qualitative research is used to minimize subjectivity and bias

How to Avoid Bias in Qualitative Research

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Research bias occurs when researchers try to influence the results of their work, in order to get the outcome they want. Often, researchers may not be aware they are doing this. Whether they are aware or not, such behavior clearly severely affects the impartiality of a study and greatly reduces the value of the results.

The Issues in Qualitative Research

Recently, I discussed the problem of bias with a researcher friend.

“I heard that research bias is a bigger problem for qualitative research than quantitative research.”

“Why is that?”

“Qualitative research relies more on the experience and judgment of the researcher. Also, the type of data collected is subjective and unique to the person or situation. So it is much harder to avoid bias than in quantitative research.”

“Are there ways to avoid bias ?”

“A good start is to recognize that bias exists in all research. We can then try to predict what type of bias we might have in our study, and try to avoid it as much as possible.”

Types of Bias in Research

“Are there different types of bias to watch out for?”

• There’s design bias , where the researcher does not consider bias in the design of the study. Factors like sample size , the range of participants, for example – all of these can cause bias.
• Next there’s also selection or sampling bias . For example, you might omit people of certain ages or ethnicities from your study. This is called omission bias. The other type, inclusive bias, is when you select a sample just because it is convenient. For example, if the people you select for your study are all college students, they are likely to share many characteristics.”

“Are there more?”

“Yes, there are lots of different types of bias.

• There’s procedural bias , where the way you carry out a study affects the results. For example, if you give people only a short time to answer questions, their responses will be rushed.
• There’s also measurement bias that can happen if the equipment you are using is faulty, or you are not using it correctly.”

“That’s a lot to think about.”

“I can think of three more.

• There’s interviewer bias , which is very hard to avoid. This is when an interviewer subconsciously influences the responses of the interviewee. Their body language might indicate their opinion, for example.
• Furthermore, there’s response bias , where someone tries to give the answers they think are “correct.”
• Finally, there’s reporting bias . This is often outside the researcher’s control. It means that research with positive, or exciting, results is far more likely to be reported, so can seem more critical.”

How to Avoid Bias in Research

“With so many types of bias, how can it be avoided?”

“There are a number of things the researcher can do to avoid bias.

• Read the guidelines : Check the guidelines of your institution or sponsor and make sure you follow them.
• Think about our objectives : Plan your study early. Be clear about what you want to achieve, and how. This will help to avoid bias when you start collecting data.”

“And next?”

• Maintain records : Keep detailed records. This reduces the chance of making mistakes.
• Be honest when reporting : Make sure you include all your results in your report. Even the results that don’t seem important. Finally, be honest about the limitations of your study in your report.”

Avoiding Participant Bias

“That explains what researchers can do. But what about participant bias?”

“Try asking indirect questions. People might change their answers to direct questions to make a good impression. But if you ask them what a friend or colleague might think, you might get a more honest response.”

“Are open-ended questions useful?”

“Yes. They allow information to flow more freely, by not forcing a limited set of answers. But even these should be used with caution . You should try to be impartial about all parts of the study, and avoid implying that there is a right answer. It might help to ask people to rate their responses on a scale of 1-5, for example, rather than agree/disagree.”

Reducing Researcher Bias

“All researchers should try to avoid confirmation bias. This is when you interpret your data in a way that supports your hypothesis. Secondly, you should make sure to analyze all your data, even if it doesn’t seem useful. Finally, always get an independent person to check your work, ideally several times during your study.”

Identifying and avoiding research bias in qualitative research is clearly tricky, with many different factors to consider. However, it is also vital. Biased research has little value; it is a waste of researchers’ valuable time and resources.

Learn even more about bias here . How did you overcome bias in your research? Share your experiences and thoughts in the comment section below.

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The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview
• What is qualitative research?
• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Theoretical framework
• Literature reviews
• Research question
• Conceptual framework
• Conceptual vs. theoretical framework
• Data collection
• Qualitative research methods
• Focus groups
• Observational research
• Case studies
• Ethnographical research
• Ethical considerations
• Confidentiality and privacy

What is research bias?

Understanding unconscious bias, how to avoid bias in research, bias and subjectivity in research.

• Power dynamics
• Reflexivity

Bias in research

In a purely objective world, research bias would not exist because knowledge would be a fixed and unmovable resource; either one knows about a particular concept or phenomenon, or they don't. However, qualitative research and the social sciences both acknowledge that subjectivity and bias exist in every aspect of the social world, which naturally includes the research process too. This bias is manifest in the many different ways that knowledge is understood, constructed, and negotiated, both in and out of research.

Understanding research bias has profound implications for data collection methods and data analysis , requiring researchers to take particular care of how to account for the insights generated from their data .

Research bias, often unavoidable, is a systematic error that can creep into any stage of the research process , skewing our understanding and interpretation of findings. From data collection to analysis, interpretation , and even publication , bias can distort the truth we seek to capture and communicate in our research.

It’s also important to distinguish between bias and subjectivity, especially when engaging in qualitative research . Most qualitative methodologies are based on epistemological and ontological assumptions that there is no such thing as a fixed or objective world that exists “out there” that can be empirically measured and understood through research. Rather, many qualitative researchers embrace the socially constructed nature of our reality and thus recognize that all data is produced within a particular context by participants with their own perspectives and interpretations. Moreover, the researcher’s own subjective experiences inevitably shape how they make sense of the data. These subjectivities are considered to be strengths, not limitations, of qualitative research approaches, because they open new avenues for knowledge generation. This is also why reflexivity is so important in qualitative research. When we refer to bias in this guide, on the other hand, we are referring to systematic errors that can negatively affect the research process but that can be mitigated through researchers’ careful efforts.

To fully grasp what research bias is, it's essential to understand the dual nature of bias. Bias is not inherently evil. It's simply a tendency, inclination, or prejudice for or against something. In our daily lives, we're subject to countless biases, many of which are unconscious. They help us navigate our world, make quick decisions, and understand complex situations. But when conducting research, these same biases can cause significant issues.

Research bias can affect the validity and credibility of research findings, leading to erroneous conclusions. It can emerge from the researcher's subconscious preferences or the methodological design of the study itself. For instance, if a researcher unconsciously favors a particular outcome of the study, this preference could affect how they interpret the results, leading to a type of bias known as confirmation bias.

Research bias can also arise due to the characteristics of study participants. If the researcher selectively recruits participants who are more likely to produce desired outcomes, this can result in selection bias.

Another form of bias can stem from data collection methods . If a survey question is phrased in a way that encourages a particular response, this can introduce response bias. Moreover, inappropriate survey questions can have a detrimental effect on future research if such studies are seen by the general population as biased toward particular outcomes depending on the preferences of the researcher.

Bias can also occur during data analysis . In qualitative research for instance, the researcher's preconceived notions and expectations can influence how they interpret and code qualitative data, a type of bias known as interpretation bias. It's also important to note that quantitative research is not free of bias either, as sampling bias and measurement bias can threaten the validity of any research findings.

Given these examples, it's clear that research bias is a complex issue that can take many forms and emerge at any stage in the research process. This section will delve deeper into specific types of research bias, provide examples, discuss why it's an issue, and provide strategies for identifying and mitigating bias in research.

What is an example of bias in research?

Bias can appear in numerous ways. One example is confirmation bias, where the researcher has a preconceived explanation for what is going on in their data, and any disconfirming evidence is (unconsciously) ignored. For instance, a researcher conducting a study on daily exercise habits might be inclined to conclude that meditation practices lead to greater engagement in exercise because that researcher has personally experienced these benefits. However, conducting rigorous research entails assessing all the data systematically and verifying one’s conclusions by checking for both supporting and refuting evidence.

What is a common bias in research?

Confirmation bias is one of the most common forms of bias in research. It happens when researchers unconsciously focus on data that supports their ideas while ignoring or undervaluing data that contradicts their ideas. This bias can lead researchers to mistakenly confirm their theories, despite having insufficient or conflicting evidence.

What are the different types of bias?

There are several types of research bias, each presenting unique challenges. Some common types include:

Confirmation bias: As already mentioned, this happens when a researcher focuses on evidence supporting their theory while overlooking contradictory evidence.

Selection bias: This occurs when the researcher's method of choosing participants skews the sample in a particular direction.

Response bias: This happens when participants in a study respond inaccurately or falsely, often due to misleading or poorly worded questions.

Observer bias (or researcher bias): This occurs when the researcher unintentionally influences the results because of their expectations or preferences.

Publication bias: This type of bias arises when studies with positive results are more likely to get published, while studies with negative or null results are often ignored.

Analysis bias: This type of bias occurs when the data is manipulated or analyzed in a way that leads to a particular result, whether intentionally or unintentionally.

What is an example of researcher bias?

Researcher bias, also known as observer bias, can occur when a researcher's expectations or personal beliefs influence the results of a study. For instance, if a researcher believes that a particular therapy is effective, they might unconsciously interpret ambiguous results in a way that supports the efficacy of the therapy, even if the evidence is not strong enough.

Even quantitative research methodologies are not immune from bias from researchers. Market research surveys or clinical trial research, for example, may encounter bias when the researcher chooses a particular population or methodology to achieve a specific research outcome. Questions in customer feedback surveys whose data is employed in quantitative analysis can be structured in such a way as to bias survey respondents toward certain desired answers.

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Identifying and avoiding bias in research

As we will remind you throughout this chapter, bias is not a phenomenon that can be removed altogether, nor should we think of it as something that should be eliminated. In a subjective world involving humans as researchers and research participants, bias is unavoidable and almost necessary for understanding social behavior. The section on reflexivity later in this guide will highlight how different perspectives among researchers and human subjects are addressed in qualitative research. That said, bias in excess can place the credibility of a study's findings into serious question. Scholars who read your research need to know what new knowledge you are generating, how it was generated, and why the knowledge you present should be considered persuasive. With that in mind, let's look at how bias can be identified and, where it interferes with research, minimized.

How do you identify bias in research?

Identifying bias involves a critical examination of your entire research study involving the formulation of the research question and hypothesis , the selection of study participants, the methods for data collection, and the analysis and interpretation of data. Researchers need to assess whether each stage has been influenced by bias that may have skewed the results. Tools such as bias checklists or guidelines, peer review , and reflexivity (reflecting on one's own biases) can be instrumental in identifying bias.

How do you identify research bias?

Identifying research bias often involves careful scrutiny of the research methodology and the researcher's interpretations. Was the sample of participants relevant to the research question ? Were the interview or survey questions leading? Were there any conflicts of interest that could have influenced the results? It also requires an understanding of the different types of bias and how they might manifest in a research context. Does the bias occur in the data collection process or when the researcher is analyzing data?

Research transparency requires a careful accounting of how the study was designed, conducted, and analyzed. In qualitative research involving human subjects, the researcher is responsible for documenting the characteristics of the research population and research context. With respect to research methods, the procedures and instruments used to collect and analyze data are described in as much detail as possible.

While describing study methodologies and research participants in painstaking detail may sound cumbersome, a clear and detailed description of the research design is necessary for good research. Without this level of detail, it is difficult for your research audience to identify whether bias exists, where bias occurs, and to what extent it may threaten the credibility of your findings.

How to recognize bias in a study?

Recognizing bias in a study requires a critical approach. The researcher should question every step of the research process: Was the sample of participants selected with care? Did the data collection methods encourage open and sincere responses? Did personal beliefs or expectations influence the interpretation of the results? External peer reviews can also be helpful in recognizing bias, as others might spot potential issues that the original researcher missed.

The subsequent sections of this chapter will delve into the impacts of research bias and strategies to avoid it. Through these discussions, researchers will be better equipped to handle bias in their work and contribute to building more credible knowledge.

Unconscious biases, also known as implicit biases, are attitudes or stereotypes that influence our understanding, actions, and decisions in an unconscious manner. These biases can inadvertently infiltrate the research process, skewing the results and conclusions. This section aims to delve deeper into understanding unconscious bias, its impact on research, and strategies to mitigate it.

What is unconscious bias?

Unconscious bias refers to prejudices or social stereotypes about certain groups that individuals form outside their conscious awareness. Everyone holds unconscious beliefs about various social and identity groups, and these biases stem from a tendency to organize social worlds into categories.

How does unconscious bias infiltrate research?

Unconscious bias can infiltrate research in several ways. It can affect how researchers formulate their research questions or hypotheses , how they interact with participants, their data collection methods, and how they interpret their data . For instance, a researcher might unknowingly favor participants who share similar characteristics with them, which could lead to biased results.

Implications of unconscious bias

The implications of unconscious research bias are far-reaching. It can compromise the validity of research findings , influence the choice of research topics, and affect peer review processes . Unconscious bias can also lead to a lack of diversity in research, which can severely limit the value and impact of the findings.

Strategies to mitigate unconscious research bias

While it's challenging to completely eliminate unconscious bias, several strategies can help mitigate its impact. These include being aware of potential unconscious biases, practicing reflexivity , seeking diverse perspectives for your study, and engaging in regular bias-checking activities, such as bias training and peer debriefing .

By understanding and acknowledging unconscious bias, researchers can take steps to limit its impact on their work, leading to more robust findings.

Why is researcher bias an issue?

Research bias is a pervasive issue that researchers must diligently consider and address. It can significantly impact the credibility of findings. Here, we break down the ramifications of bias into two key areas.

How bias affects validity

Research validity refers to the accuracy of the study findings, or the coherence between the researcher’s findings and the participants’ actual experiences. When bias sneaks into a study, it can distort findings and move them further away from the realities that were shared by the research participants. For example, if a researcher's personal beliefs influence their interpretation of data , the resulting conclusions may not reflect what the data show or what participants experienced.

The transferability problem

Transferability is the extent to which your study's findings can be applied beyond the specific context or sample studied. Applying knowledge from one context to a different context is how we can progress and make informed decisions. In quantitative research , the generalizability of a study is a key component that shapes the potential impact of the findings. In qualitative research , all data and knowledge that is produced is understood to be embedded within a particular context, so the notion of generalizability takes on a slightly different meaning. Rather than assuming that the study participants are statistically representative of the entire population, qualitative researchers can reflect on which aspects of their research context bear the most weight on their findings and how these findings may be transferable to other contexts that share key similarities.

How does bias affect research?

Research bias, if not identified and mitigated, can significantly impact research outcomes. The ripple effects of research bias extend beyond individual studies, impacting the body of knowledge in a field and influencing policy and practice. Here, we delve into three specific ways bias can affect research.

Distortion of research results

Bias can lead to a distortion of your study's findings. For instance, confirmation bias can cause a researcher to focus on data that supports their interpretation while disregarding data that contradicts it. This can skew the results and create a misleading picture of the phenomenon under study.

Undermining scientific progress

When research is influenced by bias, it not only misrepresents participants’ realities but can also impede scientific progress. Biased studies can lead researchers down the wrong path, resulting in wasted resources and efforts. Moreover, it could contribute to a body of literature that is skewed or inaccurate, misleading future research and theories.

Influencing policy and practice based on flawed findings

Research often informs policy and practice. If the research is biased, it can lead to the creation of policies or practices that are ineffective or even harmful. For example, a study with selection bias might conclude that a certain intervention is effective, leading to its broad implementation. However, suppose the transferability of the study's findings was not carefully considered. In that case, it may be risky to assume that the intervention will work as well in different populations, which could lead to ineffective or inequitable outcomes.

While it's almost impossible to eliminate bias in research entirely, it's crucial to mitigate its impact as much as possible. By employing thoughtful strategies at every stage of research, we can strive towards rigor and transparency , enhancing the quality of our findings. This section will delve into specific strategies for avoiding bias.

How do you know if your research is biased?

Determining whether your research is biased involves a careful review of your research design, data collection , analysis , and interpretation . It might require you to reflect critically on your own biases and expectations and how these might have influenced your research. External peer reviews can also be instrumental in spotting potential bias.

Strategies to mitigate bias

Minimizing bias involves careful planning and execution at all stages of a research study. These strategies could include formulating clear, unbiased research questions , ensuring that your sample meaningfully represents the research problem you are studying, crafting unbiased data collection instruments, and employing systematic data analysis techniques. Transparency and reflexivity throughout the process can also help minimize bias.

Mitigating bias in data collection

To mitigate bias in data collection, ensure your questions are clear, neutral, and not leading. Triangulation, or using multiple methods or data sources, can also help to reduce bias and increase the credibility of your findings.

Mitigating bias in data analysis

During data analysis , maintaining a high level of rigor is crucial. This might involve using systematic coding schemes in qualitative research or appropriate statistical tests in quantitative research . Regularly questioning your interpretations and considering alternative explanations can help reduce bias. Peer debriefing , where you discuss your analysis and interpretations with colleagues, can also be a valuable strategy.

By using these strategies, researchers can significantly reduce the impact of bias on their research, enhancing the quality and credibility of their findings and contributing to a more robust and meaningful body of knowledge.

Impact of cultural bias in research

Cultural bias is the tendency to interpret and judge phenomena by standards inherent to one's own culture. Given the increasingly multicultural and global nature of research, understanding and addressing cultural bias is paramount. This section will explore the concept of cultural bias, its impacts on research, and strategies to mitigate it.

What is cultural bias in research?

Cultural bias refers to the potential for a researcher's cultural background, experiences, and values to influence the research process and findings. This can occur consciously or unconsciously and can lead to misinterpretation of data, unfair representation of cultures, and biased conclusions.

How does cultural bias infiltrate research?

Cultural bias can infiltrate research at various stages. It can affect the framing of research questions , the design of the study, the methods of data collection , and the interpretation of results . For instance, a researcher might unintentionally design a study that does not consider the cultural context of the participants, leading to a biased understanding of the phenomenon being studied.

Implications of cultural bias

The implications of cultural bias are profound. Cultural bias can skew your findings, limit the transferability of results, and contribute to cultural misunderstandings and stereotypes. This can ultimately lead to inaccurate or ethnocentric conclusions, further perpetuating cultural bias and inequities.

As a result, many social science fields like sociology and anthropology have been critiqued for cultural biases in research. Some of the earliest research inquiries in anthropology, for example, have had the potential to reduce entire cultures to simplistic stereotypes when compared to mainstream norms. A contemporary researcher respecting ethical and cultural boundaries, on the other hand, should seek to properly place their understanding of social and cultural practices in sufficient context without inappropriately characterizing them.

Strategies to mitigate cultural bias

Mitigating cultural bias requires a concerted effort throughout the research study. These efforts could include educating oneself about other cultures, being aware of one's own cultural biases, incorporating culturally diverse perspectives into the research process, and being sensitive and respectful of cultural differences. It might also involve including team members with diverse cultural backgrounds or seeking external cultural consultants to challenge assumptions and provide alternative perspectives.

By acknowledging and addressing cultural bias, researchers can contribute to more culturally competent, equitable, and valid research. This not only enriches the scientific body of knowledge but also promotes cultural understanding and respect.

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Keep in mind that bias is a force to be mitigated, not a phenomenon that can be eliminated altogether, and the subjectivities of each person are what make our world so complex and interesting. As things are continuously changing and adapting, research knowledge is also continuously being updated as we further develop our understanding of the world around us.

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How to use and assess qualitative research methods

Loraine busetto.

1 Department of Neurology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany

Wolfgang Wick

2 Clinical Cooperation Unit Neuro-Oncology, German Cancer Research Center, Heidelberg, Germany

Christoph Gumbinger

Associated data.

Not applicable.

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 – 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 – 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.

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 .

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 ].

From data collection to data analysis

Attributions for icons: see Fig. ​ Fig.2, 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 – 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 .

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 – 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 – 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 ​ Table1. 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.

Take-away-points

Acknowledgements

Abbreviations, authors’ contributions.

LB drafted the manuscript; WW and CG revised the manuscript; all authors approved the final versions.

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• Published: 05 October 2018

Interviews and focus groups in qualitative research: an update for the digital age

• P. Gill 1 &
• J. Baillie 2  

British Dental Journal volume  225 ,  pages 668–672 ( 2018 ) Cite this article

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Highlights that qualitative research is used increasingly in dentistry. Interviews and focus groups remain the most common qualitative methods of data collection.

Suggests the advent of digital technologies has transformed how qualitative research can now be undertaken.

Suggests interviews and focus groups can offer significant, meaningful insight into participants' experiences, beliefs and perspectives, which can help to inform developments in dental practice.

Qualitative research is used increasingly in dentistry, due to its potential to provide meaningful, in-depth insights into participants' experiences, perspectives, beliefs and behaviours. These insights can subsequently help to inform developments in dental practice and further related research. The most common methods of data collection used in qualitative research are interviews and focus groups. While these are primarily conducted face-to-face, the ongoing evolution of digital technologies, such as video chat and online forums, has further transformed these methods of data collection. This paper therefore discusses interviews and focus groups in detail, outlines how they can be used in practice, how digital technologies can further inform the data collection process, and what these methods can offer dentistry.

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Introduction

Traditionally, research in dentistry has primarily been quantitative in nature. 1 However, in recent years, there has been a growing interest in qualitative research within the profession, due to its potential to further inform developments in practice, policy, education and training. Consequently, in 2008, the British Dental Journal (BDJ) published a four paper qualitative research series, 2 , 3 , 4 , 5 to help increase awareness and understanding of this particular methodological approach.

Since the papers were originally published, two scoping reviews have demonstrated the ongoing proliferation in the use of qualitative research within the field of oral healthcare. 1 , 6 To date, the original four paper series continue to be well cited and two of the main papers remain widely accessed among the BDJ readership. 2 , 3 The potential value of well-conducted qualitative research to evidence-based practice is now also widely recognised by service providers, policy makers, funding bodies and those who commission, support and use healthcare research.

Besides increasing standalone use, qualitative methods are now also routinely incorporated into larger mixed method study designs, such as clinical trials, as they can offer additional, meaningful insights into complex problems that simply could not be provided by quantitative methods alone. Qualitative methods can also be used to further facilitate in-depth understanding of important aspects of clinical trial processes, such as recruitment. For example, Ellis et al . investigated why edentulous older patients, dissatisfied with conventional dentures, decline implant treatment, despite its established efficacy, and frequently refuse to participate in related randomised clinical trials, even when financial constraints are removed. 7 Through the use of focus groups in Canada and the UK, the authors found that fears of pain and potential complications, along with perceived embarrassment, exacerbated by age, are common reasons why older patients typically refuse dental implants. 7

The last decade has also seen further developments in qualitative research, due to the ongoing evolution of digital technologies. These developments have transformed how researchers can access and share information, communicate and collaborate, recruit and engage participants, collect and analyse data and disseminate and translate research findings. 8 Where appropriate, such technologies are therefore capable of extending and enhancing how qualitative research is undertaken. 9 For example, it is now possible to collect qualitative data via instant messaging, email or online/video chat, using appropriate online platforms.

These innovative approaches to research are therefore cost-effective, convenient, reduce geographical constraints and are often useful for accessing 'hard to reach' participants (for example, those who are immobile or socially isolated). 8 , 9 However, digital technologies are still relatively new and constantly evolving and therefore present a variety of pragmatic and methodological challenges. Furthermore, given their very nature, their use in many qualitative studies and/or with certain participant groups may be inappropriate and should therefore always be carefully considered. While it is beyond the scope of this paper to provide a detailed explication regarding the use of digital technologies in qualitative research, insight is provided into how such technologies can be used to facilitate the data collection process in interviews and focus groups.

In light of such developments, it is perhaps therefore timely to update the main paper 3 of the original BDJ series. As with the previous publications, this paper has been purposely written in an accessible style, to enhance readability, particularly for those who are new to qualitative research. While the focus remains on the most common qualitative methods of data collection – interviews and focus groups – appropriate revisions have been made to provide a novel perspective, and should therefore be helpful to those who would like to know more about qualitative research. This paper specifically focuses on undertaking qualitative research with adult participants only.

Overview of qualitative research

Qualitative research is an approach that focuses on people and their experiences, behaviours and opinions. 10 , 11 The qualitative researcher seeks to answer questions of 'how' and 'why', providing detailed insight and understanding, 11 which quantitative methods cannot reach. 12 Within qualitative research, there are distinct methodologies influencing how the researcher approaches the research question, data collection and data analysis. 13 For example, phenomenological studies focus on the lived experience of individuals, explored through their description of the phenomenon. Ethnographic studies explore the culture of a group and typically involve the use of multiple methods to uncover the issues. 14

While methodology is the 'thinking tool', the methods are the 'doing tools'; 13 the ways in which data are collected and analysed. There are multiple qualitative data collection methods, including interviews, focus groups, observations, documentary analysis, participant diaries, photography and videography. Two of the most commonly used qualitative methods are interviews and focus groups, which are explored in this article. The data generated through these methods can be analysed in one of many ways, according to the methodological approach chosen. A common approach is thematic data analysis, involving the identification of themes and subthemes across the data set. Further information on approaches to qualitative data analysis has been discussed elsewhere. 1

Qualitative research is an evolving and adaptable approach, used by different disciplines for different purposes. Traditionally, qualitative data, specifically interviews, focus groups and observations, have been collected face-to-face with participants. In more recent years, digital technologies have contributed to the ongoing evolution of qualitative research. Digital technologies offer researchers different ways of recruiting participants and collecting data, and offer participants opportunities to be involved in research that is not necessarily face-to-face.

Research interviews are a fundamental qualitative research method 15 and are utilised across methodological approaches. Interviews enable the researcher to learn in depth about the perspectives, experiences, beliefs and motivations of the participant. 3 , 16 Examples include, exploring patients' perspectives of fear/anxiety triggers in dental treatment, 17 patients' experiences of oral health and diabetes, 18 and dental students' motivations for their choice of career. 19

Interviews may be structured, semi-structured or unstructured, 3 according to the purpose of the study, with less structured interviews facilitating a more in depth and flexible interviewing approach. 20 Structured interviews are similar to verbal questionnaires and are used if the researcher requires clarification on a topic; however they produce less in-depth data about a participant's experience. 3 Unstructured interviews may be used when little is known about a topic and involves the researcher asking an opening question; 3 the participant then leads the discussion. 20 Semi-structured interviews are commonly used in healthcare research, enabling the researcher to ask predetermined questions, 20 while ensuring the participant discusses issues they feel are important.

Interviews can be undertaken face-to-face or using digital methods when the researcher and participant are in different locations. Audio-recording the interview, with the consent of the participant, is essential for all interviews regardless of the medium as it enables accurate transcription; the process of turning the audio file into a word-for-word transcript. This transcript is the data, which the researcher then analyses according to the chosen approach.

Types of interview

Qualitative studies often utilise one-to-one, face-to-face interviews with research participants. This involves arranging a mutually convenient time and place to meet the participant, signing a consent form and audio-recording the interview. However, digital technologies have expanded the potential for interviews in research, enabling individuals to participate in qualitative research regardless of location.

Telephone interviews can be a useful alternative to face-to-face interviews and are commonly used in qualitative research. They enable participants from different geographical areas to participate and may be less onerous for participants than meeting a researcher in person. 15 A qualitative study explored patients' perspectives of dental implants and utilised telephone interviews due to the quality of the data that could be yielded. 21 The researcher needs to consider how they will audio record the interview, which can be facilitated by purchasing a recorder that connects directly to the telephone. One potential disadvantage of telephone interviews is the inability of the interviewer and researcher to see each other. This is resolved using software for audio and video calls online – such as Skype – to conduct interviews with participants in qualitative studies. Advantages of this approach include being able to see the participant if video calls are used, enabling observation of non-verbal communication, and the software can be free to use. However, participants are required to have a device and internet connection, as well as being computer literate, potentially limiting who can participate in the study. One qualitative study explored the role of dental hygienists in reducing oral health disparities in Canada. 22 The researcher conducted interviews using Skype, which enabled dental hygienists from across Canada to be interviewed within the research budget, accommodating the participants' schedules. 22

A less commonly used approach to qualitative interviews is the use of social virtual worlds. A qualitative study accessed a social virtual world – Second Life – to explore the health literacy skills of individuals who use social virtual worlds to access health information. 23 The researcher created an avatar and interview room, and undertook interviews with participants using voice and text methods. 23 This approach to recruitment and data collection enables individuals from diverse geographical locations to participate, while remaining anonymous if they wish. Furthermore, for interviews conducted using text methods, transcription of the interview is not required as the researcher can save the written conversation with the participant, with the participant's consent. However, the researcher and participant need to be familiar with how the social virtual world works to engage in an interview this way.

Conducting an interview

Ensuring informed consent before any interview is a fundamental aspect of the research process. Participants in research must be afforded autonomy and respect; consent should be informed and voluntary. 24 Individuals should have the opportunity to read an information sheet about the study, ask questions, understand how their data will be stored and used, and know that they are free to withdraw at any point without reprisal. The qualitative researcher should take written consent before undertaking the interview. In a face-to-face interview, this is straightforward: the researcher and participant both sign copies of the consent form, keeping one each. However, this approach is less straightforward when the researcher and participant do not meet in person. A recent protocol paper outlined an approach for taking consent for telephone interviews, which involved: audio recording the participant agreeing to each point on the consent form; the researcher signing the consent form and keeping a copy; and posting a copy to the participant. 25 This process could be replicated in other interview studies using digital methods.

There are advantages and disadvantages of using face-to-face and digital methods for research interviews. Ultimately, for both approaches, the quality of the interview is determined by the researcher. 16 Appropriate training and preparation are thus required. Healthcare professionals can use their interpersonal communication skills when undertaking a research interview, particularly questioning, listening and conversing. 3 However, the purpose of an interview is to gain information about the study topic, 26 rather than offering help and advice. 3 The researcher therefore needs to listen attentively to participants, enabling them to describe their experience without interruption. 3 The use of active listening skills also help to facilitate the interview. 14 Spradley outlined elements and strategies for research interviews, 27 which are a useful guide for qualitative researchers:

Greeting and explaining the project/interview

Asking descriptive (broad), structural (explore response to descriptive) and contrast (difference between) questions

Asymmetry between the researcher and participant talking

Expressing interest and cultural ignorance

Repeating, restating and incorporating the participant's words when asking questions

Creating hypothetical situations

Asking friendly questions

Knowing when to leave.

For semi-structured interviews, a topic guide (also called an interview schedule) is used to guide the content of the interview – an example of a topic guide is outlined in Box 1 . The topic guide, usually based on the research questions, existing literature and, for healthcare professionals, their clinical experience, is developed by the research team. The topic guide should include open ended questions that elicit in-depth information, and offer participants the opportunity to talk about issues important to them. This is vital in qualitative research where the researcher is interested in exploring the experiences and perspectives of participants. It can be useful for qualitative researchers to pilot the topic guide with the first participants, 10 to ensure the questions are relevant and understandable, and amending the questions if required.

Regardless of the medium of interview, the researcher must consider the setting of the interview. For face-to-face interviews, this could be in the participant's home, in an office or another mutually convenient location. A quiet location is preferable to promote confidentiality, enable the researcher and participant to concentrate on the conversation, and to facilitate accurate audio-recording of the interview. For interviews using digital methods the same principles apply: a quiet, private space where the researcher and participant feel comfortable and confident to participate in an interview.

Box 1: Example of a topic guide

Study focus: Parents' experiences of brushing their child's (aged 0–5) teeth

1. Can you tell me about your experience of cleaning your child's teeth?

How old was your child when you started cleaning their teeth?

Why did you start cleaning their teeth at that point?

How often do you brush their teeth?

What do you use to brush their teeth and why?

2. Could you explain how you find cleaning your child's teeth?

Do you find anything difficult?

What makes cleaning their teeth easier for you?

3. How has your experience of cleaning your child's teeth changed over time?

Has it become easier or harder?

Have you changed how often and how you clean their teeth? If so, why?

4. Could you describe how your child finds having their teeth cleaned?

What do they enjoy about having their teeth cleaned?

Is there anything they find upsetting about having their teeth cleaned?

5. Where do you look for information/advice about cleaning your child's teeth?

What did your health visitor tell you about cleaning your child's teeth? (If anything)

What has the dentist told you about caring for your child's teeth? (If visited)

Have any family members given you advice about how to clean your child's teeth? If so, what did they tell you? Did you follow their advice?

6. Is there anything else you would like to discuss about this?

Focus groups

A focus group is a moderated group discussion on a pre-defined topic, for research purposes. 28 , 29 While not aligned to a particular qualitative methodology (for example, grounded theory or phenomenology) as such, focus groups are used increasingly in healthcare research, as they are useful for exploring collective perspectives, attitudes, behaviours and experiences. Consequently, they can yield rich, in-depth data and illuminate agreement and inconsistencies 28 within and, where appropriate, between groups. Examples include public perceptions of dental implants and subsequent impact on help-seeking and decision making, 30 and general dental practitioners' views on patient safety in dentistry. 31

Focus groups can be used alone or in conjunction with other methods, such as interviews or observations, and can therefore help to confirm, extend or enrich understanding and provide alternative insights. 28 The social interaction between participants often results in lively discussion and can therefore facilitate the collection of rich, meaningful data. However, they are complex to organise and manage, due to the number of participants, and may also be inappropriate for exploring particularly sensitive issues that many participants may feel uncomfortable about discussing in a group environment.

Focus groups are primarily undertaken face-to-face but can now also be undertaken online, using appropriate technologies such as email, bulletin boards, online research communities, chat rooms, discussion forums, social media and video conferencing. 32 Using such technologies, data collection can also be synchronous (for example, online discussions in 'real time') or, unlike traditional face-to-face focus groups, asynchronous (for example, online/email discussions in 'non-real time'). While many of the fundamental principles of focus group research are the same, regardless of how they are conducted, a number of subtle nuances are associated with the online medium. 32 Some of which are discussed further in the following sections.

Focus group considerations

Some key considerations associated with face-to-face focus groups are: how many participants are required; should participants within each group know each other (or not) and how many focus groups are needed within a single study? These issues are much debated and there is no definitive answer. However, the number of focus groups required will largely depend on the topic area, the depth and breadth of data needed, the desired level of participation required 29 and the necessity (or not) for data saturation.

The optimum group size is around six to eight participants (excluding researchers) but can work effectively with between three and 14 participants. 3 If the group is too small, it may limit discussion, but if it is too large, it may become disorganised and difficult to manage. It is, however, prudent to over-recruit for a focus group by approximately two to three participants, to allow for potential non-attenders. For many researchers, particularly novice researchers, group size may also be informed by pragmatic considerations, such as the type of study, resources available and moderator experience. 28 Similar size and mix considerations exist for online focus groups. Typically, synchronous online focus groups will have around three to eight participants but, as the discussion does not happen simultaneously, asynchronous groups may have as many as 10–30 participants. 33

The topic area and potential group interaction should guide group composition considerations. Pre-existing groups, where participants know each other (for example, work colleagues) may be easier to recruit, have shared experiences and may enjoy a familiarity, which facilitates discussion and/or the ability to challenge each other courteously. 3 However, if there is a potential power imbalance within the group or if existing group norms and hierarchies may adversely affect the ability of participants to speak freely, then 'stranger groups' (that is, where participants do not already know each other) may be more appropriate. 34 , 35

Focus group management

Face-to-face focus groups should normally be conducted by two researchers; a moderator and an observer. 28 The moderator facilitates group discussion, while the observer typically monitors group dynamics, behaviours, non-verbal cues, seating arrangements and speaking order, which is essential for transcription and analysis. The same principles of informed consent, as discussed in the interview section, also apply to focus groups, regardless of medium. However, the consent process for online discussions will probably be managed somewhat differently. For example, while an appropriate participant information leaflet (and consent form) would still be required, the process is likely to be managed electronically (for example, via email) and would need to specifically address issues relating to technology (for example, anonymity and use, storage and access to online data). 32

The venue in which a face to face focus group is conducted should be of a suitable size, private, quiet, free from distractions and in a collectively convenient location. It should also be conducted at a time appropriate for participants, 28 as this is likely to promote attendance. As with interviews, the same ethical considerations apply (as discussed earlier). However, online focus groups may present additional ethical challenges associated with issues such as informed consent, appropriate access and secure data storage. Further guidance can be found elsewhere. 8 , 32

Before the focus group commences, the researchers should establish rapport with participants, as this will help to put them at ease and result in a more meaningful discussion. Consequently, researchers should introduce themselves, provide further clarity about the study and how the process will work in practice and outline the 'ground rules'. Ground rules are designed to assist, not hinder, group discussion and typically include: 3 , 28 , 29

Discussions within the group are confidential to the group

Only one person can speak at a time

All participants should have sufficient opportunity to contribute

There should be no unnecessary interruptions while someone is speaking

Everyone can be expected to be listened to and their views respected

Challenging contrary opinions is appropriate, but ridiculing is not.

Moderating a focus group requires considered management and good interpersonal skills to help guide the discussion and, where appropriate, keep it sufficiently focused. Avoid, therefore, participating, leading, expressing personal opinions or correcting participants' knowledge 3 , 28 as this may bias the process. A relaxed, interested demeanour will also help participants to feel comfortable and promote candid discourse. Moderators should also prevent the discussion being dominated by any one person, ensure differences of opinions are discussed fairly and, if required, encourage reticent participants to contribute. 3 Asking open questions, reflecting on significant issues, inviting further debate, probing responses accordingly, and seeking further clarification, as and where appropriate, will help to obtain sufficient depth and insight into the topic area.

Moderating online focus groups requires comparable skills, particularly if the discussion is synchronous, as the discussion may be dominated by those who can type proficiently. 36 It is therefore important that sufficient time and respect is accorded to those who may not be able to type as quickly. Asynchronous discussions are usually less problematic in this respect, as interactions are less instant. However, moderating an asynchronous discussion presents additional challenges, particularly if participants are geographically dispersed, as they may be online at different times. Consequently, the moderator will not always be present and the discussion may therefore need to occur over several days, which can be difficult to manage and facilitate and invariably requires considerable flexibility. 32 It is also worth recognising that establishing rapport with participants via online medium is often more challenging than via face-to-face and may therefore require additional time, skills, effort and consideration.

As with research interviews, focus groups should be guided by an appropriate interview schedule, as discussed earlier in the paper. For example, the schedule will usually be informed by the review of the literature and study aims, and will merely provide a topic guide to help inform subsequent discussions. To provide a verbatim account of the discussion, focus groups must be recorded, using an audio-recorder with a good quality multi-directional microphone. While videotaping is possible, some participants may find it obtrusive, 3 which may adversely affect group dynamics. The use (or not) of a video recorder, should therefore be carefully considered.

At the end of the focus group, a few minutes should be spent rounding up and reflecting on the discussion. 28 Depending on the topic area, it is possible that some participants may have revealed deeply personal issues and may therefore require further help and support, such as a constructive debrief or possibly even referral on to a relevant third party. It is also possible that some participants may feel that the discussion did not adequately reflect their views and, consequently, may no longer wish to be associated with the study. 28 Such occurrences are likely to be uncommon, but should they arise, it is important to further discuss any concerns and, if appropriate, offer them the opportunity to withdraw (including any data relating to them) from the study. Immediately after the discussion, researchers should compile notes regarding thoughts and ideas about the focus group, which can assist with data analysis and, if appropriate, any further data collection.

Qualitative research is increasingly being utilised within dental research to explore the experiences, perspectives, motivations and beliefs of participants. The contributions of qualitative research to evidence-based practice are increasingly being recognised, both as standalone research and as part of larger mixed-method studies, including clinical trials. Interviews and focus groups remain commonly used data collection methods in qualitative research, and with the advent of digital technologies, their utilisation continues to evolve. However, digital methods of qualitative data collection present additional methodological, ethical and practical considerations, but also potentially offer considerable flexibility to participants and researchers. Consequently, regardless of format, qualitative methods have significant potential to inform important areas of dental practice, policy and further related research.

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Gill, P., Baillie, J. Interviews and focus groups in qualitative research: an update for the digital age. Br Dent J 225 , 668–672 (2018). https://doi.org/10.1038/sj.bdj.2018.815

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Chapter 6. Reflexivity

Introduction.

Related to epistemological issues of how we know anything about the social world, qualitative researchers understand that we the researchers can never be truly neutral or outside the study we are conducting. As observers, we see things that make sense to us and may entirely miss what is either too obvious to note or too different to comprehend. As interviewers, as much as we would like to ask questions neutrally and remain in the background, interviews are a form of conversation, and the persons we interview are responding to us . Therefore, it is important to reflect upon our social positions and the knowledges and expectations we bring to our work and to work through any blind spots that we may have. This chapter discusses the concept of reflexivity and its importance for conducting reliable qualitative research.

Reflexivity: What It Is and Why It Is Important

Remember our discussion in epistemology ? Qualitative researchers tend to question assertions of absolute fact or reality, unmediated through subject positions and subject knowledge. There are limits to what we know because we are part of the social worlds we inhabit. To use the terminology of standpoint theorists, we have a standpoint from which we observe the world just as much as anyone else. In this, we too are the blind men, and the world is our elephant. None of us are omniscient or neutral observers. Because of this epistemological standpoint, qualitative researchers value the ability to reflect upon and think hard about our own effects on our research. We call this reflexivity. Reflexivity “generally involves the self-examination of how research findings were produced, and, particularly, the role of the researcher in their construction” ( Heaton 2004:104 ).

There are many aspects of being reflexive. First, there is the simple fact that we are human beings with the limitations that come with that condition. We have likes and dislikes, biases, blind spots, preferences, and so on. If we do not take these into account, they can prevent us from being the best researcher we can be. Being reflective means, first and foremost, trying as best as possible to bracket out elements of our own character and understanding that get in the way. It is important to note that bias (in this context, at least) is not inherently wrong. It just is. Unavoidable. But by noting it, we can minimize its impact or, in some cases, help explain more clearly what it is we see or why it is that we are asking the questions we are asking. For example, I might want to communicate to my audience that I grew up poor and that I have a lot of sympathy and concern for first-generation college students as a result. This “bias” of mine motivates me to do the work I do, even as I try to ensure that it does not blind me to things I find out in the course of my research. [1]

A second aspect of being reflexive is being aware that you yourself are part of the research when you are conducting qualitative research. This is particularly true when conducting interviews, observing interactions, or participating in activities. You have a body, and it will be “read” by those in the field. You will be perceived as an insider or an outsider, as a friend or foe, as empathetic or hostile. Some of this will be wrong. People will prejudge you based on the color of your skin, your presented gender, the accent of your language. People will classify you based on the clothes you wear, and they will be more open to you if you remind them of a friendly aunt or uncle and more reserved if you remind them of someone they don’t like. This is all natural and inevitable. Your research will suffer if you do not take this into account, if you do not reflect upon how you are being read and how this might be influencing what people tell you or what they are willing to do in front of you. The flip side of this problem is that your particular body and presence will open some doors barred to other researchers. Finding sites and contexts where your presented self is a benefit rather than a burden is an important part of your individual research career. Be honest with yourself about this, and you will be more successful as a qualitative researcher. Learn to leverage yourself in your research.

The third aspect of being reflexive is related to how we communicate our work to others. Being honest with our position, as I am about my own social background and its potential impact on what I study or about how I leveraged my own position to get people to open up to me, helps our audiences evaluate what we have found. Maybe I haven’t entirely eliminated my biases or weaknesses, but by telling my audience who I am and where I potentially stand, they can take account of those biases and weaknesses in their reading of my findings. Letting them know that I wore pink when talking with older men because that made them more likely to be kind to me (a strategy acknowledged by Posselt [ 2016 ]) helps them understand the interview context. In other words, my research becomes more reliable when my own social position and the strategies I used are communicated.

Some people think being reflective is just another form of narcissistic navel-gazing. “The study is not about you!” they might cry. True, to some degree—but that also misses the point. All studies on the social world are inevitably about us as well because we are part of that social world. It is actually more dangerous to pretend that we are neutral observers, outside what we are observing. Pierre Bourdieu makes this point several times, and I think it is worth quoting him here: “The idea of a neutral science is fiction, an interested fiction which enables its authors to present a version of the dominant representation of the social world, naturalized and euphemized into a particularly misrecognizable and symbolically, therefore, particularly effective form, and to call it scientific” (quoted in Lemert 1981:278 ).

Bourdieu ( 1984 ) argues that reflective analysis is “not an epistemological scruple” but rather “an indispensable pre-condition of scientific knowledge of the object” ( 92 ). It would be narcissistic to present findings without reflection, as that would give much more weight to any findings or insights that emerge than is due.

The critics are right about one thing, however. Putting oneself at the center of the research is also inappropriate. [2] The focus should be on what is being researched, and the reflexivity is there to advance the study, not to push it aside. This issue has emerged at times when researchers from dominant social positions reflect upon their social locations vis-à-vis study participants from marginalized locations. A researcher who studies how low-income women of color experience unemployment might need to address her White, upper-class, fully employed social location, but not at the cost of crowding out the stories, lived experiences, and understandings of the women she has interviewed. This can sometimes be a delicate balance, and not everyone will agree that a person has walked it correctly.

Examples of Reflexivity in Practice

Most qualitative researchers include a positionality statement in any “methods section” of their publications. This allows readers to understand the location of the researcher, which is often helpful for gauging reliability . Many journals now require brief positionality statements as well. Here are a few examples of such statements.

The first is from an ethnographic study of elite golfers. Ceron-Anaya ( 2017 ) writes about his class, race, and gender and how these aspects of his identity and social location affected his interactions with research participants:

My own class origins, situated near the intersection between the middle and the lower-middle class, hindered cooperation in some cases. For example, the amiable interaction with one club member changed toward the end of the interview when he realized that I commonly moved about in the city by public transportation (which is a strong class indicator). He was not rude but stopped elaborating on the answers as he had been doing up to that point.…Bodily confidence is a privilege of the privileged. My subordinate position, vis-à-vis golfers, was ameliorated by my possession of cultural capital, objectified in my status of researcher/student in a western university. However, my cultural capital dwindled in its value at the invisible but firm boundary between the upper-middle and the upper class. The few contacts I made with members of the upper class produced no connections with other members of the same group, illustrating how the research process is also inserted in the symbolic and material dynamics that shape the field. ( 288 )

What did you learn from Ceron-Anaya’s reflection? If he hadn’t told you about his background, would this have made a difference in reading about elite golfers? Would the findings be different had Ceron-Anaya driven up to the club in a limousine? Is it helpful to know he came by bus?

The second example is from a study on first-generation college students. Hinz ( 2016 ) discusses both differences and similarities between herself and those she interviewed and how both could have affected the study:

I endeavored to avoid researcher bias by allowing the data to speak for itself, but my own habitus as a White, female, middle-class second-generation college student with a few years of association with Selective State [elite university] may have influenced my interpretation. Being a Selective State student at the time of the interviews provided a familiarity with the environment in which the participants were living, and an ease of communication facilitated by a shared institutional culture. And yet, not being a first-gen myself, it seemed as if I were standing on the periphery of their experience, looking in. ( 289–290 )

Note that Hinz cannot change who she is, nor should she. Being aware (reflective) that she may “stand on the periphery” of the experience of those she interviews has probably helped her listen more closely rather than assume she understands what is really going on. Do you find her more reliable given this?

These statements can be quite long, especially when found in methodological appendixes in books rather than short statements in articles. This last lengthy example comes from my own work. I try to place myself, explaining the motivations for the research I conducted at small liberal arts colleges:

I began this project out of a deep curiosity about how college graduates today were faring in an increasingly debt-ridden and unequal labor market. I was working at a small liberal arts college when I began thinking about this project and was poised to take a job at another one. During my interview for the new job, I was told that I was a good fit, because I had attended Barnard College, so I knew what the point of a liberal arts college was. I did. A small liberal arts college was a magical place. You could study anything you wanted, for no reason at all, simply for the love of it. And people would like you for it. You were surrounded by readers, by people who liked to dress up in costume and recite Shakespeare, by people who would talk deep into the night about the meaning of life or whether “beauty” existed out there, in nature, or was simply a projection of our own circumstances. My own experience at Barnard had been somewhat like that. I studied Ancient Greek and Latin, wrote an undergraduate thesis on the legal standing of Vestal Virgins in Ancient Rome, and took frequent subway rides to the Cloisters, the medieval annex of the Metropolitan Museum of Art, where I sketched the courtyard and stared at unicorn tapestries. But I also worked full-time, as a waitress at a series of hectic and demanding restaurants around the city, as a security guard for the dorm, as a babysitter for some pretty privileged professors who lived in doorman buildings along Riverside Park, and at the library (the best job by far). I also constantly worried I would not be able to finish my degree, as every year I was unsure how I would come up with the money to pay for costs of college above and beyond the tuition (which, happily, was covered by the college given my family’s low income). Indeed, the primary reason I studied the Classics was because all the books were freely available in the library. There are no modern textbooks—you just find a copy of the Iliad. There are a lot of those in a city like New York. Due to my fears, I pushed to graduate one year early, taking a degree in “Ancient Studies” instead of “Classics,” which could have led on to graduate training. From there, I went to law school, which seemed like a safe choice. I do not remember ever having a conversation with anyone about how to find a job or what kinds of job one could do with a degree in Ancient Studies. I had little to no social networks, as I had spent my time studying and working. And I was very lucky, because I graduated with almost zero debt. For years, until that job interview, I hadn’t really thought my Barnard experience had been that great or unusual. But now it was directly helping me get a job, about fifteen years after graduation. And it probably had made me a better person, whatever that means. Had I graduated with debt, however, I am not so sure that it would have been worth it. Was it, on balance, a real opportunity and benefit for poor students like me? Even now? I had a hunch of what I might find if I looked: small liberal arts colleges were unique places of opportunity for low-income first-generation working-class students who somehow managed to find and get in to one of them (no easy task). I thought that, because of their ethos, their smallness, the fact that one could not hide from professors, these colleges would do a fair job equalizing opportunities and experiences for all their students. I wanted to tell this story. But that is not the story that I found, or not entirely. While everyone benefits from the kind of education a small liberal arts college can offer, because students begin and continue so differently burdened and privileged, the advantages of the already-advantaged are amplified, potentially increasing rather than decreasing initial inequalities. That is not really a surprising story, but it is an important one to tell and to remember. Education doesn’t reduce inequality. Going to a good college doesn’t level the playing field for low-income, first-generation, working-class students. But perhaps it can help them write a book about that. ( Hurst 2019:259–261 )

What do you think? Did you learn something about the author that would help you, as a reader, understand the reasons and context for the study? Would you trust the researcher? If you said yes, why?

How to Do It

How does one become a reflective researcher? Practice! Nearly every great qualitative researcher maintains a reflexive journal (there are exceptions that prove the rule), a type of diary where they record their thinking on the research process itself. This might include writing about the research design (chapter 2), plotting out strategies for sample selection (chapter 6), or talking through what one believes can be known (chapter 3). During analysis, this journal is a place to record ideas and insights and pose questions for further reflection or follow-up studies. This journal should be highly personal. It is a place to record fears, concerns, and hopes as well. Why are you studying what you are studying? What is really motivating you? Being clear with yourself and being able to put it down in words are invaluable to the research process.

Today, there are many blogs out there on writing reflective journals, with helpful suggestions and examples. Although you may want to take a look at some of these, the form of your own journal will probably be unique. This is you, the researcher, on the page. Each of us looks different. Use the journal to interrogate your decisions and clarify your intent. If you find something during the study of note, you might want to ask yourself what led you to note that. Why do you think this “thing” is a “thing”? What about your own position, background, or researcher status that makes you take note? And asking yourself this question might lead you to think about what you did not notice. Other questions to ask yourself include the following: How do I know “that thing” I noted? So what? What does it mean? What are the implications? Who cares about this and why? Remember that doing qualitative research well is recursive , meaning that we may begin with a research design, but the steps of doing the research often loop back to the beginning. By keeping a reflective journal, you allow yourself to circle back to the beginning, to make changes to the study to keep it in line with what you are really interested in knowing.

One might also consider designing research that includes multiple investigators, particularly those who may not share your preconceptions about the study. For example, if you are studying conservative students on campus, and you yourself thoroughly identify as liberal, you might want to pair up with a researcher interested in the topic who grew up in a conservative household. If you are studying racial regimes, consider creating a racially diverse team of researchers. Or you might include in your research design a component of participatory research wherein members of the community of interest become coresearchers. Even if you can’t form a research team, you can reach out to others for feedback as you move along. Doing research can be a lonely enterprise, so finding people who will listen to you and nudge you to clarify your thinking where necessary or move you to consider an aspect you have missed is invaluable.

Finally, make it a regular part of your practice to write a paragraph reporting your perspectives, positions, values, and beliefs and how these may have influenced the research. This paragraph may be included in publications upon request.

Internal Validity

Being reflexive can help ensure that our studies are internally valid. All research must be valid to be helpful. We say a study’s findings are externally valid when they are equally true of other times, places, people. Quantitative researchers often spend a lot of time grappling with external validity , as they are often trying to demonstrate that their sample is representative of a larger population. Although we do not do that in qualitative research, we do sometimes make claims that the processes and mechanisms we uncover here, in this particular setting, are likely to be equally active in that setting over there, although there may be (will be!) contextual differences as well. Internal validity is more peculiar to qualitative research. Is your finding an accurate representation of what you are studying? Are you describing the people you are observing or interviewing as they really are? This is internal validity , and you should be able to see how this connects with the requirement of reflexivity. To the extent that you leave unexamined your own biases or preconceptions, you will fail at accurately representing those people and processes you study. Remember that “bias” here is not a moral failing in the way we commonly use bias in the nonresearch world but an inevitable product of our being social beings who inhabit social worlds, with all the various complexities surrounding that. Because of things that have happened to you, certain things (concepts, quotes, activities) might jump out at you as being particularly important. Being reflexive allows you to take a step back and grapple with the larger picture, reflecting on why you might be seeing X (which is present) but also missing Y (which is also present). It also allows you to consider what effect/impact your presence has on what you are observing or being told and to make any adjustments necessary to minimize your impact or, at the very least, to be aware of these effects and talk about them in any descriptions or presentations you make. There are other ways of ensuring internal validity (e.g., member checking , triangulation ), but being reflective is an essential component.

Advanced: Bourdieu on Reflexivity

One researcher who really tackled the issue of reflexivity was Pierre Bourdieu. [3] Known in the US primarily as a theorist, Bourdieu was a very capable and thorough researcher, who employed a variety of methods in his wide-ranging studies. Originally trained as an anthropologist, he became uncomfortable with the unreflective “outsider perspective” he was taught to follow. How was he supposed to observe and write about the various customs and rules of the people he was studying if he did not take into account his own supposedly neutral position in the observations? And even more interestingly, how could he write about customs and rules as if they were lifted from but outside of the understandings and practice of the people following them? When you say “God bless you” to someone who sneezes, are you really following a social custom that requires the prevention of illness through some performative verbal ritual of protection, or are you saying words out of reflex and habit? Bourdieu wondered what it meant that anthropologists were so ready to attribute meaning to actions that, to those performing them, were probably unconsidered. This caused him to ponder those deep epistemological questions about the possibilities of knowledge, particularly what we can know and truly understand about others. Throughout the following decades, as he developed his theories about the social world out of the deep and various studies he engaged in, he thought about the relationship between the researcher and the researched. He came to several conclusions about this relationship.

First, he argued that researchers needed to be reflective about their position vis-à-vis the object of study. The very fact that there is a subject and an object needs to be accounted for. Too often, he argued, the researcher forgets that part of the relationship, bracketing out the researcher entirely, as if what is being observed or studied exists entirely independently of the study. This can lead to false reports, as in the case where a blind man grasps the trunk of the elephant and claims the elephant is cylindrical, not having recognized how his own limitations of sight reduced the elephant to only one of its parts.

As mentioned previously, Bourdieu ( 1984 ) argued that “reflective analysis of the tools of analysis is not an epistemological scruple but an indispensable precondition of scientific knowledge of the object” ( 92 ). It is not that researchers are inherently biased—they are—but rather that the relationship between researcher and researched is an unnatural one that needs to be accounted for in the analysis. True and total objectivity is impossible, as researchers are human subjects themselves, called to research what interests them (or what interests their supervisors) and also inhabiting the social world. The solution to this problem is to be reflective and to account for these aspects in the analysis itself. Here is how Bourdieu explains this charge:

To adopt the viewpoint of REFLEXIVITY is not to renounce objectivity but to question the privilege of the knowing subject, which the antigenetic vision arbitrarily frees, as purely noetic, from the labor of objectification. To adopt this viewpoint is to strive to account for the empirical “subject” in the very terms of the objectivity constructed by the scientific subject (notably by situating it in a determined place in social space-time) and thereby to give oneself awareness and (possible) mastery of the constraints which may be exercised on the scientific subject via all the ties which attach it to the empirical “subject,” to its interests, motives, assumptions, beliefs, its doxa, and which it must break in order to constitute itself . ( 1996:207 ; emphases added)

Reflexivity, for Bourdieu, was a trained state of mind for the researcher, essential for proper knowledge production. Let’s use a story from Hans Christian Andersen to illustrate this point. If you remember this story from your childhood, it goes something like this: Two con artists show up in a town in which its chief monarch spends a lot of money on expensive clothes and splashy displays. They sense an opportunity to make some money out of this situation and pretend they are talented weavers from afar. They tell the vain emperor that they can make the most magnificent clothes anyone has ever seen (or not seen, as the case may be!). Because what they really do is “pretend” to weave and sew and hand the emperor thin air, which they then help him to put on in an elaborate joke. They tell him that only the very stupid and lowborn will be unable to see the magnificent clothes. Embarrassed that he can’t see them either, he pretends he can. Everyone pretends they can see clothes, when really the emperor walks around in his bare nakedness. As he parades through town, people redden and bow their heads, but no one says a thing. That is, until one child looks at the naked emperor and starts to laugh. His laughter breaks the spell, and everyone realizes the “naked truth.”

Now let us add a new thread to this story. The boy did not laugh. Years go by, and the emperor continues to wear his new clothes. At the start of every day, his aides carefully drape the “new clothes” around his naked body. Decades go by, and this is all “normal.” People don’t even see a naked emperor but a fully robed leader of the free world. A researcher, raised in this milieu, visits the palace to observe court habits. She observes the aides draping the emperor. She describes the care they take in doing so. She nowhere reports that the clothes are nonexistent because she herself has been trained to see them . She thus misses a very important fact—that there are no clothes at all! Note that it is not her individual “biases” that are getting in the way but her unreflective acceptance of the reality she inhabits that binds her to report things less accurately than she might.

In his later years, Bourdieu turned his attention to science itself and argued that the promise of modern science required reflectivity among scientists. We need to develop our reflexivity as we develop other muscles, through constant practice. Bourdieu ( 2004 ) urged researchers “to convert reflexivity into a disposition, constitutive of their scientific habitus, a reflexivity reflex , capable of acting not ex poste , on the opus operatum , but a priori , on the modus operandi ” ( 89 ). In other words, we need to build into our research design an appreciation of the relationship between researcher and researched.

To do science properly is to be reflective, to be aware of the social waters in which one swims and to turn one’s researching gaze on oneself and one’s researcher position as well as on the object of the research. Above all, doing science properly requires one to acknowledge science as a social process. We are not omniscient gods, lurking above the humans we observe and talk to. We are human too.

Further Readings

Barry, Christine A., Nicky Britten, Nick Barbar, Colin Bradley, and Fiona Stevenson. 1999. “Using Reflexivity to Optimize Teamwork in Qualitative Research.”  Qualitative Health Research  9(1):26–44. The coauthors explore what it means to be reflexive in a collaborative research project and use their own project investigating doctor-patient communication about prescribing as an example.

Hsiung, Ping-Chun. 2008. “Teaching Reflexivity in Qualitative Interviewing.” Teaching Sociology 36(3):211–226. As the title suggests, this article is about teaching reflexivity to those conducting interviews.

Kenway, Jane, and Julie McLeod. 2004. “Bourdieu’s Reflexive Sociology and ‘Spaces of Points of View’: Whose Reflexivity, Which Perspective?” British Journal of Sociology of Education 25(4):525–544. For a more nuanced understanding of Bourdieu’s meaning of reflexivity and how this contrasts with other understandings of the term in sociology.

Kleinsasser, Audrey M. 2000. “Researchers, Reflexivity, and Good Data: Writing to Unlearn.” Theory into Practice 39(3):155–162. Argues for the necessity of reflexivity for the production of “good data” in qualitative research.

Linabary, Jasmine R., and Stephanie A. Hamel. 2017. “Feminist Online Interviewing: Engaging Issues of Power, Resistance and Reflexivity in Practice.” Feminist Review 115:97–113. Proposes “reflexive email interviewing” as a promising method for feminist research.

Rabbidge, Michael. 2017. “Embracing Reflexivity: The Importance of Not Hiding the Mess.” TESOL Quarterly 51(4):961–971. The title here says it all.

Wacquant, Loïc J. D. 1989. “Towards a Reflexive Sociology: A Workshop with Pierre Bourdieu.” Sociological Theory 7(1):26–63. A careful examination of Bourdieu’s notion of reflexivity by one of his most earnest disciples.

• Someone might ask me if I have truly been able to “stand” in the shoes of more privileged students and if I might be overlooking similarities among college students because of my “biased” standpoint. These are questions I ask myself all the time. They have even motivated me to conduct my latest research on college students in general so that I might check my observations that working-class college students are uniquely burdened ( Hurst 2019 ). One of the things I did find was that middle-class students, relative to upper-class students, are also relatively disadvantaged and sometimes experience (feel) that disadvantage. ↵
• Unless, of course, one is engaged in autoethnography! Even in that case, however, the point of the study should probably be about a larger phenomenon or experience that can be understood more deeply through insights that emerge in the study of the particular self, not really a study about that self. ↵
• I mentioned Pierre Bourdieu earlier in the chapter. For those who want to know more about his work, I’ve included this advanced section. Undergraduates should feel free to skip over. ↵

The practice of being conscious of and reflective upon one’s own social location and presence when conducting research.  Because qualitative research often requires interaction with live humans, failing to take into account how one’s presence and prior expectations and social location affect the data collected and how analyzed may limit the reliability of the findings.  This remains true even when dealing with historical archives and other content.  Who we are matters when asking questions about how people experience the world because we, too, are a part of that world.

The branch of philosophy concerned with knowledge.  For researchers, it is important to recognize and adopt one of the many distinguishing epistemological perspectives as part of our understanding of what questions research can address or fully answer.  See, e.g., constructivism , subjectivism, and  objectivism .

A statement created by the researcher declaring their own social position (often in terms of race, class, gender) and social location (e.g., junior scholar or tenured professor) vis-à-vis the research subjects or focus of study, with the goal of explaining and thereby limiting any potential biases or impacts of such position on data analyses, findings, or other research results.  See also reflexivity .

Reliability is most often explained as consistency and stability in a research instrument, as in a weight scale, deemed reliable if predictable and accurate (e.g., when you put a five-pound bag of rice on the scale on Tuesday, it shows the same weight as when you put the same unopened bag on the scale Wednesday).  Qualitative researchers don’t measure things in the same way, but we still must ensure that our research is reliable, meaning that if others were to conduct the same interview using our interview guide, they would get similar answers.  This is one reason that reflexivity is so important to the reliability of qualitative research – we have to take steps to ensure that our own presence does not “tip the scales” in one direction or another or that, when it does, we can recognize that and make corrections.  Qualitative researchers use a variety of tools to help ensure reliability, from intercoder reliability to triangulation to reflexivity.

In mostly quantitative research, validity refers to “the extent to which an empirical measure adequately reflects the real meaning of the concept under consideration” ( Babbie 1990 ). For qualitative research purposes, practically speaking, a study or finding is valid when we are measuring or addressing what we think we are measuring or addressing.  We want our representations to be accurate, as they really are, and not an artifact of our imaginations or a result of unreflected bias in our thinking.

A method of ensuring trustworthiness where the researcher shares aspects of written analysis (codes, summaries, drafts) with participants before the final write-up of the study to elicit reactions and/or corrections.   Note that the researcher has the final authority on the interpretation of the data collected; this is not a way of substituting the researcher’s analytical responsibilities.  See also peer debriefing . 

The process of strengthening a study by employing multiple methods (most often, used in combining various qualitative methods of data collection and analysis).  This is sometimes referred to as data triangulation or methodological triangulation (in contrast to investigator triangulation or theory triangulation).  Contrast mixed methods .

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.