scholarly articles about qualitative research

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• > BJPsych Bulletin
• > The Psychiatrist
• > Volume 37 Issue 6
• > Qualitative research: its value and applicability

Article contents

What questions are best answered using qualitative research, countering some misconceptions, in conclusion, qualitative research: its value and applicability.

Published online by Cambridge University Press:  02 January 2018

Qualitative research has a rich tradition in the study of human social behaviour and cultures. Its general aim is to develop concepts which help us to understand social phenomena in, wherever possible, natural rather than experimental settings, to gain an understanding of the experiences, perceptions and/or behaviours of individuals, and the meanings attached to them. The effective application of qualitative methods to other disciplines, including clinical, health service and education research, has a rapidly expanding and robust evidence base. Qualitative approaches have particular potential in psychiatry research, singularly and in combination with quantitative methods. This article outlines the nature and potential application of qualitative research as well as attempting to counter a number of misconceptions.

Qualitative research has a rich tradition in the social sciences. Since the late 19th century, researchers interested in studying the social behaviour and cultures of humankind have perceived limitations in trying to explain the phenomena they encounter in purely quantifiable, measurable terms. Anthropology, in its social and cultural forms, was one of the foremost disciplines in developing what would later be termed a qualitative approach, founded as it was on ethnographic studies which sought an understanding of the culture of people from other societies, often hitherto unknown and far removed in geography. Reference Bernard 1 Early researchers would spend extended periods of time living in societies, observing, noting and photographing the minutia of daily life, with the most committed often learning the language of peoples they observed, in the hope of gaining greater acceptance by them and a more detailed understanding of the cultural norms at play. All academic disciplines concerned with human and social behaviour, including anthropology, sociology and psychology, now make extensive use of qualitative research methods whose systematic application was first developed by these colonial-era social scientists.

Their methods, involving observation, participation and discussion of the individuals and groups being studied, as well as reading related textual and visual media and artefacts, form the bedrock of all qualitative social scientific inquiry. The general aim of qualitative research is thus to develop concepts which help us to understand social phenomena in, wherever possible, natural rather than experimental settings, to gain an understanding of the experiences, perceptions and/or behaviours of those studied, and the meanings attached to them. Reference Bryman 2 Researchers interested in finding out why people behave the way they do; how people are affected by events, how attitudes and opinions are formed; how and why cultures and practices have developed in the way they have, might well consider qualitative methods to answer their questions.

It is fair to say that clinical and health-related research is still dominated by quantitative methods, of which the randomised controlled trial, focused on hypothesis-testing through experiment controlled by randomisation, is perhaps the quintessential method. Qualitative approaches may seem obscure to the uninitiated when directly compared with the experimental, quantitative methods used in clinical research. There is increasing recognition among researchers in these fields, however, that qualitative methods such as observation, in-depth interviews, focus groups, consensus methods, case studies and the interpretation of texts can be more effective than quantitative approaches in exploring complex phenomena and as such are valuable additions to the methodological armoury available to them. Reference Denzin and Lincoln 3

In considering what kind of research questions are best answered using a qualitative approach, it is important to remember that, first and foremost, unlike quantitative research, inquiry conducted in the qualitative tradition seeks to answer the question ‘What?’ as opposed to ‘How often?’. Qualitative methods are designed to reveal what is going on by describing and interpreting phenomena; they do not attempt to measure how often an event or association occurs. Research conducted using qualitative methods is normally done with an intent to preserve the inherent complexities of human behaviour as opposed to assuming a reductive view of the subject in order to count and measure the occurrence of phenomena. Qualitative research normally takes an inductive approach, moving from observation to hypothesis rather than hypothesis-testing or deduction, although the latter is perfectly possible.

When conducting research in this tradition, the researcher should, if possible, avoid separating the stages of study design, data collection and analysis, but instead weave backwards and forwards between the raw data and the process of conceptualisation, thereby making sense of the data throughout the period of data collection. Although there are inevitable tensions among methodologists concerned with qualitative practice, there is broad consensus that a priori categories and concepts reflecting a researcher's own preconceptions should not be imposed on the process of data collection and analysis. The emphasis should be on capturing and interpreting research participants' true perceptions and/or behaviours.

Using combined approaches

The polarity between qualitative and quantitative research has been largely assuaged, to the benefit of all disciplines which now recognise the value, and compatibility, of both approaches. Indeed, there can be particular value in using quantitative methods in combination with qualitative methods. Reference Barbour 4 In the exploratory stages of a research project, qualitative methodology can be used to clarify or refine the research question, to aid conceptualisation and to generate a hypothesis. It can also help to identify the correct variables to be measured, as researchers have been known to measure before they fully understand the underlying issues pertaining to a study and, as a consequence, may not always target the most appropriate factors. Qualitative work can be valuable in the interpretation, qualification or illumination of quantitative research findings. This is particularly helpful when focusing on anomalous results, as they test the main hypothesis formulated. Qualitative methods can also be used in combination with quantitative methods to triangulate findings and support the validation process, for example, where three or more methods are used and the results compared for similarity (e.g. a survey, interviews and a period of observation in situ ).

‘There is little value in qualitative research findings because we cannot generalise from them’

Generalisability refers to the extent that the account can be applied to other people, times and settings other than those actually studied. A common criticism of qualitative research is that the results of a study are rarely, if ever, generalisable to a larger population because the sample groups are small and the participants are not chosen randomly. Such criticism fails to recognise the distinctiveness of qualitative research where sampling is concerned. In quantitative research, the intent is to secure a large random sample that is representative of the general population, with the purpose of eliminating individual variations, focusing on generalisations and thereby allowing for statistical inference of results that are applicable across an entire population. In qualitative research, generalisability is based on the assumption that it is valuable to begin to understand similar situations or people, rather than being representative of the target population. Qualitative research is rarely based on the use of random samples, so the kinds of reference to wider populations made on the basis of surveys cannot be used in qualitative analysis.

Qualitative researchers utilise purposive sampling, whereby research participants are selected deliberately to test a particular theoretical premise. The purpose of sampling here is not to identify a random subgroup of the general population from which statistically significant results can be extrapolated, but rather to identify, in a systematic way, individuals that possess relevant characteristics for the question being considered. Reference Strauss and Corbin 5 The researchers must instead ensure that any reference to people and settings beyond those in the study are justified, which is normally achieved by defining, in detail, the type of settings and people to whom the explanation or theory applies based on the identification of similar settings and people in the study. The intent is to permit a detailed examination of the phenomenon, resulting in a text-rich interpretation that can deepen our understanding and produce a plausible explanation of the phenomenon under study. The results are not intended to be statistically generalisable, although any theory they generate might well be.

‘Qualitative research cannot really claim reliability or validity’

In quantitative research, reliability is the extent to which different observers, or the same observers on different occasions, make the same observations or collect the same data about the same object of study. The changing nature of social phenomena scrutinised by qualitative researchers inevitably makes the possibility of the same kind of reliability problematic in their work. A number of alternative concepts to reliability have been developed by qualitative methodologists, however, known collectively as forms of trustworthiness. Reference Guba 6

One way to demonstrate trustworthiness is to present detailed evidence in the form of quotations from interviews and field notes, along with thick textual descriptions of episodes, events and settings. To be trustworthy, qualitative analysis should also be auditable, making it possible to retrace the steps leading to a certain interpretation or theory to check that no alternatives were left unexamined and that no researcher biases had any avoidable influence on the results. Usually, this involves the recording of information about who did what with the data and in what order so that the origin of interpretations can be retraced.

In general, within the research traditions of the natural sciences, findings are validated by their repeated replication, and if a second investigator cannot replicate the findings when they repeat the experiment then the original results are questioned. If no one else can replicate the original results then they are rejected as fatally flawed and therefore invalid. Natural scientists have developed a broad spectrum of procedures and study designs to ensure that experiments are dependable and that replication is possible. In the social sciences, particularly when using qualitative research methods, replication is rarely possible given that, when observed or questioned again, respondents will almost never say or do precisely the same things. Whether results have been successfully replicated is always a matter of interpretation. There are, however, procedures that, if followed, can significantly reduce the possibility of producing analyses that are partial or biased. Reference Altheide, Johnson, Denzin and Lincoln 7

Triangulation is one way of doing this. It essentially means combining multiple views, approaches or methods in an investigation to obtain a more accurate interpretation of the phenomena, thereby creating an analysis of greater depth and richness. As the process of analysing qualitative data normally involves some form of coding, whereby data are broken down into units of analysis, constant comparison can also be used. Constant comparison involves checking the consistency and accuracy of interpretations and especially the application of codes by constantly comparing one interpretation or code with others both of a similar sort and in other cases and settings. This in effect is a form of interrater reliability, involving multiple researchers or teams in the coding process so that it is possible to compare how they have coded the same passages and where there are areas of agreement and disagreement so that consensus can be reached about a code's definition, improving consistency and rigour. It is also good practice in qualitative analysis to look constantly for outliers – results that are out of line with your main findings or any which directly contradict what your explanations might predict, re-examining the data to try to find a way of explaining the atypical finding to produce a modified and more complex theory and explanation.

Qualitative research has been established for many decades in the social sciences and encompasses a valuable set of methodological tools for data collection, analysis and interpretation. Their effective application to other disciplines, including clinical, health service and education research, has a rapidly expanding and robust evidence base. The use of qualitative approaches to research in psychiatry has particular potential, singularly and in combination with quantitative methods. Reference Crabb and Chur-Hansen 8 When devising research questions in the specialty, careful thought should always be given to the most appropriate methodology, and consideration given to the great depth and richness of empirical evidence which a robust qualitative approach is able to provide.

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• Volume 37, Issue 6
• Steven J. Agius (a1)
• DOI: https://doi.org/10.1192/pb.bp.113.042770

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• Open access
• Published: 27 May 2020

How to use and assess qualitative research methods

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

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

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

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

What is qualitative research?

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

Why conduct qualitative research?

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

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

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

How to conduct qualitative research?

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

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

How to report qualitative research?

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

How to combine qualitative with quantitative research?

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

Three common mixed methods designs

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

How to assess qualitative research?

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

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

Reflexivity

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

Sampling and saturation

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

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

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

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

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

Member checking

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

Stakeholder involvement

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

How not to assess qualitative research

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

Protocol adherence

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

Sample size

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

Randomisation

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

Interrater reliability, variability and other “objectivity checks”

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

Not being quantitative research

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

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

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Abbreviations

Endovascular treatment

Randomised Controlled Trial

Standard Operating Procedure

Standards for Reporting Qualitative Research

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

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Article Contents

Introduction, when to use qualitative research, how to judge qualitative research, conclusions, authors' roles, conflict of interest.

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Qualitative research methods: when to use them and how to judge them

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K. Hammarberg, M. Kirkman, S. de Lacey, Qualitative research methods: when to use them and how to judge them, Human Reproduction , Volume 31, Issue 3, March 2016, Pages 498–501, https://doi.org/10.1093/humrep/dev334

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In March 2015, an impressive set of guidelines for best practice on how to incorporate psychosocial care in routine infertility care was published by the ESHRE Psychology and Counselling Guideline Development Group ( ESHRE Psychology and Counselling Guideline Development Group, 2015 ). The authors report that the guidelines are based on a comprehensive review of the literature and we congratulate them on their meticulous compilation of evidence into a clinically useful document. However, when we read the methodology section, we were baffled and disappointed to find that evidence from research using qualitative methods was not included in the formulation of the guidelines. Despite stating that ‘qualitative research has significant value to assess the lived experience of infertility and fertility treatment’, the group excluded this body of evidence because qualitative research is ‘not generally hypothesis-driven and not objective/neutral, as the researcher puts him/herself in the position of the participant to understand how the world is from the person's perspective’.

Qualitative and quantitative research methods are often juxtaposed as representing two different world views. In quantitative circles, qualitative research is commonly viewed with suspicion and considered lightweight because it involves small samples which may not be representative of the broader population, it is seen as not objective, and the results are assessed as biased by the researchers' own experiences or opinions. In qualitative circles, quantitative research can be dismissed as over-simplifying individual experience in the cause of generalisation, failing to acknowledge researcher biases and expectations in research design, and requiring guesswork to understand the human meaning of aggregate data.

As social scientists who investigate psychosocial aspects of human reproduction, we use qualitative and quantitative methods, separately or together, depending on the research question. The crucial part is to know when to use what method.

The peer-review process is a pillar of scientific publishing. One of the important roles of reviewers is to assess the scientific rigour of the studies from which authors draw their conclusions. If rigour is lacking, the paper should not be published. As with research using quantitative methods, research using qualitative methods is home to the good, the bad and the ugly. It is essential that reviewers know the difference. Rejection letters are hard to take but more often than not they are based on legitimate critique. However, from time to time it is obvious that the reviewer has little grasp of what constitutes rigour or quality in qualitative research. The first author (K.H.) recently submitted a paper that reported findings from a qualitative study about fertility-related knowledge and information-seeking behaviour among people of reproductive age. In the rejection letter one of the reviewers (not from Human Reproduction ) lamented, ‘Even for a qualitative study, I would expect that some form of confidence interval and paired t-tables analysis, etc. be used to analyse the significance of results'. This comment reveals the reviewer's inappropriate application to qualitative research of criteria relevant only to quantitative research.

In this commentary, we give illustrative examples of questions most appropriately answered using qualitative methods and provide general advice about how to appraise the scientific rigour of qualitative studies. We hope this will help the journal's reviewers and readers appreciate the legitimate place of qualitative research and ensure we do not throw the baby out with the bath water by excluding or rejecting papers simply because they report the results of qualitative studies.

In psychosocial research, ‘quantitative’ research methods are appropriate when ‘factual’ data are required to answer the research question; when general or probability information is sought on opinions, attitudes, views, beliefs or preferences; when variables can be isolated and defined; when variables can be linked to form hypotheses before data collection; and when the question or problem is known, clear and unambiguous. Quantitative methods can reveal, for example, what percentage of the population supports assisted conception, their distribution by age, marital status, residential area and so on, as well as changes from one survey to the next ( Kovacs et al. , 2012 ); the number of donors and donor siblings located by parents of donor-conceived children ( Freeman et al. , 2009 ); and the relationship between the attitude of donor-conceived people to learning of their donor insemination conception and their family ‘type’ (one or two parents, lesbian or heterosexual parents; Beeson et al. , 2011 ).

In contrast, ‘qualitative’ methods are used to answer questions about experience, meaning and perspective, most often from the standpoint of the participant. These data are usually not amenable to counting or measuring. Qualitative research techniques include ‘small-group discussions’ for investigating beliefs, attitudes and concepts of normative behaviour; ‘semi-structured interviews’, to seek views on a focused topic or, with key informants, for background information or an institutional perspective; ‘in-depth interviews’ to understand a condition, experience, or event from a personal perspective; and ‘analysis of texts and documents’, such as government reports, media articles, websites or diaries, to learn about distributed or private knowledge.

Qualitative methods have been used to reveal, for example, potential problems in implementing a proposed trial of elective single embryo transfer, where small-group discussions enabled staff to explain their own resistance, leading to an amended approach ( Porter and Bhattacharya, 2005 ). Small-group discussions among assisted reproductive technology (ART) counsellors were used to investigate how the welfare principle is interpreted and practised by health professionals who must apply it in ART ( de Lacey et al. , 2015 ). When legislative change meant that gamete donors could seek identifying details of people conceived from their gametes, parents needed advice on how best to tell their children. Small-group discussions were convened to ask adolescents (not known to be donor-conceived) to reflect on how they would prefer to be told ( Kirkman et al. , 2007 ).

When a population cannot be identified, such as anonymous sperm donors from the 1980s, a qualitative approach with wide publicity can reach people who do not usually volunteer for research and reveal (for example) their attitudes to proposed legislation to remove anonymity with retrospective effect ( Hammarberg et al. , 2014 ). When researchers invite people to talk about their reflections on experience, they can sometimes learn more than they set out to discover. In describing their responses to proposed legislative change, participants also talked about people conceived as a result of their donations, demonstrating various constructions and expectations of relationships ( Kirkman et al. , 2014 ).

Interviews with parents in lesbian-parented families generated insight into the diverse meanings of the sperm donor in the creation and life of the family ( Wyverkens et al. , 2014 ). Oral and written interviews also revealed the embarrassment and ambivalence surrounding sperm donors evident in participants in donor-assisted conception ( Kirkman, 2004 ). The way in which parents conceptualise unused embryos and why they discard rather than donate was explored and understood via in-depth interviews, showing how and why the meaning of those embryos changed with parenthood ( de Lacey, 2005 ). In-depth interviews were also used to establish the intricate understanding by embryo donors and recipients of the meaning of embryo donation and the families built as a result ( Goedeke et al. , 2015 ).

It is possible to combine quantitative and qualitative methods, although great care should be taken to ensure that the theory behind each method is compatible and that the methods are being used for appropriate reasons. The two methods can be used sequentially (first a quantitative then a qualitative study or vice versa), where the first approach is used to facilitate the design of the second; they can be used in parallel as different approaches to the same question; or a dominant method may be enriched with a small component of an alternative method (such as qualitative interviews ‘nested’ in a large survey). It is important to note that free text in surveys represents qualitative data but does not constitute qualitative research. Qualitative and quantitative methods may be used together for corroboration (hoping for similar outcomes from both methods), elaboration (using qualitative data to explain or interpret quantitative data, or to demonstrate how the quantitative findings apply in particular cases), complementarity (where the qualitative and quantitative results differ but generate complementary insights) or contradiction (where qualitative and quantitative data lead to different conclusions). Each has its advantages and challenges ( Brannen, 2005 ).

Qualitative research is gaining increased momentum in the clinical setting and carries different criteria for evaluating its rigour or quality. Quantitative studies generally involve the systematic collection of data about a phenomenon, using standardized measures and statistical analysis. In contrast, qualitative studies involve the systematic collection, organization, description and interpretation of textual, verbal or visual data. The particular approach taken determines to a certain extent the criteria used for judging the quality of the report. However, research using qualitative methods can be evaluated ( Dixon-Woods et al. , 2006 ; Young et al. , 2014 ) and there are some generic guidelines for assessing qualitative research ( Kitto et al. , 2008 ).

Although the terms ‘reliability’ and ‘validity’ are contentious among qualitative researchers ( Lincoln and Guba, 1985 ) with some preferring ‘verification’, research integrity and robustness are as important in qualitative studies as they are in other forms of research. It is widely accepted that qualitative research should be ethical, important, intelligibly described, and use appropriate and rigorous methods ( Cohen and Crabtree, 2008 ). In research investigating data that can be counted or measured, replicability is essential. When other kinds of data are gathered in order to answer questions of personal or social meaning, we need to be able to capture real-life experiences, which cannot be identical from one person to the next. Furthermore, meaning is culturally determined and subject to evolutionary change. The way of explaining a phenomenon—such as what it means to use donated gametes—will vary, for example, according to the cultural significance of ‘blood’ or genes, interpretations of marital infidelity and religious constructs of sexual relationships and families. Culture may apply to a country, a community, or other actual or virtual group, and a person may be engaged at various levels of culture. In identifying meaning for members of a particular group, consistency may indeed be found from one research project to another. However, individuals within a cultural group may present different experiences and perceptions or transgress cultural expectations. That does not make them ‘wrong’ or invalidate the research. Rather, it offers insight into diversity and adds a piece to the puzzle to which other researchers also contribute.

In qualitative research the objective stance is obsolete, the researcher is the instrument, and ‘subjects’ become ‘participants’ who may contribute to data interpretation and analysis ( Denzin and Lincoln, 1998 ). Qualitative researchers defend the integrity of their work by different means: trustworthiness, credibility, applicability and consistency are the evaluative criteria ( Leininger, 1994 ).

Trustworthiness

A report of a qualitative study should contain the same robust procedural description as any other study. The purpose of the research, how it was conducted, procedural decisions, and details of data generation and management should be transparent and explicit. A reviewer should be able to follow the progression of events and decisions and understand their logic because there is adequate description, explanation and justification of the methodology and methods ( Kitto et al. , 2008 )

Credibility

Credibility is the criterion for evaluating the truth value or internal validity of qualitative research. A qualitative study is credible when its results, presented with adequate descriptions of context, are recognizable to people who share the experience and those who care for or treat them. As the instrument in qualitative research, the researcher defends its credibility through practices such as reflexivity (reflection on the influence of the researcher on the research), triangulation (where appropriate, answering the research question in several ways, such as through interviews, observation and documentary analysis) and substantial description of the interpretation process; verbatim quotations from the data are supplied to illustrate and support their interpretations ( Sandelowski, 1986 ). Where excerpts of data and interpretations are incongruent, the credibility of the study is in doubt.

Applicability

Applicability, or transferability of the research findings, is the criterion for evaluating external validity. A study is considered to meet the criterion of applicability when its findings can fit into contexts outside the study situation and when clinicians and researchers view the findings as meaningful and applicable in their own experiences.

Larger sample sizes do not produce greater applicability. Depth may be sacrificed to breadth or there may be too much data for adequate analysis. Sample sizes in qualitative research are typically small. The term ‘saturation’ is often used in reference to decisions about sample size in research using qualitative methods. Emerging from grounded theory, where filling theoretical categories is considered essential to the robustness of the developing theory, data saturation has been expanded to describe a situation where data tend towards repetition or where data cease to offer new directions and raise new questions ( Charmaz, 2005 ). However, the legitimacy of saturation as a generic marker of sampling adequacy has been questioned ( O'Reilly and Parker, 2013 ). Caution must be exercised to ensure that a commitment to saturation does not assume an ‘essence’ of an experience in which limited diversity is anticipated; each account is likely to be subtly different and each ‘sample’ will contribute to knowledge without telling the whole story. Increasingly, it is expected that researchers will report the kind of saturation they have applied and their criteria for recognising its achievement; an assessor will need to judge whether the choice is appropriate and consistent with the theoretical context within which the research has been conducted.

Sampling strategies are usually purposive, convenient, theoretical or snowballed. Maximum variation sampling may be used to seek representation of diverse perspectives on the topic. Homogeneous sampling may be used to recruit a group of participants with specified criteria. The threat of bias is irrelevant; participants are recruited and selected specifically because they can illuminate the phenomenon being studied. Rather than being predetermined by statistical power analysis, qualitative study samples are dependent on the nature of the data, the availability of participants and where those data take the investigator. Multiple data collections may also take place to obtain maximum insight into sensitive topics. For instance, the question of how decisions are made for embryo disposition may involve sampling within the patient group as well as from scientists, clinicians, counsellors and clinic administrators.

Consistency

Consistency, or dependability of the results, is the criterion for assessing reliability. This does not mean that the same result would necessarily be found in other contexts but that, given the same data, other researchers would find similar patterns. Researchers often seek maximum variation in the experience of a phenomenon, not only to illuminate it but also to discourage fulfilment of limited researcher expectations (for example, negative cases or instances that do not fit the emerging interpretation or theory should be actively sought and explored). Qualitative researchers sometimes describe the processes by which verification of the theoretical findings by another team member takes place ( Morse and Richards, 2002 ).

Research that uses qualitative methods is not, as it seems sometimes to be represented, the easy option, nor is it a collation of anecdotes. It usually involves a complex theoretical or philosophical framework. Rigorous analysis is conducted without the aid of straightforward mathematical rules. Researchers must demonstrate the validity of their analysis and conclusions, resulting in longer papers and occasional frustration with the word limits of appropriate journals. Nevertheless, we need the different kinds of evidence that is generated by qualitative methods. The experience of health, illness and medical intervention cannot always be counted and measured; researchers need to understand what they mean to individuals and groups. Knowledge gained from qualitative research methods can inform clinical practice, indicate how to support people living with chronic conditions and contribute to community education and awareness about people who are (for example) experiencing infertility or using assisted conception.

Each author drafted a section of the manuscript and the manuscript as a whole was reviewed and revised by all authors in consultation.

No external funding was either sought or obtained for this study.

The authors have no conflicts of interest to declare.

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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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Principal component analysis

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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• Published: 16 May 2022

Meeting ethical challenges with authenticity when engaging patients and families in end-of-life and palliative care research: a qualitative study

• Matthew DeCamp 1 ,
• Ahmed Alasmar 2 ,
• Stacy Fischer 3 &
• Jean S. Kutner 4  

BMC Palliative Care volume  21 , Article number:  74 ( 2022 ) Cite this article

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Delivering high quality, patient- and family-centered care depends upon high quality end-of-life and palliative care (EOLPC) research. Engaging patients and families as advisors, partners, or co-investigators throughout the research lifecycle is widely regarded as critical to ensuring high quality research. Engagement is not only an ethical obligation, it also raises ethical challenges of its own. We conducted a qualitative study to understand ethical challenges and potential solutions when engaging patients and families in EOLPC research.

We recruited and interviewed 20 clinical investigators and 22 patients or family caregivers through the Palliative Care Research Cooperative Group (PCRC). Interview transcripts were analyzed using constructivist grounded theory methodology. Analysis sought to identify ethical challenges and potential solutions, as well as to synthesize findings into practical recommendations tailored to engaging patients and families in EOLPC research.

Our study identified 8 ethical challenges considered unique to the EOLPC research context and 11 potential solutions to these challenges. The most frequently described ethical challenges included the need to minimize burdens of engagement for patients and caregivers, challenges of dealing with death and illness, and paternalism or “gatekeeping” (i.e., withholding the opportunity to participate from patients or caregivers). Investigators and patients or family caregivers conceptualized ethics challenges differently; several issues appeared to fall outside a traditional research ethics paradigm and more into the ethics of relationships. We synthesized these findings into 4 practical recommendations hypothesized to support authentic engagement.

Conclusions

Engaging patients and families in EOLPC research can raise unique ethical challenges. These challenges can be overcome to empower participation, minimize the unique burdens of EOLPC, and promote diversity. Whereas traditional research ethics tend to emphasize protecting research participants who may be vulnerable, an ethics approach based on authentic engagement that explores what it means for investigators and patients or family caregivers to be in a relationship may be needed. Future research is needed to explore this approach and test these recommendations in practice.

Peer Review reports

Palliative care distinctly strives to achieve the best quality of life for patients who are experiencing serious illness and their family members and caregivers. Estimates suggest that two-thirds of all people in the United States could benefit from palliative care at some point, and this estimate does not include the family members and caregivers who may also benefit [ 1 , 2 ]. Delivering high-quality, evidence-based patient- and family-centered palliative care depends upon the conduct of rigorous end-of-life and palliative care (EOLPC) research [ 3 ].

Engagement with patients and families throughout the research lifecycle is critical to ensuring it addresses the needs, priorities, and values of patients and families. The importance of this engagement has been long recognized by the Institute of Medicine (now the National Academy of Medicine), US Patient-Centered Outcomes Research Institute (PCORI), the National Institutes of Health and others [ 3 , 4 , 5 , 6 ]. Evidence is accumulating that engagement improves research and health outcomes by ensuring research is responsive to patients’ preferences, beliefs, and values, as well as by enhancing research recruitment and dissemination of research [ 4 , 5 , 7 ].

Although engagement is widely regarded as an ethical best practice [ 5 , 8 ], engagement can also raise its own ethical issues [ 9 ]. For instance, engagement can create burdens on patient and family participants. Key justice-based issues relate to whether those engaged in research are truly “representative” of a broader patient population and whether marginalized groups are involved.

EOLPC research is arguably a unique research context [ 10 , 11 ]. Patients may be vulnerable due to their state of illness or due to absent or intermittent decision-making capacity (e.g., in advanced dementia) [ 8 ]. Family caregivers may struggle to know and represent patients’ priorities or have difficulty engaging due to caregiver burdens or ongoing grief following a loss. The nature of EOLPC means that maintaining long-term relationships – often considered essential to meaningful engagement – can be challenging. Finally, any potential ethical challenges may be particularly relevant for individuals who are doubly vulnerable because of existing racial, ethnic, socioeconomic, and geographic disparities in access to palliative care [ 12 ].

Existing research, while recognizing these challenges, has not often explored how patients, families, and investigators experience the unique ethical challenges of engaging patients and families in EOLPC research. We conducted a qualitative study to obtain insights into the real-world challenges facing investigators, patients, and family caregivers in EOLPC research engagement and to use our findings to create practical ethics guidance for managing them.

This study was conducted within the Palliative Care Research Cooperative Group (PCRC). The PCRC is an interdisciplinary palliative care research community supported by the National Institute of Nursing Research of the National Institutes of Health. When the study was conducted, the PCRC included over 500 researchers at more than 180 sites.

We recruited (i) investigators who had conducted patient- and family-engaged EOLPC research and (ii) patients and family caregivers who had been involved as partners or advisers in EOLPC research. For comparison purposes, we interviewed 6 investigators and 1 family caregiver who had not been involved in patient- and family-engaged EOLPC research.

To recruit investigators, we searched the PCORI database for funded studies related to EOLPC because these studies require patient and/or family engagement. This search identified 14 investigators, who were then contacted by a member of the study team (JK). Of these 14, 9 agreed to participate. We also recruited investigators via an email to PCRC members. Fifty-four people responded. To recruit among these 54, we used a purposive sampling strategy aimed at achieving diversity (“maximal variation” sampling) [ 13 , 14 ]. Key measures of diversity for investigators included age, discipline, years in profession, race, ethnicity, prior experience with patient or caregiver engagement in research, geographic location, and practice site characteristics (i.e., urban versus rural; academic versus non-academic).

To recruit patients and family caregivers, we asked investigators whom we interviewed (as well as those whom we did not) to refer participants to us. We also asked investigators who expressed interest in our study, but whom we did not interview, to connect us with patients and family caregivers. For patients and family caregivers, we similarly recruited purposefully for diversity. Key measures of diversity for patients and family caregivers included age, race, ethnicity, socioeconomic status, and geographic characteristics (urban versus rural). Our final sample included 20 investigators, 19 caregivers, and 3 patients.

Data collection

An interview guide was developed based on the study team’s knowledge of and experiences with ethical issues both in patient and caregiver engagement and EOLPC research. We modified the interview guide over time to allow insights gained from earlier interviews to inform later interviews. Semi-structured interviews were conducted over the phone by a member of the study team (MD or, in one case, AA) between August 2019 and May 2020.

Data analysis

Our analysis employed grounded theory methodology [ 15 ]; specifically, Charmaz’s constructivist version which acknowledges that meaning can be influenced by the researcher’s own perceptions and interactions with the data and the participants [ 16 ]. After each interview, field notes and memos were created to describe emerging themes and patterns.

To create a preliminary codebook, two members of the study team (MD and AA) coded 5 investigator interviews and 5 patient/family caregiver interviews in order to create initial index codes and categories linking codes, as well as their definitions. During this “open coding,” the researchers met after coding each interview to discuss code interpretations.

Next, we uploaded transcripts into Atlas.ti (Version 8 Windows) to facilitate ongoing data analysis. We independently re-coded the first 10 interviews and half of the remaining interviews. Constant comparative techniques [ 17 ] were employed to clarify and refine codes, develop additional categories of codes, and postulate relationships between categories (“selective coding” in grounded theory). To help ensure intercoder reliability, the researchers both coded every fifth interview and met to reconcile coding results and discuss the codebook, modifying and re-organizing codes as needed. (The final codebook is available as Additional file  1 ). Through this process, we determined that thematic saturation had been reached after 35 interviews; we conducted 7 more interviews to confirm this.

The third and final step (or “theoretical coding”) involved several distinct analytic steps. First, we analytically linked challenges to ethics concepts, drawing primarily on foundational principles of biomedical ethics: respect for persons, non-maleficence, and justice [ 18 ]. As a matter of reflexivity, this choice was made partly because of the researchers’ own background in these principles, and the influence of these principles on research ethics, at least in the United States. Second, we identified those codes and categories most unique to the EOLPC setting, and identified a unifying theme (or “core variable”) from our analysis. Finally, we iteratively created several overarching ethics recommendations based on the data. The goal of this final step was more interpretive [ 16 ] than positivist [ 15 ]. That is, rather than create a single overarching theory of engagement with defined causal relationships, we sought to synthesize our findings, abstractly and conceptually, in relation to the unifying theme. The goal was to generate hypotheses, grounded in the data and related to the unifying theme, that can be refined and tested in future research. This allowed us to create practical ethics guidance tailored to the unique context of EOLPC research for engagement of patients and family caregivers that are directly related to the semi-structured interview findings.

Throughout we employed accepted methods to ensure analytic rigor, such as expert checking (e.g., by sharing draft findings and recommendations with EOLPC researchers at the PCRC annual investigator meeting in February 2020; our local palliative care research in progress conference; the American Society of Bioethics and Humanities Annual Meeting in October 2020; and University of Colorado Palliative Care Virtual Research Day in October 2020). To illustrate, it was the PCRC annual investigator meeting where it was suggested to create recommendations according to foundational bioethics principles with which researchers are already familiar, though as we discuss later our analysis found that this framing alone was inadequate. We also engaged in member checking (e.g., by sharing our draft findings, recommendations, and the codebook with research participants, including investigators and patients/family caregivers), reflexivity, and avoidance of selectivity in data use.

Characteristics of participants

Each interview lasted approximately 1 h (range, 37 – 72 min) and was audio recorded and transcribed using a HIPAA-compliant transcription service. Demographic characteristics of our participants are in Tables  1 and 2 . Our sampling of investigators achieved expected diversity in terms of age, medical specialty/area of palliative care, and method of engaging patients and family caregivers, but less diversity in terms of race (75% white) and practice setting (i.e., 3 non-academic sites). Our sampling of patients and family caregivers achieved diversity in terms of age, clinical condition, and average income, but less diversity in race/ethnicity and gender. These patients and family caregivers were mostly involved in patient advisory boards or multi-stakeholder boards that could include clinicians and other stakeholder types.

Engagement challenges and their management strategies

Table  3 displays ethics challenges and potential solutions found in our interviews. For brevity, we present only those challenges we deemed as relatively unique to the EOLPC setting. For example, interviewee-reported challenges related to needing more time, more funding, or the general funding structure of research (which some participants thought might limit patient/family input from the outset) are not included unless they brought up issues unique to EOLPC (e.g., additional time needed to engage with people who have neurodegenerative or cognitive decline). However, a full table of all challenges and potential solutions is available in Additional file  2 .

We initially attempted to distinguish “ethical” challenges from “other,” more logistical challenges. However, we found in particular that patients and family caregivers responded to our questions about “ethics” challenges differently than investigators. Although investigators were comfortable speaking about traditionally taught research ethics principles of respect for autonomy, beneficence, and justice, patients and family members did not see ethics only through these lenses. Recognizing that almost any challenge has an ethical dimension -- i.e., what might seem a simply matter of logistics, such as meeting time or day, can relate to ethics principles of beneficence (by minimizing burdens) or justice (by promoting equal access) -- we collapsed all challenges into one category. Doing so meant we did not privilege ours, or our investigators’, definition of ethics in our analysis.

Authenticity as a unifying theme

During our analysis, “authenticity” – understood as describing an engagement activity that is motivated by an honest desire to listen to the voices of patients and caregivers and that includes specific practical actions that make that possible – emerged as a unifying theme. Authenticity appeared explicitly in some of the data – we used the code “being authentic about engagement” to capture instances of this – and through our analysis, we found that many codes reflected authenticity as well. Examples included “being explicit that the researcher will listen first,” “engagement changed the course of the research,” and participants who “felt valued.” By connecting these codes to authenticity, we found that this theme was present in almost all of our interviews. In addition, not only did we capture specific codes around authenticity in 35 of 42 interviews, but also it became clear throughout our analysis that many of the challenges in Table 3 were meaningful to patients, families, and investigators because of how these discrete issues and actions in response reflect authenticity. Likewise, ways of overcoming challenges could be seen as promoting authenticity.

To illustrate, participants described how alternative forms for feedback (outside typical board meetings) can demonstrate the sincere desire to receive feedback from patients and family caregivers:

“So having the right people in the room and making sure that the questions that are asked are genuine and actionable, I think is really important. So I think that's probably the biggest ethical concern that I have in putting CABs together, is that it's not-- I'm not checking a box. It's not so I can say, ‘Oh. I did this in the culturally right way because boom I had a CAB [Community Advisory Board].’ Tick. I checked that box off. It is about truly getting the input that you need in order to ensure that what comes out of an intervention development study, if that's what you're doing, or out of a trial, or out of whatever, is in fact something that can be made actionable...” [Investigator, Female, White, Age 49]

Authenticity, therefore, as a concept represents what we took to be the goal of engagement, particularly for patients and family caregivers.

Ethics recommendations for authentic engagement

In the final, most abstract phase of our analysis, we synthesized our analytic findings by creating recommendations as the theoretical output of our constructivist approach (see Table  4 ). These four distinct recommendations were meant to link the challenges we observed (see Table 3 ) with the concept of authenticity; they can be seen as hypotheses generated from our data for how to improve authentic engagement in EOLPC research. In this section we expand on the basis and implications of each.

Recommendation 1, based in respect for persons and their autonomy, reflected our participants’ strong belief that patients and families should decide for themselves whether to engage. Just as many reject the idea of “gatekeeping” in EOLPC research – i.e., when clinicians or others prevent or withhold research opportunities from potential research participations [ 19 , 20 , 21 ] - so too was the idea of “gatekeeping” rejected when it came to acting as a research advisor or partner. As one participant said:

“I think that’s part of that paternalism that I was talking about, when we want to protect others from what we might anticipate as harm. That can be reframed into the opportunity to have the autonomy to choose, can be seen as a gift, so the person can look you in the eye and say, are you crazy?... But I get the choice. You didn’t preselect me out because of my end-of-life status, or my symptom-burden status, or my whatever.” [Investigator, Female, White, Age 61]

To reject gatekeeping also requires taking steps to allow individuals with reduced decision-making capacity to participate by empowering them to do so (e.g., by pairing them with a caregiver or advocate, or allowing them to provide feedback in ways outside of a meeting or conference setting).

Practically, our patient and family participants (more so than our investigators) were comfortable being approached to participate even very near life’s end. This is a critical insight. If researchers believe that patients and family caregivers ought not be approached as research advisors very near the end of life or shortly after a loved one passes away, this could inadvertently create a crucial gap in the knowledge base of EOLPC – one that patients and families want to fill:

“I guess, I mean, I know if I was going through it, like I'd want to have my opinions heard. If there was ever a time to get your opinions heard, it's the end of life. So as long as I didn't feel like I was being exploited, and it was my decision to be there, then yeah, I would want the ability to be there.” [Caregiver, Female, White, Age 31]

“We want to contribute. We want to give something back. And, I mean, I have to say-- again, I have to use my mom as an example. My mother would have been more than willing to give her opinion about anything, end-of-life care, or just caring for the elderly, period. And I know that end-of-life care doesn't just include elderly people, but my mother would have been willing to give her opinion or herself in any way if she thought she was leaving something better behind. So I think it's a difficult question to ask, but I think it's also an important question to ask because you won't know until you ask.” [Caregiver, Female, Black, Age 55]

Doing so sensitively and with compassion still implied the need to do so carefully. Concretely, before asking about research engagement, it may be important for the research team to be upfront, asking openly and honestly about whether it is a convenient time to ask about research engagement and ensuring there are no competing personal or social needs that should take priority. Some, but not all, family caregivers were comfortable being recruited as advisors even within a month after a loved one’s passing – and none felt that having a known clinician do the recruiting exerted inappropriate influence. Similarly, researchers should be aware of potential cultural differences in the meaning of death and dying (e.g., in some cultures, it is taboo to talk about death or the deceased by name) while not stereotyping by merely assuming such differences exist.

Recommendation 2, based in obligations of beneficence and non-maleficence, reflected the idea that EOLPC research – by being frequently situated in settings of serious, chronic, or life-limiting illness – can require additional efforts (when compared to traditional research) to minimize the burdens of participating in research engagement. Arguably a dominant model in contemporary research is the advisory board – a group of patients, family caregivers, and others who meet regularly to provide input to a study. Whether this model serves EOLPC research depends on the details of a particular study; however, there is a need to be particularly considerate of burdens posed by meeting time, location, and especially the built environment (e.g., around access for people who are variably abled). And in the setting of EOLPC, researchers should be mindful of the potential harm caused by evoking difficult emotions and grief when discussing end-of-life issues.

Researchers also should be willing to obtain input in ways outside the traditional board meeting setting by meeting patients and families where they are in the hospital, the emergency room, the dialysis unit, or even at home (assuming that the participant is willing and able to engage comfortably in those settings). In addition, being accepting of short feedback sessions, done more frequently, can be less burdensome than meetings lasting over an hour. As one participant said:

“To have any consistency, they have to make multiple quarterly meetings. And that’s just not something that people with serious illness are often up for. And I think that’s important because then there’s an important voice. Family members provide a great perspective, but there’s an important voice missing if the patients aren’t there. And that’s why we go to one on one interviews sometimes by telephone or we travel to patients to make sure that we get that perspective as well.” [Investigator, Male, White, Age 59]

Caregiving can create additional unique or unrecognized burdens. When caregiving demands prevent participation in meetings or conference calls, researchers should plan for and be prepared to follow up separately if needed to ensure that the patient and caregiver voice remains heard. As a result of the COVID-19 pandemic, virtual methods of engagement are of particular interest. These methods can minimize travel and time burdens while still approximating face-to-face interactions. When used, however, there must be attention to inequities in technology access and technology literacy:

“One of the things that we found was that it was hard for patients sometimes to participate depending on the stage of the disease that they were in. Even if we didn’t ask people to come, like we all try to meet at the campus. But we also offer the possibility of joining by Zoom or by telephone. So even at that, for Parkinson’s patients, sometimes communication is a problem.” [Caregiver of a patient with Parkinson’s, Female, White, Age 72]

Recommendation 3, based on obligations of justice and fairness, arose because of diversity concerns. While diversity concerns are not unique to EOLPC, they were the most frequent ones we encountered in interviews. Concerns about diversity and inclusivity have been repeatedly expressed regarding research participation and regarding participation in research engagement generally [ 22 , 23 , 24 , 25 ]. Diversity in terms of race, ethnicity, and socioeconomic status, among others, were identified as key challenges for EOLPC research. This may be reflective of broader disparities in access to palliative and hospice care – disparities that are compounded when it comes to engagement [ 26 ]. For instance, individuals who are well off or who do not work may find it easier to participate (or be more likely to be invited).

In addition, interviewees noted some unique diversity challenges in end-of-life and palliative care, such as the need to include more family caregivers and more male voices (e.g., because family caregivers tend to be female). The following two quotes are illustrative of concerns around justice.

“Well, one thing I wanted to mention is I think we’re one of the very few Spanish speaking councils in the nation…I think it would be great for every hospital to have a Spanish speaking council or a Chinese speaking council, and any other language council because our needs are very different. Every culture and language has their own specific needs.” [Caregiver of a patient with cancer, Female, Hispanic/Latina, Age 29]

“A lot of careers that men get into don’t afford them the opportunity to attend, especially when they’re the primary caregiver or just caregiver of a family. They provide the resources for their family. But we definitely need them at the table because we need them to go out to share this information with people who look like them regardless of whatever their ethnicity is. They need to be able to go back into their community as men and educate the men about how important it is for them to do these things.” [Caregiver, Female, Black, Age 64, End-stage Renal Disease]

Practically, this means actively working to involve ever more diverse engagement partners and to ensure diversity is broadly construed. Building on Recommendation 2, participants noted a need to make special efforts to minimize burdens of participation that may make it hard for certain individuals to participate. For instance, the burden of meeting during daytime working hours can be disproportionately borne by individuals who work in certain jobs or vocations; as such, minimizing burdens by holding evening or weekend meetings (which may be less convenient for the research team) can simultaneously encourage more diverse participation.

Recommendation 4 arose based on our analysis of issues and challenges that did not fit neatly into the three aforementioned principles of bioethics. As a result of widespread educational requirement, researchers (but not necessarily patients and family caregivers) are steeped in human subject protections and these principles. However, the traditional research ethics model has limitations. It tends to view human subjects as being uniquely vulnerable and requiring special protection (even if recent efforts have tried to move this model toward fair participation, not just protection). Yet patient or family research advisors, partners, and co-investigators do not clearly fit into a position of vulnerability, at least not in the same way, and many believe the connotation of partner to be more indicative of equals. Moreover, the motivations for participating as a research partner may be different than those for enrolling in research, and these different motivations may affect relationships. Although specific motivations did not arise in our research interviews, both investigators and patients or caregivers might do well to be upfront about these as part of relationship building.

If the research ethics model is a poor fit, many additional and intriguing ethical questions arise. When is it appropriate to end a partnership with an advisor, and how should this be done? How should a researcher respond if a patient or family caregiver partner asks for medical advice or other support? Are research partners “friends”? Is it appropriate for researchers and partners to be “friends” or to interact socially? Below are a few examples of these sorts of situations:

“She was a partner and she’d been on this journey with us for a year and change. And I knew she liked visits and she didn’t have a lot of family…And so we got to know her friends, and her friends said they’d love us to visit. And so I remember I brought my sons and my husband to spend an hour drive away, and my son had colored a whole bunch of things that we could decorate her hospice room.” [Investigator, Female, White, Age 42]

“She is one of the most dearest friends in my life. She is remarkable. She is wonderful. She’s compassionate, she’s sensitive, she’s smart. And she used to always tell me – what I loved most about her, she said, ‘I’ll do the research part. I’ll do the writing part. You just be you.’” [Caregiver of a patient with end-stage renal disease, Female, Black, Age 64]

“We had what I call a non-normal relationship…in the sense that it really was much broader than a patient-doctor relationship. There was really an interest in each other as human beings and people, and we just so respected his commitment to the patients and families.” [Caregiver of a patient with Parkinson’s, Female, White, Age 71]

“So that’s kind of outside of that whole patient advisory role because these are human beings, you know? And they bring all of their – like you’re in a – we were in a relationship now, just like any working relationship.” [Investigator, Female, White, Age 46]

“And I really had a nice relationship, fun relationship with the principal investigator. And she is the one that I still work with on this other study they’re now doing. So I have kind of an ongoing connection from that. [Patient with cancer, Male, White, Age 75]

Understanding and addressing the potential for blurred boundaries and managing expectations upfront become key.

Our study adds to a growing body of literature around engaging patients and families in EOLPC research [ 9 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ]. A systematic review, published near the end of our data analysis, identified 25 published articles reporting on ethical considerations in engaging frail and seriously ill patients as research partners; issues identified by content analysis were, like our findings, grouped into traditional principles of biomedical ethics [ 33 ]. In this section, we highlight what our findings add to this body of literature and further expand on our qualitative analysis.

First, our study further demonstrates the value of directly asking patients and families about ethics challenges [ 9 ], rather than relying solely on researchers’ beliefs or reviews. In our study, we found that new and concrete management strategies for ethical challenges came more often from patients and families (see Additional file 2 ).

Two additional observations from our findings shed light on the importance of elevating the patient and family voice. First, when analyzing the views of investigators who had not yet engaged with patients or families as research partners, we found that inexperienced investigators expected challenges (e.g., around overly burdening families simply by asking, about not approaching them directly, and so on) that our patients and family caregivers found insignificant. Our findings and recommendations should reassure researchers and (contra “gatekeeping”) provide encouragement to engage patients and families more, not less. Second, we had a strong sense from the experience of conducting our interviews that it was difficult to get patients or families to express some issues, particularly burdens of engagement. Many seemed simply thrilled to participate in engagement and required direct prompting to endorse even simple burdens, such as parking or disability access. In practice, implementing Recommendation 2 (minimizing burdens) will therefore require careful and proactive efforts to elicit unintended or unforeseen burdens of participation. Regular evaluation of engagement activities [ 34 , 35 , 36 ] that include assessment of burdens could be a practical way to lower the activation energy that might be required for patients and families to bring these up on their own.

We observed important differences in language around ethics (hence our inability to delineate clearly “ethics” challenges from “other” challenges). From this finding, we conclude, for example, that there is not necessarily a need to teach patients and family research partners the classical principles of biomedical ethics for them to be able to think and talk about ethics with researchers. Doing so might limit the moral imagination and analysis necessary for identifying new issues or ways of managing them. There appears to be a need to find common ground and language while preserving the unique voices of patients and families.

To illustrate this, and similar to a recent review of ethical issues in engagement in research generally [ 37 ], we found a category of issues not captured by classical research ethics principles: relational ethics. In Recommendation 4, we note that researchers must be prepared and aware that patient and family engagement in research may require a different approach than a traditional researcher-human subject relationship that is based on protection or even vulnerability. From an ideal perspective, some see the goal of engagement to create relationships of equals or near equals (hence language such as “partner”). This suggests a need to consider analyzing ethical issues of research engagement through an additional lens of relational ethics or the ethics of care [ 38 , 39 ]. Such an approach makes concepts such as trust and relationships among people the fundamental units of moral analysis, rather than discrete, autonomous agents and principles [ 40 ]. The implications of such a paradigm shift should be explored in future studies.

Authenticity has recently received greater attention as an important concept in research engagement [ 41 ]. Although defined by some as ensuring patients and families are full partners in the research, in our view, authenticity applies no matter how deeply a patient or family caregiver chooses to be engaged in EOLPC research. It describes a genuine, honest, and openly transparent desire to take seriously the advice of patients and families and to treat them accordingly with respect, care, and concern. Authenticity is not unique to EOLPC research engagement, but our findings suggest that the EOLPC research context has unique characteristics that must be acknowledged to support authentic engagement. Authenticity in EOLPC research requires attention to issues even very near life’s end, recognizing the unique burdens of engagement in EOLPC and taking steps to minimize them, promoting diversity, and considering the unique relationships forged out of EOLPC. Future research studies should test whether and/or how the recommendations from our study promote authenticity in EOLPC research.

Like all studies, ours has limitations. As a qualitative study, we are unable to make claims about the population-wide frequency or importance of particular ethical challenges. In addition, qualitative research involves subjectivity in analysis; member checking and reflexivity can minimize, but not eliminate, this. Lastly, despite our attempts to recruit for diversity within a large, multidisciplinary research collaborative, our findings may not generalize beyond our participants.

Our study has provided four practical recommendations for ethically engaging patients and families in EOLPC research based upon the concept of authentic engagement and focusing on those issues most unique to the EOLPC setting. These recommendations stand together, not alone: Minimizing burdens (Recommendation 2) unique to certain patients and families can be a way to improved diversity (Recommendation 3), for example, and researchers ought not approach patients in the most convenient place for the sake of minimizing burdens if doing so unduly influences someone to participate (e.g., if an individual feels they have no choice but to participate while in the hospital). While we wholeheartedly endorse other recommendations common to all research (e.g., around compensating participants, providing appropriate training and resources, maintaining privacy and confidentiality, and so on), there is added value in recommendations specifically tailored to the EOLPC context.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request and will be available from the Palliative Care Research Cooperative De-identified Data Repository https://palliativecareresearch.org/studies .

Abbreviations

End of life and palliative care

Patient-Centered Outcomes Research Institute

Palliative Care Research Cooperative

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DeCamp, M., Alasmar, A., Fischer, S. et al. Meeting ethical challenges with authenticity when engaging patients and families in end-of-life and palliative care research: a qualitative study. BMC Palliat Care 21 , 74 (2022). https://doi.org/10.1186/s12904-022-00964-x

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Qualitative vs Quantitative Research Methods & Data Analysis

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What is the difference between quantitative and qualitative?

The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed in numerical terms. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.

Qualitative research , on the other hand, collects non-numerical data such as words, images, and sounds. The focus is on exploring subjective experiences, opinions, and attitudes, often through observation and interviews.

Qualitative research aims to produce rich and detailed descriptions of the phenomenon being studied, and to uncover new insights and meanings.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human.  Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography.

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions.  This allows the respondent to talk in some depth, choosing their own words.  This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis.

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded .

Key Features

• Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
• Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
• The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
• The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
• The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

• Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
• The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
• Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
• The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

• Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
• Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
• Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
• Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things.  However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms. 

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

• Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
• The research aims for objectivity (i.e., without bias) and is separated from the data.
• The design of the study is determined before it begins.
• For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
• Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

• Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
• Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
• Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
• Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

• Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
• Useful for testing and validating already constructed theories.
• Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
• Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
• Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

• Designing qualitative research
• Methods of data collection and analysis
• Introduction to quantitative and qualitative research
• Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
• Qualitative research in health care: Analysing qualitative data
• Qualitative data analysis: the framework approach
• Using the framework method for the analysis of
• Qualitative data in multi-disciplinary health research
• Content Analysis
• Grounded Theory
• Thematic Analysis

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What is Qualitative in Qualitative Research

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

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Unsettling definitions of qualitative research, what is “qualitative” in qualitative research why the answer does not matter but the question is important.

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

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

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

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

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

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

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

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

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

Towards a Definition of Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Analysis – What is Qualitative Research?

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

Qualitative and Quantitative

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

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

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

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

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

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

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

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

Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

Grounded Theory

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

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

Defining Qualitative Research

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

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

Distinctions

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

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

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

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

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

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

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

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

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

Improved Understanding

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

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

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

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

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

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

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

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

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

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

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

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

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

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Acknowledgements

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

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Esparza CJ , Simon M , London MR , Bath E , Ko M. Experiences of Leaders in Diversity, Equity, and Inclusion in US Academic Health Centers. JAMA Netw Open. 2024;7(6):e2415401. doi:10.1001/jamanetworkopen.2024.15401

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Experiences of Leaders in Diversity, Equity, and Inclusion in US Academic Health Centers

• 1 Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco
• 2 School of Medicine, University of California, Davis
• 3 Storywalkers Consulting, Davis, California
• 4 Division of Population Behavioral Health, UCLA Health, Los Angeles, California
• Invited Commentary Preventing the Demise of Diversity, Equity, and Inclusion Kathie-Ann Joseph, MD, MPH; Renee Williams, MD, MHPE JAMA Network Open

Question   What are the experiences of leaders in diversity, equity, and inclusion (DEI) at US academic health centers?

Findings   In this qualitative study, 32 leaders described a considerable range of expected responsibilities. Institutional resources rarely matched stated goals, with limited use of evidence or standards, and participants from marginalized backgrounds expressed strong motivation coupled with exhaustion from the mismatch between demands and support.

Meaning   The findings of this study suggest that leaders charged with promoting diverse, inclusive, and equitable environments in academic health centers would benefit from direct investment in their efforts, guidance from policymakers and organizations, and assessment and dissemination of best practices.

Importance   The murder of George Floyd in 2020 spurred an outpouring of calls for racial justice in the United States, including within academic medicine. In response, academic health centers announced new antiracism initiatives and expanded their administrative positions related to diversity, equity, and/or inclusion (DEI).

Objective   To understand the experiences of DEI leaders at US allopathic medical schools and academic health centers, ie, the structure of their role, official and unofficial responsibilities, access to resources, institutional support, and challenges.

Design, Setting, and Participants   This qualitative study used key informant interviews with participants who held formal DEI positions in their school of medicine, health system, or department. Interviews were conducted from December 2020 to September 2021. Transcripts were coded using a phenomenographic approach, with iterative concurrent analysis to identify thematic categories across participants. Data were analyzed from January to December 2021.

Exposure   Formal DEI role.

Main Outcomes and Measures   Questions elicited reflection on the responsibilities of the role and the strengths and challenges of the unit or office.

Results   A total of 32 participants (18 of 30 [56%] cisgender women; 16 [50%] Black or African American, 6 [19%] Latinx or Hispanic, and 8 [25%] White) from 27 institutions with a mean (range) of 14 (3-43) years of experience in medical education were interviewed. More than half held a dean position (17 [53%]), and multiple participants held 2 or more titled DEI roles (4 [13%]). Two-thirds self-identified as underrepresented in medicine (20 [63%]) and one-third as first generation to attend college (11 [34%]). Key themes reflected ongoing challenges for DEI leaders, including (1) variability in roles, responsibilities, and access to resources, both across participants and institutions as well as within the same position over time; (2) mismatch between institutional investments and directives, including insufficient authority, support staff, and/or funding, and reduced efficacy due to lack of integration with other units within the school or health system; (3) lack of evidence-based practices, theories of change, or standards to guide their work; and (4) work experiences that drive and exhaust leaders. Multiple participants described burnout due to increasing demands that are not met with equivalent increase in institutional support.

Conclusions and Relevance   In this qualitative study, DEI leaders described multiple institutional challenges to their work. To effectively address stated goals of DEI, medical schools and academic centers need to provide leaders with concomitant resources and authority that facilitate change. Institutions need to acknowledge and implement strategies that integrate across units, beyond one leader and office. Policymakers, including professional organizations and accrediting bodies, should provide guidance, accountability mechanisms, and support for research to identify and disseminate evidence for best practices. Creating statements and positions, without mechanisms for change, perpetuates stagnation and injustice.

Following the murder of George Floyd, leaders in academic medicine announced new initiatives related to advancing diversity, equity, and inclusion (DEI). The Association of American Medical Colleges (AAMC) found that the percentage of institutions with dedicated DEI staff and offices rose from 75% in 2018 to 97% in 2021. 1 Nearly all (96%) reported having a senior-level DEI administrator (eg, assistant dean, chief diversity officer). 1

Despite the growth in DEI efforts, evidence on the expectations of, support for, or standards for DEI in academic medicine remains limited. A 2015 AAMC survey of DEI leaders found that more than half held a dean title, although their positions varied across units, from student and faculty affairs to community engagement and outreach. 1 Most reported they had less than 50% of their time allocated to DEI work, with budgetary support ranging from $0 to $1 million. Their main priorities included student diversity, meeting Liaison Committee on Medical Education (LCME) diversity standards, institutional climate, and culturally competent care. 2 In a smaller 2018 survey, most focused on student recruitment and retention. 3 The LCME and the Accreditation Council on Graduate Medical Education (ACGME) have instituted diversity-related accreditation standards but not specifically for DEI administrators. The AAMC Group on Diversity and Inclusion published a toolkit to support new DEI leaders, and the National Association of Diversity Officers in Higher Education developed professional standards, but it is unclear whether academic medicine institutions incorporate these guidelines for diversity leaders. 4 - 6

Researchers in higher education have found that diversity initiatives are often broad in scope, unclear in meaning, and limited in their effectiveness. Following legal and political constraints on affirmative action policies, university leaders embraced the cause of diversity rather than racial justice. 1 Subsequently, universities more often tasked diversity administrators with the discussion of diversity, including publishing statements and missions, rather than pursuing meaningful systems change. 5 Furthermore, repeatedly launching new initiatives can displace substantive reforms by rearranging priorities and failing to invest in existing work. 6 DEI leaders are often scattered in silos that preclude collaboration and communication. To work effectively, DEI leaders require equity-focused directives, sustained investment, organizational authority, coordination across units, and a commitment to reforming existing institutional structures. 7 - 9

Our objective for this study was to describe the experiences of leaders in US academic medicine who have a formal DEI (or similar) position, particularly in the context of the renewed calls for attention to racial justice in medicine. We conducted key informant interviews to explore participants’ motivations, responsibilities, and their experiences in conducting DEI work. In the absence of a clear understanding of what DEI leaders can or should do, academic medicine cannot evaluate the impact of these initiatives. Consequently, schools and health systems run the risk of expending opportunities without advancing structural change. 10 By exploring perspectives from DEI leaders, we can offer insights on strategies to support their success.

We used the Standards for Reporting Qualitative Research ( SRQR ) reporting guideline to prepare this manuscript. The protocol was approved by the institutional review board of the University of California, Davis. We provided participants with a letter of information upon scheduling the interview, reviewed the document with participants, and obtained verbal consent.

The lead author (C.J.E.) identifies as a Chicane nonbinary medical student at the time of the study, who has created and participated in institutional DEI and racial equity initiatives. The primary interviewer (M.S.) identifies as a White cisgender man and professional facilitator with expertise in diversity in higher education. Coinvestigator (E.B.) identifies as a Black cisgender woman physician researcher with expertise in racism in medical education and currently serves as a senior DEI leader for an academic medical center. The senior investigator (M.K.) identifies as an Asian American cisgender woman researcher who has served in multiple DEI positions. Coinvestigator (M.R.L.) identifies as a White cisgender woman medical student. The collective team background and experience fostered planning, analysis, and discussion from multiple perspectives. Our status as a multiracial, multi-ethnic team enabled inquiry and analyses that included racial and ethnic positionality-specific examination.

We used a phenomenographic approach to construct a representation of the variation in nature, positionality, and experience of those with DEI roles. We analyzed our topic within the multilayered context of academic medical institutions. 11

We recruited participants from US medical schools and academic medical centers who held, or recently held, formal leadership roles in an office of Diversity, Equity, and/or Inclusion, which referred to all administrative units whose primary intent is to foster 1 or more of these goals at their respective program or institution. Although we used the term offices, we noted potential participants held titled roles over many types of structures, eg, committee, division, or center.

At the time of the study, there was no national directory of DEI leaders, and as noted previously, this population was rapidly changing. We conducted initial recruitment via email through professional networks, the UC Davis Center for a Diverse Healthcare Workforce, and contacts from prior studies conducted by the team. We supplemented with snowball sampling and purposive sampling to ensure we obtained perspectives from different geographic regions (West, Midwest, South, and Northeast) and types of institutions (public and private; schools and health systems). Participants were assigned an alphanumeric study identifier (ID) at recruitment.

We conducted video interviews from December 2020 to September 2021. Interviews lasted approximately 1 hour and were digitally recorded and transcribed using Zoom services. We labeled speakers with participant study ID prior to recording and labeled files by study ID. Two authors (M.R.L. and C.J.E.) then reviewed transcripts to correct errors and remove identifying information, including regional (eg, city, county, and state), institutional, and programmatic details.

No interviews were discarded. We were unable to collect data on nonparticipants, other than name and institution, so we were unable to discern patterns of nonparticipants related to individual characteristics.

Critically, we conducted interviews early in the COVID-19 pandemic, shortly following the murder of George Floyd in the summer of 2020. Therefore, our data and analyses reflected the co-occurrence with these events. Discussions explored DEI structures (eg, roles, placement within institutions, formal resources, and level of influence) as well as participants’ personal experiences (eg, motivations, challenges, and emotional hurdles). The full interview guide is provided as the eAppendix in Supplement 1 .

We used a phenomenographic approach with concurrent analysis to identify thematic categories across participants, rather than a focused analysis of singular experiences. Two authors conducted preliminary independent review of 5 transcripts (C.J.E and M.K.) to identify initial categories. Following review and full team discussion, 1 author (C.J.E.) reviewed the remaining transcripts to further develop and revise codes. In instances of differences of opinion, the team discussed and developed an agreed-on code and/or set of codes for the lead author to review and apply. The full team reevaluated the subsequent coding structure an additional 2 times, and then 1 reviewer (C.J.E.) conducted the final analysis and coding to produce final themes. We used Dedoose version 9.0.107 for initial code development, followed by hand-coding of transcripts to produce final themes. To enhance trustworthiness, we created an audit trail of detailed memos and used investigator triangulation of experiences in DEI roles for verification and context.

Our final sample consisted of 32 participants (18 of 30 [56%] cisgender women; 16 [50%] Black or African American, 6 [19%] Latinx or Hispanic, and 8 [25%] White) from 27 institutions ( Table 1 ). More than half held a dean position (17 [53%]), and several held 2 or more DEI roles (4 [13%]). Two-thirds identified as underrepresented in medicine (20 [63%]) and one-third as first generation to attend college (11 [34%]). Regional distribution somewhat favored the eastern United States, with more than one-third of participants in the South.

Participants described responsibilities spanning clinical to biomedical to public health areas ( Table 2 ). All reported formal goals of increasing workforce diversity and improving institutional climate. Many shared overlapping objectives, such as increasing capacity, broadening reach, and building credibility.

Responses indicated a broad range in authority, leadership endorsement, and resources, even when participants held seemingly similar roles. For example, among 3 participants with associate dean titles, ID62 reported 20% full-time equivalent (FTE) allocation to chair the antiracism task force and conduct oversight of medical school metrics, training, and policies, with 4 staff and a $1 million budget. ID11 had 30% FTE to oversee undergraduate medical school curriculum as well as recruitment and retention of trainees, faculty, and department chairs, with no staff or budget. Meanwhile, ID94 described their time as 20% or 50%, depending on their leadership’s perspective, and supervised undergraduate pathway programs, curriculum, LCME and ACGME accreditation, and faculty diversity, with the assistance of 1 staff coordinator and federal grants. Those working at the department level had no staff and minimal compensation and funding.

Many reported a high level of autonomy, but nearly all preferred clearer, more structured expectations from leadership ( Table 2 ). Participants regularly juggled informal on-demand requests, such as providing emotional support following incidents of discrimination and crafting rapid institutional response statements. They described how complex reporting structures (eg, reporting simultaneously to school, health system, and university leadership) required them to expend time and energy developing and maintaining a broad network of connections.

Participants with longer tenure described institutional volatility in commitment and resources. Many reported that expectations increased following the renewed racial justice movement but questioned whether these changes merely reflected a temporary institutional response vs sustained effort. Furthermore, institutions hired underrepresented individuals for DEI positions; this offered needed perspective but placed these individuals at heightened vulnerability: DEI failures could also be blamed on leaders from marginalized racial, ethnic, income, or gender groups.

Two participants (ID48 and ID62) expressed optimism because they had received new directives with clear expectations, appropriate staffing and budget, and institutional accountability. Their institutions required department chairs and division chiefs to prepare detailed faculty DEI plans and accountability incorporated into performance reviews, signaling DEI as an institutional priority. The DEI office provided data and programming support for these leaders, positioning the DEI administrator as a collaborative, rather than adversarial, partner.

Participants consistently described insufficient investment relative to institutional expectations ( Table 2 ). Investment consisted of both tangible resources, eg, budget, staff, time, and compensation, as well as intangible resources, such as authority and leadership endorsement. Most felt that senior leadership did not understand the level of support needed to pursue DEI goals effectively. Participant ID224 summarized, “They have high expectations, and the reality is that I am only one person.… Diversity is seen as compliance accreditation. [If] you’re really interested in changing the landscape… then you have to put money where your mouth is, to move the needle.”

Furthermore, participants had no consistent positioning within their organizations and often occupied a place in parallel to (rather than integrated in) main organizational units (eg, medical education, faculty development). Without the ability to directly guide operations, participants struggled to meet expectations. One participant (ID207) explained that they “do not have true power” but rather “power… by proxy.” Many characterized their institutional leadership as verbally supportive without concomitant sponsorship, thus hampering their abilities to advance organizational accountability ( Table 2 ).

The mismatch between institutional expectations and resources, particularly relative to investments in research and clinical activities, undermined participants’ trust in their institution’s commitment to DEI. They questioned whether they played superficial, rather than substantive, roles. One (ID11) worried that the creation of the DEI office allowed their institution to absolve other units of accountability. Institutional devaluation further amplified racial prejudice from peers and staff, who perceived DEI leaders as less capable.

Participants felt that the absence of structured institutional expectations increased the difficulty of their work ( Table 2 ). They perceived that leadership frequently operated by reactionary response to an event, such as LCME accreditation or a major news crisis, that resulted in “clamoring for activities, statements, and webinars” rather than addressing “real concerns [such as] structural racism” (ID239). Participants noted the lack of root-cause analysis also contributed to the perception of institutional DEI as performative rather than substantive. As ID236 explained, DEI work required new expertise—otherwise, there would be no need for change. Several endorsed “that nobody knows how to do it” and wished for more scholarship on DEI practice in academic medicine.

The limited evidence base contributed to inconsistency in measurement and accountability. Participants expressed uncertainty around how to demonstrate success, which undermined their confidence and ability to advocate for DEI to institutional leadership. Some perceived LCME and ACGME accreditation as diversity compliance, but others felt the threat of losing accreditation at least motivated small steps toward reform.

Without a strong base of theory and scholarship, participants described a vacuum in expertise to assess qualifications for DEI positions. Participants explained that given that the majority of academic medicine faculty are physicians, most lack training on organizational development theory, implementation science, and historical and current systems of oppression in medicine. Instead, ID236 reflected, the lack of physicians with appropriate training contributes to the problems that DEI work is supposed to fix.

Participants referenced personal sources of motivation, often arising from their own lived experiences with tokenism, discrimination, and mistreatment in academic medicine ( Table 2 ). Thus, despite the challenges described in the preceding themes, they held a strong commitment to support trainees and faculty from marginalized groups. As ID83 noted, “I understand the importance of my own presence in the territory, and try to share the values that I have developed over time with others, in a way that’s not combative but hopefully compelling.” Some reported leveraging their own marginalized identity to educate peers and leadership, putting a “personal spin on it” for people “to see the humanness.”

Many reported that the combination of personal and institutional marginalization contributed to deep professional isolation. Their DEI roles required them to serve as the face of their institutions in managing internal incidents of interpersonal discrimination and abuse yet also supporting trainees and peers. They also described the toll of leading institutional responses following highly publicized cases of racial and gender-based violence, while being chronically undersupported and unrecognized for their emotional labor. Participants reported growing burnout from the pressure of navigating the narrow space between institutional and community demands. Participant ID207 shared, “My job is to have hope, to absorb for everybody else, figure out what I can do after every kaboom to help the community heal…. But [I] don’t have time to heal or process [myself].”

Our findings offer insights into the experiences of DEI leaders in academic medicine during a period of heightened attention to racial injustices. The variability in roles and institutional investment reveal an overall lack of clarity on the aims and implementation of DEI initiatives. Furthermore, DEI work can occur at high personal cost to the individuals tasked with carrying it through.

Our findings are consistent with earlier studies that have found high variability in titles, scope, role, authority, and resources. 3 , 12 The ambiguity of DEI roles and responsibilities, and the mismatch between expectations and investment, are emblematic of decentralization, described by sociologist James Thomas as: “1) lack of/slow coordination; 2) absence of regulations and/or enforcement; 3) unresponsiveness; 4) poor observational capabilities; 5) shared belief that no matter what organizational actors do, the same outcome persists.” 6 Our participants’ guarded perceptions of new antiracism initiatives reflect the concern that academic medicine will remain unchanged. Recognizing this pattern is crucial, because some may conclude that the lack of progress suggests that DEI work cannot, or should not, be done.

Participants believed their challenges arose partly due to the absence of theories of change within academic medicine. Institutional leaders reference business and management fields to pursue clinical and educational reforms, but not for DEI work. 12 For example, the field of implementation science applies organizational behavior knowledge, yet no participants reported using implementation science in DEI. This may reflect institutional oversight, but diversity scholars argue that the overall lack of strategy is a feature, rather than a bug, in the system. 7 , 8 Under these conditions, DEI leaders run the risk of being perceived as ineffectual, and their own work as performative. 5

Our participants expressed exhaustion and burnout from compensating for DEI decentralization, which was further amplified participants from minoritized racial and ethnic groups by staging difference: “the constant push for new programs, managed by men and women of color,” to signal a “new” effort by the university. 6 Feminist scholar Sara Ahmed 5 raised the cautionary warning that racially and ethnically minoritized DEI professionals then embody DEI for the institution, at a steep cost to their personal health. Black DEI professionals are particularly exploited by institutions to address systemic problems (without systemic resources), serve as a buffer between leadership and their constituents, and use their own identity as a stand-in for entire communities. 13 , 14 Our participants detailed the fatigue that arises when they selectively express and repress aspects of their identities, without the structural or material support to change the very institutions that continue to harm them. Thomas 6 cautions that “rather than addressing structural inequalities, the performative culture of diversity reproduces and exaggerates them.” Staging difference reproduces DEI leadership churn, leading to failed initiatives and repeated calls for minoritized workers to lead the next new initiative.

Our study offers rich detail on how DEI leaders may be stymied in academic medicine; however, they also suggest opportunities for change. First, organizations such as the AAMC can support developing specific guidelines on DEI objectives and resources and invest in successful programs. Second, the LCME and the ACGME can institute detailed DEI standards, including requirements for clear expectations, measurement, and institutional investment in monitoring and evaluation. 15 The current diversity and inclusion accreditation standards created a theoretical structure for assessment, but measurement and evaluation remain vague and limited in fostering accountability. 16 , 17 Third, institutions can establish professional expectations for DEI leaders, such as training and experience in organizational behavior, power assessment, critical race theory, and historical understanding of structural inequities. Fourth, DEI leaders must be granted resources—including staff, budgets, and authority—concomitant with their objectives and scope.

These recommendations may be particularly challenging to enact as policymakers in multiple states have terminated DEI funding, programming, and positions. The current climate further demonstrates the need for greater specificity and understanding of DEI objectives in academic medicine. DEI work that is valued only for its appearance, and not the design and impact, cannot produce the changes necessary to create diverse, equitable, or inclusive systems of care for our communities.

The limitations of this study include the timing, in a period when medical institutions and organizations increased DEI resources. 18 However, as higher education and health care institutions experience growing staff shortages and public attention to racial justice wanes, institutional investment may be declining. Second, our recruitment process and stated aims may have selected for participants who were motivated to participate due to their personal challenges at work. As a qualitative study, we aimed for range and depth of experiences, rather than generalizability to the entire academic medicine population. We could not recruit from a national directory of DEI offices, leaders, or administrators in academic medicine. In 2018, Chen et al 3 identified 112 offices in 148 allopathic schools, but since then, institutions have created multiple offices and positions within schools and across departments. Third, we focused on those with formal titles, but effective DEI initiatives rely on the broader campus community, so our findings do not capture the experiences of other important actors. We interviewed only 7 participants with departmental-level roles, and thus may not sufficiently capture how these positions have expanded recently; systematic documentation is needed.

In this qualitative study, DEI leaders described multiple institution-level challenges to their work, including limited resources, unclear expectations, and a lack of evidence-based practices. While the transformation of academic medicine is long overdue, dismantling systems requires large-scale, sustained investment, grounded in theories of change, supported by evidence, and constantly interrogated for purpose, operationalization, and impact. Relegating the work to a handful of siloed individuals can set DEI leaders up for burnout and perceived failures. Recent events—from litigation against affirmative action to states’ efforts to eliminate DEI offices and related work on university campuses—reflect societal pushback against the (small) gains of the racial justice movements of 2020. 19 - 21 Sustained commitment to health equity, including the training and membership of the medical profession, is more important than ever.

Accepted for Publication: March 17, 2024.

Published: June 13, 2024. doi:10.1001/jamanetworkopen.2024.15401

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Esparza CJ et al. JAMA Network Open .

Corresponding Author: Michelle Ko, MD, PhD, University of California, Davis, One Shields Avenue, Medical Sciences 1C, Davis, CA 95616 ( [email protected] ).

Author Contributions: Drs Ko and Esparza had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Esparza, London, Bath, Ko.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: Esparza, London.

Obtained funding: Ko.

Administrative, technical, or material support: Esparza, Simon, London, Ko.

Supervision: Bath, Ko.

Conflict of Interest Disclosures: Dr Esparza reported receiving grants from Health Resources and Services Administration (HRSA) of the US Department of Health and Human Services (HHS) during the conduct of the study. Mr Simon reported receiving grants from HRSA during the conduct of the study and outside the submitted work. Ms London reported receiving grants from HRSA during the conduct of the study. Dr Ko reported receiving grants from HRSA during the conduct of the study. No other disclosures were reported.

Funding/Support: This work was supported by the HRSA of the HHS as part of an award totaling $3 791 026 with 0% financed with nongovernmental sources.

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The contents are those of the authors and do not necessarily represent the official views of HRSA, HHS, or the US government.

Data Sharing Statement: See Supplement 2 .

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• Published: 08 June 2024

A multi-method exploration of a cardiac rehabilitation service delivered by registered Clinical Exercise Physiologists in the UK: key learnings for current and new services

• Anthony Crozier 1 ,
• Lee E. Graves 1 ,
• Keith P. George 1 ,
• David Richardson 2 ,
• Louise Naylor 3 ,
• Daniel J. Green 3 ,
• Michael Rosenberg 3 &
• Helen Jones 1  

BMC Sports Science, Medicine and Rehabilitation volume  16 , Article number:  127 ( 2024 ) Cite this article

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Cardiac rehabilitation has been identified as having the most homogenous clinical exercise service structure in the United Kingdom (UK), but inconsistencies are evident in staff roles and qualifications within and across services. The recognition of Clinical Exercise Physiologists (CEPs) as a registered health professional in 2021 in the UK, provides a potential solution to standardise the cardiac rehabilitation workforce. This case study examined, in a purposefully selected cardiac exercise service that employed registered CEPs, (i) how staff knowledge, skills and competencies contribute to the provision of the service, (ii) how these components assist in creating effective service teams, and (iii) the existing challenges from staff and patient perspectives.

A multi-method qualitative approach (inc., semi-structured interviews, observations, field notes and researcher reflections) was employed with the researcher immersed for 12-weeks within the service. The Consolidated Framework for Implementation Research was used as an overarching guide for data collection. Data derived from registered CEPs ( n  = 5), clinical nurse specialists ( n  = 2), dietitians ( n  = 1), service managers/leads ( n  = 2) and patients ( n  = 7) were thematically analysed.

Registered CEPs delivered innovative exercise prescription based on their training, continued professional development (CPD), academic qualifications and involvement in research studies as part of the service. Exposure to a wide multidisciplinary team (MDT) allowed skill and competency transfer in areas such as clinical assessments. Developing an effective behaviour change strategy was challenging with delivery of lifestyle information more effective during less formal conversations compared to timetabled education sessions.

Conclusions

Registered CEPs have the specialist knowledge and skills to undertake and implement the latest evidence-based exercise prescription in a cardiac rehabilitation setting. An MDT service structure enables a more effective team upskilling through shared peer experiences, observations and collaborative working between healthcare professionals.

Peer Review reports

In the UK, 26 million people live with a long-term health condition, of which 24% have two or more conditions [ 1 ]. By 2035 the UK population is estimated to grow by over four million, with a 50% increase in the over 65s, and a quadrupling of those with four or more illnesses (multi-morbidities) [ 2 ]. In recognition of this rise in both population growth and associated chronic and complex medical conditions, the National Health Service (NHS) long-term plan identified the need for clinical exercise services within acute care pathways to aid the prevention and treatment of non-communicable diseases [ 3 ]. The need for specialist exercise staff within clinical settings, primarily with higher education qualifications / backgrounds, has been frequently acknowledged [ 1 , 2 , 3 , 4 , 5 ]. Yet until recently, a lack of clarity has existed regarding what exercise services are being offered, to whom, and by whom to create an effective system-wide approach in exercise service provision for long-term health conditions [ 4 , 5 ]. We [ 5 ] reported inconsistency in UK clinical exercise service provision, notably disparities in exercise specific job titles (e.g., clinical exercise physiologist (CEP) or exercise instructor) for individuals not part of statutory regulation, leading to inconsistency in staff scope of practice, knowledge, skills, competencies and experience within services [ 1 , 2 ]. Such variances have led to a diverse workforce ranging from vocational to postgraduate master’s level qualified staff delivering exercise within clinical settings making it difficult to compare within and across services [ 1 , 2 , 3 , 4 , 5 ].

In the UK, clinical exercise service provision are most frequently available for those with cardiovascular disease ( n  = 242) or more specifically for coronary heart disease, with the British Association for Cardiovascular Prevention and Rehabilitation (BACPR) providing guidance to standardise exercise provision [ 2 , 6 ] and the National Audit of Cardiac Rehabilitation (NACR) [ 7 ] auditing delivery. Although UK cardiac provision retains some similarities to its international peers (e.g., Australia) regarding service structure [ 8 , 9 ], there are differences in staff knowledge, skills, competencies and job titles for those delivering the exercise components [ 2 ]. Indeed, structured education and employment pathways for registered/accredited CEPs have existed internationally across long-term conditions for ~ 30 years (e.g., Australia and USA) [ 10 , 11 ]. Conversely, in the UK only 18% ( n  = 61) of exercise staff within cardiac services were postgraduate qualified CEPs [ 2 ]. This lack of consistency even in the most standardised service network is concerning when trying to regulate patient care and ensure patient safety [ 1 , 2 ]. The recognition of Clinical Exercise Physiologists (CEPs) as a registered health professional in 2021 in the UK, provided a potential solution to standardise the cardiac rehabilitation workforce.

Our recent case study examining a unique, successful and large UK cancer pre/rehabilitation service found that exercise specialists were (typically) degree qualified and possessed equivalent knowledge, skills and competency levels to apply for Academy for Healthcare Sciences (AHCS) CEP registration via an equivalency process [ 12 ]. Yet, this level of qualification is rare as 88% of exercise delivering staff in UK cancer services did not possess an undergraduate degree or higher [ 2 ]. Therefore, a purposeful case study to understand how registered CEP knowledge, skills and competencies contribute to the provision of a cardiac-based clinical exercise service is valuable to understand best practice, as job titles alone are not sufficient to judge service effectiveness or staff qualities [ 1 , 2 , 3 , 5 ]. Consequently, the service purposefully selected to be examined in this study was chosen because it was; (i) well established ( n  = 30 years) and delivered clinical exercise provision by registered CEPs as part of a multidisciplinary team (MDT), (ii) delivering exercise to wider range of patients with cardiovascular disease including high-risk cardiac and vascular conditions as well as with congestive heart failure, (iii) conducting research into enhancing exercise service provision for cardiac rehabilitation as well as other conditions, (iv) uniquely operating in a dedicated building for exercise services with use of a purpose build gymnasium for strength and conditioning, and (v) commissioned by the NHS. This purpose-built study aimed to explore how CEP staff knowledge, skills and competencies contribute to the provision of a cardiac-based clinical exercise service, how these components assist in creating effective service teams, how they differ to previously explored services, and to identify what challenges currently exist from staff and patient perspectives.

Design and theoretical underpinning

A case study format employed ethnographic principles (the exploration of peoples’ habits and beliefs) to uncover values and attitudes retained by the participants [ 13 ]. Multiple qualitative methods (online semi-structured interviews and face-to-face observation and field notes) were employed to explore the service from staff and patient perspectives both individually and collectively [ 13 ]. This qualitative multi-method approach, combined with the longevity of the study and data triangulation, was employed to reduce potential social desirability and bias from staff and patient perspectives [ 14 ]. Ethical approval was obtained from East Midlands - Leicester South Research Ethics Committee [ref: 21/EM/0227]. The lead researcher spent 2–3 days per week for 12 weeks in the service between April - July 2022. The ethnographic data via field notes and observation was the primary focus allowing rapport to be developed with both staff and patients before the completion of semi-structured interviews at the end of the 12 weeks [ 14 ].

Consolidated framework for implementation research (CFIR)

A comprehensive implementation framework (CFIR) was adopted [ 15 ]. CFIR links existing theories to create ideas concerning what works, where, and why within services, aiding future service implementation and evaluation [ 15 ]. Specific components relating to service delivery including staffing structures, staff skills and competencies, and patient perceptions allow a detailed exploration of these areas through contextual discussions regarding service operations [ 15 , 16 ]. All five sections of CFIR were drawn upon throughout this study (see Table  1 ) and provide a framework for interview guide (additional file 1).

The AHCS registered CEP-led cardiac service

This NHS service was created over 30 years ago, initially as a nurse and physiotherapist-led cardiac rehabilitation programme, which shifted to being CEP-led for exercise provision ~ 25 years. The programme is delivered over two sites. The primary site being community-based, the other being within a hospital. An umbrella term for the service is cardiac rehabilitation, yet face-to-face exercise support for patients is offered for a variety of cardiac (e.g., post-myocardial infarction), vascular (e.g., peripheral vascular disease) and heart failure (e.g., left ventricular failure) conditions. Patients are contacted after diagnosis or treatment (either surgical or non-surgical) regarding the uptake of physical (e.g., exercise), nutritional and psychological support. Full details of the intervention are provided in Table  2 [ 17 ].

Participant recruitment

Participant recruitment was based on convenience sampling across both staff and patients, with all CEPs expressing a willingness to participate. An initial (virtual) scoping meeting was conducted with the service multidisciplinary team (MDT) [ 17 ]. In this service the MDT included AHCS-registered CEPs, dieticians, cardiac nurse specialists, and clinical service leads/managers, with occasional consultant interactions in the event of unforeseen complications. The meeting explained the study aims and objectives, after which written consent was obtained covering each aspect of the data collection, including semi-structured interviews and observation. The final sample included MDT staff ( n  = 10); a clinical service manager ( n  = 1), clinical service lead ( n  = 1) who oversaw the intervention, AHCS-registered CEPs ( n  = 5), cardiac nurse specialists ( n  = 2) and a dietician ( n  = 1). Staff members were white British, female ( n  = 7) and male ( n  = 2) and black male ( n  = 1), aged between 26 and 45 (mean age of 40). All participants were employed full-time by the NHS with a minimum of two years’ experience in the role.

Patient recruitment was conducted using a verbal announcement before weekly classes ( n  = 8) asking if attendees ( n  = 45) wanted to participate in the study with field notes used to record observational data, including conversations. All patients attending the sessions verbally consented to observational data collection by the lead researcher and were provided with a written study information sheet and consent form. No one formally declined or stated any reasons for not taking part, but often participants preferred to concentrate on the exercise components without fielding questions during conversations for data purposes. Patients ( n  = 7) were white British, female ( n  = 3), male ( n  = 2) and Asian, male ( n  = 2). Patients were retired/not working, had a mean age of 61 years, reported various long-term medical conditions, but were specifically referred due to having one of the umbrella terms of cardiac-related conditions accepted via the service inclusion criteria (e.g., post-myocardial infarction, heart failure, peripheral vascular disease). The research team’s involvement was limited to participant recruitment and data collection.

Data collection

Staff participants had individual caseloads, although patients came together during group exercise sessions. Patients were assigned to specific sessions (days/times) of their choosing, yet could be unpredictable in their attendance due to various factors (e.g., health, transport). Observational data in the form of field notes were used to capture a sufficient cross-section of patient experiences across different sessions within the intervention, encouraging peer interaction and the promotion of shared experience where possible [ 12 ].

Semi-structured interviews

The semi-structured interview guide (see additional file 1) was developed based on the CFIR framework. Pilot interviews were conducted by the first author with three independent researcher peers prior to study commencement to enhance credibility and refine interview questions where necessary [ 12 ]. Interviews ( n  = 10) were conducted on an individual basis by the first author via a secure virtual platform (Microsoft teams) lasting 28 min on average (ranging from 24 min to 36 min). Written consent was obtained and interviews were visually and audio recorded with prompts and probes used to elicit more detailed responses from participants [ 18 ]. A brief verbal summary was provided by the researcher at the end of the interview to clarify the main points and allow participants to add further information (where required) [ 19 ].

Observation and field notes

Ethnographic principles were adopted during the observation of the setting, including the daily practices of the staff and their patient interactions [ 13 ]. Notable moments were written down in a note pad in the form of keyword entries [ 14 ]. Memories and reminders in the field notes then allowed the observations and conversations to be developed into a research log, typically completed during lunch breaks or at the end of each day, and never more than 24 h after the original observation to prevent the risk of memory fading and details being lost [ 14 , 20 ]. Such accounts were accompanied by researcher insights and interpretations of events which contributed to the understanding of the setting and a narrowing of the research lens [ 14 , 20 ]. During this process, the research team acted as “critical friends” and theoretical sounding boards [ 21 ].

Data analysis

Data obtained through the semi-structured interviews and field notes via participant observations were audio and visually recorded using a portable Dictaphone and Microsoft Teams, then transcribed verbatim. Data were thematically analysed manually using reflexive thematic analysis recommendations such as data familiarisation, generating initial themes, coding and finalising patterns of shared meanings underpinned by a central concept, and writing up using data extracts interspersed with researcher insights and interpretations [ 22 ]. Although the data themes generated were (deductively) linked in relevance to the pre-determined categories formed by the CFIR-guided research questions, the patterns of shared meanings were generated from the data themselves allowing interpretation and researcher contextual awareness to be discussed [ 22 ]. Flexibility in analysis was driven by both the prevalence (number of speakers articulating the theme) and the importance placed on information [ 22 ]. It is important to note that “data saturation” or “data adequacy” could be assumed as no new themes were identified when analysing the final few transcripts [ 23 , 24 ]. Primary analysis was conducted by the first author with frequent debriefing sessions with the research team to discuss, challenge and reframe the thematic structure [ 21 , 25 ].

Creating the non-fiction composite characters

Large volumes of data were collected and analysed, therefore, alongside confidentiality issues, it was deemed unrealistic to present singular case studies for all staff and patients [ 26 ]. Subsequently, four ‘composite characters’ were created to tell the stories and journeys throughout the service. The narratives of the four participants were created based on participants who shared some similar, common experiences or backgrounds during their time within the clinical exercise service setting, but also have potentially different perspectives on the culture of clinical exercise services [ 26 ]. The theme and identity that holds these characters together are; Character 1 (Sam) was a CEP with more than six years’ experience in the role, undergraduate degree qualified in sport and exercise science with additional vocational qualifications in cardiac rehabilitation; Character 2 (Lauren) was a CEP with a minimum of three years’ experience in the role, has a master`s degree in a clinical exercise physiology-related field and additional vocational qualifications in cardiac rehabilitation; Character 3 (Tom) represented the wider MDT team of non-CEP clinical leads/managers, clinical nurse specialists and dieticians who had undergraduate degrees, Health and Care Professions Council (HCPC) or relevant nursing council registration and excess of five years’ experience working in cardiac rehabilitation; Character 4 (Mira) was a retired/non-working patient attending the 12-week programme due to cardiac-related condition. The stories and interactions are told using the CFIR themes as underpinning headings, through the critical moments that occurred within the journey through the programme, but not necessarily in chronological order [ 27 ]. The composite character interactions are told from the researchers first-person perspective as they had come to understand them [ 28 ].

Lead researcher positioning

Given this study was based upon ethnographic principles, lead researcher self-reflexivity was important due to researcher background and training within clinical exercise provision [ 29 ]. This experience could provide pre-conceived ideas regarding exercise provision and enable a broader interpretation of participant concerns or thoughts [ 29 ]. Such reflection means that this article will retain the use of “I,” “me,” or “my” on occasion and as such refers to the first author [ 29 ]. What follows is a researcher’s story of “self” experience, alongside the “other,” in this case, the collective thoughts of staff and patients concerning their experiences within a clinical exercise service [ 29 , 30 ]. The data extracts represent each individual’s experiences and opinions at a given time and, in combination with my observations, re-creates a holistic view of experience representative of what any individual may be exposed to in the service at a point in time [ 29 , 30 ].

As an AHCS registered CEP who had been employed in a similar role previously, I acknowledged that I needed to see past my own preconceptions or bias and use such constructs as a basis to probe further into specific actions and behaviours. An open and honest relationship developed during the early weeks of observation with any researcher vs. participant barriers seemingly lowered after the initial 2–3 weeks. At the outset I would have classified myself as an outsider in collaboration with insiders given that I approached the service to observe it [ 31 , 32 ]. Yet, after this initial period and given my cardiac rehabilitation background, the relationship felt like it had morphed into one of an insider, in collaboration with other insiders due to the flowing nature of the conversations and the mutual respect that appeared to develop through shared experiences [ 31 , 32 ]. The following findings and discussion include reflective extracts that are in italics, indented and single-spaced to ensure separation from the descriptive representation.

Results and discussion

Introduction.

The service was exiting COVID-19 restrictions when I was first introduced to Sam, Lauren and Tom, resulting in a pre-arranged virtual discussion over MS Teams. At this point they had little knowledge of me, my background, or how I might portray them and their service. After a brief introduction I verbally explained my purpose. Following this, I paused to allow time for questions/concerns (of which few were raised). I felt my research aims were understood and an acceptance of me (given my background) was initiated. Although the online meeting was challenging as it was hard to gain a true representation and sense of feeling displayed by staff, I had experienced this before (e.g [ 33 ]) and was prepared for some silences [ 34 ]. Moreover, because all staff were engaged (currently or previously) in research projects within their work, there was an understanding of what to expect and a recognition that research is vital in furthering the evidence base and maintaining currency in the field. Their acknowledgement of, and familiarity with, research alongside their level of comfort with observation was reassuring. I would be surprised if other services without research links would have been so at ease. I left the meeting feeling content that I had set the tone for my face-to-face encounter in a few days.

Face-to-face contact

I arrived on the primary community-based site early hoping to create a good impression, but also expecting to see how staff prepared for the day ahead. I received a warm welcome with open body language while being re-introduced to the team by Sam. A walk around the facility followed, accompanied by an explanation of the current staffing levels (two CEPs had recently left) and how that impacted exercise sessions. The building was two-floored, on the bottom was a café and seating area for patients to relax, prepare and recover from their exercise sessions. It had toilets, changing and showering facilities and included the main gym floor area where the cardiac-based sessions took place. The first-floor featured meeting rooms, offices, assessment rooms and exercise studio space which contained portable equipment for use within classes when applicable. The first hint of NHS involvement and clinical working was the separation of these spaces. There was a clear divide from a logistical perspective; keypad restrictions were in place throughout the second floor to negate public access, alongside telecom access through the front door into the building itself. The gym environment had a friendly, yet clinical feel, mainly due to uniforms displaying NHS logos, half of which were worn by clinical nurse specialists. Mask wearing by staff, although no longer mandatory by law, provided another example of how (inadvertently I`m sure) the service presented a clinical feel. Yet its size (roughly 20 m by 15 m) and the volume of apparatus (six rowers, two Ski Ergs, double digit treadmills/X-trainers, resistance machines, TRX suspension trainers, free weights and portable equipment) made the gym unique in its appearance compared to other clinical services I had observed.

This was a considered layout that maximises the available space. An area for walking around the equipment was ideal for a warm up and cool down and guidance resources were on the walls (information that could remind patients about how they should be feeling such as Rate of Perceived Exertion (RPE) and claudication charts, stretching and resistance-based exercise posters). Anecdotally this is not uncommon, but I`d be interested to see how staff use these – do they get patients to actively engage with the materials? Or, are they included because it`s best practice only?

Sam and I discussed current service operations, but swiftly digressed into how incorporating virtual exercise classes could improve their offering. There was a feeling from Sam that integration of online sessions could potentially lessen some of the access barriers regularly cited by patients (e.g., transport), in addition to advancing their `menu-based` delivery [ 35 ]. Rather unexpectedly, this discussion shifted into a Q&A led by Sam who wanted to understand my experiences of virtual exercise delivery (an area I had previously observed, e.g [ 33 ]).  Offsetting safety with expanding reach and exercise adherence were main discussion points, but from a personal perspective being a sounding board for virtual exercise delivery in practice felt fantastic and demonstrated a level of acceptance even at such an early stage of my stay.

One of my underlying concerns before I entered the service was the staff perceptions of me, as an unknown entity I expected doubts about my skillset and knowledge of the setting. It was refreshing to openly chat about patient screening and risk assessment, accessibility, exercise prescription and adherence – all of which I was familiar with and could offer insight into. My impression was that Sam gained confidence in my ability during our conversations (shared knowledge and findings) which demonstrated my own researcher and practitioner credibility. Over time I found these types of discussion became more prevalent and enabled me to be accepted as a peer rather than seen as an outsider collecting research. My opinions mattered and a more natural relationship with the staff began to form.

CFIR Sect. 1.1 – CEP-led service conception

I entered the service knowing that certain components were unique compared to the wider cardiac rehabilitation landscape through my previous research; primarily the sole use of registered CEPs for exercise delivery, compared to unregistered CEPs or exercise specialists with vocational qualifications [ 2 ]. I wanted to understand the reasons behind this; Did it change, why and how long has it been like this? Numerous conversations skirted around the subject over the weeks as both Sam and Lauren acknowledged that it was all they had known within this service. Interestingly, they talked about their initial assumptions regarding exercise delivery within clinical services, which centered on the belief that others (services) followed suit and utilized CEPs similar to themselves with training and education in exercise prescription and the ability to become registered once AHCS registration became available;

Sam: “I`ve never known anything different, it`s only when you start talking to other people (at other services) that you discover they are different…lots (of services) are nurse or physio-led…I don`t know why or when we changed…but to me it comes down to the knowledge and skillset…exercise prescription quality and knowledge…I feel the CEP background of exercise prescription is strongest due to CEP degree training (undergraduate and/or postgraduate)…physio`s and nurses look at things in a different way, more recovery focused”.

Without wanting to misrepresent the abilities of other health professionals, Sam made it clear that CEPs were his choice to lead the exercise component within clinical services. CEP inception within this service, however, came from somewhere and it was only during a conversation with Tom at the back end of my stay where I finally found some answers;

Tom: “We were working with physiotherapists some ~ 25 years ago, but they were coming to the end of their careers, so we looked at what was going on in America, how their private care providers worked. At the time BACPR was just taking off, we did some exercise-specific training for the nurses and we were approached to see if we wanted to take on a very young exercise specialist (officially titled a CEP) for 7 hours a week to complete our assessments and it grew from there…it was a new concept, nationally rehab was more about the nursing teams and physiotherapists… overall care could be very static and traditional for these patients…discharged at 10 days…rehab was 6–8 weeks post-MI but (exercise) with the physiotherapist felt quite static…a one size fits all approach…we felt that having a CEP that was solely exercise focused would be beneficial”.

This was one of many lightbulb moments for me. This service did not want to just follow tradition. Although they had no issue with the exercise provision that was being provided and valued the work of the current team (physiotherapists), they wanted to explore additional ways to improve the service and enhance the care they offered…they felt that a combination of healthcare professionals would do this and expanded the skillset across the team.

Tom identified that personalized patient care had to be at the forefront of service delivery. Exercise, although prominent in later stage care, was now even more vital in the rehabilitation process, therefore, the most specialist people (CEPs) were needed to deliver it.

CFIR Sect. 1.2 – referral pathways and health care professional interactions

It was clear from the outset that this service had a well-established referral pathway due to the levels of organization and clear protocols that were in place (e.g., referral forms sent via secure NHS email). Lauren explained that “Patients are picked up on the wards by the nurses, they’re referred straight into the service, from bedside risk factor education to consent for exercise participation”. From a patient perspective, the ease of the journey was vital. Mira acknowledged that the service was efficient; “I couldn`t believe how quick I got started and how thorough it was…they helped me understand my condition and that it was safe to exercise”. It became apparent when discussing referrals that the ability to educate and `recruit` patients efficiently was, in part, explained by their capacity to engage straight away, but also the knowledge and skills of how to communicate with patients. Conversations were engaging, open and friendly, with active listening taking precedence. I observed Sam discuss Mira`s procedure (angioplasty) and then listened as he provided a detailed brief of the steps she would go through during her time in the service, allowing questions along the way.

Active participation in research was also vital in the development and exploration of different referral pathways. One example being the Post-sternotomy Cardiac Rehabilitation Exercise Training Study (SCAR) which identified that (qualifying) patients could be exercising earlier than guidelines stated (2 weeks rather than 6 weeks post-sternotomy) [ 36 ]. This innovative research was translated into practice and shifted the referral process guidelines within this service into a new evidence-based format;

Sam: “I worked on the SCAR trial which monitored patients during exercise earlier than normal post-surgery…6 weeks was the guidance, but that had seemed to be plucked out of thin air with no real evidence…once the study had finished I went to the surgeons at the hospital, delivered the outcome evidence and developed new referral pathways…we have started bringing people in earlier, I had someone today who is at 4 1/2 weeks, rather than them sitting at home festering for 6 weeks”.

Generally, exercise services will rightly follow national guidelines (e.g., BACPR) for patient recruitment, this service (due to the knowledge and skills of the CEPs) looked to use their latest evidence to enhance patient outcomes in areas such as cardiovascular fitness in an earlier timeframe [ 36 ]. Moreover, this decisive integration into the rehabilitation system allowed a speedier onward referral into the CEP-led phase IV service that was available on site but delivered by a private partner. The concept of phase IV is nothing new, but having CEPs deliver it is quite unique [ 2 ] as Sam explained to me;

“It`s great being able to see patients move from us (to phase IV) and remain here…we can follow their journey from a distance…it`s great to know they`re remaining active…being looked after by similarly qualified CEPs in phase IV…I don`t think this continuity of care is common”.

Having that seamless onward referral process extremely positive for the service. There was a level of trust in Sam`s voice, happiness in the knowledge that patients were going to be looked after by equally qualified peers.

An on-site MDT was a positive factor in the whole referral process (more control and capacity to deal with the patient flow) [ 37 ]. From working in this setting, I know that creating a fluid, timely and consistent patient journey is not easy. Here, in part, it came from longevity of the service (pathway development over time), but primarily through the knowledge of how a clinical service should operate and a willingness to implement it by the team. The service had long-standing relationships with the hospital-based health care professionals (e.g., consultants) which enhanced their referral pathways. Even though patient suitability and uptake fell within the realms of Tom, frequent conversations by all team members could be had with consultants regarding surgical or non-surgical treatments, complications, or re-referrals if contraindications were identified at any point. Yet, even in this service, Sam made me realise that interactions with health care professionals can, on occasion, be difficult and sometimes a barrier to providing specialist care;

Sam: “…we speak to consultants, there was a time when they were not really sure who I was or what I did, for example, if I noticed someone hadn’t been started on a medication and queried it, they’d wonder why as I was not a nurse…I think it was a lack of understanding…it’s a fairly new role and not many trusts have CEPs”.

This lack of awareness, even in such an innovative service, was concerning, but not uncommon based on my own experiences. Sat in the office during admin time, I wanted to understand the cause of this issue so I questioned the team;

AC: “How could you improve your relationship with other health professionals?”

Sam: “…recognition of our role within a hospital setting in terms of registration is one way, but it`s challenging, we’re not recognised as a as an allied health professional, even though we`re now AHCS-CEPs”.

AC: “How`s that a problem?”

Sam: “It’s the understanding of our role, people (in the NHS) don’t feel that we have the skillset to deliver the intervention, sometimes it can be an issue, I`m sure it could impact referrals (in other services)” .

AC: “ But it doesn’t here ?”

Sam: “For us, not massively, but I would imagine it could do if we were not as well established as we are”.

On a wider scale, referral pathways could be impacted if a lack of confidence from referring practitioners were identified [ 4 ]. Moreover, perceptions about scope of practice may impact the patient journey, and ultimately the level of care they receive [ 4 ].

After two months of observation it is evident and acknowledged by the team that service links with health care professionals were in place. Having Tom on the wards with a nursing background made the whole process easier. Perceived or real scepticism from other health care professionals in NHS regarding the skillset and scope of CEPs was concerning. The questioning of their belonging and what they could offer, especially as they now hold healthcare registration, demonstrates that an awareness of CEPs is needed to improve interprofessional relationships which can only improve healthcare services in the long-term.

CFIR Sect. 2.1 – patient integration and support

A few weeks into my observations and keen to see the level of support Mira received, I sat in on an outpatient consultation (on site in the community exercise facility) led by Tom. This was the first time Mira met Tom outside of the hospital environment (4-weeks post-surgery). We sat in a small office upstairs which reminded me of a doctor’s surgery with its white walls and randomly placed NHS-based posters. There was a relaxed atmosphere yet the discussion, although polite, friendly and occasionally humorous, was clearly one of a patient/nurse due to its interview-based format. Tom and Mira exchanged high volumes of questions/answers/explanations, with the occasional probing for additional information by Tom. Mira described the build-up to the heart attack; “ …I had shortness of breath on various occasions when we were walking…it led to some chest pain…my husband called 999”.

Throughout the conversation Tom was friendly, clinically focused, yet compassionate during the enquiries, empathy was evident and matched by a clear understanding of the experience Mira had undergone. It was fascinating (and not uncommon I`m sure) to hear Mira describe the discomfort as “coming out of nowhere” , an interesting observation given the discomfort occurred at “multiple times” leading up to what was eventually diagnosed as a heart attack. Tom educated Mira that her symptoms were signs of a heart attack and not uncommon, frequently using lay terminology to explain the complexity of the condition and associated surgery via visual and verbal descriptors (e.g., pictures). This demonstrated a high level of knowledge, skill and experience as it factored in patient learning styles to the information delivery. In addition to re-enacting the sequence of events, this consultation was used as an extension of the behaviour change discussions from Mira`s bedside (e.g., risk factors for future events). The conversation shifted towards medications as Tom described (in great depth) each tablet Mira was taking, its purpose, side effects and why it was important.

I would have expected medications to have been discussed earlier, only to discover (via Tom after the consultation) that it had been, but to enable adherence there was a constant reiteration in the importance of compliance. This in itself formed a major part of Mira`s lifestyle change, one that had been thrust upon her quickly. I got the impression that without this discussion, medications could have been seen as short-term and not necessary, just from her body language and terminology used.

Mira could easily have fallen back into a curative mindset, no longer associating risk of future events with medication conformity. This again was a teachable moment created by Tom and relayed in a manner that Mira appreciated and hopefully accepted. A referral for CEP assessment was explained and consented, with Mira extremely receptive to attending. Overall, the appointment lasted ~ 45 min, not especially drawn out by either party, so I would take this as a standard timeframe. This consultation confirmed that support was individualised and tailored to Mira. Moreover, it continued the theme of a seamless patient journey created by a diverse MDT working efficiently in conjunction with their service protocols [ 37 ].

The behaviour change element was definitely initiated then followed through by Tom. Long-term observations (12 weeks) showed that it was Tom who began the goal setting process and CEPs only got involved during the exercise sessions when trying to encourage patients to work in a range of intensity or duration that facilitated progression. Behaviour change was not something the CEPs touched on in great detail, in fact, they themselves recognised it as an area they needed to improve and they had undergone a change recently to try an address the balance… .

I arrived on site (during week 8) to find no exercise sessions were planned. Sam explained that a behaviour change/education session was taking place;

“…we`ve tried the traditional exercise followed by education sessions that most services use…these were ok but some (patients) weren`t in favour…we now tell people there is no exercise this week and to turn up for some talks about how to manage their condition, but uptake hasn`t been great and the feedback is that they`d prefer to be exercising” .

The session I witnessed was led by Lauren via a Microsoft PowerPoint presentation. The group was small, I got the impression (closed body language through crossed arms) that they really wanted to be exercising rather than talking about cardiac risk factors, in fact, there was little engagement in the talk, and they finished early. Interestingly, Mira asked if they could use the gym before they left. After the talk Lauren gave her opinion on how it went; “It`s hard to find a balance, the turnout was disappointing (only 4 people rather than the 12–15 in sessions normally) and lack of interaction made it hard for me”. During the talk Mira frequently nodded, acknowledged information and appeared to understand the content, yet was not willing to step outside of the self-created comfort zone and answer questions that were posed or even challenge ideas that were presented, either positively or negatively. Was this due to the lack of numbers, or just the nature of the situation, i.e., discussing personal trauma in front of others, even those experiencing similar circumstances can be daunting and intrusive? Mira`s passion to exercise however was clear;

“…To be honest I`ve come because I feel that I should, the team are great and I don`t want to let anyone down, but really I`d prefer to be downstairs (exercising)…I can read this in a booklet I got off Tom anytime”.

There seemed to be a lack of value associated to the education (Mira`s perspective), suggesting that a format change may be needed for future cohorts.

That night I thought about behaviour change within services, especially what I had experienced and seen over the past few weeks. Was it ineffective or was it just wrong place/time in this service? Staff here were excellent at delivering impromptu support during conversations. Moreover, the patients identified the CEPs as exercise specialists, this is what they wanted from them, to get `fitter`. But, if the CEPs continued to subtly use their communication skills to integrate more behaviour change prompts into simple conversations, it may be sufficient. Sam and Lauren had the skills; the communication was good, specifically their empathy and active listening as they took note and responded to Mira when required. What this service lacked was a clear strategy, but not through a lack of trying or the ability to deliver the content successfully. A generic consideration may be how/when services present behaviour change information to a patient, who does it, and the depth of information needed.

CFIR Sect. 2.2 – patient safety mechanisms – `the huddle`

Patient safety underpinned everything I witnessed within this service. One of the most prevalent and enlightening examples of this was the `team huddle`, a daily activity that included the whole MDT. This event was equivalent to a pre-exercise session meeting taking place in a small conference room, whereby all patients were discussed re: progress and status (new starters and current attendees) including condition overviews and adherence. New starter referrals were explained in detail by either Sam or Lauren to ensure everyone who had contact with them were aware of any considerations such as medications or multi-morbidities. Sam/Lauren, in conjunction with Tom, completed the fitness assessment and retained primary responsibility and case management of specific patients during the exercise component, yet all staff were required to monitor the sessions and therefore needed these updates. On a Friday the discussions included a summary of the past week and information about the forthcoming week, including session fill rates, fitness testing waiting lists and any issues or potential problems (e.g., service capacity due to staffing levels or holidays). The shared responsibility and addition of Tom into these discussions highlighted the integrated nature of the service;

Tom: “There is nothing better than sitting and listening to the team discuss patients…there`s a real crossover of skills and learning via the shared experiences…everybody’s upskilling without even knowing it”.

This collective and unified working process is an unofficial and unaccredited knowledge exchange that enhances MDT skillsets [ 37 ]. The huddle facilitated this learning. Allowing different members of the team to lead the huddle each day fostered personal growth, developed workplace craft and enhanced the team ethic, demonstrating that each member held equal status concerning patient safety and were capable of adhering to NHS policy in this area [ 37 , 38 ].

Staff were vocal, no one hid, which demonstrated solidarity and respect – no fear of being chastised if they spoke. In the past hierarchal status might have overridden everything else, but this discussion was informal with room for social banter if the opportunity arose. Kudos regarding any achievements were given, but at the same time areas for improvement and development were highlighted. I watched an inclusive and engaging 15–20 min `chat` each day which created a learning environment in patient centered care, something I`d have liked to have been part of in the workplace.

CFIR Sect. 2.3 – patient safety mechanisms – fitness assessments

Patient facing activities that required a high level of risk management and in-depth safety protocols were often completed jointly between Sam/Lauren and Tom, an example being fitness assessments. Clinical services utilize a variety of fitness assessments, some highly clinical (e.g., cardiopulmonary exercise testing) and others more field-based (e.g., 6-minute walk test) [ 39 ]. The primary one in this service was a submaximal bike or treadmill assessment with a 12-lead electrocardiogram (ECG) and blood pressure monitor attached to the patient during the assessment. I observed Tom and Lauren work in combination to monitor Mira during a bike assessment. Lauren used lay terminology to explain the procedure, including the function and purpose of the ECG and focusing on what Mira would be asked as she pedaled (such as RPE levels). Mira seemed slightly anxious as Tom attached the leads, uncertain of what lay ahead, but Tom was empathetic whilst explaining how the results would help Mira`s exercise programme design. Mira was happy with this and continued though the assessment, pedaling at the required speeds against the increasing resistance and answering Lauren`s questions regarding RPE levels, while Tom monitored any ECG changes. The assessment itself went without issue. Mira looked comfortable throughout, even when faced with increasing resistance she challenged herself, clearly understanding the importance of providing an accurate representation of her capability as was explained by Lauren and Tom before she started. This itself displayed a high level of communication skill, specifically empathy as Mira was anxious about the unknown, yet this was managed by Lauren using active listening and questioning to dispel any undue fears. After Mira had left, I questioned Lauren and Tom about the importance of the assessment process in relation to patient safety;

Lauren: “Assessments are really important…it’s the first time we see that patient from an exercise viewpoint…understanding their fitness levels and their physiological responses is vital…observing the ECG, detecting issues…you need to be competent by conducting the assessment correctly, but also interpreting that information, then developing an exercise prescription that is fit for purpose”.

Lauren recognized that patient safety is multi-dimensional. Not only is there a theoretical knowledge requirement of how to carry out the assessment, there is the skill of completing it safely whilst screening/monitoring patients and then competently analyzing the results to formulate suitable exercise prescription. Tom outlined the nurse role;

“…I`m responsible for recognition analysis; having an understanding of ECG, chest pain management, the safety aspects for patients that have had a sternotomy during an assessment, aetiology of any particular condition and what adverse reactions we could see…we monitor that in conjunction with the CEP, it`s a shared responsibility, the CEP takes the lead but we collaborate throughout”.

It was interesting to hear that this service had adopted a policy of using both CEPs and clinical nurse specialists within the assessment process to further reduce risk. This `belts and braces` approach seemed to be valued in this service. It was good to see this level of collaboration between staff as I doubt a newly qualified, inexperienced CEP, with minimal exposure to a real-world setting would have been able to undertake that assessment safely and effectively without it. Personally, I think only being exposed to this type of situation would prepare you, therefore, having work placements during your training would greatly increase your understanding of the standards needed to provide safe, patient-centered care in a workplace, thus raising the standard of CEPs coming out of education settings.

CFIR Sect. 3.1 – MDT roles: training and development

Internal training and development have been recognised as good practice within MDTs [ 37 , 38 ] and it was pleasing to hear that this was evident in this service;

Sam: “I came here for work experience and basically stayed…the varying types of experience was great, you had people that had worked here for over 10 years…there were loads of opportunities to learn from others in the team, being able to sit and observe… discussing how and why they worked that way”.

As Sam moved quickly to assist Mira with the rower set up, I pondered about how this type of learning or craft within a real-world setting can only be achieved with the support of highly trained and skilled peers [ 38 ]. Moreover, a few weeks later the subject of planned supervision and observation was raised again by Tom;

“…CEPs come out of university with a masters or BACPR qualifications and that’s great, but it`s less clinical and includes less placement time (if any in non AHCS accredited masters courses) than a nursing degree… it’s that hands on experience that`s really important and where the learning occurs, and that`s missing”.

Tom identified that work placements are the cornerstone of a nursing degree, and this type of experience cannot be overlooked for CEPs. Here, internal staff training included observation of all MDT roles during the first few weeks of employment. This promoted growth for all staff, i.e., leadership opportunities for more senior members of the team through unofficial mentoring, and theoretical learning and practical application experience for the newer members of the team. Tom stressed that staff development was vital for preserving a consistent level of provision (and staff engagement/retainment) within the service. Moreover, the research generated by the team added further knowledge and skill development as described by Sam; “ …completing research with the university brings a whole new light on rehab as a service…our learning and how we think about exercise prescription”. I had never been exposed to a service that actively completed research within a cardiac rehabilitation setting, Lauren continued;

` …a couple of years ago the HIIT (high intensity interval training) or MISS (moderate intensity steady-state training) trial was done here…it heavily influenced our exercise prescription…recently we`ve completed the SCAR trial with similar changes being made in how we exercise patients .`

Interestingly, the research, although focused on exercise prescription in most cases also influenced MDT practice as a whole as Tom explained during our interview;

Tom: “SCAR was a really big learning curve for the nursing team who were set in their ways with regards to enrolling patients, but we embraced it and changed our referral policies… implementation into wider practice, regional or beyond is hard though as it requires a change in resources and working practice”.

Research was a driving force throughout this service epitomised by the working practice changes based on the scientific evidence and forward thinking. Whether it related to exercise prescription design or delivery, referral pathways, internal training programmes or progressive recognition of skills, this service pushed the boundaries in the field of cardiac rehabilitation through a determination to expand the evidence base and implement new findings into practice.

When I reflected on what I had been told, I concluded that real-world practitioner research completed by highly qualified and skilled practitioners with academic understanding was the ideal solution for advancing the field. This service is unique due to its long standing relationship with the local university developed by practitioner links and the academic development of staff. Such collaboration demonstrates the value in closing the gaps between research and practice yet I had not experienced this before. The evidence they unearthed was shared within the team and the service adapted, it didn`t conform to traditional guidelines, they took the proactive approach to develop their own safe and more effective practice based on scientific literature which I feel can only be commended.

CFIR 4.1 – theoretical knowledge levels

Exercise testing, assessment, interpretation, prescription, delivery and outcomes evaluation for individuals with chronic and complex conditions requires a specialist knowledge base and expertise [ 1 , 3 , 40 ]. Eight weeks into my visit and during an afternoon gym session I saw something that I had never seen in this setting before. Not unusually, patients were using their programme cards as guidance and referring to the charts on the walls on occasion for assistance in clarifying exercises or intensity, which answered one of my previous questions about Mira actively using resources rather than seeing them as decorations. But, more significantly as I walked past the rowing machines I noticed the speed and intensity of one particular patient. I know from speaking to Lauren that patient autonomy was encouraged, i.e., CEPs wanted patient`s to challenge themselves (safely) using the guidelines they have devised. Yet, this patient could have been in a regular `mainstream` gym. Rowing at a pace of ~ 2:00 min/500 meters for 1000 m is not something you generally see in a phase III cardiac setting in my experience, and would be challenging for most people. Technique was good; legs and arms in tandem, breathing maintained and visibly working hard. It was enlightening and I wanted to understand what gave the CEPs the confidence to safely prescribe and monitor this level of exercise and to have the confidence to let patients do it;

Sam: “…core knowledge is physiology of the body, cardiovascular response to exercise and the cardiovascular disease process including risk factors…you definitely need to have done a bachelors in sport and exercise science…also a masters specifically in exercise physiology would be ideal covering associated pathologies like obesity, diabetes…we get a wide range of patients presenting with multiple morbidities”.

Lauren reiterated the need for higher level academic qualifications and knowledge in exercise prescription and physiology, whilst stressing that experience in the role was vital. The stipulation of high-level qualifications (e.g., master`s degrees) is recommended in clinical exercise services [ 1 , 3 , 41 ] and in this service, it allowed for a more expansive patient inclusion/exclusion criteria as I discovered in one conversation with Tom;

“Some services are much more cautious in terms of high-risk patients or exercising patients to a level that`s effective…we’ve done a lot of research and have staff that are highly qualified, so we accept higher risk conditions and understand how to safely progress them”.

Academic knowledge of physiology and exercise prescription not only underpinned the way CEPs approached each patient but allowed a higher catchment of patients. Having AHCS-registered CEPs with exercise-specific knowledge and the application of it within research studies extended into challenging their own service effectiveness, alongside national guidelines which have been previously identified as ineffective [ 42 , 43 , 44 ].

Discussions concerning current practice were frequent. The topic of other services not aligning with newly updated literature and that national guidelines were outdated, or least needed more depth, demonstrated that a culture of learning and service evolvement was in place. This service went further and applied changes based on the evidence base (some of which they created) to support their rationale for innovative exercise design and delivery.

CFIR Sect. 4.2 – practical skill application and competency (effective task completion)

Clinical exercise skills relate to the practical application of theoretical learning (e.g., conducting physical assessments) and the ability to communicate the information effectively to patients [ 1 , 45 ]. Having previously discussed the importance of monitoring physiological responses in ECG or blood pressure during assessment, the implementation of the latest HIIT exercise design and acceptance of complex (higher risk) patients, it became clear that monitoring patients was a critical skill. One area of this was the ability to demonstrate and identify how to progress (or regress) exercise by coaching patients through sessions and leading group exercise activities (warm up/cool down) [ 46 ] as explained by Lauren after a group session warm up;

Lauren: “…putting exercise onto paper is the theory behind the practice….coaching patients, leading the class, making sure that everybody is safe and they understand what you`re asking them to do are the practical skills….ongoing monitoring using RPE, heart rate and pain scales is vital…adaptations could be range of movement, intensity, options for balance, avoiding exercises that could exacerbate risk such as quick turns or direction changes…we have to respond to the patient, how they feel…it cannot be generic and it might change daily”.   Working patients intermittently at heart rate percentages challenging 70% or above required clinical knowledge of physiology, patient history, accurate fitness assessments, precise exercise prescription and most importantly, excellent exercise delivery skills and monitoring throughout. For me, such replication across services requires an AHCS-CEP level of knowledge and skills as those individuals have demonstrated competence in adapting exercise to meet the needs of each individual and are capable of monitoring them at a level that minimises risk yet increase effectiveness.

The CEP role is diverse and complex, therefore, skills and competencies are wide ranging and not just associated with exercise per se [ 1 ]. Tom expanded and emphasised that potential employees (in this service) needed communication skills such as empathy, but also experience (and competency) in working with real patients;

Tom: “…we have some really challenging patients that don’t want to engage or haven’t got the literacy levels…CEPs need some of those softer skills that help to deliver personalized care to patients. I feel that at the moment that isn’t there nationally, when we’re interviewing CEPs with academic ability (master’s level) they don’t know what they don’t know… they’re hit with patients that come from all sorts of backgrounds, have all sorts of challenges and this is where soft skills come in”.

The combination of CEP and wider MDT interaction during daily/weekly huddles, the learning culture of shared practice and craft learning (teachable moments), alongside research exposure and proficiency in communication ensures that the knowledge and skills of this team were exceptional. I feel that this combination of theoretical and practical learning sees knowledge, skills and competency unify [ 22 , 40 ]. Similar research [ 40 ] identified that education alone would not be sufficient to create a well-rounded or complete CEP. The specialist nature of the role requires exposure to real world practice, with peer support and training (akin to Tom`s suggestions) essential [ 38 , 46 ]. This service provided that support network in abundance with staff able to reference it when applying for AHCS registration.

Hearing Tom, Lauren and Sam discuss the knowledge, skills and competencies required by a CEP made me think about how the AHCS registration could change the landscape of clinical exercise provision. Firstly, individuals could demonstrate they had undertaken the education and training akin to other health care professionals (e.g., physiotherapists), including rigorous assessments and exposure to the up-to-date scientific evidence base. Secondly, academic institutions would have to conform to Clinical Exercise Physiology UK standards to gain AHCS accreditation, updating their curriculum accordingly and ensuring it contained suitable work placements for students to observe those teachable moments (one of Tom`s concerns). Finally, I know from my own registration that behaviour change and communication skills feature prominently within the registration requirements, thus increasing student proficiency in these areas is essential for effective service provision. This service is unique, it has multiple AHCS-registered CEPs within it and a research arm that provides opportunities for staff to participate in innovative projects that undoubtably advance their knowledge within the field. Even so, a learning culture that supports staff and enhances their skills through shared practice has been created and exposure to it makes me feel that we (clinical exercise service providers) have to learn from it.

CFIR Sect. 5.1 - service effectiveness

My experience has shown me that service effectiveness can be subjective depending on who you are talking to and what level of interest (or bias) they have. Translating evidence into practice is not always easy, it requires a high level of understanding between team members who can communicate with each other to implement change as described by Lauren;

Lauren: “…we`ve all got different ways of prescribing exercise but we have a similar level of education, so if I talk about something and explain what I’m doing the other person understands…so qualifications are a big part of it (effectiveness) plus this culture of always trying to find the best ways of working … the passion of the staff that genuinely want to give their best and as a result of that our programme has got lots of options (for patients)”.

Moreover, the individualised case management approach, identified as effective in clinical MDT settings [ 37 ], was one of the real strengths of the service displaying a dedication to patient-centred care as recognised by Tom: “.from bedside to cardiac discharge post-exercise the patient receives personalised care…we help people get back to what they want to do in the long-term”. It would be remis of me not to highlight the strict NHS safety protocols in place which ensured streamlined referral pathways and the safeguarding of patients throughout their journey. Additionally, the facilities that were available to patients were, in my opinion, unrivalled in this field and duly recognised by the team while we were delivering exercise sessions;

“…w e are lucky with what we have in terms of our facilities…we’re able to use a fully equipped gym…we have consultation rooms, assessment rooms with dedicated equipment and clinical monitoring, other services only have circuit-based portable equipment” (Sam).

These processes all contributed to high levels of patient care highlighted by the 81% uptake from those eligible into the service, compared to the national average of 52% [ 7 ].

Strengths and limitations

The main strength of this study was the multi-method exploration of clinical exercise provision which allowed an in depth look at service operations and effectiveness, including staff knowledge, skills, competencies and challenges. The study was however conducted as a single service case study focusing on one long-term condition, therefore limited by a small, convenience sample. Some caution must be taken in generalising across the cardiac rehabilitation landscape as this service, although operating as an MDT, solely employed CEPs for exercise provision and had links to an academic institution for the research activities which is not widely available in the UK. It does, however, go some way in explaining the key considerations for effective clinical exercise provision for a long-term condition.

AHCS-registered CEPs within this cardiac-specific, hospital and community-based service were essential for the provision of innovative and individualised exercise prescription, underpinned by their high levels of academic education and participation in real-world clinical research trials. The localised (site specific) MDT structure enabled staff upskilling through shared peer experiences, observations and collaborative working between CEPs and healthcare professionals, ensuring effective working practices were maintained throughout the service. Clinical nurse specialists enabled a smooth transition of referrals from hospital into the exercise component of the service and delivered most of the behaviour change elements of the programme. Registered CEPs were able to take part in impromptu lifestyle conversations and `teachable moments` with patients, yet a clear strategy for delivering behaviour change information required development. It is important to consider that this cardiac-specific service was unique by solely employing registered CEPs for exercise provision and had links to an academic institution for the research activities which is not widely available in the UK. Future research should explore daily practices within CEP-led clinical exercise services across other long-term conditions (e.g., pulmonary rehabilitation) to assist in the generalisation of findings. These observations should focus on understanding how exercise specialists utilise their knowledge, skills and competencies within a service to create optimal exercise prescription.

Availability of data and materials

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

Abbreviations

British Association for Cardiovascular Prevention and Rehabilitation

Clinical Exercise Physiologist

Electrocardiogram

Multi Disciplinary Team

National Audit of Cardiac Rehabilitation

National Health Service

Academy for Healthcare Science

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Acknowledgements

We would like to thank all the research participants without whom this study would not have been possible.

Patient involvement

Patient involvement was completed during the ethics application with a conclusion that the research methods were suitable with exploration required in this area.

This research was funded by Research England International Investment Initiative funding (i-CARDIO).

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AC contributed to the design of the study, collected and analyzed the data, and led the writing of the manuscript. HJ secured funding for the study. HJ, LG, KG and DR contributed to the study design and advised on data collection and analysis. All authors contributed to data interpretation and writing of the manuscript and approved the final version.

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Crozier, A., Graves, L.E., George, K.P. et al. A multi-method exploration of a cardiac rehabilitation service delivered by registered Clinical Exercise Physiologists in the UK: key learnings for current and new services. BMC Sports Sci Med Rehabil 16 , 127 (2024). https://doi.org/10.1186/s13102-024-00907-4

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7th edition table of contents

• Front Matter
• 1. Scholarly Writing and Publishing Principles
• 2. Paper Elements and Format
• 3. Journal Article Reporting Standards
• 4. Writing Style and Grammar
• 5. Bias-Free Language Guidelines
• 6. Mechanics of Style
• 7. Tables and Figures
• 8. Works Credited in the Text
• 9. Reference List
• 10. Reference Examples
• 11. Legal References
• 12. Publication Process
• Back Matter

List of Tables and Figures

Editorial Staff and Contributors

Acknowledgments

Introduction (PDF, 94KB)

Types of Articles and Papers

1.1 Quantitative Articles 1.2 Qualitative Articles 1.3 Mixed Methods Articles 1.4 Replication Articles 1.5 Quantitative and Qualitative Meta-Analyses 1.6 Literature Review Articles 1.7 Theoretical Articles 1.8 Methodological Articles 1.9 Other Types of Articles 1.10 Student Papers, Dissertations, and Theses

Ethical, legal, and professional standards in publishing

Ensuring the Accuracy of Scientific Findings

1.11 Planning for Ethical Compliance 1.12 Ethical and Accurate Reporting of Research Results 1.13 Errors, Corrections, and Retractions After Publication 1.14 Data Retention and Sharing 1.15 Additional Data-Sharing Considerations for Qualitative Research 1.16 Duplicate and Piecemeal Publication of Data 1.17 Implications of Plagiarism and Self-Plagiarism

Protecting the Rights and Welfare of Research Participants and Subjects

1.18 Rights and Welfare of Research Participants and Subjects 1.19 Protecting Confidentiality 1.20 Conflict of Interest

Protecting Intellectual Property Rights

1.21 Publication Credit 1.22 Order of Authors 1.23 Authors’ Intellectual Property Rights During Manuscript Review 1.24 Authors’ Copyright on Unpublished Manuscripts 1.25 Ethical Compliance Checklist

Required Elements

2.1 Professional Paper Required Elements 2.2 Student Paper Required Elements

Paper Elements

2.3 Title Page 2.4 Title 2.5 Author Name (Byline) 2.6 Author Affiliation 2.7 Author Note 2.8 Running Head 2.9 Abstract 2.10 Keywords 2.11 Text (Body) 2.12 Reference List 2.13 Footnotes 2.14 Appendices 2.15 Supplemental Materials

2.16 Importance of Format 2.17 Order of Pages 2.18 Page Header 2.19 Font 2.20 Special Characters 2.21 Line Spacing 2.22 Margins 2.23 Paragraph Alignment 2.24 Paragraph Indentation 2.25 Paper Length

Organization

2.26 Principles of Organization 2.27 Heading Levels 2.28 Section Labels

Sample papers

Overview of Reporting Standards

3.1 Application of the Principles of JARS 3.2 Terminology Used in JARS

Common Reporting Standards Across Research Designs

3.3 Abstract Standards 3.4 Introduction Standards

Reporting Standards for Quantitative Research

3.5 Basic Expectations for Quantitative Research Reporting 3.6 Quantitative Method Standards 3.7 Quantitative Results Standards 3.8 Quantitative Discussion Standards 3.9 Additional Reporting Standards for Typical Experimental and Nonexperimental Studies 3.10 Reporting Standards for Special Designs 3.11 Standards for Analytic Approaches 3.12 Quantitative Meta-Analysis Standards

Reporting Standards for Qualitative Research

3.13 Basic Expectations for Qualitative Research Reporting 3.14 Qualitative Method Standards 3.15 Qualitative Findings or Results Standards 3.16 Qualitative Discussion Standards 3.17 Qualitative Meta-Analysis Standards

Reporting Standards for Mixed Methods Research

3.18 Basic Expectations for Mixed Methods Research Reporting

Effective scholarly writing

Continuity and Flow

4.1 Importance of Continuity and Flow 4.2 Transitions 4.3 Noun Strings

Conciseness and Clarity

4.4 Importance of Conciseness and Clarity 4.5 Wordiness and Redundancy 4.6 Sentence and Paragraph Length 4.7 Tone 4.8 Contractions and Colloquialisms 4.9 Jargon 4.10 Logical Comparisons 4.11 Anthropomorphism

Grammar and usage

4.12 Verb Tense 4.13 Active and Passive Voice 4.14 Mood 4.15 Subject and Verb Agreement

4.16 First- Versus Third-Person Pronouns 4.17 Editorial “We” 4.18 Singular “They” 4.19 Pronouns for People and Animals (“Who” vs. “That”) 4.20 Pronouns as Subjects and Objects (“Who” vs. “Whom”) 4.21 Pronouns in Restrictive and Nonrestrictive Clauses (“That” vs. “Which”)

Sentence Construction

4.22 Subordinate Conjunctions 4.23 Misplaced and Dangling Modifiers 4.24 Parallel Construction

Strategies to Improve Your Writing

4.25 Reading to Learn Through Example 4.26 Writing From an Outline 4.27 Rereading the Draft 4.28 Seeking Help From Colleagues 4.29 Working With Copyeditors and Writing Centers 4.30 Revising a Paper

General Guidelines for Reducing Bias

5.1 Describe at the Appropriate Level of Specificity 5.2 Be Sensitive to Labels

Reducing Bias by Topic

5.3 Age 5.4 Disability 5.5 Gender 5.6 Participation in Research 5.7 Racial and Ethnic Identity 5.8 Sexual Orientation 5.9 Socioeconomic Status 5.10 Intersectionality

Punctuation

6.1 Spacing After Punctuation Marks 6.2 Period 6.3 Comma 6.4 Semicolon 6.5 Colon 6.6 Dash 6.7 Quotation Marks 6.8 Parentheses 6.9 Square Brackets 6.10 Slash

6.11 Preferred Spelling 6.12 Hyphenation

Capitalization

6.13 Words Beginning a Sentence 6.14 Proper Nouns and Trade Names 6.15 Job Titles and Positions 6.16 Diseases, Disorders, Therapies, Theories, and Related Terms 6.17 Titles of Works and Headings Within Works 6.18 Titles of Tests and Measures 6.19 Nouns Followed by Numerals or Letters 6.20 Names of Conditions or Groups in an Experiment 6.21 Names of Factors, Variables, and Effects

6.22 Use of Italics 6.23 Reverse Italics

Abbreviations

6.24 Use of Abbreviations 6.25 Definition of Abbreviations 6.26 Format of Abbreviations 6.27 Unit of Measurement Abbreviations 6.28 Time Abbreviations 6.29 Latin Abbreviations 6.30 Chemical Compound Abbreviations 6.31 Gene and Protein Name Abbreviations

6.32 Numbers Expressed in Numerals 6.33 Numbers Expressed in Words 6.34 Combining Numerals and Words to Express Numbers 6.35 Ordinal Numbers 6.36 Decimal Fractions 6.37 Roman Numerals 6.38 Commas in Numbers 6.39 Plurals of Numbers

Statistical and Mathematical Copy

6.40 Selecting Effective Presentation 6.41 References for Statistics 6.42 Formulas 6.43 Statistics in Text 6.44 Statistical Symbols and Abbreviations 6.45 Spacing, Alignment, and Punctuation for Statistics

Presentation of Equations

6.46 Equations in Text 6.47 Displayed Equations 6.48 Preparing Statistical and Mathematical Copy for Publication

6.49 List Guidelines 6.50 Lettered Lists 6.51 Numbered Lists 6.52 Bulleted Lists

General Guidelines for Tables and Figures

7.1 Purpose of Tables and Figures 7.2 Design and Preparation of Tables and Figures 7.3 Graphical Versus Textual Presentation 7.4 Formatting Tables and Figures 7.5 Referring to Tables and Figures in the Text 7.6 Placement of Tables and Figures 7.7 Reprinting or Adapting Tables and Figures

7.8 Principles of Table Construction 7.9 Table Components 7.10 Table Numbers 7.11 Table Titles 7.12 Table Headings 7.13 Table Body 7.14 Table Notes 7.15 Standard Abbreviations in Tables and Figures 7.16 Confidence Intervals in Tables 7.17 Table Borders and Shading 7.18 Long or Wide Tables 7.19 Relation Between Tables 7.20 Table Checklist 7.21 Sample Tables

Sample tables

7.22 Principles of Figure Construction 7.23 Figure Components 7.24 Figure Numbers 7.25 Figure Titles 7.26 Figure Images 7.27 Figure Legends 7.28 Figure Notes 7.29 Relation Between Figures 7.30 Photographs 7.31 Considerations for Electrophysiological, Radiological, Genetic, and Other Biological Data 7.32 Electrophysiological Data 7.33 Radiological (Imaging) Data 7.34 Genetic Data 7.35 Figure Checklist 7.36 Sample Figures

Sample figures

General Guidelines for Citation

8.1 Appropriate Level of Citation 8.2 Plagiarism 8.3 Self-Plagiarism 8.4 Correspondence Between Reference List and Text 8.5 Use of the Published Version or Archival Version 8.6 Primary and Secondary Sources

Works Requiring Special Approaches to Citation

8.7 Interviews 8.8 Classroom or Intranet Sources 8.9 Personal Communications

In-Text Citations

8.10 Author–Date Citation System 8.11 Parenthetical and Narrative Citations 8.12 Citing Multiple Works 8.13 Citing Specific Parts of a Source 8.14 Unknown or Anonymous Author 8.15 Translated, Reprinted, Republished, and Reissued Dates 8,16 Omitting the Year in Repeated Narrative Citations 8.17 Number of Authors to Include in In-Text Citations 8.18 Avoiding Ambiguity in In-Text Citations 8.19 Works With the Same Author and Same Date 8.20 Authors With the Same Surname 8.21 Abbreviating Group Authors 8.22 General Mentions of Websites, Periodicals, and Common Software and Apps

Paraphrases and Quotations

8.23 Principles of Paraphrasing 8.24 Long Paraphrases 8.25 Principles of Direct Quotation 8.26 Short Quotations (Fewer Than 40 Words) 8.27 Block Quotations (40 Words or More) 8.28 Direct Quotation of Material Without Page Numbers 8.29 Accuracy of Quotations 8.30 Changes to a Quotation Requiring No Explanation 8.31 Changes to a Quotation Requiring Explanation 8.32 Quotations That Contain Citations to Other Works 8.33 Quotations That Contain Material Already in Quotation Marks 8.34 Permission to Reprint or Adapt Lengthy Quotations 8.35 Epigraphs 8.36 Quotations From Research Participants

Reference Categories

9.1 Determining the Reference Category 9.2 Using the Webpages and Websites Reference Category 9.3 Online and Print References

Principles of Reference List Entries

9.4 Four Elements of a Reference 9.5 Punctuation Within Reference List Entries 9.6 Accuracy and Consistency in References

Reference elements

9.7 Definition of Author 9.8 Format of the Author Element 9.9 Spelling and Capitalization of Author Names 9.10 Identification of Specialized Roles 9.11 Group Authors 9.12 No Author

9.13 Definition of Date 9.14 Format of the Date Element 9.15 Updated or Reviewed Online Works 9.16 Retrieval Dates 9.17 No Date

9.18 Definition of Title 9.19 Format of the Title Element 9.20 Series and Multivolume Works 9.21 Bracketed Descriptions 9.22 No Title

9.23 Definition of Source 9.24 Format of the Source Element 9.25 Periodical Sources 9.26 Online Periodicals With Missing Information 9.27 Article Numbers 9.28 Edited Book Chapter and Reference Work Entry Sources 9.29 Publisher Sources 9.30 Database and Archive Sources 9.31 Works With Specific Locations 9.32 Social Media Sources 9.33 Website Sources 9.34 When to Include DOIs and URLs 9.35 Format of DOIs and URLs 9.36 DOI or URL Shorteners 9.37 No Source

Reference Variations

9.38 Works in Another Language 9.39 Translated Works 9.40 Reprinted Works 9.41 Republished or Reissued Works 9.42 Religious and Classical Works

Reference List Format and Order

9.43 Format of the Reference List 9.44 Order of Works in the Reference List 9.45 Order of Surname and Given Name 9.46 Order of Multiple Works by the Same First Author 9.47 Order of Works With the Same Author and Same Date 9.48 Order of Works by First Authors With the Same Surname 9.49 Order of Works With No Author or an Anonymous Author 9.50 Abbreviations in References 9.51 Annotated Bibliographies 9.52 References Included in a Meta-Analysis

Author Variations

Date Variations

Title Variations

Source Variations

Textual Works

10.1 Periodicals 10.2 Books and Reference Works 10.3 Edited Book Chapters and Entries in Reference Works 10.4 Reports and Gray Literature 10.5 Conference Sessions and Presentations 10.6 Dissertations and Theses 10.7 Reviews 10.8 Unpublished Works and Informally Published Works

Data Sets, Software, and Tests

10.9 Data Sets 10.10 Computer Software, Mobile Apps, Apparatuses, and Equipment 10.11 Tests, Scales, and Inventories

Audiovisual Media

10.12 Audiovisual Works 10.13 Audio Works 10.14 Visual Works

Online Media

10.15 Social Media 10.16 Webpages and Websites

General Guidelines for Legal References

11.1 APA Style References Versus Legal References 11.2 General Forms 11.3 In-Text Citations of Legal Materials

Legal Reference Examples

11.4 Cases or Court Decisions 11.5 Statutes (Laws and Acts) 11.6 Legislative Materials 11.7 Administrative and Executive Materials 11.8 Patents 11.9 Constitutions and Charters 11.10 Treaties and International Conventions

Preparing for Publication

12.1 Adapting a Dissertation or Thesis Into a Journal Article 12.2 Selecting a Journal for Publication 12.3 Prioritizing Potential Journals 12.4 Avoiding Predatory Journals

Understanding the Editorial Publication Process

12.5 Editorial Publication Process 12.6 Role of the Editors 12.7 Peer Review Process 12.8 Manuscript Decisions

Manuscript Preparation

12.9 Preparing the Manuscript for Submission 12.10 Using an Online Submission Portal 12.11 Writing a Cover Letter 12.12 Corresponding During Publication 12.13 Certifying Ethical Requirements

Copyright and Permission Guidelines

12.14 General Guidelines for Reprinting or Adapting Materials 12.15 Materials That Require Copyright Attribution 12.16 Copyright Status 12.17 Permission and Fair Use 12.18 Copyright Attribution Formats

During and After Publication

12.19 Article Proofs 12.20 Published Article Copyright Policies 12.21 Open Access Deposit Policies 12.22 Writing a Correction Notice 12.23 Sharing Your Article Online 12.24 Promoting Your Article

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Qualitative study.

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Last Update: September 18, 2022 .

• Introduction

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. [1] Instead of collecting numerical data points or intervening or introducing treatments just like in quantitative research, qualitative research helps generate hypothenar to further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a standalone study, purely relying on qualitative data, or part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and applications of qualitative research.

Qualitative research, at its core, asks open-ended questions whose answers are not easily put into numbers, such as "how" and "why." [2] Due to the open-ended nature of the research questions, qualitative research design is often not linear like quantitative design. [2] One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. [3] Phenomena such as experiences, attitudes, and behaviors can be complex to capture accurately and quantitatively. In contrast, a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a particular time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify, and it is essential to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore "compete" against each other and the philosophical paradigms associated with each other, qualitative and quantitative work are neither necessarily opposites, nor are they incompatible. [4] While qualitative and quantitative approaches are different, they are not necessarily opposites and certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated.

Qualitative Research Approaches

Ethnography

Ethnography as a research design originates in social and cultural anthropology and involves the researcher being directly immersed in the participant’s environment. [2] Through this immersion, the ethnographer can use a variety of data collection techniques to produce a comprehensive account of the social phenomena that occurred during the research period. [2] That is to say, the researcher’s aim with ethnography is to immerse themselves into the research population and come out of it with accounts of actions, behaviors, events, etc, through the eyes of someone involved in the population. Direct involvement of the researcher with the target population is one benefit of ethnographic research because it can then be possible to find data that is otherwise very difficult to extract and record.

Grounded theory

Grounded Theory is the "generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior." [5] Unlike quantitative research, which is deductive and tests or verifies an existing theory, grounded theory research is inductive and, therefore, lends itself to research aimed at social interactions or experiences. [3] [2] In essence, Grounded Theory’s goal is to explain how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.

Phenomenology

Phenomenology is the "study of the meaning of phenomena or the study of the particular.” [5] At first glance, it might seem that Grounded Theory and Phenomenology are pretty similar, but the differences can be seen upon careful examination. At its core, phenomenology looks to investigate experiences from the individual's perspective. [2] Phenomenology is essentially looking into the "lived experiences" of the participants and aims to examine how and why participants behaved a certain way from their perspective. Herein lies one of the main differences between Grounded Theory and Phenomenology. Grounded Theory aims to develop a theory for social phenomena through an examination of various data sources. In contrast, Phenomenology focuses on describing and explaining an event or phenomenon from the perspective of those who have experienced it.

Narrative research

One of qualitative research’s strengths lies in its ability to tell a story, often from the perspective of those directly involved in it. Reporting on qualitative research involves including details and descriptions of the setting involved and quotes from participants. This detail is called a "thick" or "rich" description and is a strength of qualitative research. Narrative research is rife with the possibilities of "thick" description as this approach weaves together a sequence of events, usually from just one or two individuals, hoping to create a cohesive story or narrative. [2] While it might seem like a waste of time to focus on such a specific, individual level, understanding one or two people’s narratives for an event or phenomenon can help to inform researchers about the influences that helped shape that narrative. The tension or conflict of differing narratives can be "opportunities for innovation." [2]

Research Paradigm

Research paradigms are the assumptions, norms, and standards underpinning different research approaches. Essentially, research paradigms are the "worldviews" that inform research. [4] It is valuable for qualitative and quantitative researchers to understand what paradigm they are working within because understanding the theoretical basis of research paradigms allows researchers to understand the strengths and weaknesses of the approach being used and adjust accordingly. Different paradigms have different ontologies and epistemologies. Ontology is defined as the "assumptions about the nature of reality,” whereas epistemology is defined as the "assumptions about the nature of knowledge" that inform researchers' work. [2] It is essential to understand the ontological and epistemological foundations of the research paradigm researchers are working within to allow for a complete understanding of the approach being used and the assumptions that underpin the approach as a whole. Further, researchers must understand their own ontological and epistemological assumptions about the world in general because their assumptions about the world will necessarily impact how they interact with research. A discussion of the research paradigm is not complete without describing positivist, postpositivist, and constructivist philosophies.

Positivist versus postpositivist

To further understand qualitative research, we must discuss positivist and postpositivist frameworks. Positivism is a philosophy that the scientific method can and should be applied to social and natural sciences. [4] Essentially, positivist thinking insists that the social sciences should use natural science methods in their research. It stems from positivist ontology, that there is an objective reality that exists that is wholly independent of our perception of the world as individuals. Quantitative research is rooted in positivist philosophy, which can be seen in the value it places on concepts such as causality, generalizability, and replicability.

Conversely, postpositivists argue that social reality can never be one hundred percent explained, but could be approximated. [4] Indeed, qualitative researchers have been insisting that there are “fundamental limits to the extent to which the methods and procedures of the natural sciences could be applied to the social world,” and therefore, postpositivist philosophy is often associated with qualitative research. [4] An example of positivist versus postpositivist values in research might be that positivist philosophies value hypothesis-testing, whereas postpositivist philosophies value the ability to formulate a substantive theory.

Constructivist

Constructivism is a subcategory of postpositivism. Most researchers invested in postpositivist research are also constructivist, meaning they think there is no objective external reality that exists but instead that reality is constructed. Constructivism is a theoretical lens that emphasizes the dynamic nature of our world. "Constructivism contends that individuals' views are directly influenced by their experiences, and it is these individual experiences and views that shape their perspective of reality.” [6]  constructivist thought focuses on how "reality" is not a fixed certainty and how experiences, interactions, and backgrounds give people a unique view of the world. Constructivism contends, unlike positivist views, that there is not necessarily an "objective"reality we all experience. This is the ‘relativist’ ontological view that reality and our world are dynamic and socially constructed. Therefore, qualitative scientific knowledge can be inductive as well as deductive.” [4]

So why is it important to understand the differences in assumptions that different philosophies and approaches to research have? Fundamentally, the assumptions underpinning the research tools a researcher selects provide an overall base for the assumptions the rest of the research will have. It can even change the role of the researchers. [2] For example, is the researcher an "objective" observer, such as in positivist quantitative work? Or is the researcher an active participant in the research, as in postpositivist qualitative work? Understanding the philosophical base of the study undertaken allows researchers to fully understand the implications of their work and their role within the research and reflect on their positionality and bias as it pertains to the research they are conducting.

Data Sampling 

The better the sample represents the intended study population, the more likely the researcher is to encompass the varying factors. The following are examples of participant sampling and selection: [7]

• Purposive sampling- selection based on the researcher’s rationale for being the most informative.
• Criterion sampling selection based on pre-identified factors.
• Convenience sampling- selection based on availability.
• Snowball sampling- the selection is by referral from other participants or people who know potential participants.
• Extreme case sampling- targeted selection of rare cases.
• Typical case sampling selection based on regular or average participants. 

Data Collection and Analysis

Qualitative research uses several techniques, including interviews, focus groups, and observation. [1] [2] [3] Interviews may be unstructured, with open-ended questions on a topic, and the interviewer adapts to the responses. Structured interviews have a predetermined number of questions that every participant is asked. It is usually one-on-one and appropriate for sensitive topics or topics needing an in-depth exploration. Focus groups are often held with 8-12 target participants and are used when group dynamics and collective views on a topic are desired. Researchers can be participant-observers to share the experiences of the subject or non-participants or detached observers.

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or the participants' environment, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed, which may then be coded manually or using computer-assisted qualitative data analysis software or CAQDAS such as ATLAS.ti or NVivo. [8] [9] [10]

After the coding process, qualitative research results could be in various formats. It could be a synthesis and interpretation presented with excerpts from the data. [11] Results could also be in the form of themes and theory or model development.

Dissemination

The healthcare team can use two reporting standards to standardize and facilitate the dissemination of qualitative research outcomes. The Consolidated Criteria for Reporting Qualitative Research or COREQ is a 32-item checklist for interviews and focus groups. [12] The Standards for Reporting Qualitative Research (SRQR) is a checklist covering a more comprehensive range of qualitative research. [13]

Applications

Many times, a research question will start with qualitative research. The qualitative research will help generate the research hypothesis, which can be tested with quantitative methods. After the data is collected and analyzed with quantitative methods, a set of qualitative methods can be used to dive deeper into the data to better understand what the numbers truly mean and their implications. The qualitative techniques can then help clarify the quantitative data and also help refine the hypothesis for future research. Furthermore, with qualitative research, researchers can explore poorly studied subjects with quantitative methods. These include opinions, individual actions, and social science research.

An excellent qualitative study design starts with a goal or objective. This should be clearly defined or stated. The target population needs to be specified. A method for obtaining information from the study population must be carefully detailed to ensure no omissions of part of the target population. A proper collection method should be selected that will help obtain the desired information without overly limiting the collected data because, often, the information sought is not well categorized or obtained. Finally, the design should ensure adequate methods for analyzing the data. An example may help better clarify some of the various aspects of qualitative research.

A researcher wants to decrease the number of teenagers who smoke in their community. The researcher could begin by asking current teen smokers why they started smoking through structured or unstructured interviews (qualitative research). The researcher can also get together a group of current teenage smokers and conduct a focus group to help brainstorm factors that may have prevented them from starting to smoke (qualitative research).

In this example, the researcher has used qualitative research methods (interviews and focus groups) to generate a list of ideas of why teens start to smoke and factors that may have prevented them from starting to smoke. Next, the researcher compiles this data. The research found that, hypothetically, peer pressure, health issues, cost, being considered "cool," and rebellious behavior all might increase or decrease the likelihood of teens starting to smoke.

The researcher creates a survey asking teen participants to rank how important each of the above factors is in either starting smoking (for current smokers) or not smoking (for current nonsmokers). This survey provides specific numbers (ranked importance of each factor) and is thus a quantitative research tool.

The researcher can use the survey results to focus efforts on the one or two highest-ranked factors. Let us say the researcher found that health was the primary factor that keeps teens from starting to smoke, and peer pressure was the primary factor that contributed to teens starting smoking. The researcher can go back to qualitative research methods to dive deeper into these for more information. The researcher wants to focus on keeping teens from starting to smoke, so they focus on the peer pressure aspect.

The researcher can conduct interviews and focus groups (qualitative research) about what types and forms of peer pressure are commonly encountered, where the peer pressure comes from, and where smoking starts. The researcher hypothetically finds that peer pressure often occurs after school at the local teen hangouts, mostly in the local park. The researcher also hypothetically finds that peer pressure comes from older, current smokers who provide the cigarettes.

The researcher could further explore this observation made at the local teen hangouts (qualitative research) and take notes regarding who is smoking, who is not, and what observable factors are at play for peer pressure to smoke. The researcher finds a local park where many local teenagers hang out and sees that the smokers tend to hang out in a shady, overgrown area of the park. The researcher notes that smoking teenagers buy their cigarettes from a local convenience store adjacent to the park, where the clerk does not check identification before selling cigarettes. These observations fall under qualitative research.

If the researcher returns to the park and counts how many individuals smoke in each region, this numerical data would be quantitative research. Based on the researcher's efforts thus far, they conclude that local teen smoking and teenagers who start to smoke may decrease if there are fewer overgrown areas of the park and the local convenience store does not sell cigarettes to underage individuals.

The researcher could try to have the parks department reassess the shady areas to make them less conducive to smokers or identify how to limit the sales of cigarettes to underage individuals by the convenience store. The researcher would then cycle back to qualitative methods of asking at-risk populations their perceptions of the changes and what factors are still at play, and quantitative research that includes teen smoking rates in the community and the incidence of new teen smokers, among others. [14] [15]

Qualitative research functions as a standalone research design or combined with quantitative research to enhance our understanding of the world. Qualitative research uses techniques including structured and unstructured interviews, focus groups, and participant observation not only to help generate hypotheses that can be more rigorously tested with quantitative research but also to help researchers delve deeper into the quantitative research numbers, understand what they mean, and understand what the implications are. Qualitative research allows researchers to understand what is going on, especially when things are not easily categorized. [16]

• Issues of Concern

As discussed in the sections above, quantitative and qualitative work differ in many ways, including the evaluation criteria. There are four well-established criteria for evaluating quantitative data: internal validity, external validity, reliability, and objectivity. Credibility, transferability, dependability, and confirmability are the correlating concepts in qualitative research. [4] [11] The corresponding quantitative and qualitative concepts can be seen below, with the quantitative concept on the left and the qualitative concept on the right:

• Internal validity: Credibility
• External validity: Transferability
• Reliability: Dependability
• Objectivity: Confirmability

In conducting qualitative research, ensuring these concepts are satisfied and well thought out can mitigate potential issues from arising. For example, just as a researcher will ensure that their quantitative study is internally valid, qualitative researchers should ensure that their work has credibility. 

Indicators such as triangulation and peer examination can help evaluate the credibility of qualitative work.

• Triangulation: Triangulation involves using multiple data collection methods to increase the likelihood of getting a reliable and accurate result. In our above magic example, the result would be more reliable if we interviewed the magician, backstage hand, and the person who "vanished." In qualitative research, triangulation can include telephone surveys, in-person surveys, focus groups, and interviews and surveying an adequate cross-section of the target demographic.
• Peer examination: A peer can review results to ensure the data is consistent with the findings.

A "thick" or "rich" description can be used to evaluate the transferability of qualitative research, whereas an indicator such as an audit trail might help evaluate the dependability and confirmability.

• Thick or rich description:  This is a detailed and thorough description of details, the setting, and quotes from participants in the research. [5] Thick descriptions will include a detailed explanation of how the study was conducted. Thick descriptions are detailed enough to allow readers to draw conclusions and interpret the data, which can help with transferability and replicability.
• Audit trail: An audit trail provides a documented set of steps of how the participants were selected and the data was collected. The original information records should also be kept (eg, surveys, notes, recordings).

One issue of concern that qualitative researchers should consider is observation bias. Here are a few examples:

• Hawthorne effect: The effect is the change in participant behavior when they know they are being observed. Suppose a researcher wanted to identify factors that contribute to employee theft and tell the employees they will watch them to see what factors affect employee theft. In that case, one would suspect employee behavior would change when they know they are being protected.
• Observer-expectancy effect: Some participants change their behavior or responses to satisfy the researcher's desired effect. This happens unconsciously for the participant, so it is essential to eliminate or limit the transmission of the researcher's views.
• Artificial scenario effect: Some qualitative research occurs in contrived scenarios with preset goals. In such situations, the information may not be accurate because of the artificial nature of the scenario. The preset goals may limit the qualitative information obtained.
• Clinical Significance

Qualitative or quantitative research helps healthcare providers understand patients and the impact and challenges of the care they deliver. Qualitative research provides an opportunity to generate and refine hypotheses and delve deeper into the data generated by quantitative research. Qualitative research is not an island apart from quantitative research but an integral part of research methods to understand the world around us. [17]

• Enhancing Healthcare Team Outcomes

Qualitative research is essential for all healthcare team members as all are affected by qualitative research. Qualitative research may help develop a theory or a model for health research that can be further explored by quantitative research. Much of the qualitative research data acquisition is completed by numerous team members, including social workers, scientists, nurses, etc. Within each area of the medical field, there is copious ongoing qualitative research, including physician-patient interactions, nursing-patient interactions, patient-environment interactions, healthcare team function, patient information delivery, etc. 

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Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

Disclosure: Janelle Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Grace Brannan declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Tenny S, Brannan JM, Brannan GD. Qualitative Study. [Updated 2022 Sep 18]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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