, make the same large contribution as Becker’s, but are nonetheless qualitative research.

Understanding in the phenomenological sense, which is a hallmark of qualitative research, we argue, requires meaning and this meaning is derived from the context, and above all the data being analyzed. The ideal-typical quantitative research operates with given variables with different numbers. This type of material is not enough to establish meaning at the level that truly justifies understanding. In other words, many social science explanations offer ideas about correlations or even causal relations, but this does not mean that the meaning at the level of the data analyzed, is understood. This leads us to say that there are indeed many explanations that meet the criteria of understanding, for example the explanation of how one becomes a marihuana smoker presented by Becker. However, we may also understand a phenomenon without explaining it, and we may have potential explanations, or better correlations, that are not really understood.

We may speak more generally of quantitative research and its data to clarify what we see as an important distinction. The “raw data” that quantitative research—as an idealtypical activity, refers to is not available for further analysis; the numbers, once created, are not to be questioned (Franzosi 2016 : 138). If the researcher is to do “more” or “change” something, this will be done by conjectures based on theoretical knowledge or based on the researcher’s lifeworld. Both qualitative and quantitative research is based on the lifeworld, and all researchers use prejudices and pre-understanding in the research process. This idea is present in the works of Heidegger ( 2001 ) and Heisenberg (cited in Franzosi 2010 :619). Qualitative research, as we argued, involves the interaction and questioning of concepts (theory), data, and evidence.

Ragin ( 2004 :22) points out that “a good definition of qualitative research should be inclusive and should emphasize its key strengths and features, not what it lacks (for example, the use of sophisticated quantitative techniques).” We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. Qualitative research, as defined here, is consequently a combination of two criteria: (i) how to do things –namely, generating and analyzing empirical material, in an iterative process in which one gets closer by making distinctions, and (ii) the outcome –improved understanding novel to the scholarly community. Is our definition applicable to our own study? In this study we have closely read the empirical material that we generated, and the novel distinction of the notion “qualitative research” is the outcome of an iterative process in which both deduction and induction were involved, in which we identified the categories that we analyzed. We thus claim to meet the first criteria, “how to do things.” The second criteria cannot be judged but in a partial way by us, namely that the “outcome” —in concrete form the definition-improves our understanding to others in the scientific community.

We have defined qualitative research, or qualitative scientific work, in relation to quantitative scientific work. Given this definition, qualitative research is about questioning the pre-given (taken for granted) variables, but it is thus also about making new distinctions of any type of phenomenon, for example, by coining new concepts, including the identification of new variables. This process, as we have discussed, is carried out in relation to empirical material, previous research, and thus in relation to theory. Theory and previous research cannot be escaped or bracketed. According to hermeneutic principles all scientific work is grounded in the lifeworld, and as social scientists we can thus never fully bracket our pre-understanding.

We have proposed that quantitative research, as an idealtype, is concerned with pre-determined variables (Small 2008 ). Variables are epistemically fixed, but can vary in terms of dimensions, such as frequency or number. Age is an example; as a variable it can take on different numbers. In relation to quantitative research, qualitative research does not reduce its material to number and variables. If this is done the process of comes to a halt, the researcher gets more distanced from her data, and it makes it no longer possible to make new distinctions that increase our understanding. We have above discussed the components of our definition in relation to quantitative research. Our conclusion is that in the research that is called quantitative there are frequent and necessary qualitative elements.

Further, comparative empirical research on researchers primarily working with ”quantitative” approaches and those working with ”qualitative” approaches, we propose, would perhaps show that there are many similarities in practices of these two approaches. This is not to deny dissimilarities, or the different epistemic and ontic presuppositions that may be more or less strongly associated with the two different strands (see Goertz and Mahoney 2012 ). Our point is nonetheless that prejudices and preconceptions about researchers are unproductive, and that as other researchers have argued, differences may be exaggerated (e.g., Becker 1996 : 53, 2017 ; Marchel and Owens 2007 :303; Ragin 1994 ), and that a qualitative dimension is present in both kinds of work.

Several things follow from our findings. The most important result is the relation to quantitative research. In our analysis we have separated qualitative research from quantitative research. The point is not to label individual researchers, methods, projects, or works as either “quantitative” or “qualitative.” By analyzing, i.e., taking apart, the notions of quantitative and qualitative, we hope to have shown the elements of qualitative research. Our definition captures the elements, and how they, when combined in practice, generate understanding. As many of the quotations we have used suggest, one conclusion of our study holds that qualitative approaches are not inherently connected with a specific method. Put differently, none of the methods that are frequently labelled “qualitative,” such as interviews or participant observation, are inherently “qualitative.” What matters, given our definition, is whether one works qualitatively or quantitatively in the research process, until the results are produced. Consequently, our analysis also suggests that those researchers working with what in the literature and in jargon is often called “quantitative research” are almost bound to make use of what we have identified as qualitative elements in any research project. Our findings also suggest that many” quantitative” researchers, at least to some extent, are engaged with qualitative work, such as when research questions are developed, variables are constructed and combined, and hypotheses are formulated. Furthermore, a research project may hover between “qualitative” and “quantitative” or start out as “qualitative” and later move into a “quantitative” (a distinct strategy that is not similar to “mixed methods” or just simply combining induction and deduction). More generally speaking, the categories of “qualitative” and “quantitative,” unfortunately, often cover up practices, and it may lead to “camps” of researchers opposing one another. For example, regardless of the researcher is primarily oriented to “quantitative” or “qualitative” research, the role of theory is neglected (cf. Swedberg 2017 ). Our results open up for an interaction not characterized by differences, but by different emphasis, and similarities.

Let us take two examples to briefly indicate how qualitative elements can fruitfully be combined with quantitative. Franzosi ( 2010 ) has discussed the relations between quantitative and qualitative approaches, and more specifically the relation between words and numbers. He analyzes texts and argues that scientific meaning cannot be reduced to numbers. Put differently, the meaning of the numbers is to be understood by what is taken for granted, and what is part of the lifeworld (Schütz 1962 ). Franzosi shows how one can go about using qualitative and quantitative methods and data to address scientific questions analyzing violence in Italy at the time when fascism was rising (1919–1922). Aspers ( 2006 ) studied the meaning of fashion photographers. He uses an empirical phenomenological approach, and establishes meaning at the level of actors. In a second step this meaning, and the different ideal-typical photographers constructed as a result of participant observation and interviews, are tested using quantitative data from a database; in the first phase to verify the different ideal-types, in the second phase to use these types to establish new knowledge about the types. In both of these cases—and more examples can be found—authors move from qualitative data and try to keep the meaning established when using the quantitative data.

A second main result of our study is that a definition, and we provided one, offers a way for research to clarify, and even evaluate, what is done. Hence, our definition can guide researchers and students, informing them on how to think about concrete research problems they face, and to show what it means to get closer in a process in which new distinctions are made. The definition can also be used to evaluate the results, given that it is a standard of evaluation (cf. Hammersley 2007 ), to see whether new distinctions are made and whether this improves our understanding of what is researched, in addition to the evaluation of how the research was conducted. By making what is qualitative research explicit it becomes easier to communicate findings, and it is thereby much harder to fly under the radar with substandard research since there are standards of evaluation which make it easier to separate “good” from “not so good” qualitative research.

To conclude, our analysis, which ends with a definition of qualitative research can thus both address the “internal” issues of what is qualitative research, and the “external” critiques that make it harder to do qualitative research, to which both pressure from quantitative methods and general changes in society contribute.

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Acknowledgements

Financial Support for this research is given by the European Research Council, CEV (263699). The authors are grateful to Susann Krieglsteiner for assistance in collecting the data. The paper has benefitted from the many useful comments by the three reviewers and the editor, comments by members of the Uppsala Laboratory of Economic Sociology, as well as Jukka Gronow, Sebastian Kohl, Marcin Serafin, Richard Swedberg, Anders Vassenden and Turid Rødne.

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Aspers, P., Corte, U. What is Qualitative in Qualitative Research. Qual Sociol 42 , 139–160 (2019). https://doi.org/10.1007/s11133-019-9413-7

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Choosing a Qualitative Research Approach

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Editor's Note: The online version of this article contains a list of further reading resources and the authors' professional information .

The Challenge

Educators often pose questions about qualitative research. For example, a program director might say: “I collect data from my residents about their learning experiences in a new longitudinal clinical rotation. If I want to know about their learning experiences, should I use qualitative methods? I have been told that there are many approaches from which to choose. Someone suggested that I use grounded theory, but how do I know this is the best approach? Are there others?”

What Is Known

Qualitative research is the systematic inquiry into social phenomena in natural settings. These phenomena can include, but are not limited to, how people experience aspects of their lives, how individuals and/or groups behave, how organizations function, and how interactions shape relationships. In qualitative research, the researcher is the main data collection instrument. The researcher examines why events occur, what happens, and what those events mean to the participants studied. 1 , 2

Qualitative research starts from a fundamentally different set of beliefs—or paradigms—than those that underpin quantitative research. Quantitative research is based on positivist beliefs that there is a singular reality that can be discovered with the appropriate experimental methods. Post-positivist researchers agree with the positivist paradigm, but believe that environmental and individual differences, such as the learning culture or the learners' capacity to learn, influence this reality, and that these differences are important. Constructivist researchers believe that there is no single reality, but that the researcher elicits participants' views of reality. 3 Qualitative research generally draws on post-positivist or constructivist beliefs.

Qualitative scholars develop their work from these beliefs—usually post-positivist or constructivist—using different approaches to conduct their research. In this Rip Out, we describe 3 different qualitative research approaches commonly used in medical education: grounded theory, ethnography, and phenomenology. Each acts as a pivotal frame that shapes the research question(s), the method(s) of data collection, and how data are analyzed. 4 , 5

Choosing a Qualitative Approach

Before engaging in any qualitative study, consider how your views about what is possible to study will affect your approach. Then select an appropriate approach within which to work. Alignment between the belief system underpinning the research approach, the research question, and the research approach itself is a prerequisite for rigorous qualitative research. To enhance the understanding of how different approaches frame qualitative research, we use this introductory challenge as an illustrative example.

The clinic rotation in a program director's training program was recently redesigned as a longitudinal clinical experience. Resident satisfaction with this rotation improved significantly following implementation of the new longitudinal experience. The program director wants to understand how the changes made in the clinic rotation translated into changes in learning experiences for the residents.

Qualitative research can support this program director's efforts. Qualitative research focuses on the events that transpire and on outcomes of those events from the perspectives of those involved. In this case, the program director can use qualitative research to understand the impact of the new clinic rotation on the learning experiences of residents. The next step is to decide which approach to use as a frame for the study.

The table lists the purpose of 3 commonly used approaches to frame qualitative research. For each frame, we provide an example of a research question that could direct the study and delineate what outcomes might be gained by using that particular approach.

Methodology Overview

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How You Can Start TODAY

  • 1 Examine the foundations of the existing literature: As part of the literature review, make note of what is known about the topic and which approaches have been used in prior studies. A decision should be made to determine the extent to which the new study is exploratory and the extent to which findings will advance what is already known about the topic.
  • 2 Find a qualitatively skilled collaborator: If you are interested in doing qualitative research, you should consult with a qualitative expert. Be prepared to talk to the qualitative scholar about what you would like to study and why . Furthermore, be ready to describe the literature to date on the topic (remember, you are asking for this person's expertise regarding qualitative approaches—he or she won't necessarily have content expertise). Qualitative research must be designed and conducted with rigor (rigor will be discussed in Rip Out No. 8 of this series). Input from a qualitative expert will ensure that rigor is employed from the study's inception.
  • 3 Consider the approach: With a literature review completed and a qualitatively skilled collaborator secured, it is time to decide which approach would be best suited to answering the research question. Questions to consider when weighing approaches might include the following:
  • • Will my findings contribute to the creation of a theoretical model to better understand the area of study? ( grounded theory )
  • • Will I need to spend an extended amount of time trying to understand the culture and process of a particular group of learners in their natural context? ( ethnography )
  • • Is there a particular phenomenon I want to better understand/describe? ( phenomenology )

What You Can Do LONG TERM

  • 1 Develop your qualitative research knowledge and skills : A basic qualitative research textbook is a valuable investment to learn about qualitative research (further reading is provided as online supplemental material). A novice qualitative researcher will also benefit from participating in a massive online open course or a mini-course (often offered by professional organizations or conferences) that provides an introduction to qualitative research. Most of all, collaborating with a qualitative researcher can provide the support necessary to design, execute, and report on the study.
  • 2 Undertake a pilot study: After learning about qualitative methodology, the next best way to gain expertise in qualitative research is to try it in a small scale pilot study with the support of a qualitative expert. Such application provides an appreciation for the thought processes that go into designing a study, analyzing the data, and reporting on the findings. Alternatively, if you have the opportunity to work on a study led by a qualitative expert, take it! The experience will provide invaluable opportunities for learning how to engage in qualitative research.

Supplementary Material

The views expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Uniformed Services University of the Health Sciences, the Department of the Navy, the Department of Defense, or the US government.

References and Resources for Further Reading

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Published on 11.3.2024 in Vol 26 (2024)

The Impact of Digital Hospitals on Patient and Clinician Experience: Systematic Review and Qualitative Evidence Synthesis

Authors of this article:

Author Orcid Image

  • Oliver J Canfell 1, 2, 3, 4 * , PhD   ; 
  • Leanna Woods 1, 2 * , PhD   ; 
  • Yasaman Meshkat 5 , MBBS   ; 
  • Jenna Krivit 5 , BSc   ; 
  • Brinda Gunashanhar 5 , BSc   ; 
  • Christine Slade 6 , PhD   ; 
  • Andrew Burton-Jones 4 , PhD   ; 
  • Clair Sullivan 1, 2, 7 , MBBS, MD  

1 Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia

2 Queensland Digital Health Centre, Faculty of Medicine, The University of Queensland, Brisbane, Australia

3 Digital Health Cooperative Research Centre, Australian Government, Sydney, Australia

4 UQ Business School, Faculty of Business, Economics and Law, The University of Queensland, Brisbane, Australia

5 School of Clinical Medicine, Faculty of Medicine, The University of Queensland, Brisbane, Australia

6 Institute for Teaching and Learning Innovation, The University of Queensland, Brisbane, Australia

7 Metro North Hospital and Health Service, Department of Health, Queensland Government, Brisbane, Australia

*these authors contributed equally

Corresponding Author:

Oliver J Canfell, PhD

Centre for Health Services Research

Faculty of Medicine

The University of Queensland

Level 5 Health Sciences Building

Central, Fig Tree Cres

Brisbane, 4006

Phone: 61 731765530

Email: [email protected]

Background: The digital transformation of health care is advancing rapidly. A well-accepted framework for health care improvement is the Quadruple Aim: improved clinician experience, improved patient experience, improved population health, and reduced health care costs. Hospitals are attempting to improve care by using digital technologies, but the effectiveness of these technologies is often only measured against cost and quality indicators, and less is known about the clinician and patient experience.

Objective: This study aims to conduct a systematic review and qualitative evidence synthesis to assess the clinician and patient experience of digital hospitals.

Methods: The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and ENTREQ (Enhancing the Transparency in Reporting the Synthesis of Qualitative Research) guidelines were followed. The PubMed, Embase, Scopus, CINAHL, and PsycINFO databases were searched from January 2010 to June 2022. Studies that explored multidisciplinary clinician or adult inpatient experiences of digital hospitals (with a full electronic medical record) were included. Study quality was assessed using the Mixed Methods Appraisal Tool. Data synthesis was performed narratively for quantitative studies. Qualitative evidence synthesis was performed via (1) automated machine learning text analytics using Leximancer (Leximancer Pty Ltd) and (2) researcher-led inductive synthesis to generate themes.

Results: A total of 61 studies (n=39, 64% quantitative; n=15, 25% qualitative; and n=7, 11% mixed methods) were included. Most studies (55/61, 90%) investigated clinician experiences, whereas few (10/61, 16%) investigated patient experiences. The study populations ranged from 8 to 3610 clinicians, 11 to 34,425 patients, and 5 to 2836 hospitals. Quantitative outcomes indicated that clinicians had a positive overall satisfaction (17/24, 71% of the studies) with digital hospitals, and most studies (11/19, 58%) reported a positive sentiment toward usability. Data accessibility was reported positively, whereas adaptation, clinician-patient interaction, and workload burnout were reported negatively. The effects of digital hospitals on patient safety and clinicians’ ability to deliver patient care were mixed. The qualitative evidence synthesis of clinician experience studies (18/61, 30%) generated 7 themes: inefficient digital documentation, inconsistent data quality, disruptions to conventional health care relationships, acceptance, safety versus risk, reliance on hybrid (digital and paper) workflows, and patient data privacy. There was weak evidence of a positive association between digital hospitals and patient satisfaction scores.

Conclusions: Clinicians’ experience of digital hospitals appears positive according to high-level indicators (eg, overall satisfaction and data accessibility), but the qualitative evidence synthesis revealed substantive tensions. There is insufficient evidence to draw a definitive conclusion on the patient experience within digital hospitals, but indications appear positive or agnostic. Future research must prioritize equitable investigation and definition of the digital clinician and patient experience to achieve the Quadruple Aim of health care.

Introduction

Investment in digital health is advancing rapidly. In 2020, the total global funding for digital health was the highest recorded at US $26.5 billion [ 1 ]. A global appetite for digital health, fueled recently by the COVID-19 pandemic and the associated rapid adoption of point-of-care technological solutions [ 2 ], including telehealth [ 3 ], has driven the digital disruption of health care. A core pillar of digital health investment is the digital transformation of hospitals [ 4 ].

The World Health Organization Global Strategy on Digital Health (2020-2025) recommends the implementation of a national digital health architecture, including digital hospitals [ 5 ]. Digital hospitals represent significant jurisdictional investments to improve the quality and safety of acute care [ 6 ]. A digital hospital uses a comprehensive electronic medical record (EMR) to achieve its clinical goals [ 7 ] and is becoming the predominant method of care delivery worldwide. These new digital hospital environments radically disrupt well-rehearsed clinical workflows and create unfamiliar environments for patients and clinicians, potentially affecting quality, safety, and experience of care [ 8 - 10 ].

It has been difficult to determine the value of digital hospital implementations as what is considered valuable changes over time and place and from person to person [ 11 ]. Previous studies evaluating digital health implementations have focused on three domains: (1) improving patient or hospital outcomes using quantitative evaluation [ 12 ]; (2) exploring patient [ 13 ] and clinician behavior, workflows, and attitudes toward EMRs or digital hospital transformations [ 10 ]; and (3) quantifying value using economic evaluations [ 4 ]. Evidence to date demonstrates conflicting impacts of EMRs on hospital practice, with positive indications for medication safety, guideline adherence, and decision support [ 12 , 14 ] and negative indications for physician-patient communication, staff attitude, and workflow disruption [ 15 , 16 ]. Focusing on the narrow aspects of digital health implementations has resulted in patchy assessments of the value of digital health technologies.

The Quadruple Aim is the overarching goal of a learning health care system of enhancing patient experience, improving population health, reducing health care costs, and improving the provider experience ( Figure 1 ) [ 17 ]. The Quadruple Aim of health care has been proposed as a strategic compass to guide digital health investment planning, decision-making, and evaluation [ 11 ] and has been used in the health care workforce [ 18 , 19 ], innovation implementation [ 20 ], and COVID-19 pandemic [ 21 ] contexts to identify current trends and research gaps.

qualitative research 2

The experience of patients and clinicians has yet to be explored as important contributors to the Quadruple Aim. Previous evaluations of clinician experience have focused on individual retrospective recalls of attitudes, perceptions of EMR implementation [ 10 ], and observational time and motion studies [ 22 ]. Existing patient experience research has focused on bespoke digital systems for patient use (eg, internet-based care technologies, web-based patient platforms, and mobile health apps) or emerging trends (eg, COVID-19 impacts, effects of specific technologies, research methods, and new technologies) [ 23 , 24 ]. Traditional evaluations of technology in health care are selective in the outcomes they measure, with an overwhelming focus on clinical outcomes and efficiency.

To address this research gap, our research question was as follows: what is the clinician and patient experience of digital hospitals? We hypothesized that clinicians and patients would report digital hospital experiences positively (eg, patient safety benefits because of digital safeguards [ 25 ]), negatively (eg, productivity loss because of documentation burden [ 15 ]), and ambivalently (eg, no observed impact of the digital environment on patient experience [ 10 ]). The study aim was to conduct a systematic literature review and qualitative evidence synthesis to assess the clinician and patient experience of digital hospitals.

Search Strategy and Identification of Included Articles

This review adhered to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement checklist [ 26 ] ( Multimedia Appendix 1 [ 26 ]) and the ENTREQ (Enhancing the Transparency in Reporting the Synthesis of Qualitative Research) guidelines [ 27 ] ( Multimedia Appendix 2 ). The protocol for this review was registered in PROSPERO (CRD42021258719).

The PubMed, Embase, Scopus, CINAHL, and PsycINFO databases were searched twice—on June 24, 2021 (version [V1]), and subsequently on June 23, 2022 (version [V2])—using the same search strategy restricted by year of publication (2010 to the present) because of the relative novelty of the digital transformation of acute care.

The search strategy was initially developed in PubMed using the population, intervention, comparison, and outcome structure ( Table 1 ) [ 28 ] and translated to other databases ( Multimedia Appendix 3 ). We define experience as an individual’s perception of events, incorporating themes of expectation and satisfaction. Thus, synonyms for “experience” were used to characterize the outcome. A combination of indexed terms (eg, Medical Subject Headings) and keywords identified after consultation with a research librarian and subject matter experts was used. Truncations, synonyms, and terminological variations (eg, “EMR” vs “EHR”) were also used.

a PICO: population, intervention, comparison, and outcome.

b MeSH: Medical Subject Headings.

c tiab: title and abstract.

d EMR: electronic medical record.

e EHR: electronic health record.

f ti: title.

In total, 2 reviewers (YM and OJC) performed title and abstract screening. Full-text review was then performed based on the eligibility criteria. Backward citation tracking (snowballing) was used to identify additional articles in the reference lists of included articles and relevant reviews. Decision conflicts were resolved through internal discussion or by involving a third reviewer’s opinion (C Slade) when required.

Eligibility Criteria

Studies were included if they described a quantitative, qualitative, or mixed methods investigation of clinician or adult inpatient “experience” in a digital hospital ( Table 2 ). This review focused on multidisciplinary clinicians and adult inpatients as a first step in synthesizing evidence of digital hospital experience. Pediatric inpatients were excluded because of possible environmental factors that could confound the digital hospital experience (eg, patient entertainment systems). Our study setting prioritized EMRs—a real-time patient health record that collects, stores, and displays clinical information in a tertiary setting [ 29 ] (eg, Cerner Millenium and Epic)—as the foundation of a digital hospital [ 30 ] as opposed to an electronic health record (or personal health record), which displays summarized patient information to the consumer in the community and across multiple health care providers [ 29 ] (eg, My Health Record [Australia], the National Health Service app [United Kingdom], and personal health record [Ministry of National Guard Health Affairs, Kingdom of Saudi Arabia]). The terms “EMR” and “EHR” may be used interchangeably in some countries, so both terms were adopted in the search strategy. The stage of digital hospital implementation (eg, EMR maturity [ 31 ]) was not considered.

a EMR: electronic medical record.

b IoT: Internet of Things.

Data Extraction

The Covidence software (Veritas Health Innovation) and Excel (Microsoft Corp) facilitated data extraction of study details ( Multimedia Appendix 4 ). For studies eligible for the qualitative evidence synthesis (eg, presence of verbatim participant quotes), additional data that explained the qualitative findings were extracted, including the primary and main themes; secondary and subthemes; minor and unexpected themes; participant quotations; and any text labeled within the “results” or “findings” (ie, narrative) sections, including data-driven discoveries, judgments, or explanations the researchers offered about their phenomena [ 32 , 33 ]. All extracted data were cross-checked by a second reviewer for accuracy, and any discrepancies were resolved through discussion. Owing to the heterogeneity in study design, populations, and outcome measures for quantitative studies, a meta-analysis was inappropriate, and a narrative synthesis of quantitative study results was conducted.

Quality Assessment

The quality of the included studies was assessed using the Mixed Methods Appraisal Tool (MMAT) [ 34 ]. Each study’s methodology was evaluated against 5 criteria ( Yes , No , or Can’t tell ) that differed between study designs (qualitative, quantitative randomized controlled trial, quantitative nonrandomized, quantitative descriptive, and mixed methods). The included studies were divided equally among 5 reviewers (LW, YM, C Slade, JK, and OJC). An MMAT star rating was generated for each article ( Yes =1 star; up to 5 stars in total), a method adapted from a recent systematic review by Freire et al [ 35 ], and the scores were cross-checked by a second reviewer. Discrepancies were discussed and resolved within the research team. No study was excluded from the review based on its MMAT score.

Data Synthesis

Data synthesis was conducted in 2 stages in accordance with our study aims.

Systematic Review: Narrative Synthesis

A narrative (qualitative) synthesis of quantitative studies was conducted to summarize and compare key findings [ 36 ]. We first developed a preliminary synthesis based on extracted data and then explored the relationships within and between studies to identify and explain any heterogeneity. Identified experience outcomes were inductively grouped together based on similarity (eg, ease of use and user-friendliness), and the group was given a descriptor (eg, usability) that would accurately reflect the experience outcomes within the group.

Qualitative Evidence Synthesis

The qualitative evidence synthesis [ 37 ] was conducted in 2 steps.

Step 1: Automated Text Analytics Using Machine Learning

Step 1 was undertaken using the text analytics tool Leximancer (version 4.5; Leximancer Pty Ltd) [ 38 ], an increasingly adopted [ 39 ] approach to qualitative analysis that is 74% effective at mapping complex concepts from matched qualitative data and >3 times faster than manual thematic analysis [ 40 ]. Leximancer applies an unsupervised machine learning algorithm and inbuilt thesaurus to uncover networks or patterns of word- and namelike terms in a body of text [ 41 , 42 ]. Leximancer then generates interconnections, structures, and patterns among terms to develop “concepts”—collections of words that are linked together within the text—and group them into “themes”—concepts that are highly connected. The interrelationships between concepts and themes are visualized on a map. Advantages include expediting the early stages of qualitative analysis and providing a first impression of meaning within qualitative data that limits researcher bias.

After data extraction, qualitative data from the included articles were synthesized into 3 data sets—“themes” (primary, secondary, and minor), “quotes” (from participants), and “narrative” (any text under the “results” or “discussion” sections)—ready for separate Leximancer analysis. We chose to analyze each data set separately to account for any significant (but unknown at the time) heterogeneity across the studies. In total, 3 researchers were allocated 1 data set each using Leximancer to create an initial concept map without altering any settings. Initial concepts were reviewed for meaning, and redundant conversational words were removed where appropriate (eg, study , doing , and participants ). Concept variations of EMR or electronic health record were removed as this was labeled as the independent variable and the target context already under analysis. Concept variations (eg, patient and patients ) were merged where necessary. All other software settings were kept as the default values.

Step 2: Researcher-Led Thematic Analysis

The preliminary themes and concepts identified via text analytics underwent validation and researcher-led thematic analysis in accordance with a modified version of the method by Thomas and Harden [ 33 ]. First, the top 5 Leximancer-identified concepts (eg, “patient”) were identified and connected with their 2 most related concepts (eg, “patient” AND “documentation” or “patient” AND “time”) to create a concept grouping. In total, 3 researchers (OJC, LW, and JK) validated each Leximancer concept grouping by extracting relevant text and generating a preliminary interpretation of the meaning of each concept grouping, which was cross-checked between researchers. Researchers (OJC, LW, JK, and BG) then worked collaboratively across all 3 data sets to conduct a rapid thematic analysis using a cluster and name technique to generate a working thematic framework [ 43 ]. Through an iterative and interpretive process, researchers then grouped similar concepts into parent themes. Discrepancies were resolved through discussion until the final themes were decided and approved by consensus.

Identification of Included Articles

In total, 2059 studies were identified from the first search (V1), and an additional 462 studies were identified from the second search (V2; Figure 2 ). Following duplicate removal and title and abstract screening, a total of 109 studies (V1: n=84, 77.1%; V2: n=25, 22.9%) remained and underwent full-text review. Of these 109 studies, 61 (56%) met our inclusion criteria and were included in this review, comprising quantitative (n=39, 64%), qualitative (n=15, 25%), and mixed methods (n=7, 11%) designs.

qualitative research 2

In total, 52% (32/61) of the included studies met all 5 MMAT quality criteria ( Multimedia Appendix 5 [ 44 - 104 ]). An additional 20% (12/61) of the studies met 4 out of 5 of the quality criteria. Only 7% (4/61) of the studies met ≤2 of the 5 quality criteria, of which 75% (3/4) were mixed methods studies and 25% (1/4) had a quantitative descriptive design. For these studies, a score of ≤2 indicated inadequate sampling, and in the case of the mixed methods studies, the integration of and inconsistencies between quantitative and qualitative elements were not adequately described.

Characteristics of the Included Studies

Study design.

Of the 61 included articles ( Multimedia Appendix 6 [ 44 - 104 ]), most (n=39, 64%) adopted quantitative methods to assess clinician and patient experiences. Most quantitative studies (31/39, 79%) conducted descriptive cross-sectional surveys to assess experience at one point. A total of 21% (8/39) of the studies assessed clinician and patient experience through quantitative nonrandomized methods in the pre– and post–EMR implementation periods. A minority of the included studies (15/61, 25%) qualitatively assessed experience through interviews, focus groups, and ethnographic observations. A total of 11% (7/61) of the studies used both quantitative and qualitative methods (mixed methods).

The most common country of study was the United States (21/61, 34%), followed by Australia (6/61, 10%), Saudi Arabia (5/61, 8%), and Canada (4/61, 7%). More than half (32/61, 52%) of the included studies were published after 2018. The settings included diversity across large tertiary academic hospitals and private hospitals in rural and metropolitan settings. The number of participating hospitals ranged from 1 to 2836.

Participants

In total, 90% (55/61) of the studies investigated the clinician experience using quantitative, qualitative, or mixed methods. Within the clinician experience group, 35% (19/55) of the studies included all EMR users, followed by nursing staff only (17/55, 31%) and physicians only (15/55, 27%). Study participation ranged from 8 to 3610 across the clinician experience studies. Only 16% (10/61) of the included studies investigated the patient experience. In total, 60% (6/10) of the studies focused exclusively on the patient experience with EMR, and 40% (4/10) included perspectives from both stakeholder groups. Patient participant counts ranged from 11 to 34,425.

Quantitative Results: Clinician and Patient Experience in Digital Hospitals

Table 3 reports the outcome measures of the digital hospital experience identified in the studies with quantitative components (46/61, 75%; 39/46, 85% quantitative and 7/46, 15% mixed methods).

Patient Experience in a Digital Hospital

Of the 9 quantitative or mixed methods studies reporting the patient perspective, 7 (78%) [ 48 , 51 , 57 , 69 , 84 , 96 , 102 ] used different survey methods (eg, the Hospital Consumer Assessment of Healthcare Providers and Systems [HCAHPS] survey) to quantify “patient experience” using various satisfaction metrics. Of these studies, 57% (4/7) reported a positive association [ 48 , 57 , 69 , 84 ] between EMR and patient satisfaction scores and 43% (3/7) reported no substantial change [ 51 , 96 , 102 ]. In total, 22% (2/9) of the studies [ 67 , 92 ] used hospital outcomes rather than patient feedback, which did not meet our definition of “experience.”

A total of 33% (3/9) of the studies [ 57 , 96 , 102 ] reported patient experience before and after EMR implementation (or transition between EMR systems). Tian et al [ 96 ] surveyed 34,425 patients using the standardized HCAHPS survey and found a significant decreasing trend in patient experience scores for the 6 months after implementation followed by a return to baseline, with no significant changes overall. Monturo et al [ 102 ] surveyed 55 patients and found no significant changes in overall patient satisfaction.

Of the 9 studies, 3 (33%) cross-sectional studies [ 48 , 51 , 84 ] compared patient experiences in hospitals with and without an advanced EMR. Hu et al [ 84 ], using the HCAHPS survey at 1006 hospitals, and Kazley et al [ 48 ], using Hospital Compare data at 2836 hospitals, both found a positive association between EMR adoption and overall hospital rating and discharge information. Jarvis et al [ 51 ] found no significant difference in HCAHPS scores in advanced EMR versus non–advanced EMR hospitals.

Clinician Satisfaction With the EMR

Of the 41 quantitative studies that investigated the clinician experience, 24 (59%) included an overall EMR satisfaction metric, and 71% (17/24) of these studies reported a positive sentiment [ 47 , 49 , 59 , 60 , 62 , 70 , 72 , 73 , 76 , 79 , 80 , 85 , 87 - 89 , 98 , 101 ]. For instance, Kutney-Lee et al [ 76 ] used the registered nurse forecasting study (RN4CAST-US) nursing survey with 12,377 nurses across 353 hospitals and found a 74.9% “satisfaction with current EMR.” In total, 25% (6/24) of the studies [ 64 , 68 , 72 , 75 , 89 , 94 ] used features of the technology acceptance model, and “perceived usefulness” or “perceived value” was equated to overall satisfaction . Evidence of increasing satisfaction with increased digitization was found in a study that stratified results by level of EMR adoption, including groups for basic EMR (71.3% satisfaction reported) and comprehensive EMR (78.4% satisfaction) [ 76 ].

Of the 24 studies that reported overall EMR satisfaction as an outcome of clinician experience, 7 (29%) [ 46 , 54 , 56 , 61 , 77 , 97 , 104 ] reported negative sentiment with the EMR. For instance, Tilahun and Fritz [ 61 ] surveyed 406 clinicians and found that 64.4% were dissatisfied with the use of the EMR system; however, only 22.8% strongly disagreed with the following statement: “I prefer EMR than the paper record.” One study found that only 15.6% of respondents (n=141 physicians) felt that the EMR was an “effective tool” [ 46 ], and another found that only 38.9% of users (n=262 nurses and physicians using the National Usability-Focused Health Information System Scale) rated the EMR system as “high quality” [ 104 ].

Usability of the EMR by Clinicians

Of the 41 studies that included the EMR user perspective, 19 (46%) reported a usability metric, and 11 (58%) of these reported a positive sentiment [ 50 , 54 , 68 , 70 , 71 , 72 , 76 , 82 , 83 , 89 , 99 ]. Survey components that investigated usability used outcomes such as “ease of use,” “user friendly,” and “technical quality.”

Positive sentiment was considered to be >3.5/5 on a 5-point Likert scale or >50% agreement with usability statements. Of those using a Likert scale, statements such as “the health record I am working with is user-friendly” scored 3.62 (n=667 nurses) [ 82 ], and “perceived ease of use” scored 3.7 (n=1539 nurses in 15 hospitals) [ 72 ] and 3.78 (n=223 nurses) [ 89 ]. Aldosari et al [ 68 ] surveyed 153 nurses and found a 79.7% agreement with the following statement—“It is easy to use the EMR”—and 70.5% agreement with the following statement: “I find the EMR system interface to be user friendly.”

A negative sentiment regarding usability was found in 42% (8/19) of the studies [ 49 , 53 , 66 , 77 , 87 , 93 , 98 , 104 ]. In the study using the National Usability-Focused Health Information System Scale (n=3013 physicians), most participants (60.15%) disagreed with the following statement: “routine tasks can be performed in a straightforward manner without the need for extra steps using the systems” [ 66 ]. Comparatively fewer nurses (n=3560) in the same study disagreed with this statement [ 66 ].

Adaptation to New Systems

A total of 30% (14/41) of the studies discussed the experience of adapting existing workflows to integrate the new digital interface and transitioning to a digital environment on the wards [ 47 , 50 , 56 , 60 , 64 , 66 , 70 , 71 , 75 , 77 , 93 , 98 , 99 , 101 ]. Generally, the adaptation outcome had a negative sentiment from EMR users. One survey of 285 nurses 8 to 13 months after EMR implementation found that users felt that the EMR provided a “holistic view of the patient, but fragmentation and complexity introduce workflow challenges” [ 64 ]. Another study found that 35.1% of physicians (n=317) agreed with the following statement: “EMR does not disrupt workflow” [ 60 ]. A third study found that 48.7% of physicians (n=3013) and 62.3% of nurses (n=3560) disagreed with the following statement: “learning the EHR did not require a lot of training” [ 66 ].

Data Accessibility and Clinician-Patient Interaction

Data accessibility in digital hospitals was reported in 39% (18/41) of the quantitative studies [ 49 , 50 , 53 , 54 , 66 , 68 , 70 , 71 , 75 , 76 , 80 , 82 , 83 , 87 , 93 , 98 , 99 , 104 ]. Much of the sentiment was positive as clinicians agreed that the EMR allowed users to access information when and where they needed it. One survey of 153 nurses in a Saudi Arabian hospital found that 85.6% of respondents agreed with the following statement—“I have access to the information where I need it”—and 83.6% agreed with the following statement: “I have access to the information when I need it” [ 68 ]. One large cross-sectional study of 2684 clinicians found a 50.3% agreement with the following statement: “EMR provides precise information I need” [ 98 ]. Neutral sentiment was indicated in one study by an average of 3.5 (5-point Likert scale) in response to the following statement—“it is easy to find the information I need”—from 244 clinicians 2 months after EMR implementation [ 50 ]. The survey by Lloyd et al [ 93 ] found that 49% of physicians (n=224) and 59.4% of nurses (n=72) agreed that “it is easy to obtain necessary patient information using the EMR system.”

A total of 7% (3/41) [ 67 , 98 , 101 ] of the studies reported on the impact of EMR on clinician-patient interaction, with all 3 studies agreeing that the EMR reduced this communication. Czernik et al [ 101 ] found that 39% of 126 physicians agreed (7-point Likert scale) with the statement that EMR causes “lack of proper patient-doctor communication.” A total of 43% (3/7) [ 57 , 69 , 102 ] of patient experience studies reported on the impact of EMR on patient-provider interaction. Migdal et al [ 57 ] focused more specifically on physician-patient communication with their patient participants using a CICARE survey (17-question Likert scale) designed by the University of California, Los Angeles, Health system to assess resident physician performance. Of the 3417 patient surveys, Migdal et al [ 57 ] found that 9 of 16 relevant questions had statistically significant improvements after EMR implementation, suggesting improvement in communication between patients and providers after EMR implementation.

Workload and Burnout

Many studies (19/41, 46%) reported on the impact of EMR on clinical workload, including symptoms of burnout and subjective productivity. One cross-sectional study in Canada surveyed 208 physicians and found that 68.2% of respondents felt that the EMR “added to daily frustration”; 24.5% of respondents had one or more symptoms of burnout; and, of those with burnout, nearly 75% “identified EMR as contributor to burnout symptoms” [ 88 ]. Another study across 343 hospitals including 12,004 nurses compared EMR usability (as per the RN4CAST-US usability survey) with symptoms of burnout and found that lower EMR usability scores were associated with higher odds of burnout (odds ratio 1.41, 95% CI 1.21-1.64) [ 92 ]. Often, studies assessed workload in terms of productivity. In 5 low-resource hospitals 3 years after EMR implementation (n=405 physicians and nurses), 82.4% of physicians disagreed that “EMR improves productivity,” whereas 61% of nurses agreed [ 61 ].

Patient Safety and Delivery of Care

There was a mixed sentiment across 34% (14/41) of the quantitative studies [ 50 , 53 , 56 , 66 , 73 , 75 , 79 , 80 , 85 , 87 , 88 , 93 , 94 , 98 ], which included survey items on the impact of the EMR on patient safety. In total, 43% (6/14) of these studies [ 53 , 56 , 66 , 73 , 93 , 98 ] included survey items about EMR preventing errors in patient care, especially mistakes associated with medications. One study in a large specialist hospital in Nigeria (n=35 health care workers) found that the EMR made clinicians “more prone to errors” [ 80 ]. Similarly, Kaipio et al [ 66 ] found that less than half of the surveyed physicians (44.7%) and nurses (40.2%) agreed with the following statement: “IT systems help in preventing errors and mistakes associated with medication.” Conversely, Al Otaybi et al [ 98 ] (n=2684 health care workers) found that only 15.5% agreed with the following statement: “EMR increases the risk of making errors.” One study investigated the change in user experience over time and found that agreement with the statement that the EMR “improves prevention in errors and mistakes associated with medications” increased by 13% from 2010 to 2014 [ 85 ].

There was also a mixed sentiment across 29% (12/41) of the studies, which included outcomes on the impact of the EMR on clinicians’ ability to deliver care to their patients. In a large study of >12,000 US nurses, more than half (55.4%) reported agreement with the statement that the EMR “systems interfere with the provision of care” [ 76 ], and in a smaller study, 84.2% of participants disagreed with the statement that the EMR “system has positive impact on quality of care” [ 61 ]. Conversely, in the Netherlands, nurses were more likely to agree with the following statement: “the information in the health records supports my activities during the provision of care” [ 82 ].

Qualitative Results: Clinician and Patient Experience in Digital Hospitals

A total of 18 studies (n=14, 78% qualitative and n=4, 22% mixed methods) with qualitative components were included in the qualitative evidence synthesis. Only 7% (1/15) of the qualitative studies in our review explored the patient experience in a digital hospital [ 52 ]; however, this study was excluded from the qualitative evidence synthesis and is reported narratively in the following paragraph. A total of 29% (2/7) of the mixed methods studies were also excluded for lacking direct participant quotes as per the exclusion criteria [ 50 , 75 ]; however, the quantitative results are reported in the previous sections.

Strauss [ 52 ] interviewed 11 patients about the dynamics with their nurses and the EMR. Similar to the qualitative evidence synthesis, participants described a positive perception of the EMR when the nurses acknowledged the participants before using the electronic device; however, many “expressed concerns [for] the privacy of their health record information.” Interestingly, participants’ expectations of the “clinical knowledge and competency of the nurse, within the technological arena, have increased with the implementation of the [EMR].”

Qualitative Evidence Synthesis: Clinician Experience Only

Step 1: automated text analytics using leximancer.

Multimedia Appendix 7 presents the results of the automated text analytics using Leximancer. Figures S1 to S3 in Multimedia Appendix 7 present the intertopic concept maps derived from the themes, quotes, and narrative qualitative data, respectively.

Table S1 in Multimedia Appendix 7 compares the top 5 concepts and their 2 most related concepts identified by Leximancer across each qualitative group. Owing to the relative homogeneity in the top 5 concepts identified among the themes, quotes, and narrative qualitative data, it was decided to perform researcher-led thematic analysis (step 2) collectively instead of individually for each data group. This decision was not a predetermined method and was made organically during data analysis.

Textbox 1 presents 7 themes that describe the clinician experience in digital hospitals derived from the qualitative evidence synthesis (18/61, 30% of the studies).

  • Slow and inefficient digital documentation detracts from other clinical priorities.
  • Inconsistent data quality and discoverability challenge clinician trust in making data-driven decisions.
  • Digital technology creates new tensions that disrupt conventional health care relationships.
  • Acceptance of digital hospitals is a value-based spectrum that changes over time.
  • Clinicians value patient safety benefits while acknowledging concerns about new digital risks.
  • Clinicians feel reliant on hybrid (digital and paper) workflows to maintain the standard of care.
  • Clinicians worry about compromising patient data privacy to improve care efficiency.

Theme 1: Slow and Inefficient Digital Documentation Detracts From Other Clinical Priorities

Documentation was a time burden for clinicians with a slow and inefficient workflow [ 95 ] in which it was difficult to find information [ 95 ], there were “too many steps to accomplish simple tasks” [ 44 ], and users were required to re-enter the same data repeatedly [ 63 ].

Clinicians felt challenged by the requirement for accurate and complete documentation during the provision of patient care. Staff reported wanting to provide care but needing to complete medical records:

A lot of the time we’re having to say [to patients], “Oh look, I’ll have to come back to you, I’ve got to do my documentation.” [ 81 ]

The study by Schenk et al [ 64 ] concluded that “EHR implementation was disruptive to nursing care and adversely influenced nursing attitudes,” reporting “too many steps to find and chart information, information that is fragmented and overly complex, leading to workflow challenges and interruptions of care.” Shortcuts and quick orders save time [ 95 ] and were used as workarounds to improve efficiency.

Theme 2: Inconsistent Data Quality and Discoverability Challenge Trust in Decisions

Clinicians found that data quality improved in digital hospitals. Studies highlighted various benefits of digitization, including improved documentation of data [ 78 ], efficient display of information [ 95 ], improved data completeness [ 78 ], and improved documentation readability [ 63 ]. This was summarized by the following participant quote:

...the availability of data in the EHR is a good thing. [ 101 ]

“Note bloat” was reported as a theme regarding difficulties finding information in the digital system [ 95 ]. Discoverability challenged clinicians and negatively affected their trust in making data-driven decisions. It was difficult to find information [ 95 ] and easy to miss information [ 95 ], as described by one participant:

...you’ve got to look through 100 documents to find the information you are looking for. [ 65 ]

Inefficiencies in the EMR design may lead to inappropriate care:

A wrong decision happens based on the missing information. [ 45 ]

Theme 3: Digital Technology Creates New Tensions That Disrupt Conventional Health Care Relationships

Reduced patient contact [ 55 ] from EMRs “inserted” between the patient and clinician deteriorated the personal relationship [ 44 ]. There was the potential to lose focus on the patient, undermine rapport [ 86 ], and communicate with the computer in lieu of direct bedside patient communication [ 81 ]. The effect of digital documentation on trust in the psychiatrist-patient relationship was noted, and required open communication between the psychiatrist and patient to promote transparency about what was documented [ 100 ].

Managing disrupted communication [ 81 ] to preserve the patient’s personhood in the digital environment [ 81 ] created notable tension [ 69 ]. For example, the EMR can improve information accuracy [ 44 ] by viewing a patient history [ 103 ] or using a computer to facilitate conversation [ 86 ]. Preparing notes before consultations, minimizing screen use and explaining computer use, taking paper notes, sharing screens with patients, and viewing results digitally together “seems to counterbalance the negative effects of computer use” [ 86 ].

Interprofessional communication between clinicians was affected by digital notes “only when the data entered by different roles in the healthcare system are accurate, the clinicians can make timely and correct decisions” [ 103 ].

Theme 4: Acceptance of Digital Hospitals Is a Value-Based Spectrum That Changes Over Time

Individual beliefs about digital hospitals trended negatively (eg, threats to patient safety, waste of human resources, and perceived inefficiency), but objective experiences trended positively (eg, access to records, optimized treatment, efficiency and health system coordination [ 45 ], cost savings, improved productivity, and quality of care). Acceptance fluctuated between perception and reality—a mismatch between “work as imagined” and “work as done.”

Negative experiences with “work as imagined” were related to perceived inefficiencies [ 45 ]. Digital hospitals created their own unique time pressures with improved productivity in some cases [ 45 ], with participants viewing technology as “both time saving and time consuming” [ 74 ].

Positive experiences with “work as done” coincided with a longer time since implementation, when adoption had progressed, disruption to their work processes had eased, and workflows had been integrated [ 58 ]. Initially, clinicians reported having a negative first impression of the EMR, especially perceived complexity and ease of use [ 91 ].

Theme 5: Clinicians Value Patient Safety Benefits While Acknowledging Concerns About New Digital Risks

Digital hospitals generate patient safety benefits while creating new ways to make errors and increase risks. New errors may negatively affect patient safety. These include wrong patient errors, alert fatigue, inappropriate alerts, data entry errors, technical problems [ 78 ], field auto-population or auto-refresh errors, and the absence of aids for dose calculations [ 95 ]. Concerns regarding clinician overreliance on the system, ignoring correct alerts, and prioritizing system compliance over clinical accuracy were raised in some cases [ 45 ].

Reduced medication errors were the primary reported patient safety benefit, including awareness of known adverse reactions to medications [ 103 ] and improved legibility [ 78 ]. Clinical decision support enabled by the EMR was seen as a safety benefit to alert staff for prompt intervention [ 78 ]:

There is a pop up in the system which questions are you supposed to give that medication right now? [ 103 ]

The safety benefits of sharing medical information [ 100 ] and applying regulatory frameworks to the workflow [ 100 ] were noted. Entering clinical data into structured mandatory fields and managerial-level review improved thoroughness and was considered to enhance patient safety [ 78 ].

Theme 6: Clinicians Feel Reliant on Hybrid (Digital and Paper) Workflows to Maintain Standard of Care

Digital transformation caused workflow disruption. New digital workflows were time consuming, with a one-size-only user interface and limited ability to adapt to individual patient characteristics or change information once documented [ 86 ]. The digital interface was insufficient to meet clinical workflow needs. Often, EMR workflows were supplemented with paper workflows [ 81 ]. Paper enabled total customization to fit with workflow conventions and was a “cognitive support” to supplement personal workflows to plan and prioritize in a flexible, convenient, comfortable, and trusted way [ 58 ]:

I go to my [paper] notes and I make little boxes, and if I do those tasks I tick them. [ 81 ]

Theme 7: Clinicians Worry About Compromising Patient Data Privacy to Improve Care Efficiency

The improved documentation captured by the EMR created a perceived privacy risk for the patient. Perceptions on patient preferences to protect the disclosure of medical information involved elements such as diagnoses [ 100 ], mental health–related stigma [ 100 ], and patient distrust of the EMR system or its users [ 86 ]. Reported strategies enlisted by health care professionals were to only include clinical documentation that was general in nature, avoid labeling (eg, “mood disorder” instead of “depression”) [ 100 ], prioritize based on clinical relevance [ 100 ], or limit types of information to critical information related to medication that is considered essential knowledge [ 86 ].

Principal Findings and Comparison With Prior Work

Our findings revealed mixed and complex clinician and patient experiences of digital hospitals ( Figure 3 ). Generally, clinicians reported positive overall satisfaction (17/24, 71% of the studies) with digital hospitals in quantitative measures; however, there were negative experiences for clinicians reported in qualitative studies, including compromised clinician-patient interactions, inefficient data workflows, and patient data privacy concerns. For example, acceptance of digital hospitals fluctuated over time and trended negatively if grounded in individual perceptions and beliefs (ie, “work as imagined”) yet trended positively if based on objective measures of practice (ie, “work as done”) [ 105 ]. These inconsistencies are likely reflective of the various contextual factors that influence experience, such as intervention design or stage of implementation. It is likely that the quantitative finding of mixed usability of EMRs explains clinician reliance on hybrid (digital and paper) workflows revealed in the qualitative evidence synthesis as clinicians seek to maintain their clinical workflow standard and validate data using additional sources of truth, such as paper [ 10 ].

qualitative research 2

The effect of digital hospitals on clinician-reported patient safety and clinician ability to deliver care were mixed; there was acknowledgment that digitization primarily reduces medication error risk but creates new risks driven by questionable data quality. In the small proportion of studies that explored patient experience (10/61, 16%), there was weak evidence supporting a positive association between digital hospitals and patient satisfaction scores. To our knowledge, this is the first review to systematically evaluate clinician and patient experience in digital hospitals and use qualitative evidence synthesis with machine learning (Leximancer) to consolidate identified themes in previous qualitative research into an empirical “umbrella” view of digital hospital experience.

Previous studies have evaluated the adoption of health ITs and identified enablers of and barriers to the routine use of EMRs in practice. The perceived value of the EMR to clinical workflows and data accessibility are key adoption facilitators, whereas cost and time consumption are barriers to adoption [ 106 ]. Our findings revealed that clinicians reported high satisfaction with digital hospitals and positively viewed data accessibility in quantitative measures; however, our qualitative evidence synthesis revealed themes of frustration with slow digital workflows and inconsistent data discoverability. Evidence of EMR adoption in low-income countries also highlights clinician perception of the EMR as a key facilitator and interoperability and clinician burnout as barriers, similar to our findings on the impact of EMR on workload and burnout symptoms [ 107 ].

Our review found that the patient experience of digital hospitals was reported disproportionately less frequently than the clinician experience. Evidence of patient satisfaction with EMRs was systematically reviewed in 2013, and it was found that a small number of studies (n=8) indicated positive patient satisfaction with the EMR in mixed settings across primary care, emergency, and outpatient departments [ 13 ]. This evidence is consistent with our findings of a positive or neutral association but remains grounded in cross-sectional methods that warrant rigorous trial evaluation. Beyond the clinician-facing EMR, patient-centered digital health records have emerged as a mechanism to engage and empower consumers living with chronic conditions. Patient portals within EMRs can contribute positively to health care quality and safety by improving medication adherence and clinician-patient communication [ 24 ] and have been shown to improve patient care navigation and disease knowledge without adverse effects and with high patient satisfaction [ 108 ]. Measuring satisfaction with digital hospitals using a simple quantitative scale is unlikely to capture the complexity and heterogeneity of digital hospital environments. There was dissonance in clinician perspective on data accessibility (or discoverability) between quantitative and qualitative studies. Clinicians reported objective satisfaction with data accessibility and positive attitudes toward data quality; however, they were dissatisfied with the inefficient workflows required to generate high-quality data (ie, input) and the ability to leverage these data for secondary use (ie, output).

Although patient experience is consistently positively associated with patient safety, clinical effectiveness, and self-rated and objectively measured health outcomes [ 109 ], there remains a paucity of empirical research that directly investigates patient experience in digital hospital environments. Our results revealed that, in a small number of studies, patient satisfaction scores were positively associated with digital hospitals (4/61, 7%) or remained unchanged (3/61, 5%). Patients and clinicians shared positive overall impressions of EMRs and negative attitudes toward data privacy in a digital hospital environment; however, this result must be considered in the disproportionate context of patient and clinician experience data reported in studies (10/61, 16% vs 55/61, 90%, respectively).

Patient experience in a digital hospital was sometimes inferred from surrogate measures, including hospital recommendations and discharge information quality, that do not capture the complexity of personal experience. For patients, crude quantitative measurement of satisfaction with digital hospitals neglects the complex nature of the digital patient experience [ 110 ] or emerging consumer digital health themes (eg, ethical implications, security, choice, privacy, transparency, accuracy, user-friendliness, and equity of access) [ 111 , 112 ]. The authors support the call by Viitanen et al [ 23 ] to develop a framework to describe the different aspects of patient experience and correlate them with appropriate methods for studying patient experience in this context.

The effect of digital hospitals on the clinician-patient relationship was consistently reported by clinicians as a negative outcome of digitization. These results align with the well-researched relationship between EMRs and the clinician-patient dynamic, with evidence supporting negative communication outcomes (eg, rapport, quality of interaction, and time) [ 113 ] from a clinician perspective. Patient perceptions of clinician-patient communication when using EMRs are relatively stable in previous systematic reviews despite objective studies describing potentially negative (eg, interrupted speech) and positive (eg, facilitating questions) effects [ 16 ]. Patient portals within EMRs can improve clinician-patient communication and should be considered a necessary infrastructure for health services implementing EMRs to mitigate potential negative effects [ 24 ].

Implications for Practice

“Improved patient experience” and “improved clinician experience” are 2 quadrants of the Quadruple Aim of health care that warrant significant health service investment amidst the widespread digital transformation of health care. Our findings highlight the need to address pervasive barriers to positive clinician and patient experiences in digital hospitals. To tackle the issues of clinician-patient interaction, inefficient documentation, workload, and burnout identified in this review, health services can invest in feasible and cost-effective solutions such as clinical education and training that are tailored to each clinical discipline as each discipline has unique EMR needs [ 10 ]. Prioritizing investment in patient-facing digital solutions such as patient portals can democratize clinical knowledge and empower patients on their unique health care journey [ 24 ].

Investment in optimizing EMR infrastructure will build a strong foundation for new clinical applications in descriptive, predictive (ie, artificial intelligence [AI]), and prescriptive (ie, causal AI and decision support) analytics that can benefit clinical workflows and patient outcomes [ 114 ]. COVID-19 initiated the rapid adoption of virtual health care [ 115 ], and clinical applications of AI are rapidly emerging as the future primary disruptors of health care [ 116 ]. Global health services are building machinery to shift from reactive (treat-manage) to proactive (predict-prevent) models of care, with evidence of success for acute clinical problems such as reducing mortality rate and organ failure in the early identification of sepsis [ 117 ]. Stakeholder perspectives on implementing clinical AI have been recently consolidated in a qualitative evidence synthesis [ 118 ]; however, similarly to our review, patients, carers, and consumers were an underrepresented group compared with clinicians (11.4% vs 70% of data, respectively).

Our approach of using AI (machine learning) via Leximancer to perform the qualitative evidence synthesis is a novel approach compared with recent manual evidence synthesis methods [ 118 - 120 ]. The use of semiautomated content analysis tools such as Leximancer can accelerate progress toward a learning health system. These tools offer an accelerated pipeline for analyzing “big” qualitative data that suffer from traditional yet burdensome manual analytic workflows. Key health care use cases of applying digital tools to routine analytical workflows are patient-reported experience measures [ 121 ], unstructured clinical notes in EMRs [ 122 ], and social media [ 123 ]. Natural language processing and machine learning have been tested to analyze free-text comments from patient experience feedback [ 124 ]. Applications of Leximancer can be pushed by investigating how its algorithms can be used in real-world health care to drive continuous cycles of quality improvement with greater speed and efficiency compared with a manual control. Leximancer offers an impartial starting point for content analysis by automating the identification of key concepts and themes that warrant further qualitative refinement by the research team.

Limitations

The scope of this review was limited to experiences in a digital hospital environment, and thus, the experiences of specific digital systems (eg, telehealth and patient portals) were not considered. The complex, interacting factors that influence experience; the stage of digital hospital implementation; and the differences among settings were not explored in this review and offer important foci for future research. By not including gray literature and articles not published in English, our search strategy may have missed informal evaluations of clinician and patient experience of digital hospitals (eg, within health service annual reports) and geographical variation in digital hospital evaluations. The heterogeneity of digital health environments is reflected in the heterogeneity of studies included in this review, meaning that it is difficult to draw definitive conclusions agnostic to time and place. One limitation of using Leximancer for the qualitative evidence synthesis is that it does not automatically identify emotive concepts; these are identified by researchers when interpreting the results. Although Leximancer reduces the potential for human bias when compared with manual analysis, researcher interpretation of Leximancer results remains a gateway for introducing bias [ 40 ]. A qualitative evidence synthesis for patient experience studies was not possible as we only identified one eligible study. The patient experience results should be interpreted with caution because of the relatively limited patient experience data in studies (10/61, 16%) compared with clinician experience data in studies (55/61, 90%).

Conclusions

The clinician experience of digital hospitals appeared positive according to high-level indicators (eg, overall satisfaction and data accessibility); however, the qualitative evidence synthesis revealed substantive tensions between digital hospitals and overall experience, such as weakening clinician-patient interaction, change burden, and inefficient data workflows. There is insufficient evidence to draw a definitive conclusion on the patient experience of digital hospitals, but quantitative indications of satisfaction appear positive or agnostic to digitization. Future research must prioritize investigating the patient experience in digital hospitals and measuring the link between exposure (digital hospital) and outcome (experience) in carefully designed pragmatic trials. Areas of interest include examining the interacting factors that influence experience, the stage of digital hospital implementation, and the differences among settings. Equitable investigation of the patient (including pediatric patients) and clinician digital hospital experience must be prioritized in future research. Worldwide, as digital health becomes inseparable from hospitals and general health care, understanding how to optimize the clinician and patient experience in digital hospital environments will be critical to achieving the Quadruple Aim of (digital) health care.

Acknowledgments

OJC and LW are funded by the Digital Health Cooperative Research Centre (DHCRC). DHCRC is funded under the Commonwealth Government Cooperative Research Centres Program, Australia. OJC was also funded by the Australian Research Council Linkage Program Grant (ARC LP170101154). The funder had no role in study design, data collection, data analysis, data interpretation, or writing of the report.

Data Availability

The data supporting the findings of this study are available from the corresponding author (OJC) upon reasonable request.

Authors' Contributions

OJC and YM conceptualized the study. YM designed the search strategy with input from OJC and C Slade. OJC and YM executed the search. OJC, YM, JK, and BG performed article screening. OJC, LW, JK, and BG performed data extraction and quality appraisal. OJC and LW validated the article screening and data extraction. C Slade assisted with designing the search strategy and article screening. OJC, LW, JK, and BG performed data analysis. OJC and LW wrote the first draft of the paper with input from JK and BG. C Sullivan and ABJ critically reviewed the manuscript and provided expert input. OJC, LW, and JK revised the manuscript. All authors have read and approved the final version of the manuscript.

Conflicts of Interest

None declared.

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 checklist.

ENTREQ (Enhancing the Transparency in Reporting the Synthesis of Qualitative Research) guideline checklist.

Final search strategies for all included databases.

Data extraction template.

Mixed Methods Appraisal Tool results.

Characteristics of the studies included in the systematic review and qualitative evidence synthesis on clinician and patient experience in digital hospitals (N=61).

Leximancer results—qualitative evidence synthesis.

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Abbreviations

Edited by T Leung; submitted 29.03.23; peer-reviewed by W Tam, E Pittman; comments to author 07.09.23; revised version received 08.11.23; accepted 31.01.24; published 11.03.24.

©Oliver J Canfell, Leanna Woods, Yasaman Meshkat, Jenna Krivit, Brinda Gunashanhar, Christine Slade, Andrew Burton-Jones, Clair Sullivan. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 11.03.2024.

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 the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

This paper is in the following e-collection/theme issue:

Published on 13.3.2024 in Vol 8 (2024)

Implementing a Sodium-Glucose Cotransporter 2 Inhibitor Module With a Software Tool (Future Health Today): Qualitative Study

Authors of this article:

Author Orcid Image

Matthew Suen   1 , BBiomed, MD ;   Jo-Anne Manski-Nankervis   1 , MBBS, PhD ;   Caroline McBride   1 , MD ;   Natalie Lumsden   1 , PhD ;   Barbara Hunter   1 , PhD

1 Department of General Practice and Primary Care, University of Melbourne, Parkville, Australia

Corresponding Author:

  • Matthew Suen , BBiomed, MD
  • Department of General Practice and Primary Care
  • University of Melbourne
  • Level 3, North Wing, Building
  • 181 Grattan Street, Medical Building
  • Parkville , 3010
  • Phone: 61 383443369
  • Email: [email protected]

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COMMENTS

  1. What Is Qualitative Research?

    Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research. Qualitative research is the opposite of quantitative research, which involves collecting and ...

  2. Qualitative Study

    Qualitative research is a type of research that explores and provides deeper insights into real-world problems.[1] Instead of collecting numerical data points or intervene or introduce treatments just like in quantitative research, qualitative research helps generate hypotheses as well as further investigate and understand quantitative data.

  3. Planning Qualitative Research: Design and Decision Making for New

    Qualitative research draws from interpretivist and constructivist paradigms, seeking to deeply understand a research subject rather than predict outcomes, as in the positivist paradigm (Denzin & Lincoln, 2011).Interpretivism seeks to build knowledge from understanding individuals' unique viewpoints and the meaning attached to those viewpoints (Creswell & Poth, 2018).

  4. What is Qualitative in Qualitative Research

    Qualitative research involves the studied use and collection of a variety of empirical materials - case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts - that describe routine and problematic moments and meanings in individuals' lives.

  5. How to use and assess qualitative research methods

    Abstract. This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions ...

  6. How to use and assess qualitative research methods

    Quality assessment. Download PDF. This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi ...

  7. Qualitative Research: Sage Journals

    Qualitative Research is a peer-reviewed international journal that has been leading debates about qualitative methods for over 20 years. The journal provides a forum for the discussion and development of qualitative methods across disciplines, publishing high quality articles that contribute to the ways in which we think about and practice the craft of qualitative research.

  8. The Oxford Handbook of Qualitative Research

    Abstract. The Oxford Handbook of Qualitative Research, second edition, presents a comprehensive retrospective and prospective review of the field of qualitative research. Original, accessible chapters written by interdisciplinary leaders in the field make this a critical reference work. Filled with robust examples from real-world research ...

  9. What Is Qualitative Research?

    Qualitative research methods. Each of the research approaches involve using one or more data collection methods.These are some of the most common qualitative methods: Observations: recording what you have seen, heard, or encountered in detailed field notes. Interviews: personally asking people questions in one-on-one conversations. Focus groups: asking questions and generating discussion among ...

  10. PDF Qualitative Research

    Chapter 1 Qualitative Research 3. Still other definitions focus on the process and context of data collection: Qualitative research is a situated activity that locates the observer in the world. It consists of a set of interpretive, material practices that makes the world visible. These practices transform the world.

  11. Qualitative Study

    Qualitative research is a type of research that explores and provides deeper insights into real-world problems. Instead of collecting numerical data points or intervene or introduce treatments just like in quantitative research, qualitative research helps generate hypotheses as well as further inves …

  12. Qualitative research

    Qualitative research is a type of research that aims to gather and analyse non-numerical (descriptive) data in order to gain an understanding of individuals' social reality, including understanding their attitudes, beliefs, and motivation. This type of research typically involves in-depth interviews, focus groups, or observations in order to collect data that is rich in detail and context.

  13. Qualitative Research: An Overview

    Qualitative research Footnote 1 —research that primarily or exclusively uses non-numerical data—is one of the most commonly used types of research and methodology in the social sciences. Unfortunately, qualitative research is commonly misunderstood. It is often considered "easy to do" (thus anyone can do it with no training), an "anything goes approach" (lacks rigor, validity and ...

  14. (PDF) Qualitative Research Methods: A Practice-Oriented Introduction

    The book examines questions such as why people do such research, how they go about doing it, what results it leads to, and how results can be presented in a plausible and useful way. Its ...

  15. Definition

    Qualitative research is the naturalistic study of social meanings and processes, using interviews, observations, and the analysis of texts and images. In contrast to quantitative researchers, whose statistical methods enable broad generalizations about populations (for example, comparisons of the percentages of U.S. demographic groups who vote in particular ways), qualitative researchers use ...

  16. Qualitative Research: Data Collection, Analysis, and Management

    For example, the title of the research report by Thurston and others, 7 "Discordant indigenous and provider frames explain challenges in improving access to arthritis care: a qualitative study using constructivist grounded theory," indicates at least 2 theoretical standpoints. The first is the culture of the indigenous population of Canada ...

  17. Qualitative Research

    Qualitative Research. Qualitative research is a type of research methodology that focuses on exploring and understanding people's beliefs, attitudes, behaviors, and experiences through the collection and analysis of non-numerical data. It seeks to answer research questions through the examination of subjective data, such as interviews, focus groups, observations, and textual analysis.

  18. Chapter 2. Research Design

    Chapter 2. Research Design Getting Started. When I teach undergraduates qualitative research methods, the final product of the course is a "research proposal" that incorporates all they have learned and enlists the knowledge they have learned about qualitative research methods in an original design that addresses a particular research question.

  19. What is Qualitative in Qualitative Research

    DOI: 10.1007/s11133-019-9413-7. Keywords: What is qualitative research? If we look for a precise definition of qualitative research, and specifically for one that addresses its distinctive feature of being "qualitative," the literature is meager. In this article we systematically search, identify and analyze a sample of 89 sources using or ….

  20. Mental health professionals' perceived barriers and enablers to shared

    A qualitative research synthesis examining stakeholders' attitudes towards SDM in mental health reported that service users valued their voice being heard, listened to, and supported to express themselves in encounters with professionals . Several barriers to SDM were identified from the service user's perspective, including feelings of ...

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    Construct a position in the context of qualitative literacy scholarship e. Develop approaches to qualitative scholarship appropriate for graduate work Required Texts and/or Readings and Course Materials Sunstein, B. S., & Chiseri-Strater, E. (2011). Fieldworking: Reading and writing research. Macmillan. 2

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    This study adopted a qualitative research design, employing interpretive phenomenological analysis (IPA; Smith et al., 2022), for three reasons. First, the phenomenological approach of IPA was best suited to understand the lived reality of autistic transgender people's GD in their own terms. Second, IPA's emphasis on researchers ...

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    Trauma-focused therapies (TFTs) are first-line treatments for posttraumatic stress disorder (PTSD). However, TFTs are under-utilised, partly due to clinicians' and patients' fear that TFT is too challenging or harmful. We review the qualitative studies on how adults with PTSD experience TFTs to enhance the understanding of user perspectives, therapeutic processes, and outcomes.

  24. What is Qualitative in Qualitative Research

    What is qualitative research? If we look for a precise definition of qualitative research, and specifically for one that addresses its distinctive feature of being "qualitative," the literature is meager. In this article we systematically search, identify and analyze a sample of 89 sources using or attempting to define the term "qualitative." Then, drawing on ideas we find scattered ...

  25. Qualitative Methods in Health Care Research

    Mixed methods research, the third methodological approach, involves collection and analysis of both qualitative and quantitative information with an objective to solve different but related questions, or at times the same questions.[1,2] In healthcare, qualitative research is widely used to understand patterns of health behaviors, describe ...

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    To analyze the data, we used a descriptive qualitative content analysis approach, which "serves as a vehicle for presenting and treating research methods as living entities" (Vaismoradi et al., Citation 2013, p. 399). This method involves a systematic coding and categorizing approach which was especially useful for our analysis, allowing us ...

  28. Choosing a Qualitative Research Approach

    In qualitative research, the researcher is the main data collection instrument. The researcher examines why events occur, what happens, and what those events mean to the participants studied. 1, 2. Qualitative research starts from a fundamentally different set of beliefs—or paradigms—than those that underpin quantitative research.

  29. Journal of Medical Internet Research

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    Background: Primary care plays a key role in the management of type 2 diabetes. Sodium-glucose cotransporter 2 (SGLT2) inhibitors have been demonstrated to reduce hospitalization and cardiac and renal complications. Tools that optimize management, including appropriate prescribing, are a priority for treating chronic diseases. Future Health Today (FHT) is software that facilitates clinical ...