qualitative research can best address concerns about validity

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• Published: 27 May 2020

How to use and assess qualitative research methods

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

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

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

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

What is qualitative research?

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

Why conduct qualitative research?

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

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

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

How to conduct qualitative research?

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

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.

Availability of data and materials

Not applicable.

Abbreviations

Endovascular treatment

Randomised Controlled Trial

Standard Operating Procedure

Standards for Reporting Qualitative Research

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

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Series: Practical guidance to qualitative research. Part 4: Trustworthiness and publishing

Irene korstjens.

a Faculty of Health Care, Research Centre for Midwifery Science, Zuyd University of Applied Sciences, Maastricht, The Netherlands;

Albine Moser

b Faculty of Health Care, Research Centre Autonomy and Participation of Chronically Ill People, Zuyd University of Applied Sciences, Heerlen, The Netherlands;

c Faculty of Health, Medicine and Life Sciences, Department of Family Medicine, Maastricht University, Maastricht, The Netherlands

In the course of our supervisory work over the years we have noticed that qualitative research tends to evoke a lot of questions and worries, so-called frequently asked questions (FAQs). This series of four articles intends to provide novice researchers with practical guidance for conducting high-quality qualitative research in primary care. By ‘novice’ we mean Master’s students and junior researchers, as well as experienced quantitative researchers who are engaging in qualitative research for the first time. This series addresses their questions and provides researchers, readers, reviewers and editors with references to criteria and tools for judging the quality of qualitative research papers. The first article provides an introduction to this series. The second article focused on context, research questions and designs. The third article focused on sampling, data collection and analysis. This fourth article addresses FAQs about trustworthiness and publishing. Quality criteria for all qualitative research are credibility, transferability, dependability, and confirmability. Reflexivity is an integral part of ensuring the transparency and quality of qualitative research. Writing a qualitative research article reflects the iterative nature of the qualitative research process: data analysis continues while writing. A qualitative research article is mostly narrative and tends to be longer than a quantitative paper, and sometimes requires a different structure. Editors essentially use the criteria: is it new, is it true, is it relevant? An effective cover letter enhances confidence in the newness, trueness and relevance, and explains why your study required a qualitative design. It provides information about the way you applied quality criteria or a checklist, and you can attach the checklist to the manuscript.

Key points on trustworthiness and publishing

• The quality criteria for all qualitative research are credibility, transferability, dependability, and confirmability.
• In addition, reflexivity is an integral part of ensuring the transparency and quality of qualitative research.
• Writing a qualitative article reflects the iterative nature of the qualitative research process: continuous data analysis continues with simultaneous fine-tuning.
• Editors essentially use the criteria: is it new, is it true, and is it relevant?
• An effective cover letter enhances confidence in the newness, trueness and relevance, and explains why your study required a qualitative design.

Introduction

This article is the fourth and last in a series of four articles aiming to provide practical guidance for qualitative research. In an introductory paper, we have described the objective, nature and outline of the series [ 1 ]. Part 2 of the series focused on context, research questions and design of qualitative research [ 2 ], whereas Part 3 concerned sampling, data collection and analysis [ 3 ]. In this paper Part 4, we address frequently asked questions (FAQs) about two overarching themes: trustworthiness and publishing.

Trustworthiness

What are the quality criteria for qualitative research.

The same quality criteria apply to all qualitative designs, including the ‘big three’ approaches. Quality criteria used in quantitative research, e.g. internal validity, generalizability, reliability, and objectivity, are not suitable to judge the quality of qualitative research. Qualitative researchers speak of trustworthiness, which simply poses the question ‘Can the findings to be trusted?’ [ 4 ]. Several definitions and criteria of trustworthiness exist (see Box 1 ) [ 2 ], but the best-known criteria are credibility, transferability, dependability, and confirmability as defined by Lincoln and Guba [ 4 ].

Trustworthiness: definitions of quality criteria in qualitative research. Based on Lincoln and Guba [ 4 ].

What is credibility and what strategies can be used to ensure it?

Credibility is the equivalent of internal validity in quantitative research and is concerned with the aspect of truth-value [ 4 ]. Strategies to ensure credibility are prolonged engagement, persistent observation, triangulation and member check ( Box 2 ). When you design your study, you also determine which of these strategies you will use, because not all strategies might be suitable. For example, a member check of written findings might not be possible for study participants with a low level of literacy. Let us give an example of the possible use of strategies to ensure credibility. A team of primary care researchers studied the process by which people with type 2 diabetes mellitus try to master diabetes self-management [ 6 ]. They used the grounded theory approach, and their main finding was an explanatory theory. The researchers ensured credibility by using the following strategies.

Definition of strategies to ensure trustworthiness in qualitative research. Based on Lincoln and Guba [ 4 ]; Sim and Sharp [ 5 ].

Prolonged engagement . Several distinct questions were asked regarding topics related to mastery. Participants were encouraged to support their statements with examples, and the interviewer asked follow-up questions. The researchers studied the data from their raw interview material until a theory emerged to provide them with the scope of the phenomenon under study.

Triangulation . Triangulation aims to enhance the process of qualitative research by using multiple approaches [ 7 ]. Methodological triangulation was used by gathering data by means of different data collection methods such as in-depth interviews, focus group discussions and field notes. Investigator triangulation was applied by involving several researchers as research team members, and involving them in addressing the organizational aspects of the study and the process of analysis. Data were analysed by two different researchers. The first six interviews were analysed by them independently, after which the interpretations were compared. If their interpretations differed, they discussed them until the most suitable interpretation was found, which best represented the meaning of the data. The two researchers held regular meetings during the process of analysis (after analysing every third data set). In addition, regular analytical sessions were held with the research team. Data triangulation was secured by using the various data sets that emerged throughout the analysis process: raw material, codes, concepts and theoretical saturation.

Persistent observation . Developing the codes, the concepts and the core category helped to examine the characteristics of the data. The researchers constantly read and reread the data, analysed them, theorized about them and revised the concepts accordingly. They recoded and relabelled codes, concepts and the core category. The researchers studied the data until the final theory provided the intended depth of insight.

Member check . All transcripts of the interviews and focus group discussions were sent to the participants for feedback. In addition, halfway through the study period, a meeting was held with those who had participated in either the interviews or the focus group discussions, enabling them to correct the interpretation and challenge what they perceived to be ‘wrong’ interpretations. Finally, the findings were presented to the participants in another meeting to confirm the theory.

What does transferability mean and who makes a ‘transferability judgement’?

Transferability concerns the aspect of applicability [ 4 ]. Your responsibility as a researcher is to provide a ‘thick description’ of the participants and the research process, to enable the reader to assess whether your findings are transferable to their own setting; this is the so-called transferability judgement. This implies that the reader, not you, makes the transferability judgment because you do not know their specific settings.

In the aforementioned study on self-management of diabetes, the researchers provided a rich account of descriptive data, such as the context in which the research was carried out, its setting, sample, sample size, sample strategy, demographic, socio-economic, and clinical characteristics, inclusion and exclusion criteria, interview procedure and topics, changes in interview questions based on the iterative research process, and excerpts from the interview guide.

What is the difference between dependability and confirmability and why is an audit trail needed?

Dependability includes the aspect of consistency [ 4 ]. You need to check whether the analysis process is in line with the accepted standards for a particular design. Confirmability concerns the aspect of neutrality [ 4 ]. You need to secure the inter-subjectivity of the data. The interpretation should not be based on your own particular preferences and viewpoints but needs to be grounded in the data. Here, the focus is on the interpretation process embedded in the process of analysis. The strategy needed to ensure dependability and confirmability is known as an audit trail. You are responsible for providing a complete set of notes on decisions made during the research process, research team meetings, reflective thoughts, sampling, research materials adopted, emergence of the findings and information about the data management. This enables the auditor to study the transparency of the research path.

In the aforementioned study of diabetes self-management, a university-based auditor examined the analytical process, the records and the minutes of meetings for accuracy, and assessed whether all analytical techniques of the grounded theory methodology had been used accordingly. This auditor also reviewed the analysis, i.e. the descriptive, axial and selective codes, to see whether they followed from the data (raw data, analysis notes, coding notes, process notes, and report) and grounded in the data. The auditor who performed the dependability and confirmability audit was not part of the research team but an expert in grounded theory. The audit report was shared with all members of the research team.

Why is reflexivity an important quality criterion?

As a qualitative researcher, you have to acknowledge the importance of being self-aware and reflexive about your own role in the process of collecting, analysing and interpreting the data, and in the pre-conceived assumptions, you bring to your research [ 8 ]. Therefore, your interviews, observations, focus group discussions and all analytical data need to be supplemented with your reflexive notes. In the aforementioned study of diabetes self-management, the reflexive notes for an interview described the setting and aspects of the interview that were noted during the interview itself and while transcribing the audio tape and analysing the transcript. Reflexive notes also included the researcher’s subjective responses to the setting and the relationship with the interviewees.

How do I report my qualitative study?

The process of writing up your qualitative study reflects the iterative process of performing qualitative research. As you start your study, you make choices about the design, and as your study proceeds, you develop your design further. The same applies to writing your manuscript. First, you decide its structure, and during the process of writing, you adapt certain aspects. Moreover, while writing you are still analysing and fine-tuning your findings. The usual structure of articles is a structured abstract with subheadings, followed by the main text, structured in sections labelled Introduction-Methods-Results-Discussion. You might apply this structure loosely, for example renaming Results as Findings, but sometimes your specific study design requires a different structure. For example, an ethnographic study might use a narrative abstract and then start by describing a specific case, or combine the Findings and Discussion sections. A qualitative article is usually much longer (5000–7000 words) than quantitative articles, which often present their results in tables. You might present quantified characteristics of your participants in tables or running text, and you are likely to use boxes to present your interview guide or questioning route, or an overview of the main findings in categories, subcategories and themes. Most of your article is running text, providing a balanced presentation. You provide a thick description of the participants and the context, transparently describe and reflect on your methods, and do justice to the richness of your qualitative findings in reporting, interpreting and discussing them. Thus, the Methods and Findings sections will be much longer than in a quantitative paper.

The difference between reporting quantitative and qualitative research becomes most visible in the Results section. Quantitative articles have a strict division between the Results section, which presents the evidence, and the Discussion section. In contrast, the Findings section in qualitative papers consists mostly of synthesis and interpretation, often with links to empirical data. Quantitative and qualitative researchers alike, however, need to be concise in presenting the main findings to answer the research question, and avoid distractions. Therefore, you need to make choices to provide a comprehensive and balanced representation of your findings. Your main findings may consist, for example, of interpretations, relationships and themes, and your Findings section might include the development of a theory or model, or integration with earlier research or theory. You present evidence to substantiate your analytic findings. You use quotes or citations in the text, or field notes, text excerpts or photographs in boxes to illustrate and visualize the variety and richness of the findings.

Before you start preparing your article, it is wise to examine first the journal of your choice. You need to check its guidelines for authors and recommended sources for reference style, ethics, etc., as well as recently accepted qualitative manuscripts. More and more journals also refer to quality criteria lists for reporting qualitative research, and ask you to upload the checklist with your submission. Two of these checklists are available at http://www.equator-network.org/reporting-guidelines .

How do I select a potential journal for publishing my research?

Selecting a potential journal for publishing qualitative articles is not much different from the procedure used for quantitative articles. First, you consider your potential public and the healthcare settings, health problems, field, or research methodology you are focusing on. Next, you look for journals in the Journal Citation Index of Web of Science, consult other researchers and study the potential journals’ aims, scopes, and author guidelines. This also enables you to find out how open these journals are to publishing qualitative research and accepting articles with different designs, structures and lengths. If you are unsure whether the journal of your choice would accept qualitative research, you might contact the Editor in Chief. Lastly, you might look in your top three journals for qualitative articles, and try to decide how your manuscript would fit in. The author guidelines and examples of manuscripts will support you during your writing, and your top three offers alternatives in case you need to turn to another journal.

What are the journal editors’ considerations in accepting a qualitative manuscript?

Your article should effectively present high-quality research and should adhere to the journal’s guidelines. Editors essentially use the same criteria for qualitative articles as for quantitative articles: Is it new, it is true, is it relevant? However, editors may use—implicitly or explicitly—the level-of-evidence pyramid, with qualitative research positioned in the lower ranks. Moreover, many medical journal editors will be more familiar with quantitative designs than with qualitative work.

Therefore, you need to put some extra effort in your cover letter to the editor, to enhance their confidence in the newness, trueness and relevance, and the quality of your work. It is of the utmost importance that you explain in your cover letter why your study required a qualitative design, and probably more words than usual. If you need to deviate from the usual structure, you have to explain why. To enhance confidence in the quality of your work, you should explain how you applied quality criteria or refer to the checklist you used ( Boxes 2 and ​ and3). 3 ). You might even attach the checklist as additional information to the manuscript. You might also request that the Editor-in-Chief invites at least one reviewer who is familiar with qualitative research.

Quality criteria checklists for reporting qualitative research. Based on O’Brien et al. [ 9 ]; Tong et al. [ 10 ].

Acknowledgements

The authors wish to thank the following junior researchers who have been participating for the last few years in the so-called ‘Think tank on qualitative research’ project, a collaborative project between Zuyd University of Applied Sciences and Maastricht University, for their pertinent questions: Erica Baarends, Jerome van Dongen, Jolanda Friesen-Storms, Steffy Lenzen, Ankie Hoefnagels, Barbara Piskur, Claudia van Putten-Gamel, Wilma Savelberg, Steffy Stans, and Anita Stevens. The authors are grateful to Isabel van Helmond, Joyce Molenaar and Darcy Ummels for proofreading our manuscripts and providing valuable feedback from the ‘novice perspective’.

Disclosure statement

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

Validity in Qualitative Research

How do we assess and assure Validity in Qualitative Research ?  This can be a bit of a tricky topic, as qualitative research involves humans understanding humans, a necessarily subjective practice from the get-go.  Nevertheless, there are some questions the researcher can ask and some techniques he or she can employ to establish a reasonable level of validity.

Whether it is employed in business or the social sciences, it is often used to inform decisions that have important implications, thus assuring a high level of validity is essential.  While the results should never be extrapolated over a larger population, (as they never come from a large enough sample to be statistically significant), validity can be established such that it can be used to inform meaningful decisions.

One measure of validity in qualitative research is to ask questions such as: “Does it make sense?” and “Can I trust it?”  This may seem like a fuzzy measure of validity to someone disciplined in quantitative research, for example, but in a science that deals in themes and context, these questions are important.

Steps in Ensuring Validity

The first step in ensuring validity is choosing a well-trained and skilled moderator (or facilitator).  A good moderator will check personal bias and expectations at the door.  He or she is interested in learning as much candid information from the research participants as possible, and respectful neutrality is a must if the goal is valid qualitative research.  For this reason, organizations often employ moderators from outside the group or organization to help ensure that the responses are genuine and not influenced by “what we want to hear.”  For some academic applications, the moderator will disclose his or her perspectives and biases in the reporting of the data as a matter of full disclosure.

While a good moderator is key, a good sample group is also essential.  Are the participants truly members of the segment from which they are recruited?  Ethical recruiting is an important issue in qualitative research, as data collected from individuals who are not truly representative of their segment will not lead to valid results.

Another way to promote validity is to employ a strategy known as triangulation.  To accomplish this, the research is done from multiple perspectives.   This could take the form of using several moderators, different locations, multiple individuals analyzing the same data . . . essentially any technique that would inform the results from different angles.   For some applications, for example, an organization may choose to run focus groups in parallel through two entirely different researchers and then compare the results.

Validity in qualitative research can also be checked by a technique known as respondent validation.  This technique involves testing initial results with participants to see if they still ring true.   Although the research has been interpreted and condensed, participants should still recognize the results as authentic and, at this stage, may even be able to refine the researcher’s understanding.

When the study permits, deep saturation into the research will also promote validity.  If responses become more consistent across larger numbers of samples, the data becomes more reliable.

Another technique to establish validity is to actively seek alternative explanations to what appear to be research results.  If the researcher is able to exclude other scenarios, he is or she is able to strengthen the validity of the findings.   Related to this technique is asking questions in an inverse format.

While the techniques to establish validity in qualitative research may seem less concrete and defined than in some of the other scientific disciplines, strong research techniques will, indeed, assure an appropriate level of validity in qualitative research.

Additional Webpages Related to Validity in Qualitative Research

• Intellectus Qualitative : The ultimate platform designed to redefine your qualitative research experience.
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• Open access
• Published: 16 August 2024

Examining the perception of undergraduate health professional students of their learning environment, learning experience and professional identity development: a mixed-methods study

• Banan Mukhalalati 1 ,
• Aaliah Aly 1 ,
• Ola Yakti 1 ,
• Sara Elshami 1 ,
• Alaa Daud 2 ,
• Ahmed Awaisu 1 ,
• Ahsan Sethi 3 ,
• Alla El-Awaisi 1 ,
• Derek Stewart 1 ,
• Marwan Farouk Abu-Hijleh 4 &
• Zubin Austin 5  

BMC Medical Education volume  24 , Article number:  886 ( 2024 ) Cite this article

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The quality of the learning environment significantly impacts student engagement and professional identity formation in health professions education. Despite global recognition of its importance, research on student perceptions of learning environments across different health education programs is scarce. This study aimed to explore how health professional students perceive their learning environment and its influence on their professional identity development.

An explanatory mixed-methods approach was employed. In the quantitative phase, the Dundee Ready Education Environment Measure [Minimum–Maximum possible scores = 0–200] and Macleod Clark Professional Identity Scale [Minimum–Maximum possible scores = 1–45] were administered to Qatar University-Health students ( N  = 908), with a minimum required sample size of 271 students. Data were analyzed using SPSS, including descriptive statistics and inferential analysis. In the qualitative phase, seven focus groups (FGs) were conducted online via Microsoft Teams. FGs were guided by a topic guide developed from the quantitative results and the framework proposed by Gruppen et al. (Acad Med 94:969-74, 2019), transcribed verbatim, and thematically analyzed using NVIVO®.

The questionnaire response rate was 57.8% (525 responses out of 908), with a usability rate of 74.3% (390 responses out of 525) after excluding students who only completed the demographic section. The study indicated a “more positive than negative” perception of the learning environment (Median [IQR] = 132 [116–174], Minimum–Maximum obtained scores = 43–185), and a “good” perception of their professional identity (Median [IQR] = 24 [22–27], Minimum–Maximum obtained scores = 3–36). Qualitative data confirmed that the learning environment was supportive in developing competence, interpersonal skills, and professional identity, though opinions on emotional support adequacy were mixed. Key attributes of an ideal learning environment included mentorship programs, a reward system, and measures to address fatigue and boredom.

Conclusions

The learning environment at QU-Health was effective in developing competence and interpersonal skills. Students' perceptions of their learning environment positively correlated with their professional identity. Ideal environments should include mentorship programs, a reward system, and strategies to address fatigue and boredom, emphasizing the need for ongoing improvements in learning environments to enhance student satisfaction, professional identity development, and high-quality patient care.

Peer Review reports

The learning environment is fundamental to higher education and has a profound impact on student outcomes. As conceptualized by Gruppen et al. [ 1 ], it comprises a complex interplay of physical, social, and virtual factors that shape student engagement, perception, and overall development. Over the last decade, there has been a growing global emphasis on the quality of the learning environment in higher education [ 2 , 3 , 4 ]. This focus stems from the recognition that a well-designed learning environment that includes good facilities, effective teaching methods, strong social interactions, and adherence to cultural and administrative standards can greatly improve student development [ 2 , 5 , 6 , 7 ]. Learning environments impact not only knowledge acquisition and skill development but also value formation and the cultivation of professional attitudes [ 5 ].

Professional identity is defined as the “attitudes, values, knowledge, beliefs, and skills shared with others within a professional group” [ 8 ]. The existing research identified a significant positive association between the development of professional identity and the quality of the learning environment, and this association is characterized by being multifaceted and dynamic [ 9 ]. According to Hendelman and Byszewski [ 10 ] a supportive learning environment, characterized by positive role models, effective feedback mechanisms, and opportunities for reflective practice, fosters the development of a strong professional identity among medical students. Similarly, Jarvis-Selinger et al. [ 11 ] argue that a nurturing learning environment facilitates the socialization process which enables students to adopt and integrate the professional behaviors and attitudes expected in their field. Furthermore, Sarraf-Yazdi et al. [ 12 ] highlighted that professional identity formation is a continuous and multifactorial process involving the interplay of individual values, beliefs, and environmental factors. This dynamic process is shaped by both clinical and non-clinical experiences within the learning environment [ 12 ].

Various learning theories, such as the Communities of Practice (CoP) theory [ 13 ], emphasize the link between learning environments and learning outcomes, including professional identity development. The CoP theory describes communities of professionals with a shared knowledge interest who learn through regular interaction [ 13 , 14 ]. Within the CoP, students transition from being peripheral observers to central members [ 15 ]. Therefore, the CoP theory suggests that a positive learning environment is crucial for fostering learning, professional identity formation, and a sense of community [ 16 ].

Undoubtedly, health professional education programs (e.g., Medicine, Dental Medicine, Pharmacy, and Health Sciences) play a vital role not only in shaping the knowledge, expertise, and abilities of health professional students but also in equipping them with the necessary competencies for implementing healthcare initiatives and strategies and responding to evolving healthcare demands [ 17 ]. Within the field of health professions education, international organizations like the United Nations Educational, Scientific, and Cultural Organization (UNESCO), European Union (EU), American Council on Education (ACE), and World Federation for Medical Education (WFME) have emphasized the importance of high-quality learning environments in fostering the development of future healthcare professionals and called for considerations of the enhancement of the quality of the learning environment of health profession education programs [ 18 , 19 ]. These environments are pivotal for nurturing both the academic and professional growth necessary to navigate an increasingly globalized healthcare landscape [ 18 , 19 ].

Professional identity development is integral to health professions education which evolves continuously from early university years until later stages of the professional life as a healthcare practitioner [ 20 , 21 ]. This ongoing development helps students establish clear professional roles and boundaries, thereby reducing role ambiguity within multidisciplinary teams [ 9 ]. It is expected that as students advance in their professional education, their perception of the quality of the learning environment changes, which influences their learning experiences, the development of their professional identity, and their sense of community [ 22 ]. Cruess et al. [ 23 ] asserted that medical schools foster professional identity through impactful learning experiences, effective role models, clear curricula, and assessments. A well-designed learning environment that incorporates these elements supports medical students' socialization and professional identity formation through structured learning, reflective practices, and constructive feedback in both preclinical and clinical stages [ 23 ].

Despite the recognized importance of the quality of learning environments and their influence on student-related outcomes, this topic has been overlooked regionally and globally [ 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. There is a significant knowledge gap in understanding how different components of the learning environment specifically contribute to professional identity formation. Most existing studies focus on general educational outcomes without exploring the detailed ways in which the learning environment shapes professional attitudes, values, and identity. Moreover, there is a global scarcity of research exploring how students’ perceptions of the quality of the learning environment and professional identity vary across various health profession education programs at different stages of their undergraduate education. This lack of comparative studies makes it challenging to identify best practices that can be adapted across different educational contexts. Furthermore, most research tends to focus on single-discipline studies, neglecting the interdisciplinary nature of modern healthcare education, which is essential for preparing students for collaborative practice in real-world healthcare settings. Considering the complex and demanding nature of health profession education programs and the increased emphasis on the quality of learning environments by accreditation bodies, examining the perceived quality of the educational learning environment by students is crucial [ 19 ]. Understanding students’ perspectives can provide valuable insights into areas needing improvement and highlight successful strategies that enhance both learning environment and experiences and professional identity development.

This research addresses this gap by focusing on the interdisciplinary health profession education programs to understand the impact of the learning environment on the development of the professional identity of students and its overall influence on their learning experiences. The objectives of this study are to 1) examine the perception of health professional students of the quality of their learning environment and their professional identity, 2) identify the association between health professional students’ perception of the quality of their learning environment and the development of their professional identity, and 3) explore the expectations of health professional students of the ideal educational learning environment. This research is essential in providing insights to inform educational practices globally to develop strategies to enhance the quality of health profession education.

Study setting and design

This study was conducted at Qatar University Health (QU Health) Cluster which is an interdisciplinary health profession education program that was introduced as the national provider of higher education in health and medicine in the state of Qatar. QU Health incorporates five colleges: Health Sciences (CHS), Pharmacy (CPH), Medicine (CMED), Dental Medicine (CDEM) and Nursing (CNUR) [ 31 ]. QU Health is dedicated to advancing inter-professional education (IPE) through its comprehensive interdisciplinary programs. By integrating IPE principles into the curriculum and fostering collaboration across various healthcare disciplines, the cluster prepares students to become skilled and collaborative professionals. Its holistic approach to teaching, research, and community engagement not only enhances the educational experience but also addresses local and regional healthcare challenges, thereby making a significant contribution to the advancement of population health in Qatar [ 32 ]. This study was conducted from November 2022 to July 2023. An explanatory sequential mixed methods triangulation approach was used for an in-depth exploration and validation of the quantitative results qualitatively [ 33 , 34 ]. Ethical approval for the study was obtained from the Qatar University Institutional Review Board (approval number: QU-IRB 1734-EA/22).

For the quantitative phase, a questionnaire was administered via SurveyMonkey® incorporating two previously validated questionnaires: the Dundee Ready Educational Environment Measure (DREEM), developed by Roff et al. in 1997 [ 35 ], and the Macleod Clark Professional Identity Scale-9 (MCPIS-9), developed by Adam et al. in 2006 [ 8 ]. Integrating DREEM and MCPIS-9 into a single questionnaire was undertaken to facilitate a comprehensive evaluation of two distinct yet complementary dimensions—namely, the educational environment and professional identity—that collectively influence the learning experience and outcomes of students, as no single instrument effectively assesses both aspects simultaneously [ 36 ]. The survey comprised three sections—Section A: sociodemographic characteristics, Section B: the DREEM scoring scale for assessing the quality of the learning environment, and Section C: the MCPIS-9 scoring scale for assessing professional identity. For the qualitative phase, seven focus groups (FGs) were arranged with a sample of QU-Health students. The qualitative and quantitative data obtained were integrated at the interpretation and reporting level using a narrative, contiguous approach [ 37 , 38 ].

Quantitative phase

Population and sampling.

The total population sampling approach in which all undergraduate QU-Health students who had declared their majors (i.e., the primary field of study that an undergraduate student has chosen during their academic program) at the time of conducting the study in any of the four health colleges under QU-Health ( N  = 908), namely, CPH, CMED, CDEM, and CHS, such as Human Nutrition (Nut), Biomedical Science (Biomed), Public Health (PH), and Physiotherapy (PS), were invited to participate in the study. Nursing students were excluded from this study because the college was just established in 2022; therefore, students were in their general year and had yet to declare their majors at the time of the study. The minimum sample size required for the study was determined to be 271 students based on a margin error of 5%, a confidence level of 95%, and a response distribution of 50%.

Data collection

Data was collected in a cross-sectional design. After obtaining the approval of the head of each department, contact information for eligible students was extracted from the QU-Health student databases for each college, and invitations were sent via email. The distribution of these invitations was done by the administrators of the respective colleges. The invitation included a link to a self-administered questionnaire on SurveyMonkey® (Survey Monkey Inc., San Mateo, California, USA), along with informed consent information. All 908 students were informed about the study’s purpose, data collection process, anonymity and confidentiality assurance, and the voluntary nature of participation. The participants were sent regular reminders to complete the survey to increase the response rate.

A focused literature review identified the DREEM as the most suitable validated tool for this study. The DREEM is considered the gold standard for assessing undergraduate students' perceptions of their learning environment [ 35 ]. Its validity and reliability have been consistently demonstrated across various settings (i.e., clinical and non-clinical) and health professions (e.g., nursing, medicine, dentistry, and pharmacy), in multiple countries worldwide, including the Gulf Cooperation Council countries [ 24 , 35 , 39 , 40 , 41 , 42 ]. The DREEM is a 50-item inventory divided into 5 subscales and developed to measure the academic climate of educational institutions using a five-point Likert scale from 0 “strongly disagree” to 4 “strongly agree”. The total score ranges from 0 to 200, with higher scores reflecting better perceptions of the learning environment [ 35 , 39 , 43 ]. The interpretation includes very poor (0–50), plenty of problems (51–100), more positive than negative (101–151), and excellent (151–200).

The first subscale, Perception to Learning (SpoL), with 12 items scoring 0–48. Interpretation includes very poor (0–12), teaching is viewed negatively (13–24), a more positive approach (25–36), and teaching is highly thought of (37–48). The second domain, Perception to Teachers (SpoT), with 11 items scoring 0–44. Interpretation includes abysmal (0–11), in need of some retraining (12–22), moving in the right direction (23–33), and model teachers (34–44). The third domain, academic self-perception (SASP), with 8 items scoring 0–32. Interpretation includes a feeling of total failure (0–8), many negative aspects (9–16), feeling more on the positive side (17–24), and confident (25–32). The fourth domain, Perception of the atmosphere (SPoA), with 12 items scoring 0–48. Interpretation includes a terrible environment (0–12); many issues need to be changed (13–24), a more positive atmosphere (25–36), and a good feeling overall (37–48). Lastly, the fifth domain, social self-perception (SSSP), with 7 items scoring 0–28. Interpretation includes Miserable (0–7), Not a nice place (8–14), Not very bad (15–21), and very good socially (22–28).

Several tools have been developed to explore professional identity in health professions [ 44 ], but there is limited research on their psychometric qualities [ 45 ]. The MCPIS-9 is notable for its robust psychometric validation and was chosen for this study due to its effectiveness in a multidisciplinary context as opposed to other questionnaires that were initially developed for the nursing profession [ 8 , 46 , 47 ]. MCPIS-9 is a validated 9-item instrument, which uses a 5-point Likert response scale, with scores ranging from 1 “strongly disagree” to 5 “strongly agree”. Previous studies that utilized the MCPIS-9 had no universal guidance for interpreting the MCPIS-9 score; however, the higher the score, the stronger the sense of professional identity [ 46 , 48 ].

Data analysis

The quantitative data were analyzed using SPSS software (IBM SPSS Statistics for Windows, version 27.0; IBM Corp., Armonk, NY, USA). The original developers of the DREEM inventory identified nine negative items: items 11, 12, 19, 20, 21, 23, 42, 43, and 46 – these items were reverse-coded. Additionally, in the MCPIS-9 tool, the original developers identified three negative items: items 3, 4, and 5. Descriptive and inferential analyses were also conducted. Descriptive statistics including number (frequencies [%]), mean ± SD, and median (IQR), were used to summarize the demographics and responses to the DREEM and MCPIS-9 scoring scales. In the inferential analysis, to test for significant differences between demographic subgroups in the DREEM and MCPIS-9 scores, Kruskal–Wallis tests were used for variables with more than two categories, and Mann–Whitney U-tests were used for variables with two categories. Spearman's rank correlation analysis was used to investigate the association between perceived learning environment and professional identity development. The level of statistical significance was set a priori at p  < 0.05. The internal consistency of the DREEM and MCPIS-9 tools was tested against the acceptable Cronbach's alpha value of 0.7.

Qualitative phase

A purposive sampling approach was employed to select students who were most likely to provide valuable insights to gain a deeper understanding of the topic. The inclusion criteria required that participants should have declared their major in one of the following programs: CPH, CMED, CDEM, CHS: Nut, Biomed, PS, and PH. This selection criterion aimed to ensure that participants had sufficient knowledge and experience related to their chosen fields of study within QU-Health. Students were included if they were available and willing to share their experiences and thoughts. Students who did not meet these criteria were excluded from participation. To ensure a representative sample, seven FGs were conducted, one with each health professional education program. After obtaining the approval of the head of each department, participants were recruited by contacting the class representative of each professional year to ask for volunteers to join and provide their insights. Each FG involved students from different professional years to ensure a diverse representation of experiences and perspectives.

The topic guide (Supplementary Material 1) was developed and conceptualized based on the research objectives, selected results from the quantitative phase, and the Gruppen et. al. framework [ 1 ]. FGs were conducted online using Microsoft Teams® through synchronous meetings. Before initiating the FGs, participants were informed of their rights and returned signed consent forms to the researchers. FGs were facilitated by two research assistants (AA and OY), each facilitating separate sessions. The facilitators, who had prior experience with conducting FGs and who were former pharmacy students from the CPH, were familiar with some of the participants, and hence were able to encourage open discussion, making it easier for students to share their perceptions of the learning environment within the QU Health Cluster. Participants engaged in concurrent discussions were encouraged to use the "raise hand" feature on Microsoft Teams to mimic face-to-face interactions. Each FG lasted 45–60 min, was conducted in English, and was recorded and transcribed verbatim and double-checked for accuracy. After the seventh FG, the researchers were confident that a saturation point had been reached where no new ideas emerged, and any further data collection through FGs was unnecessary. Peer and supervisory audits were conducted throughout the research process.

The NVIVO ® software (version 12) was utilized to perform a thematic analysis incorporating both deductive and inductive approaches. The deductive approach involved organizing the data into pre-determined categories based on the Gruppen et al. framework, which outlines key components of the learning environment. This framework enabled a systematic analysis of how each component of the learning environment contributes to students' professional development and highlighted areas for potential improvement. Concurrently, the inductive approach was applied to explore students' perceptions of an ideal learning environment, facilitating the emergence of new themes and insights directly from the data, independent of pre-existing categories. This dual approach provided a comprehensive understanding of the data by validating the existing theory while also exploring new findings [ 49 ]. Two coders were involved in coding the transcripts (AA and BM) and in cases of disagreements between researchers, consensus was achieved through discussion.

The response rate was 57.8% (525 responses out of 908), while the usability rate was 74.3% (390 responses out of 525) after excluding students who only completed the demographic section. The demographic and professional characteristics of the participants are presented in Table  1 . The majority were Qataris (37.0% [ n  = 142]), females (85.1% [ n  = 332]), and of the age group of 21–23 years (51.7% [ n  = 201]). The students were predominantly studying at the CHS (36.9%[ n  = 144]), in their second professional year (37.4% [ n  = 146]), and had yet to be exposed to experiential learning, that is, clinical rotations (70.2% [ n  = 273]).

Perceptions of students of their learning environment

The overall median DREEM score for study participants indicated that QU Health students perceive their learning environment to be "more positive than negative" (132 [IQR = 116–174]). The reliability analysis for this sample of participants indicated a Cronbach's alpha for the total DREEM score of 0.94, and Cronbach's alpha scores for each domain of the DREEM tool, SPoL, SPoT, SASP, SPoA, and SSSP of 0.85, 0.74, 0.81, 0.85, and 0.65, respectively.

Individual item responses representing each domain of the DREEM tool are presented in Table  2 . For Domain I, QU Health students perceived the teaching approach in QU Health to be "more positive" (32 [IQR = 27–36]). Numerous participants agreed that the teaching was well-focused (70.7% [ n  = 274]), student-focused (66.1% [ n  = 254]) and aimed to develop the competencies of students (72.0% [ n  = 278]). The analysis of students’ perceptions related to Domain II revealed that faculty members were perceived to be “moving in the right direction” (30 [IQR = 26–34]). Most students agreed that faculty members were knowledgeable (90.7%[ n  = 345]) and provided students with clear examples and constructive feedback (77.6% [ n  = 294] and 63.8% [ n  = 224], respectively. Furthermore, the analysis of Domain III demonstrated that QU Health students were shown to have a "positive academic self-perception" (22 [IQR = 19–25]). In this regard, most students believed that they were developing their problem-solving skills (78% [ n  = 292]) and that what they learned was relevant to their professional careers (76% [ n  = 288]). Furthermore, approximately 80% ( n  = 306) of students agreed that they had learned empathy in their profession. For Domain IV, students perceived the atmosphere of their learning environment to be "more positive" (32 [IQR = 14–19]). A substantial number of students asserted that there were opportunities for them to develop interpersonal skills (77.7% [ n  = 293]), and that the atmosphere motivated them as learners (63.0% [ n  = 235]). Approximately one-third of students believed that the enjoyment did not outweigh the stress of studying (32.3% [ n  = 174]). Finally, analysis of Domain V indicates that students’ social self-perception was “not very bad” (17 [IQR = 27–36]). Most students agreed that they had good friends at their colleges (83% [ n  = 314]) and that their social lives were good (68% [ n  = 254]).

Table 3 illustrates the differences in the perception of students of their overall learning environment according to their demographic and professional characteristics. No significant differences were noted in the perception of the learning environment among the subgroups with selected demographic and professional characteristics, except for the health profession program in which they were enrolled ( p -value < 0.001), whether they had relatives who studied or had studied the same profession ( p -value < 0.002), and whether they started their experiential learning ( p -value = 0.043). Further analyses comparing the DREEM subscale scores according to their demographic and professional characteristics are presented in Supplementary Material 1.

Students’ perceptions of their professional identities

The students provided positive responses relating to their perceptions of their professional identity (24.00 IQR = [22–27]). The reliability analysis of this sample indicated a Cronbach's alpha of 0.605. The individual item responses representing the MCPIS-9 tool are presented in Table  2 . Most students (85% [ n  = 297]) expressed pleasant feelings about belonging to their own profession, and 81% ( n  = 280) identified positively with members of their profession. No significant differences were noted in the perception of students of their professional identity when analyzed against selected demographic subgroups, except for whether they had relatives who had studied or were studying the same profession ( p -value = 0.027). Students who had relatives studying or had studied the same profession tended to perceive their professional identity better (25 IQR = [22–27] and 24 IQR = [21–26], respectively) (Table  3 ).

Association between MCPIS-9 and DREEM

Spearman's rank correlation between the DREEM and MCPIS-9 total scores indicated an intermediate positive correlation between perceptions of students toward their learning environment and their professional identity development (r = 0.442, p -value < 0.001). The DREEM questionnaire, with its 50 items divided into five subscales, comprehensively assessed various dimensions of the learning environment. Each subscale evaluated a distinct aspect of the educational experience, such as the effectiveness of teaching, teacher behavior and attitudes, academic confidence, the overall learning atmosphere, and social integration. The MCPIS-9 questionnaire specifically assessed professional identity through nine items that measure attitudes, values, and self-perceived competence in the professional domain. The positive correlation demonstrated between the DREEM and MCPIS-9 scores indicated that as students perceive their learning environment more positively, their professional identity is also enhanced.

Thirty-seven students from the QU Health colleges were interviewed: eleven from CPH, eight from CMED, four from CDEM, and fourteen from CHS (six from Nut, three from PS, three from Biomed, and three from PH). Four conventional themes were generated deductively using Gruppen et al.’s conceptual framework, while one theme was derived through inductive analysis. The themes and sub-themes generated are demonstrated in Table  4 .

Theme 1. The personal component of the learning environment

This theme focused on student interactions and experiences within their learning environment and their impact on perceptions of learning, processes, growth, and professional development.

Sub-theme 1.1. Experiences influencing professional identity formation

Students classified their experiences into positive and negative. Positive experiences included hands-on activities such as on-campus practical courses and pre-clinical activities, which built their confidence and professional identity. In this regard, one student mentioned:

“Practical courses are one of the most important courses to help us develop into pharmacists. They make you feel confident in your knowledge and more willing to share what you know.” [CPH-5]

Many students claimed that interprofessional education (IPE) activities enhanced their self-perception, clarified their roles, and boosted their professional identity and confidence. An interviewee stated:

"I believe that the IPE activity,…., is an opportunity for us to explore our role. It has made me know where my profession stands in the health sector and how we all depend on each other through interprofessional thinking and discussions." [CHS-Nut-32]

However, several participants reported that an extensive workload hindered their professional identity development. A participant stated:

“The excessive workload prevents us from joining activities that would contribute to our professional identity development. Also, it restricts our networking opportunities and makes us always feel burnt out.” [CHS-Nut-31]

Sub-theme 1.2. Strategies used by students to pursue their goals

QU Health students employed various academic and non-academic strategies to achieve their objectives, with many emphasizing list-making and identifying effective study methods as key approaches:

“Documentation. I like to see tasks that I need to do on paper. Also, I like to classify my tasks based on their urgency. I mean, deadlines.” [CHS-Nut-31]

“I always try to be as efficient as possible when studying and this can be by knowing what studying method best suits me.” [CHS-Biomed-35]

Nearly all students agreed that seeking feedback from faculty was crucial for improving their work and performance. In this context, a student said:

“We must take advantage of the provided opportunity to discuss our assignments, projects, and exams, like what we did correctly, and what we did wrongly. They always discuss with us how to improve our work on these things.” [CHS-Nut-32]

Moreover, many students also believed that developing communication skills was vital for achieving their goals, given their future roles in interprofessional teams. A student mentioned:

“Improving your communication skills is a must because inshallah (with God’s will) in the future we will not only work with biomedical scientists, but also with nurses, pharmacists, and doctors. So, you must have good communication abilities.” [CHS-Biomed-34]

Finally, students believe that networking is crucial for achieving their goals because it opens new opportunities for them as stated by a student:

“Networking with different physicians or professors can help you to know about research or training opportunities that you could potentially join.” [CMED-15]

Subtheme 1.3. Students’ mental and physical well-being

Students agreed that while emotional well-being is crucial for good learning experiences and professional identity development, colleges offered insufficient support. An interviewee stated:

“We simply don't have the optimal support we need to take care of our emotional well-being as of now, despite how important it is and how it truly reflects on our learning and professional development” [CDEM-20]

Another student added:

“…being in an optimal mental state provides us with the opportunity to acquire all required skills that would aid in our professional identity development. I mean, interpersonal skills, adaptability, self-reflection” [CPH-9]

Students mentioned some emotional support provided by colleges, such as progress tracking and stress-relief activities. Students said:

“During P2 [professional year 2], I missed a quiz, and I was late for several lectures. Our learning support specialist contacted me … She was like, are you doing fine? I explained everything to her, and she contacted the professors for their consideration and support.” [CPH-7]

“There are important events that are done to make students take a break and recharge, but they are not consistent” [CHS-PS-27]

On the physical well-being front, students felt that their colleges ensured safety, especially in lab settings, with proper protocols to avoid harm. A student mentioned:

“The professors and staff duly ensure our safety, especially during lab work. They make sure that we don't go near any harmful substances and that we abide by the lab safety rules” [CHS-Biomed -35]

Theme 2. Social component of the learning environment

This theme focused on how social interactions shape students’ perceptions of learning environments and learning experiences.

Sub-theme 2.1. Opportunities for community engagement

Participants identified various opportunities for social interactions through curricular and extracurricular activities. Project-based learning (PBL) helped them build connections, improve teamwork and enhance critical thinking and responsibility as stated by one student:

“I believe that having PBL as a big part of our learning process improves our teamwork and interpersonal skills and makes us take responsibility in learning, thinking critically, and going beyond what we would have received in class to prepare very well and deep into the topic.” [CMED-12]

Extracurricular activities, including campaigns and events, helped students expand their social relationships and manage emotional stress. A student stated:

“I think that the extracurricular activities that we do, like the campaigns or other things that we hold in the college with other students from other colleges, have been helpful for me in developing my personality and widening my social circle. Also, it dilutes the emotional stress we are experiencing in class” [CDEM-22]

Sub-theme 2.2. Opportunities for learner-to-patient interactions

Students noted several approaches their colleges used to enhance patient-centered education and prepare them for real-world patient interactions. These approaches include communication skills classes, simulated patient scenarios, and field trips. Students mentioned:

“We took a class called Foundation of Health, which mainly focused on how to communicate our message to patients to ensure that they were getting optimal care. This course made us appreciate the term ‘patient care’ more.” [CHS-PH-38]

“We began to appreciate patient care when we started to take a professional skills course that entailed the implementation of a simulated patient scenario. We started to realize that communication with patients didn’t go as smoothly as when we did it with a colleague in the classroom.” [CPH-1]

“We went on a field trip to ‘Shafallah Center for Persons with Disability’ and that helped us to realize that there were a variety of patients that we had to care for, and we should be physically and mentally prepared to meet their needs.” [CDEM-21]

Theme 3. Organizational component of the learning environment

This theme explored students' perceptions of how the college administration, policies, culture, coordination, and curriculum design impact their learning experiences.

Sub-theme 3.1. Curriculum and study plan

Students valued clinical placements for their role in preparing them for the workplace and developing professional identity. A student stated:

“Clinical placements are very crucial for our professional identity development; we get the opportunity to be familiarized with and prepared for the work environment.” [CHS-PS-27]

However, students criticized their curriculum for not equipping them with adequate knowledge and skills. For example, a student said:

“… Not having a well-designed curriculum is of concern. We started very late in studying dentistry stuff and that led to us cramming all the necessary information that we should have learned.” [CDEM-20]

Furthermore, students reported that demanding schedules and limited course availability hindered learning and delayed progress:

“Last semester, I had classes from Sunday to Thursday from 8:00 AM till 3:00 PM in the same classroom, back-to-back, without any break. I was unable to focus in the second half of the day.” [CHS-Nut-38]

“Some courses are only offered once a year, and they are sometimes prerequisites for other courses. This can delay our clinical internship or graduation by one year.” [CHS-Biomed-36]

Additionally, the outdated curriculum was seen as misaligned with advancements in artificial intelligence (AI). One student stated:

“… What we learn in our labs is old-fashioned techniques, while Hamad Medical Corporation (HMC) is following a new protocol that uses automation and AI. So, I believe that we need to get on track with HMC as most of us will be working there after graduation.” [CHS-Biomed-35]

Sub-theme 3.2. Organizational climate and policies

Students generally appreciated the positive university climate and effective communication with the college administration which improves course quality:

“Faculty members and the college administration usually listen to our comments about courses or anything that we want to improve, and by providing a course evaluation at the end of the semester, things get better eventually.” [CPH-2]

Students also valued faculty flexibility with scheduling exams and assignments, and praised the new makeup exam policy which enhances focus on learning:

“Faculty members are very lenient with us. If we want to change the date of the exam or the deadline for any assignment, they agree if everyone in the class agrees. They prioritize the quality of our work over just getting an assignment done.” [CHS-PS-37]

“I am happy with the introduction of makeup exams. Now, we are not afraid of failing and losing a whole year because of a course. I believe that this will help us to focus on topics, not just cramming the knowledge to pass.” [CPH-9]

However, students expressed concerns about the lack of communication between colleges and clinical placements and criticized the lengthy approval process for extracurricular activities:

“There is a contract between QU and HMC, but the lack of communication between them puts students in a grey area. I wish there would be better communication between them.” [CMED-15]

“To get a club approved by QU, you must go through various barriers, and it doesn't work every time. A lot of times you won't get approved.” [CMED-14]

Theme 4. Materialistic component of the learning environment

This theme discussed how physical and virtual learning spaces affect students' learning experiences and professional identity.

Sub-theme 4.1. The physical space for learning

Students explained that the interior design of buildings and the fully equipped laboratory facilities in their programs enhanced focus and learning:

“The design has a calming effect, all walls are simple and isolate the noise, the classrooms are big with big windows, so that the sunlight enters easily, and we can see the green grass. This is very important for focusing and optimal learning outcomes.” [CPH-5]

“In our labs, we have beds and all the required machines for physiotherapy exercises and practical training, and we can practice with each other freely.” [CHS-PS-27]

Students from different emphasized the need for dedicated lecture rooms for each batch and highlighted the importance of having on-site cafeterias to avoid disruptions during the day:

“We don't have lecture rooms devoted to each batch. Sometimes we don't even find a room to attend lectures and we end up taking the lectures in the lab, which makes it hard for us to focus and study later.” [CDEM-23]

“Not having a cafeteria in this building is a negative point. Sometimes we miss the next lecture or part of it if we go to another building to buy breakfast.” [CHS-Nut-29]

Sub-theme 4.2. The virtual space for online learning

Students appreciated the university library's extensive online resources and free access to platforms like Microsoft Teams and Webex for efficient learning and meetings. They valued recorded lectures for flexible study and appreciated virtual webinars and workshops for global connectivity.

“QU Library provides us with a great diversity and a good number of resources, like journals or books, as well as access medicine, massive open online courses, and other platforms that are very useful for studying.” [CMED-16].

“Having your lectures recorded through virtual platforms made it easier to take notes efficiently and to study at my own pace.” [CHS-PS-38]

"I hold a genuine appreciation for the provided opportunities to register in online conferences. I remember during the COVID-19 pandemic, I got the chance to attend an online workshop. This experience allowed me to connect with so many people from around the world." [CMED-15]

Theme 5. Characteristics of an ideal learning environment

This theme explored students’ perceptions of an ideal learning environment and its impact on their professional development and identity.

Sub-theme 5.1. Active learning and professional development supporting environment

Students highlighted that an ideal learning environment should incorporate active learning methods and a supportive atmosphere. They suggested using simulated patients in case-based learning and the use of game-based learning platforms:

“I think if we have, like in ITQAN [a Clinical Simulation and Innovation Center located on the Hamad Bin Khalifa Medical City (HBKMC) campus of Hamad Medical Corporation (HMC)], simulated patients, I think that will be perfect like in an “Integrated Case-Based Learning” case or professional skills or patient assessment labs where we can go and intervene with simulated patients and see what happens as a consequence. This will facilitate our learning.” [CPH-4]

“I feel that ‘Kahoot’ activities add a lot to the session. We get motivated and excited to solve questions and win. We keep laughing, and I honestly feel that the answers to these questions get stuck in my head.” [CHS-PH-38].

Students emphasized the need for more opportunities for research, career planning, and equity in terms of providing resources and opportunities for students:

“Students should be provided with more opportunities to do research, publish, and practice.” [CMED-16]

“We need better career planning and workshops or advice regarding what we do after graduation or what opportunities we have.” [CHS-PS-25]

“I think that opportunities are disproportionate, and this is not ideal. I believe all students should have the same access to opportunities like having the chance to participate in conferences and receiving research opportunities, especially if one fulfills the requirements.” [CHS-Biomed-35]

Furthermore, the students proposed the implementation of mentorship programs and a reward system to enable a better learning experience:

“Something that could enable our personal development is a mentorship program, which our college started to implement this year, and I hope they continue to because it’s an attribute of an ideal learning environment.” [CPH-11]

“There has to be some form of reward or acknowledgments to students, especially those who, for example, have papers published or belong to leading clubs, not just those who are, for example, on a dean’s list because education is much more than just academics.” [CHS-PS-26]

Subtheme 5.2. Supportive physical environment

Participants emphasized that the physical environment of the college significantly influences their learning attitudes. A student said:

“The first thing that we encounter when we arrive at the university is the campus. I mean, our early thoughts toward our learning environment are formed before we even know anything about our faculty members or the provided facilities. So, ideally, it starts here.” [CPH-10]

Therefore, students identified key characteristics of an optimal physical environment which included: having a walkable campus, designated study and social areas, and accessible food and coffee.

“I think that learning in what they refer to as a walkable campus, which entails having the colleges and facilities within walking distance from each other, without restrictions of high temperature and slow transportation, is ideal.” [CPH-8]

“The classrooms and library should be conducive to studying and focusing, and there should also be other places where one can actually socialize and sit with one’s friends.” [CDEM-22]

“It is really important to have a food court or café in each building, as our schedules are already packed, and we have no time to go get anything for nearby buildings.” [CHS-Biomed-34]

Data integration

Table 5 represents the integration of data from the quantitative and qualitative phases. It demonstrates how the quantitative findings informed and complemented the qualitative analysis and explains how quantitative data guided the selection of themes in the qualitative phase. The integration of quantitative and qualitative data revealed both convergences and divergences in students' views of their learning environment. Both data sources consistently indicated that the learning environment supported the development of interpersonal skills, fostered strong relationships with faculty, and promoted an active, student-centered learning approach. This environment was credited with enhancing critical thinking, independence, and responsibility, as well as boosting students' confidence and competence through clear role definitions and constructive faculty feedback.

However, discrepancies emerged between the two phases. Quantitative data suggested general satisfaction with timetables and support systems, while qualitative data uncovered significant dissatisfaction. Although quantitative results indicated that students felt well-prepared and able to memorize necessary material, qualitative findings revealed challenges with concentration and focus. Furthermore, while quantitative data showed contentment with institutional support, qualitative responses pointed to shortcomings in emotional and physical support.

This study examined the perceptions of QU Health students regarding the quality of their learning environment and the characteristics of an ideal learning environment. Moreover, this study offered insights into the development of professional identity, emphasizing the multifaceted nature of learning environments and their substantial impact on professional identity formation.

Perceptions of the learning environment

The findings revealed predominantly positive perceptions among students regarding the quality of the overall learning environment at QU Health and generally favorable perception of all five DREEM subscales, which is consistent with the international studies using the DREEM tool [ 43 , 50 , 51 , 52 , 53 , 54 ]. Specifically, participants engaged in experiential learning expressed heightened satisfaction, which aligns with existing research indicating that practical educational approaches enhance student engagement and satisfaction [ 55 , 56 ]. Additionally, despite limited literature, students without relatives in the same profession demonstrated higher perceptions of their learning environment, possibly due to fewer preconceived expectations. A 2023 systematic review highlighted how students’ expectations influence their satisfaction and academic achievement [ 57 ]. However, specific concerns arose regarding the learning environment, including overemphasis on factual learning in teaching, student fatigue, and occasional boredom. These issues were closely linked to the overwhelming workload and conventional teaching methods, as identified in the qualitative phase.

Association between learning environment and professional identity

This study uniquely integrated the perceptions of the learning environment with insights into professional identity formation in the context of healthcare education which is a relatively underexplored area in quantitative studies [ 44 , 58 , 59 , 60 ]. This study demonstrated a positive correlation between students' perceptions of the learning environment (DREEM) and their professional identity development (MCPIS-9) which suggested that a more positive learning environment is associated with enhanced professional identity formation. For example, a supportive and comfortable learning atmosphere (i.e., high SPoA scores) can enhance students' confidence and professional self-perception (i.e., high MCPIS-9 scores). The relationship between these questionnaires is fundamental to this study. The DREEM subscales, particularly Perception of Learning (SpoL) and Academic Self-Perception (SASP), relate to how the learning environment supports or hinders the development of a professional identity, as measured by MCPIS-9. Furthermore, the Perception of Teachers (SpoT) subscale examines how teacher behaviors and attitudes impact students, which can influence their professional identity development. The Perception of Atmosphere (SPoA) and Social Self-Perception (SSSP) subscales evaluate the broader environment and social interactions, which are crucial for professional identity formation as they foster a sense of community and belonging.

Employing a mixed methods approach and analyzing both questionnaires and FGs through the framework outlined by Gruppen et al. highlighted key aspects across four dimensions of the learning environment: personal development, social dimension, organizational setting, and materialistic dimension [ 1 ]. First, the study underscored the significance of both personal development and constructive feedback. IPE activities emerged as a key factor that promotes professional identity by cultivating collaboration and role identification which is consistent with Bendowska and Baum's findings [ 61 ]. Similarly, the positive impact of constructive faculty feedback on student learning outcomes aligned with the work of Gan et al. which revealed that feedback from faculty members positively influences course satisfaction and knowledge retention, which are usually reflected in course results [ 62 ]. Importantly, the research also emphasized the need for workload management strategies to mitigate negative impacts on student well-being, a crucial factor for academic performance and professional identity development [ 63 , 64 ]. The inclusion of community events and support services could play a significant role in fostering student well-being and reducing stress, as suggested by Hoferichter et al. [ 65 ]. Second, the importance of the social dimension of the learning environment was further highlighted by the study. Extracurricular activities were identified as opportunities to develop essential interpersonal skills needed for professional identity, mirroring the conclusions drawn by Achar Fujii et al. who argued that extracurricular activities lead to the development of fundamental skills and attitudes to build and refine their professional identity and facilitate the learning process, such as leadership, commitment, and responsibility [ 66 ]. Furthermore, Magpantay-Monroe et al. concluded that community and social engagement led to professional identity development in nursing students through the expansion of their knowledge and communication with other nursing professionals [ 67 ]. PBL activities were another key element that promoted critical thinking, learning, and ultimately, professional identity development in this study similar to what was reported by Zhou et al. and Du et al. [ 68 , 69 ]. Third, the organizational setting, particularly the curriculum and clinical experiences, emerged as crucial factors. Clinical placements and field trips were found to be instrumental in cultivating empathy and professional identity [ 70 , 71 ]. However, maintaining an up-to-date curriculum that reflects advancements in AI healthcare education is equally important, as highlighted by Randhawa and Jackson in 2019 [ 72 ]. Finally, the study underlined the role of the materialistic dimension of the learning environment. Physical learning environments with natural light and managed noise levels were found to contribute to improved academic performance [ 73 , 74 ]. Additionally, the value of online educational resources, such as online library resources and massive open online course, as tools facilitating learning by providing easy access to materials, was emphasized, which is consistent with the observations of Haleem et al. [ 75 ].

The above collectively contribute to shaping students' professional identities through appreciating their roles, developing confidence, and understanding the interdependence of different health professions. These indicate that a supportive and engaging learning environment is crucial for fostering a strong sense of professional identity. Incorporating these student-informed strategies can assist educational institutions in cultivating well-rounded healthcare professionals equipped with the knowledge, skills, and emotional resilience needed to thrive in the dynamic healthcare landscape. Compared to existing quantitative data, this study reported a lower median MCPIS-9 score of 24.0, in contrast to previously reported scores of 39.0, 38.0, 38.0, respectively. [ 76 , 77 , 78 ]. This discrepancy may be influenced by the fact that the participants were in their second professional year, known for weaker identity development [ 79 ]. Students with relatives in the same profession perceived their identity more positively, which is likely due to role model influences [ 22 ].

Expectations of the ideal educational learning environment

This study also sought to identify the key attributes of an ideal learning environment from the perspective of students at QU-Health. The findings revealed a strong emphasis on active learning strategies, aligning with Kolb's experiential learning theory [ 80 ]. This preference suggests a desire to move beyond traditional lecture formats and engage in activities that promote experimentation and reflection, potentially mitigating issues of student boredom. Furthermore, students valued the implementation of simple reward systems such as public recognition, mirroring the positive impact such practices have on academic achievement reported by Dannan in 2020 [ 81 ]. The perceived importance of mentorship programs resonates with the work of Guhan et al. who demonstrated improved academic performance, particularly for struggling students [ 82 ]. Finally, the study highlighted the significance of a walkable campus with accessible facilities. This aligns with Rohana et al. who argued that readily available and useable facilities contribute to effective teaching and learning processes, ultimately resulting in improved student outcomes [ 83 ]. Understanding these student perceptions, health professions education programs can inform strategic planning for curricular and extracurricular modifications alongside infrastructural development.

The complementary nature of qualitative and quantitative methods in understanding student experiences

This study underscored the benefits of employing mixed methods to comprehensively explore the interplay between the learning environment and professional identity formation as complex phenomena. The qualitative component provided nuanced insights that complemented the baseline data provided by DREEM and MCPIS-9 questionnaires. While DREEM scores generally indicated positive perceptions, qualitative findings highlighted the significant impact of experiential learning on students' perceptions of the learning environment and professional identity development. Conversely, discrepancies emerged between questionnaire responses and FG interviews, revealing deeper issues such as fatigue and boredom associated with traditional teaching methods and heavy workloads, potentially influenced by cultural factors. In FGs, students revealed cultural pressures to conform and stigma against expressing dissatisfaction, which questionnaire responses may not capture. Qualitative data allowed students to openly discuss culturally sensitive issues, indicating that interviews complement surveys by revealing insights overlooked in quantitative assessments alone. These insights can inform the design of learning environments that support holistic student development. The study also suggested that cultural factors can influence student perceptions and should be considered in educational research and practice.

Application of findings

The findings from this study can be directly applied to inform and enhance educational practices, as well as to influence policy and practice sectors. Educational institutions should prioritize integrating active learning strategies and mentorship programs to combat issues such as student fatigue and boredom. Furthermore, practical opportunities, including experiential learning and IPE activities, should be emphasized to strengthen professional identity and engagement. To address these challenges comprehensively, policymakers should consider developing policies that support effective workload management and community support services, which are essential for improving student well-being and academic performance. Collaboration between educational institutions and practice sectors can greatly improve students' satisfaction with their learning environment and experience. This partnership enhances the relevance and engagement of their education, leading to a stronger professional identity and better preparation for successful careers.

Limitations

As with all research, this study has several limitations. For instance, there was a higher percentage of female participants compared to males; however, it is noteworthy to highlight the demographic composition of QU Health population, where students are majority female. Furthermore, the CHS, which is one of the participating colleges in this study, enrolls only female students. Another limitation is the potentially underpowered statistical comparisons among the sociodemographic characteristics in relation to the total DREEM and MCPIS-9 scores. Thus, the findings of this study should be interpreted with caution.

The findings of this study reveal that QU Health students generally hold a positive view of their learning environment and professional identity, with a significant positive correlation exists between students’ perceptions of their learning environment and their professional identity. Specifically, students who engaged in experiential learning or enrolled in practical programs rated their learning environment more favorably, and those with relatives in the same profession had a more positive view of their professional identity. The participants of this study also identified several key attributes that contribute to a positive learning environment, including active learning approaches and mentorship programs. Furthermore, addressing issues like fatigue and boredom is crucial for enhancing student satisfaction and professional development.

To build on these findings, future research should focus on longitudinal studies that monitor changes in the perceptions of students over time and identify the long-term impact of implementing the proposed attributes of an ideal learning environment on the learning process and professional identity development of students. Additionally, exploring the intricate dynamics of learning environments and their impact on professional identity can allow educators to better support students in their professional journey. Future research should also continue to explore these relationships, particularly on diverse cultural settings, in order to develop more inclusive and effective educational strategies. This approach will ensure that health professional students are well-prepared to meet the demands of their profession and provide high-quality care to their patients.

Availability of data and materials

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

Abbreviations

United Nations Educational, Scientific, and Cultural Organization

European Union

American Council on Education

World Federation for Medical Education

Communities of Practice

Qatar University Health

College of Health Sciences

College of Pharmacy

College of Medicine

Dental Medicine

College of Nursing

Human Nutrition

Biomedical Science

Public Health

Physiotherapy

Dundee Ready Education Environment Measure

Perception to Learning

Perception to Teachers

Academic Self-Perception

Perception of the Atmosphere

Social Self-Perception

Macleod Clark Professional Identity Scale

Focus Group

InterProfessional Education

Project-Based Learning

Hamad Medical Corporation

Hamad Bin Khalifa Medical City

Artificial Intelligence

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The authors would like to thank all students who participated in this study.

This work was supported by the Qatar University Internal Collaborative Grant: QUCG-CPH-22/23–565.

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Study conception and design: BM, and SE; data collection: BM, OY, AA, and AD; analysis and interpretation of results: all authors; draft manuscript preparation: all authors. All authors reviewed the results and approved the final version of the manuscript.

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Mukhalalati, B., Aly, A., Yakti, O. et al. Examining the perception of undergraduate health professional students of their learning environment, learning experience and professional identity development: a mixed-methods study. BMC Med Educ 24 , 886 (2024). https://doi.org/10.1186/s12909-024-05875-4

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DOI : https://doi.org/10.1186/s12909-024-05875-4

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Exploring the violent enforcement stereotype of Chengguan: a qualitative study in China

• Published: 17 August 2024

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• Yutong Pan 1 ,
• Yujiao Feng 1 ,
• Yan Liu 1 &
• Jinfa Liu   ORCID: orcid.org/0000-0002-4592-4659 1  

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This study aimed to investigate the reasons of the violent enforcement stereotype of Chengguan. To achieve this objective, 55 semi-structured qualitative interviews were conducted with street vendors, Chengguan staff and the public in 2022 and 2023. The analysis drew upon street-level bureaucracy theory and employed inductive content analysis to thoroughly examine the interview data. The research revealed that the public commonly associates Chengguan with violent enforcement, mainly due to a pattern of violent tendencies and behaviors observed in specific enforcement actions. A deeper analysis indicated that the ambiguous positioning of Chengguan department, the low thresholds of staff recruitment, and the perfunctory accountability of staff dismissal are the root reasons for violent enforcement by Chengguan. Additionally, the negative portrayal of Chengguan in self-media and the reduced effectiveness of traditional authoritative media in conveying objective information have both shaped and entrenched this negative image. This paper extends the application of street-level bureaucracy theory, offering a new perspective and analytical framework to better understand the stereotype of violent enforcement by Chengguan. Moreover, the study presents practical strategies to address or mitigate the negative stereotype. To our knowledge, this work represents a comprehensive and systematic theoretical discussion on the stereotype of violent enforcement by Chengguan, providing significant theoretical insights and practical relevance.

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Research achievements of Shandong Social Science Planning Project (Grant No.: 22CGLJ15).

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Yutong Pan, Yujiao Feng, Yan Liu & Jinfa Liu

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YP conceived the study, and all four authors participated in its design. JL contributed to the conception of the study and writing of the manuscript. YF and YL contributed to the analysis and manuscript preparation. All authors contributed to the article and approved the submitted version.

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Correspondence to Jinfa Liu .

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The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of Qufu Normal University.

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Pan, Y., Feng, Y., Liu, Y. et al. Exploring the violent enforcement stereotype of Chengguan: a qualitative study in China. Curr Psychol (2024). https://doi.org/10.1007/s12144-024-06444-0

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Accepted : 20 July 2024

Published : 17 August 2024

DOI : https://doi.org/10.1007/s12144-024-06444-0

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