qualitative research method articles

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

Methodology

• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on June 19, 2020 by Pritha Bhandari . Revised on September 5, 2024.

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

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

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

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

Table of contents

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

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

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

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

Prevent plagiarism. Run a free check.

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

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

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

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

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

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

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

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

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

• Flexibility

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

• Natural settings

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

• Meaningful insights

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

• Generation of new ideas

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

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

• Academic style
• Vague sentences
• Style consistency

See an example

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

• Unreliability

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

• Subjectivity

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

• Limited generalizability

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

• Labor-intensive

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

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

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

Research bias

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

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

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

There are five common approaches to qualitative research :

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

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

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

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

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

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Bhandari, P. (2024, September 05). What Is Qualitative Research? | Methods & Examples. Scribbr. Retrieved September 16, 2024, from https://www.scribbr.com/methodology/qualitative-research/

Is this article helpful?

Pritha Bhandari

Other students also liked, qualitative vs. quantitative research | differences, examples & methods, how to do thematic analysis | step-by-step guide & examples, "i thought ai proofreading was useless but..".

I've been using Scribbr for years now and I know it's a service that won't disappoint. It does a good job spotting mistakes”

• Open access
• Published: 27 May 2020

How to use and assess qualitative research methods

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

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

779k Accesses

369 Citations

90 Altmetric

Metrics details

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

Philipsen, H., & Vernooij-Dassen, M. (2007). Kwalitatief onderzoek: nuttig, onmisbaar en uitdagend. In L. PLBJ & H. TCo (Eds.), Kwalitatief onderzoek: Praktische methoden voor de medische praktijk . [Qualitative research: useful, indispensable and challenging. In: Qualitative research: Practical methods for medical practice (pp. 5–12). Houten: Bohn Stafleu van Loghum.

Chapter   Google Scholar  

Punch, K. F. (2013). Introduction to social research: Quantitative and qualitative approaches . London: Sage.

Kelly, J., Dwyer, J., Willis, E., & Pekarsky, B. (2014). Travelling to the city for hospital care: Access factors in country aboriginal patient journeys. Australian Journal of Rural Health, 22 (3), 109–113.

Article   Google Scholar  

Nilsen, P., Ståhl, C., Roback, K., & Cairney, P. (2013). Never the twain shall meet? - a comparison of implementation science and policy implementation research. Implementation Science, 8 (1), 1–12.

Howick J, Chalmers I, Glasziou, P., Greenhalgh, T., Heneghan, C., Liberati, A., Moschetti, I., Phillips, B., & Thornton, H. (2011). The 2011 Oxford CEBM evidence levels of evidence (introductory document) . Oxford Center for Evidence Based Medicine. https://www.cebm.net/2011/06/2011-oxford-cebm-levels-evidence-introductory-document/ .

Eakin, J. M. (2016). Educating critical qualitative health researchers in the land of the randomized controlled trial. Qualitative Inquiry, 22 (2), 107–118.

May, A., & Mathijssen, J. (2015). Alternatieven voor RCT bij de evaluatie van effectiviteit van interventies!? Eindrapportage. In Alternatives for RCTs in the evaluation of effectiveness of interventions!? Final report .

Google Scholar  

Berwick, D. M. (2008). The science of improvement. Journal of the American Medical Association, 299 (10), 1182–1184.

Article   CAS   Google Scholar  

Christ, T. W. (2014). Scientific-based research and randomized controlled trials, the “gold” standard? Alternative paradigms and mixed methodologies. Qualitative Inquiry, 20 (1), 72–80.

Lamont, T., Barber, N., Jd, P., Fulop, N., Garfield-Birkbeck, S., Lilford, R., Mear, L., Raine, R., & Fitzpatrick, R. (2016). New approaches to evaluating complex health and care systems. BMJ, 352:i154.

Drabble, S. J., & O’Cathain, A. (2015). Moving from Randomized Controlled Trials to Mixed Methods Intervention Evaluation. In S. Hesse-Biber & R. B. Johnson (Eds.), The Oxford Handbook of Multimethod and Mixed Methods Research Inquiry (pp. 406–425). London: Oxford University Press.

Chambers, D. A., Glasgow, R. E., & Stange, K. C. (2013). The dynamic sustainability framework: Addressing the paradox of sustainment amid ongoing change. Implementation Science : IS, 8 , 117.

Hak, T. (2007). Waarnemingsmethoden in kwalitatief onderzoek. In L. PLBJ & H. TCo (Eds.), Kwalitatief onderzoek: Praktische methoden voor de medische praktijk . [Observation methods in qualitative research] (pp. 13–25). Houten: Bohn Stafleu van Loghum.

Russell, C. K., & Gregory, D. M. (2003). Evaluation of qualitative research studies. Evidence Based Nursing, 6 (2), 36–40.

Fossey, E., Harvey, C., McDermott, F., & Davidson, L. (2002). Understanding and evaluating qualitative research. Australian and New Zealand Journal of Psychiatry, 36 , 717–732.

Yanow, D. (2000). Conducting interpretive policy analysis (Vol. 47). Thousand Oaks: Sage University Papers Series on Qualitative Research Methods.

Shenton, A. K. (2004). Strategies for ensuring trustworthiness in qualitative research projects. Education for Information, 22 , 63–75.

van der Geest, S. (2006). Participeren in ziekte en zorg: meer over kwalitatief onderzoek. Huisarts en Wetenschap, 49 (4), 283–287.

Hijmans, E., & Kuyper, M. (2007). Het halfopen interview als onderzoeksmethode. In L. PLBJ & H. TCo (Eds.), Kwalitatief onderzoek: Praktische methoden voor de medische praktijk . [The half-open interview as research method (pp. 43–51). Houten: Bohn Stafleu van Loghum.

Jansen, H. (2007). Systematiek en toepassing van de kwalitatieve survey. In L. PLBJ & H. TCo (Eds.), Kwalitatief onderzoek: Praktische methoden voor de medische praktijk . [Systematics and implementation of the qualitative survey (pp. 27–41). Houten: Bohn Stafleu van Loghum.

Pv, R., & Peremans, L. (2007). Exploreren met focusgroepgesprekken: de ‘stem’ van de groep onder de loep. In L. PLBJ & H. TCo (Eds.), Kwalitatief onderzoek: Praktische methoden voor de medische praktijk . [Exploring with focus group conversations: the “voice” of the group under the magnifying glass (pp. 53–64). Houten: Bohn Stafleu van Loghum.

Carter, N., Bryant-Lukosius, D., DiCenso, A., Blythe, J., & Neville, A. J. (2014). The use of triangulation in qualitative research. Oncology Nursing Forum, 41 (5), 545–547.

Boeije H: Analyseren in kwalitatief onderzoek: Denken en doen, [Analysis in qualitative research: Thinking and doing] vol. Den Haag Boom Lemma uitgevers; 2012.

Hunter, A., & Brewer, J. (2015). Designing Multimethod Research. In S. Hesse-Biber & R. B. Johnson (Eds.), The Oxford Handbook of Multimethod and Mixed Methods Research Inquiry (pp. 185–205). London: Oxford University Press.

Archibald, M. M., Radil, A. I., Zhang, X., & Hanson, W. E. (2015). Current mixed methods practices in qualitative research: A content analysis of leading journals. International Journal of Qualitative Methods, 14 (2), 5–33.

Creswell, J. W., & Plano Clark, V. L. (2011). Choosing a Mixed Methods Design. In Designing and Conducting Mixed Methods Research . Thousand Oaks: SAGE Publications.

Mays, N., & Pope, C. (2000). Assessing quality in qualitative research. BMJ, 320 (7226), 50–52.

O'Brien, B. C., Harris, I. B., Beckman, T. J., Reed, D. A., & Cook, D. A. (2014). Standards for reporting qualitative research: A synthesis of recommendations. Academic Medicine : Journal of the Association of American Medical Colleges, 89 (9), 1245–1251.

Saunders, B., Sim, J., Kingstone, T., Baker, S., Waterfield, J., Bartlam, B., Burroughs, H., & Jinks, C. (2018). Saturation in qualitative research: Exploring its conceptualization and operationalization. Quality and Quantity, 52 (4), 1893–1907.

Moser, A., & Korstjens, I. (2018). Series: Practical guidance to qualitative research. Part 3: Sampling, data collection and analysis. European Journal of General Practice, 24 (1), 9–18.

Marlett, N., Shklarov, S., Marshall, D., Santana, M. J., & Wasylak, T. (2015). Building new roles and relationships in research: A model of patient engagement research. Quality of Life Research : an international journal of quality of life aspects of treatment, care and rehabilitation, 24 (5), 1057–1067.

Demian, M. N., Lam, N. N., Mac-Way, F., Sapir-Pichhadze, R., & Fernandez, N. (2017). Opportunities for engaging patients in kidney research. Canadian Journal of Kidney Health and Disease, 4 , 2054358117703070–2054358117703070.

Noyes, J., McLaughlin, L., Morgan, K., Roberts, A., Stephens, M., Bourne, J., Houlston, M., Houlston, J., Thomas, S., Rhys, R. G., et al. (2019). Designing a co-productive study to overcome known methodological challenges in organ donation research with bereaved family members. Health Expectations . 22(4):824–35.

Piil, K., Jarden, M., & Pii, K. H. (2019). Research agenda for life-threatening cancer. European Journal Cancer Care (Engl), 28 (1), e12935.

Hofmann, D., Ibrahim, F., Rose, D., Scott, D. L., Cope, A., Wykes, T., & Lempp, H. (2015). Expectations of new treatment in rheumatoid arthritis: Developing a patient-generated questionnaire. Health Expectations : an international journal of public participation in health care and health policy, 18 (5), 995–1008.

Jun, M., Manns, B., Laupacis, A., Manns, L., Rehal, B., Crowe, S., & Hemmelgarn, B. R. (2015). Assessing the extent to which current clinical research is consistent with patient priorities: A scoping review using a case study in patients on or nearing dialysis. Canadian Journal of Kidney Health and Disease, 2 , 35.

Elsie Baker, S., & Edwards, R. (2012). How many qualitative interviews is enough? In National Centre for Research Methods Review Paper . National Centre for Research Methods. http://eprints.ncrm.ac.uk/2273/4/how_many_interviews.pdf .

Sandelowski, M. (1995). Sample size in qualitative research. Research in Nursing & Health, 18 (2), 179–183.

Sim, J., Saunders, B., Waterfield, J., & Kingstone, T. (2018). Can sample size in qualitative research be determined a priori? International Journal of Social Research Methodology, 21 (5), 619–634.

Download references

Acknowledgements

no external funding.

Author information

Authors and affiliations.

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

Loraine Busetto, Wolfgang Wick & Christoph Gumbinger

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

Wolfgang Wick

You can also search for this author in PubMed   Google Scholar

Contributions

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

Corresponding author

Correspondence to Loraine Busetto .

Ethics declarations

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

The authors declare no competing interests.

Additional information

Publisher’s note.

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

Rights and permissions

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

Reprints and permissions

About this article

Cite this article.

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

Download citation

Received : 30 January 2020

Accepted : 22 April 2020

Published : 27 May 2020

DOI : https://doi.org/10.1186/s42466-020-00059-z

Share this article

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

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

Provided by the Springer Nature SharedIt content-sharing initiative

• Qualitative research
• Mixed methods
• Quality assessment

Neurological Research and Practice

ISSN: 2524-3489

• Submission enquiries: Access here and click Contact Us
• General enquiries: [email protected]

• Search Menu
• Sign in through your institution
• Advance articles
• Mini-reviews
• ESHRE Pages
• Editor's Choice
• Supplements
• Author Guidelines
• Submission Site
• Reasons to Publish
• Open Access
• Advertising and Corporate Services
• Advertising
• Reprints and ePrints
• Sponsored Supplements
• Branded Books
• Journals Career Network
• About Human Reproduction
• About the European Society of Human Reproduction and Embryology
• Editorial Board
• Self-Archiving Policy
• Dispatch Dates
• Contact ESHRE
• Journals on Oxford Academic
• Books on Oxford Academic

Article Contents

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

• < Previous

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

• Article contents
• Figures & tables
• Supplementary Data

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

• Permissions Icon Permissions

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Trustworthiness

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

Credibility

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

Applicability

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

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

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

Consistency

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

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

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

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

The authors have no conflicts of interest to declare.

Beeson D , Jennings P , Kramer W . Offspring searching for their sperm donors: how family types shape the process . Hum Reprod 2011 ; 26 : 2415 – 2424 .

Google Scholar

Brannen J . Mixing methods: the entry of qualitative and quantitative approaches into the research process . Int J Soc Res Methodol 2005 ; 8 : 173 – 184 .

Charmaz K . Grounded Theory in the 21st century; applications for advancing social justice studies . In: Denzin NK , Lincoln YS (eds). The Sage Handbook of Qualitative Research . California : Sage Publications Inc. , 2005 .

Google Preview

Cohen D , Crabtree B . Evaluative criteria for qualitative research in health care: controversies and recommendations . Ann Fam Med 2008 ; 6 : 331 – 339 .

de Lacey S . Parent identity and ‘virtual’ children: why patients discard rather than donate unused embryos . Hum Reprod 2005 ; 20 : 1661 – 1669 .

de Lacey SL , Peterson K , McMillan J . Child interests in assisted reproductive technology: how is the welfare principle applied in practice? Hum Reprod 2015 ; 30 : 616 – 624 .

Denzin N , Lincoln Y . Entering the field of qualitative research . In: Denzin NK , Lincoln YS (eds). The Landscape of Qualitative Research: Theories and Issues . Thousand Oaks : Sage , 1998 , 1 – 34 .

Dixon-Woods M , Bonas S , Booth A , Jones DR , Miller T , Shaw RL , Smith JA , Young B . How can systematic reviews incorporate qualitative research? A critical perspective . Qual Res 2006 ; 6 : 27 – 44 .

ESHRE Psychology and Counselling Guideline Development Group . Routine Psychosocial Care in Infertility and Medically Assisted Reproduction: A Guide for Fertility Staff , 2015 . http://www.eshre.eu/Guidelines-and-Legal/Guidelines/Psychosocial-care-guideline.aspx .

Freeman T , Jadva V , Kramer W , Golombok S . Gamete donation: parents' experiences of searching for their child's donor siblings or donor . Hum Reprod 2009 ; 24 : 505 – 516 .

Goedeke S , Daniels K , Thorpe M , Du Preez E . Building extended families through embryo donation: the experiences of donors and recipients . Hum Reprod 2015 ; 30 : 2340 – 2350 .

Hammarberg K , Johnson L , Bourne K , Fisher J , Kirkman M . Proposed legislative change mandating retrospective release of identifying information: consultation with donors and Government response . Hum Reprod 2014 ; 29 : 286 – 292 .

Kirkman M . Saviours and satyrs: ambivalence in narrative meanings of sperm provision . Cult Health Sex 2004 ; 6 : 319 – 336 .

Kirkman M , Rosenthal D , Johnson L . Families working it out: adolescents' views on communicating about donor-assisted conception . Hum Reprod 2007 ; 22 : 2318 – 2324 .

Kirkman M , Bourne K , Fisher J , Johnson L , Hammarberg K . Gamete donors' expectations and experiences of contact with their donor offspring . Hum Reprod 2014 ; 29 : 731 – 738 .

Kitto S , Chesters J , Grbich C . Quality in qualitative research . Med J Aust 2008 ; 188 : 243 – 246 .

Kovacs GT , Morgan G , Levine M , McCrann J . The Australian community overwhelmingly approves IVF to treat subfertility, with increasing support over three decades . Aust N Z J Obstetr Gynaecol 2012 ; 52 : 302 – 304 .

Leininger M . Evaluation criteria and critique of qualitative research studies . In: Morse J (ed). Critical Issues in Qualitative Research Methods . Thousand Oaks : Sage , 1994 , 95 – 115 .

Lincoln YS , Guba EG . Naturalistic Inquiry . Newbury Park, CA : Sage Publications , 1985 .

Morse J , Richards L . Readme First for a Users Guide to Qualitative Methods . Thousand Oaks : Sage , 2002 .

O'Reilly M , Parker N . ‘Unsatisfactory saturation’: a critical exploration of the notion of saturated sample sizes in qualitative research . Qual Res 2013 ; 13 : 190 – 197 .

Porter M , Bhattacharya S . Investigation of staff and patients' opinions of a proposed trial of elective single embryo transfer . Hum Reprod 2005 ; 20 : 2523 – 2530 .

Sandelowski M . The problem of rigor in qualitative research . Adv Nurs Sci 1986 ; 8 : 27 – 37 .

Wyverkens E , Provoost V , Ravelingien A , De Sutter P , Pennings G , Buysse A . Beyond sperm cells: a qualitative study on constructed meanings of the sperm donor in lesbian families . Hum Reprod 2014 ; 29 : 1248 – 1254 .

Young K , Fisher J , Kirkman M . Women's experiences of endometriosis: a systematic review of qualitative research . J Fam Plann Reprod Health Care 2014 ; 41 : 225 – 234 .

• conflict of interest
• credibility
• qualitative research
• quantitative methods

Email alerts

Citing articles via.

• Recommend to your Library

Affiliations

• Online ISSN 1460-2350
• Copyright © 2024 European Society of Human Reproduction and Embryology
• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Institutional account management
• Rights and permissions
• Get help with access
• Accessibility
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

Our systems are now restored following recent technical disruption, and we’re working hard to catch up on publishing. We apologise for the inconvenience caused. Find out more: https://www.cambridge.org/universitypress/about-us/news-and-blogs/cambridge-university-press-publishing-update-following-technical-disruption

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings .

Login Alert

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

Article contents

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

Published online by Cambridge University Press:  02 January 2018

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

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

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

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

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

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

Using combined approaches

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

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

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

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

‘Qualitative research cannot really claim reliability or validity’

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

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

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

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

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

Declaration of interest

This article has been cited by the following publications. This list is generated based on data provided by Crossref .

• Google Scholar

View all Google Scholar citations for this article.

Save article to Kindle

To save this article to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle .

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

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

Save article to Dropbox

To save this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about saving content to Dropbox .

Save article to Google Drive

To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about saving content to Google Drive .

Reply to: Submit a response

- No HTML tags allowed - Web page URLs will display as text only - Lines and paragraphs break automatically - Attachments, images or tables are not permitted

Your details

Your email address will be used in order to notify you when your comment has been reviewed by the moderator and in case the author(s) of the article or the moderator need to contact you directly.

You have entered the maximum number of contributors

Conflicting interests.

Please list any fees and grants from, employment by, consultancy for, shared ownership in or any close relationship with, at any time over the preceding 36 months, any organisation whose interests may be affected by the publication of the response. Please also list any non-financial associations or interests (personal, professional, political, institutional, religious or other) that a reasonable reader would want to know about in relation to the submitted work. This pertains to all the authors of the piece, their spouses or partners.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• My Bibliography
• Collections
• Citation manager

Save citation to file

Email citation, add to collections.

• Create a new collection
• Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed, qualitative study, affiliations.

• 1 University of Nebraska Medical Center
• 2 GDB Research and Statistical Consulting
• 3 GDB Research and Statistical Consulting/McLaren Macomb Hospital
• PMID: 29262162
• Bookshelf ID: NBK470395

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

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

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

Copyright © 2024, StatPearls Publishing LLC.

PubMed Disclaimer

Conflict of interest statement

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

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

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

• Introduction
• Issues of Concern
• Clinical Significance
• Enhancing Healthcare Team Outcomes
• Review Questions

Similar articles

• Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas. Crider K, Williams J, Qi YP, Gutman J, Yeung L, Mai C, Finkelstain J, Mehta S, Pons-Duran C, Menéndez C, Moraleda C, Rogers L, Daniels K, Green P. Crider K, et al. Cochrane Database Syst Rev. 2022 Feb 1;2(2022):CD014217. doi: 10.1002/14651858.CD014217. Cochrane Database Syst Rev. 2022. PMID: 36321557 Free PMC article.
• Macromolecular crowding: chemistry and physics meet biology (Ascona, Switzerland, 10-14 June 2012). Foffi G, Pastore A, Piazza F, Temussi PA. Foffi G, et al. Phys Biol. 2013 Aug;10(4):040301. doi: 10.1088/1478-3975/10/4/040301. Epub 2013 Aug 2. Phys Biol. 2013. PMID: 23912807
• The future of Cochrane Neonatal. Soll RF, Ovelman C, McGuire W. Soll RF, et al. Early Hum Dev. 2020 Nov;150:105191. doi: 10.1016/j.earlhumdev.2020.105191. Epub 2020 Sep 12. Early Hum Dev. 2020. PMID: 33036834
• Invited review: Qualitative research in dairy science-A narrative review. Ritter C, Koralesky KE, Saraceni J, Roche S, Vaarst M, Kelton D. Ritter C, et al. J Dairy Sci. 2023 Sep;106(9):5880-5895. doi: 10.3168/jds.2022-23125. Epub 2023 Jul 18. J Dairy Sci. 2023. PMID: 37474366 Review.
• Participation in environmental enhancement and conservation activities for health and well-being in adults: a review of quantitative and qualitative evidence. Husk K, Lovell R, Cooper C, Stahl-Timmins W, Garside R. Husk K, et al. Cochrane Database Syst Rev. 2016 May 21;2016(5):CD010351. doi: 10.1002/14651858.CD010351.pub2. Cochrane Database Syst Rev. 2016. PMID: 27207731 Free PMC article. Review.
• Moser A, Korstjens I. Series: Practical guidance to qualitative research. Part 1: Introduction. Eur J Gen Pract. 2017 Dec;23(1):271-273. - PMC - PubMed
• Cleland JA. The qualitative orientation in medical education research. Korean J Med Educ. 2017 Jun;29(2):61-71. - PMC - PubMed
• Foley G, Timonen V. Using Grounded Theory Method to Capture and Analyze Health Care Experiences. Health Serv Res. 2015 Aug;50(4):1195-210. - PMC - PubMed
• Devers KJ. How will we know "good" qualitative research when we see it? Beginning the dialogue in health services research. Health Serv Res. 1999 Dec;34(5 Pt 2):1153-88. - PMC - PubMed
• Huston P, Rowan M. Qualitative studies. Their role in medical research. Can Fam Physician. 1998 Nov;44:2453-8. - PMC - PubMed

Publication types

• Search in PubMed
• Search in MeSH
• Add to Search

Related information

• Cited in Books

LinkOut - more resources

Full text sources.

• NCBI Bookshelf

• Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

Home » Research Methods » Qualitative Methods "How-To" Guides

Qualitative Methods "How-To" Guides Edited by Patricia Leavy

This series provides researchers and students with step-by-step, practical instruction on established and emerging qualitative methods. Authors are leaders in their respective areas of expertise who demystify the research process and share innovative practices and invaluable insider advice. The basics of each method are addressed, including philosophical underpinnings, and guidance is offered on designing studies; generating, analyzing, interpreting, and representing data; and evaluating the quality of research. With accessible writing, robust examples, and ample pedagogical features, books in this series are ideal for use in courses or by individual researchers.

What is Qualitative in Qualitative Research

• Open access
• Published: 27 February 2019
• Volume 42 , pages 139–160, ( 2019 )

Cite this article

You have full access to this open access article

• Patrik Aspers 1 , 2 &
• Ugo Corte 3  

630k Accesses

354 Citations

25 Altmetric

Explore all metrics

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

Similar content being viewed by others

What is Qualitative in Research

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

• Artificial Intelligence

Avoid common mistakes on your manuscript.

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

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

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

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

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

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

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

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

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

Towards a Definition of Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Analysis – What is Qualitative Research?

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

Qualitative and Quantitative

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

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

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

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

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

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

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

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

Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

Grounded Theory

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

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

Defining Qualitative Research

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

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

Distinctions

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

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

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

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

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

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

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

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

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

Improved Understanding

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

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

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

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

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

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

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

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

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

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

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

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

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

Åkerström, Malin. 2013. Curiosity and serendipity in qualitative research. Qualitative Sociology Review 9 (2): 10–18.

Google Scholar  

Alford, Robert R. 1998. The craft of inquiry. Theories, methods, evidence . Oxford: Oxford University Press.

Alvesson, Mats, and Dan Kärreman. 2011. Qualitative research and theory development. Mystery as method . London: SAGE Publications.

Book   Google Scholar  

Aspers, Patrik. 2006. Markets in Fashion, A Phenomenological Approach. London Routledge.

Atkinson, Paul. 2005. Qualitative research. Unity and diversity. Forum: Qualitative Social Research 6 (3): 1–15.

Becker, Howard S. 1963. Outsiders. Studies in the sociology of deviance . New York: The Free Press.

Becker, Howard S. 1966. Whose side are we on? Social Problems 14 (3): 239–247.

Article   Google Scholar  

Becker, Howard S. 1970. Sociological work. Method and substance . New Brunswick: Transaction Books.

Becker, Howard S. 1996. The epistemology of qualitative research. In Ethnography and human development. Context and meaning in social inquiry , ed. Jessor Richard, Colby Anne, and Richard A. Shweder, 53–71. Chicago: University of Chicago Press.

Becker, Howard S. 1998. Tricks of the trade. How to think about your research while you're doing it . Chicago: University of Chicago Press.

Becker, Howard S. 2017. Evidence . Chigaco: University of Chicago Press.

Becker, Howard, Blanche Geer, Everett Hughes, and Anselm Strauss. 1961. Boys in White, student culture in medical school . New Brunswick: Transaction Publishers.

Berezin, Mabel. 2014. How do we know what we mean? Epistemological dilemmas in cultural sociology. Qualitative Sociology 37 (2): 141–151.

Best, Joel. 2004. Defining qualitative research. In Workshop on Scientific Foundations of Qualitative Research , eds . Charles, Ragin, Joanne, Nagel, and Patricia White, 53-54. http://www.nsf.gov/pubs/2004/nsf04219/nsf04219.pdf .

Biernacki, Richard. 2014. Humanist interpretation versus coding text samples. Qualitative Sociology 37 (2): 173–188.

Blumer, Herbert. 1969. Symbolic interactionism: Perspective and method . Berkeley: University of California Press.

Brady, Henry, David Collier, and Jason Seawright. 2004. Refocusing the discussion of methodology. In Rethinking social inquiry. Diverse tools, shared standards , ed. Brady Henry and Collier David, 3–22. Lanham: Rowman and Littlefield.

Brown, Allison P. 2010. Qualitative method and compromise in applied social research. Qualitative Research 10 (2): 229–248.

Charmaz, Kathy. 2006. Constructing grounded theory . London: Sage.

Corte, Ugo, and Katherine Irwin. 2017. “The Form and Flow of Teaching Ethnographic Knowledge: Hands-on Approaches for Learning Epistemology” Teaching Sociology 45(3): 209-219.

Creswell, John W. 2009. Research design. Qualitative, quantitative, and mixed method approaches . 3rd ed. Thousand Oaks: SAGE Publications.

Davidsson, David. 1988. 2001. The myth of the subjective. In Subjective, intersubjective, objective , ed. David Davidsson, 39–52. Oxford: Oxford University Press.

Denzin, Norman K. 1970. The research act: A theoretical introduction to Ssociological methods . Chicago: Aldine Publishing Company Publishers.

Denzin, Norman K., and Yvonna S. Lincoln. 2003. Introduction. The discipline and practice of qualitative research. In Collecting and interpreting qualitative materials , ed. Norman K. Denzin and Yvonna S. Lincoln, 1–45. Thousand Oaks: SAGE Publications.

Denzin, Norman K., and Yvonna S. Lincoln. 2005. Introduction. The discipline and practice of qualitative research. In The Sage handbook of qualitative research , ed. Norman K. Denzin and Yvonna S. Lincoln, 1–32. Thousand Oaks: SAGE Publications.

Emerson, Robert M., ed. 1988. Contemporary field research. A collection of readings . Prospect Heights: Waveland Press.

Emerson, Robert M., Rachel I. Fretz, and Linda L. Shaw. 1995. Writing ethnographic fieldnotes . Chicago: University of Chicago Press.

Esterberg, Kristin G. 2002. Qualitative methods in social research . Boston: McGraw-Hill.

Fine, Gary Alan. 1995. Review of “handbook of qualitative research.” Contemporary Sociology 24 (3): 416–418.

Fine, Gary Alan. 2003. “ Toward a Peopled Ethnography: Developing Theory from Group Life.” Ethnography . 4(1):41-60.

Fine, Gary Alan, and Black Hawk Hancock. 2017. The new ethnographer at work. Qualitative Research 17 (2): 260–268.

Fine, Gary Alan, and Timothy Hallett. 2014. Stranger and stranger: Creating theory through ethnographic distance and authority. Journal of Organizational Ethnography 3 (2): 188–203.

Flick, Uwe. 2002. Qualitative research. State of the art. Social Science Information 41 (1): 5–24.

Flick, Uwe. 2007. Designing qualitative research . London: SAGE Publications.

Frankfort-Nachmias, Chava, and David Nachmias. 1996. Research methods in the social sciences . 5th ed. London: Edward Arnold.

Franzosi, Roberto. 2010. Sociology, narrative, and the quality versus quantity debate (Goethe versus Newton): Can computer-assisted story grammars help us understand the rise of Italian fascism (1919- 1922)? Theory and Society 39 (6): 593–629.

Franzosi, Roberto. 2016. From method and measurement to narrative and number. International journal of social research methodology 19 (1): 137–141.

Gadamer, Hans-Georg. 1990. Wahrheit und Methode, Grundzüge einer philosophischen Hermeneutik . Band 1, Hermeneutik. Tübingen: J.C.B. Mohr.

Gans, Herbert. 1999. Participant Observation in an Age of “Ethnography”. Journal of Contemporary Ethnography 28 (5): 540–548.

Geertz, Clifford. 1973. The interpretation of cultures . New York: Basic Books.

Gilbert, Nigel. 2009. Researching social life . 3rd ed. London: SAGE Publications.

Glaeser, Andreas. 2014. Hermeneutic institutionalism: Towards a new synthesis. Qualitative Sociology 37: 207–241.

Glaser, Barney G., and Anselm L. Strauss. [1967] 2010. The discovery of grounded theory. Strategies for qualitative research. Hawthorne: Aldine.

Goertz, Gary, and James Mahoney. 2012. A tale of two cultures: Qualitative and quantitative research in the social sciences . Princeton: Princeton University Press.

Goffman, Erving. 1989. On fieldwork. Journal of Contemporary Ethnography 18 (2): 123–132.

Goodwin, Jeff, and Ruth Horowitz. 2002. Introduction. The methodological strengths and dilemmas of qualitative sociology. Qualitative Sociology 25 (1): 33–47.

Habermas, Jürgen. [1981] 1987. The theory of communicative action . Oxford: Polity Press.

Hammersley, Martyn. 2007. The issue of quality in qualitative research. International Journal of Research & Method in Education 30 (3): 287–305.

Hammersley, Martyn. 2013. What is qualitative research? Bloomsbury Publishing.

Hammersley, Martyn. 2018. What is ethnography? Can it survive should it? Ethnography and Education 13 (1): 1–17.

Hammersley, Martyn, and Paul Atkinson. 2007. Ethnography. Principles in practice . London: Tavistock Publications.

Heidegger, Martin. [1927] 2001. Sein und Zeit . Tübingen: Max Niemeyer Verlag.

Heidegger, Martin. 1988. 1923. Ontologie. Hermeneutik der Faktizität, Gesamtausgabe II. Abteilung: Vorlesungen 1919-1944, Band 63, Frankfurt am Main: Vittorio Klostermann.

Hempel, Carl G. 1966. Philosophy of the natural sciences . Upper Saddle River: Prentice Hall.

Hood, Jane C. 2006. Teaching against the text. The case of qualitative methods. Teaching Sociology 34 (3): 207–223.

James, William. 1907. 1955. Pragmatism . New York: Meredian Books.

Jovanović, Gordana. 2011. Toward a social history of qualitative research. History of the Human Sciences 24 (2): 1–27.

Kalof, Linda, Amy Dan, and Thomas Dietz. 2008. Essentials of social research . London: Open University Press.

Katz, Jack. 2015. Situational evidence: Strategies for causal reasoning from observational field notes. Sociological Methods & Research 44 (1): 108–144.

King, Gary, Robert O. Keohane, S. Sidney, and S. Verba. 1994. Designing social inquiry. In Scientific inference in qualitative research . Princeton: Princeton University Press.

Chapter   Google Scholar  

Lamont, Michelle. 2004. Evaluating qualitative research: Some empirical findings and an agenda. In Report from workshop on interdisciplinary standards for systematic qualitative research , ed. M. Lamont and P. White, 91–95. Washington, DC: National Science Foundation.

Lamont, Michèle, and Ann Swidler. 2014. Methodological pluralism and the possibilities and limits of interviewing. Qualitative Sociology 37 (2): 153–171.

Lazarsfeld, Paul, and Alan Barton. 1982. Some functions of qualitative analysis in social research. In The varied sociology of Paul Lazarsfeld , ed. Patricia Kendall, 239–285. New York: Columbia University Press.

Lichterman, Paul, and Isaac Reed I (2014), Theory and Contrastive Explanation in Ethnography. Sociological methods and research. Prepublished 27 October 2014; https://doi.org/10.1177/0049124114554458 .

Lofland, John, and Lyn Lofland. 1995. Analyzing social settings. A guide to qualitative observation and analysis . 3rd ed. Belmont: Wadsworth.

Lofland, John, David A. Snow, Leon Anderson, and Lyn H. Lofland. 2006. Analyzing social settings. A guide to qualitative observation and analysis . 4th ed. Belmont: Wadsworth/Thomson Learning.

Long, Adrew F., and Mary Godfrey. 2004. An evaluation tool to assess the quality of qualitative research studies. International Journal of Social Research Methodology 7 (2): 181–196.

Lundberg, George. 1951. Social research: A study in methods of gathering data . New York: Longmans, Green and Co..

Malinowski, Bronislaw. 1922. Argonauts of the Western Pacific: An account of native Enterprise and adventure in the archipelagoes of Melanesian New Guinea . London: Routledge.

Manicas, Peter. 2006. A realist philosophy of science: Explanation and understanding . Cambridge: Cambridge University Press.

Marchel, Carol, and Stephanie Owens. 2007. Qualitative research in psychology. Could William James get a job? History of Psychology 10 (4): 301–324.

McIntyre, Lisa J. 2005. Need to know. Social science research methods . Boston: McGraw-Hill.

Merton, Robert K., and Elinor Barber. 2004. The travels and adventures of serendipity. A Study in Sociological Semantics and the Sociology of Science . Princeton: Princeton University Press.

Mannay, Dawn, and Melanie Morgan. 2015. Doing ethnography or applying a qualitative technique? Reflections from the ‘waiting field‘. Qualitative Research 15 (2): 166–182.

Neuman, Lawrence W. 2007. Basics of social research. Qualitative and quantitative approaches . 2nd ed. Boston: Pearson Education.

Ragin, Charles C. 1994. Constructing social research. The unity and diversity of method . Thousand Oaks: Pine Forge Press.

Ragin, Charles C. 2004. Introduction to session 1: Defining qualitative research. In Workshop on Scientific Foundations of Qualitative Research , 22, ed. Charles C. Ragin, Joane Nagel, Patricia White. http://www.nsf.gov/pubs/2004/nsf04219/nsf04219.pdf

Rawls, Anne. 2018. The Wartime narrative in US sociology, 1940–7: Stigmatizing qualitative sociology in the name of ‘science,’ European Journal of Social Theory (Online first).

Schütz, Alfred. 1962. Collected papers I: The problem of social reality . The Hague: Nijhoff.

Seiffert, Helmut. 1992. Einführung in die Hermeneutik . Tübingen: Franke.

Silverman, David. 2005. Doing qualitative research. A practical handbook . 2nd ed. London: SAGE Publications.

Silverman, David. 2009. A very short, fairly interesting and reasonably cheap book about qualitative research . London: SAGE Publications.

Silverman, David. 2013. What counts as qualitative research? Some cautionary comments. Qualitative Sociology Review 9 (2): 48–55.

Small, Mario L. 2009. “How many cases do I need?” on science and the logic of case selection in field-based research. Ethnography 10 (1): 5–38.

Small, Mario L 2008. Lost in translation: How not to make qualitative research more scientific. In Workshop on interdisciplinary standards for systematic qualitative research, ed in Michelle Lamont, and Patricia White, 165–171. Washington, DC: National Science Foundation.

Snow, David A., and Leon Anderson. 1993. Down on their luck: A study of homeless street people . Berkeley: University of California Press.

Snow, David A., and Calvin Morrill. 1995. New ethnographies: Review symposium: A revolutionary handbook or a handbook for revolution? Journal of Contemporary Ethnography 24 (3): 341–349.

Strauss, Anselm L. 2003. Qualitative analysis for social scientists . 14th ed. Chicago: Cambridge University Press.

Strauss, Anselm L., and Juliette M. Corbin. 1998. Basics of qualitative research. Techniques and procedures for developing grounded theory . 2nd ed. Thousand Oaks: Sage Publications.

Swedberg, Richard. 2017. Theorizing in sociological research: A new perspective, a new departure? Annual Review of Sociology 43: 189–206.

Swedberg, Richard. 1990. The new 'Battle of Methods'. Challenge January–February 3 (1): 33–38.

Timmermans, Stefan, and Iddo Tavory. 2012. Theory construction in qualitative research: From grounded theory to abductive analysis. Sociological Theory 30 (3): 167–186.

Trier-Bieniek, Adrienne. 2012. Framing the telephone interview as a participant-centred tool for qualitative research. A methodological discussion. Qualitative Research 12 (6): 630–644.

Valsiner, Jaan. 2000. Data as representations. Contextualizing qualitative and quantitative research strategies. Social Science Information 39 (1): 99–113.

Weber, Max. 1904. 1949. Objectivity’ in social Science and social policy. Ed. Edward A. Shils and Henry A. Finch, 49–112. New York: The Free Press.

Download references

Acknowledgements

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

Author information

Authors and affiliations.

Department of Sociology, Uppsala University, Uppsala, Sweden

Patrik Aspers

Seminar for Sociology, Universität St. Gallen, St. Gallen, Switzerland

Department of Media and Social Sciences, University of Stavanger, Stavanger, Norway

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Patrik Aspers .

Additional information

Publisher’s note.

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

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and permissions

About this article

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

Download citation

Published : 27 February 2019

Issue Date : 01 June 2019

DOI : https://doi.org/10.1007/s11133-019-9413-7

Share this article

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

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

Provided by the Springer Nature SharedIt content-sharing initiative

• Qualitative research
• Epistemology
• Philosophy of science
• Phenomenology
• Find a journal
• Publish with us
• Track your research

• Methodology
• Research Methodology

Qualitative Research

• January 2023
• This person is not on ResearchGate, or hasn't claimed this research yet.

• Kampala International University (KIU)

Abstract and Figures

Discover the world's research

• 25+ million members
• 160+ million publication pages
• 2.3+ billion citations

• Nabunya Cynthia

• Nakate Maria Theresa
• Semambo Nathan
• Cecilia Shevon
• Mutesi Amina

• Chidinma Esther
• Gerthrude Vershiy Banyuy

• Generous Tugume Begumisa
• Aruho Rukundo
• Nuwatuhaire Benard

• H Philipsen
• M Vernooij-Dassen
• Recruit researchers
• Join for free
• Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

• Open access
• Published: 15 September 2024

Exploring academic and clinical nurses’ perspectives on evidence-based nursing course for undergraduates from perspectives of academic-practice partnerships: a qualitative study

• Guiyun Wang 1 ,
• Yuting Xia 2 ,
• Qirong Chen 2 ,
• Xirongguli Halili 2 &
• Hui Huang 3  

BMC Nursing volume  23 , Article number:  657 ( 2024 ) Cite this article

Metrics details

To explore nurses’ perceptions of evidence-based nursing courses for undergraduates through academic-practice partnerships.

A deductive thematic analysis based on the practice-academic logic model.

Fifteen academic and clinical nurses were interviewed between November and December 2023, either online or through face-to-face meetings. Each interview lasted 20–30 min. The interview outline was constructed based on the practice-academic partnership logic model, which was followed during the process of recorded, analyzed, and checked.

Themes identified include inputs (e.g., stakeholder commitment), activities (e.g., communication), outputs (e.g., nursing projects), and outcomes (e.g., improved competence). These themes highlight the various aspects and outcomes of academic-practice partnerships in evidence-based nursing courses.

Effective academic-practice partnerships are crucial for developing evidence-based nursing courses, leading to positive educational and professional outcomes.

Nurses’ perceptions provide valuable guidelines for developing effective evidence-based nursing courses.

Patient or public contribution

No patient or public users participated in this study.

Peer Review reports

Introduction

Evidence-based nursing (EBN) is a systematic approach to addressing clinical questions that combines research findings, clinicians’ expertise, and patients’ values [ 1 ]. Conducting evidence-based nursing practices (EBNP) has a significant effect on improving the quality of nursing care and reducing healthcare expenses [ 2 , 3 , 4 ]. Over the past decade, researchers have emphasized the importance of EBNP [ 5 ]. However, limited EBNP projects has been conducted in clinical nursing [ 6 ]. The main reason for the insufficient implementation of EBNP is the lack of EBN knowledge, competence, resources, and adherence to complete processes and pathways by nurses [ 7 ]. Conducting high-quality EBN education is a key measure to improve the EBN competence of nurses [ 8 ]. Undergraduate nursing students are the future of the nursing workforce [ 9 , 10 ]. Undergraduate nursing students will have the competence to conduct EBNP projects to promote the development of nursing care towards a more professional and scientific direction [ 11 ]. American Medical Association has pointed out that conducting EBP education for undergraduate nursing students is the key to equipping them with EBN competence and enabling them to conduct EBNP [ 12 ].

Nevertheless, there is limited studies focused on developing of EBN education for undergraduate nursing students [ 11 ]. Existing studies have shown that EBN education for undergraduate nursing students mainly focuses on lectures, interactive, and blended online and offline teaching and the EBNP education for undergraduate nursing students were conducted by clinical nurses [ 12 , 13 , 14 ]. However, most of the clinical nurses lacked of time to provide systematic EBN theory education for undergraduate, which caused the undergraduate nursing student with low level of EBN knowledge and ability [ 13 , 14 , 15 , 16 , 17 ]. The separation of theory and practice is the main drawback of existing EBN education for undergraduate nursing students [ 13 , 14 ]. However, theory and practice are two essential and complementary components of EBN [ 18 ].

Academic-practice partnerships (APPs) refers to the establishment of strategic relationships between academic and clinical institutions, fully utilizing the advantages of both sides, and promoting common vision in teaching, practice, and research [ 19 ]. Conducting APPs in EBN (APPs-EBN) education will overcome the key obstacle of the existing EBN education for undergraduate nursing students [ 12 , 20 ]. To understand the content of APPs-EBN education, the steps of existing research of APPs-EBN training program for nursing students was shown as following [ 21 , 22 ]: (1) clinical nurses to identify their needs; (2) academic nurses assigned nursing students specific topics, provide reading materials and videos; (3) nursing students formulated EBNP questions (PICOs, including participants, interventions, comparison, outcomes, and study design [ 23 ]. PICOs were the important content of EBNP questions [ 23 ].); (4) academic nurses, clinical nurses and nursing students discussed the accuracy of EBNP questions (PICOs); (5) nursing students submitted their homework and received their grades with feedback; (6) academic and clinical nurses chose a final EBNP question (PICOs) that was befitting for each student group.

Academic nurses and clinical nurses should be the core of APPs-EBN education for undergraduate nursing students, actively participating in all stages of EBN education process [ 22 ]. Moreover, conducting APPs-EBN education must be achieved through individual-level partnerships of academic nurses and clinical nurses [ 20 , 24 ]. However, existing studies focused on discussing APPs-EBN practice at institutional level, with limited studies focused on the individual perspectives of APPs-EBN education, especially for the undergraduate nursing student’s EBN education [ 19 , 20 , 25 ]. Therefore, it is crucial to understand the perceptions of academic and clinical nurses on APPs-EBN course for undergraduate nursing students to provide information for improving the quality of APPs-EBN course for undergraduate nursing students. However, there is a lack of individual-level evidence on specific perceptions of APPs-EBN course for undergraduate nursing students.

Practice-academic partnership logic model was designed for APPs program. Given the efficacy of this model has been approved in the aspect of APPs and its appropriateness for this qualitative study to deductive specific and essential content during the process of APPs, further to provide basis for researchers conduct APPs-EBN course for undergraduate nursing students [ 22 ]. This model emphasizes that having specific inputs and conducting specific activities in the process of APPs may result in corresponding outputs and outcomes (inputs and activities → outputs and outcomes). Inputs encompass the necessary investments in the APPs-EBN education program, including partnership champions, compatible philosophies, common vision, key stakeholder commitment, formalized partnership agreement, shared goals and accountabilities and dedicated time and resources [ 22 , 26 ]. Activities involve specific actions or processes that must be undertaken to yield desired outcomes from the APPs, including open, ongoing communications, shared decision-making and professional development [ 22 , 26 ]. Outputs are the tangible and immediate deliverables stemming from the inputs and activities, including action plans and strategic plans [ 22 , 26 ]. Outcomes, both short-term and long-term, denote the changes or impacts that arise from the APPs, including successful completion of short-term (action plan) goals and successful completion of long-term (strategic) goals [ 22 , 26 ]. Therefore, this study aimed to explore and interpret the perceptions on APPs-EBN course for undergraduate nursing students among the academic nurses and clinical nurses based on the partnership-academic partnership logic model. This study will provide a valuable information for further constructing APPs-EBN course for undergraduate nursing students.

This qualitative study used deductive thematic analysis by using the practice-academic logic model [ 27 ]. The qualitative study was reported following the Consolidated Criteria for Reporting Qualitative Research checklist [ 28 ].

Participants

Considering that academic and clinical nurses were the main stakeholders in APPs-EBN course for undergraduate nursing students, this study conducted qualitative interviews with these two groups of people. Inclusion criteria for academic nurses was that academic nurses had experience in teaching EBN course for undergraduate and/or graduate nursing students. Inclusion criteria for clinical nurses were as follows: (1) clinical nurses were responsible for providing direct care to patients in a hospital unit. (2) clinical nurses have the experience in EBNP.

Data collection

The data were collected between November and December 2023. The interviews were conducted through online videoconferencing meetings or face-to-face meetings in participants’ offices. Each participant underwent a single interview session, with each interview lasting approximately 20–30 min. The interviews were conducted by the corresponding author (Y.X.) who was a female master’s nursing student and has completed qualitative research training.

The sampling method employed was purposive sampling, which can consciously select some participants who understand the research questions and provide rich information in the interviews [ 29 ]. The interview outline was constructed based on the practice-academic partnership logic model, which mainly includes what support did we need from both the organizational and individual levels to conduct APPs-EBN course for undergraduate nursing students? What activities could be conducted in APPs-EBN course to improve teaching effectiveness? What were the outputs of conducting APPs-EBN course for undergraduate nursing students? What were the outcomes for conducting APPs-EBN course for undergraduate nursing students?

Before conducting the formal interview, the researchers contacted the interviewees through WeChat (the social media most commonly used in China) to introduce the purpose, significance, and methods of this part of the research. After obtaining consent from the participants, the interview schedule was arranged to accommodate their availability. Before commencing the formal interviews, the researchers reiterated the research’s purpose, significance, and methodologies to the interviewees, while also ensuring the protection of their privacy. Detailed explanations were provided concerning the recording procedures, and the interviewees were requested to sign an informed consent form before the interviews officially commenced, including the recording process. The semi-structured interview outline served as a comprehensive guide throughout the interview process, ensuring that the interview content remained closely aligned with the research objectives. All the interviews were recorded. Any questions that arose during the interview were promptly addressed to maintain clarity and depth of the responses.

Data analysis

Within 24 h after the interview, two researchers (Y.X. and H.H) converted 15 interview recordings into written materials and listened to the recordings multiple times to ensure the accuracy of the transcription results. The interview transcriptions were analyzed in NVivo 12.0. The corresponding author (Y.X.) followed the following steps to code the perspectives of participants: immersing in the data, developing an initial thematic template, organizing the data based on the template, condensing data and reflecting, comparing and contrasting data within similar participant categories, and comparing and contrasting data with different participant categories [ 20 ]. After completing the initial encoding of all data, the corresponding author (Y.X.) shared and validated the encoding results with other members of the research team to form the final encoding result [ 30 ].

Ethic considerations

This study was approved by the Ethics Committee of a nursing school in Hunan Province in March 2023 (review number: E202313). All the recorded data are only used for this study and were backed up in an encrypted computer without Internet connection.

Nine academic nurses participated in this study, two males and seven females, with an average age of (38.00 ± 8.00) years. Among them, eight academic nurses have a doctoral degree, and one academic nurse has a master’s degree. The nine academic nurses were from five different school of nursing in China and both of them have the experience in participating the APP-EBN courses for nurses or graduate nursing students. Six clinical nurses participated in this study, all of them were females and have a master’s degree, with an average age of (37.17 ± 4.26) years. And six clinical nurses were from four different comprehensive hospital in China and three clinical nurses have the experience in participating the APP-EBN projects.

Four themes with 16 subthemes were generated based on practice-academic partnership logic model (Table  1 ), including inputs, activities, outputs, outcomes.

All participants considered the multilevel contents of inputs were the necessary investment of APPs-EBN course for undergraduate nursing students.

Key stakeholder commitment

A few participants noted that academic and clinical institutions needed to form formal partnership before developed APPs-EBN course for undergraduate nursing students, which was beneficial for promoting APPs-EBN course. As the opinion by one participant, “The first step of developing APPs-EBN course is to reach a consensus and sign a partnership agreement between academic and clinical leadership , and vigorously promote developing APPs-EBN course.” (Participant 14 , Clinical nurse) Developing a teaching team was one of the important aspects of achieving key stakeholder commitment of APPs. “How to attract clinical nurses to participate in the teaching team requires the academic and clinical institutions to sign some partnership agreements.” (Participant 2 , Academic nurse).

Key stakeholder commitment was an important input for developing APPs-EBN course for undergraduate nursing students and further promoting common interests in EBN education, practice, and research [ 31 ].

Shared mission

Some participants believed that shared mission was an important input for developing of APPs-EBN course for undergraduate nursing students. As a participant mentioned, “It is necessary to consider shared mission. For example , if the goal is to implement EBNP projects in clinical settings after the course , plans must be made to enhance these projects while developing the course.” (Participant 2 , Academic nurse) Academic and clinical institution had shared mission was conducive to making the partnerships process smoother [ 26 ]. For example, “The leadership is very important during the process of APPs. Leaderships of the academic and the nursing department of the clinical focus on a shared mission to develop this course , which may have a significant impact (on the development of APPs-EBN course for undergraduate nursing students).” (Participant 3 , Academic nurse) .

EBN training

Participants mentioned that EBN training was necessary for academic and clinical nurses to improve their EBN competence and acquire the newest knowledge about EBN.

“From organizational level , it is necessary to regularly provide EBNP training opportunities for clinical nurses or provide more updates and lectures on this EBN to academic nurses.” (Participant 3 , Academic nurse) . “If there is such specialized EBN training , it would be best for academic and clinical nurses to participate in systematic learning.” (Participant 5 , Academic nurse) . “Regular training for academic and clinical nurses is necessary. Academic nurses primarily participate in training programs related to EBNP and teaching ability , while clinical nurses primarily participate in training programs related to teaching ability.” (Participant 8 , Academic nurse) .

Developing and conducting APPs-EBN course for undergraduate nursing students required academic and clinical nurses to input a significant amount of time in communication and preparing for teaching APPs-EBN course.

“For some (academic and clinical) nurses , time may be the biggest problem , as building the APPs-EBN course requires partnerships between academic and clinical nurses , including spending time on partnership and individual lesson preparation.” (Participant 10 , Clinical nurse) . “It is difficult for clinical nurses to participant in teaching APPs-EBN course for undergraduate student during their own rest.” (Participant 7 , Academic nurse) . “Developing the APPs-EBN course demands a substantial investment of time from both academic and clinical nurses. From a clinical perspective , the success of this endeavor largely hinges on the level of support from nursing leaders. If nursing leaders truly value this course , they will ensure that clinical nurses have sufficient time to contribute to its teaching.” (Participant 14 , Clinical nurse) .

Instructional design

According to the characteristics of the target population (undergraduate nursing students), the development of APPs-EBN course instructional design (including learning objectives, learning contents, learning methods, and learning resources) was the cornerstone of developing and implementing EBN education [ 32 ]. “The learning objectives is actually your initial origin of instructional design. Firstly , it is necessary to analyze what abilities undergraduate nursing students need to possess in the future clinical nursing , what kind of foundation they need nurses (academic and clinical nurses) to lay for them during their learning period , and what kind of (EBN) knowledge and skills they need to be taught.” (Participant 9 , Academic nurse) .

Comprehensive and systematic educational resources form the foundation for promoting the acquisition of EBN knowledge among undergraduate nursing students [ 33 , 34 ]. Evidence retrieval is a crucial prerequisite for evidence implementation, and ample database resources can significantly enhance the teaching of evidence retrieval in APPs-EBN courses for these students [ 35 ]. Several participants highlighted that database resources are essential for developing APPs-EBN courses for undergraduate nursing students.

“Provide them (undergraduate nursing students) with database resources to access relevant databases for retrieval.” (Participant 8 , Academic nurse) . “Sometimes , we use databases from other universities , because our university actually doesn’t have any databases about evidence-based nursing. It is necessary for university to support more database resources.” (Participant 5 , Academic nurse) .

The participants stated that universities and hospitals provide incentives for academic and clinical nurses, which could enhance the teaching engagement of these professionals.

“The clinical nurses who participated in this course (APPs-EBN course for undergraduate nursing students) have some corresponding incentives , including establishing some educational reform projects and funding.” (Participant 5 , Academic nurse) . “Perhaps there should be time support and performance rewards for nurses (academic and clinical nurses) to participate in this course (APPs-EBN course for undergraduate nursing students). Especially for clinical nurses , they should be provided more time support and performance rewards and honors for the engagement in EBNP education.” (Participant 8 , Academic nurse) . “It is necessary that both the academic and clinical institutions provide clear incentives. If you participate in APPs-EBN course for undergraduate nursing students , it will be beneficial for evaluating professional titles. In addition , it is basic to provide academic and clinical teachers more salary.” (Participant 10 , Clinical nurse) .

Mutual trust

Mutual respect was a key condition for developing of APPs-EBN course for undergraduate nursing students [ 26 ]. As participants said that, “It is important to establish a good relationship between academic and clinical nurses , as well as to have some communication during the teaching process.” (Participant 1 , Academic nurse) “Academic and clinical nurses definitely need to fully respect each other’s suggestions and skills , which is actually a very important prerequisite for partnerships.” (Participant 9 , Academic nurse) .

Leadership support

Leadership support was an important input in developing of APPs-EBN course for undergraduate nursing students. Academic and clinical nurses participating in teaching were more familiar with the characteristics of nursing undergraduate students. The leadership of academic and clinical institutions should provide these professionals with greater rights in developing of APPs-EBN course. “Because this (APPs-EBN course) is intended for students (undergraduate nursing students). It is necessary for leaderships of academic and clinical institutions to provide them (academic and clinical nurses) full freedom to design or optimize this course on their own. ” (Participant 9 , Academic nurse) .

In addition, the time for participating in the teaching of APPs-EBN course the requires the leadership-level support. Leaders should provide academic and clinical nurses with more opportunities to conduct EBNP.

“The support of leaders is essential. For example , if undergraduate nursing students come to a hospital for internships , nursing leaders need to provide them with sufficient support to conduct EBNP projects or participate in the application of clinical guidelines.” (Participant 8 , Academic nurse) . “It is necessary to have the support of the nursing teaching and research department , as this department could identity clinical nurses (with EBNP experience). In addition , the support of nursing leaders is also very important , they could arrange the scheduling and teaching tasks for clinical nurses.” (Participant 15 , Clinical nurse) .

Participants considered activities were essential part during the process of developing of APPs-EBN course for undergraduate nursing student. The effective activities included ongoing communication and share decision-making.

Ongoing communication

Ongoing communications between academic and clinical teachers were beneficial for them to jointly develop and optimize the course, and clarified the teaching tasks of both sides.

“Academic and clinical nurses need to engage in lesson preparation collaboratively. While academic nurses may primarily teach theoretical courses , clinical nurses should work with them to monitor the course’s progress and integrate clinical questions into practical sessions. Both groups should discuss and coordinate to define the teaching tasks effectively.” (Participant 1 , Academic nurse) . “Academic and clinical nurses may need to discuss with both sides about how to better integrate the theory knowledge into the practical course. Firstly , partnership lesson preparation is a part of the teaching process in which both sides are aware of each other’s teaching tasks…… Some partnership discussions and feedback are also important.” (Participant 9 , Academic nurse) .

Share decision-making

Academic and clinical nurses shared decision-making to each other during the teaching process of APPs-EBN course for undergraduate nursing students, which was beneficial to APPs-EBN course for undergraduate nursing students [ 26 ]. For example, “Clinical nurses need to provide timely feedback to academic nurses on any suggestions they may have during the implementation of the course. Academic nurses should also observe if there are some problems that effect teaching quality that require optimization. In other words , adjustments need to be made through regular discussions and feedback between both sides , in order to optimize the course in a timely manner” (Participant 9 , Academic nurse) .

Participants described that APPs-EBN course for undergraduate nursing students may could form outputs.

EBNP projects

More EBNP projects could be conducted in the future. “In the future , academic and clinical nurses could establish partnerships channels , and more EBNP projects may generated.” (Participant 1 , Academic nurse) .

EBN manuals

EBN manuals may be the important output of APPs-EBN course for undergraduate nursing students. “If academic and clinical nurses collaborate to develop EBN course , they could create some manuals including case reports , teaching manuals or reference books to ensure teaching quality and homogeneity.” (Participant 5 , Academic nurse) .

Almost all the participants considered that six positive outcomes were short-term and long-term goals of APPs-EBN course for undergraduate nursing students.

Improved EBN awareness

Improving EBN awareness among undergraduate nursing students was a crucial learning objective of APPs-EBN course for undergraduate nursing students. As a participant mentioned, “Improving EBN awareness among undergraduate nursing students and ensuring they recognize its significance and value is crucial.” (Participant 9 , Academic nurse) .

Improving EBN awareness among undergraduate nursing students would be beneficial for them to conduct EBNP in future clinical nursing work. “They (undergraduate nursing students) should understand the process of EBN. For example , they know what the meaning of evidence transformation. When they work in clinical nursing , they may encounter some clinical problems. At that time , they could conduct evidence retrieval instead of judging just based on experience.” (Participant 7 , Academic nurse) .

Improved EBN competence

Undergraduate nursing students could master the basic knowledge and skills of EBP through participating in APPs-EBN course.

“Undergraduate nursing students are able to develop PICO questions for clinical questions and conduct evidence implementation projects.” (Participant 8 , Academic nurse) . “Through this course , students (undergraduate nursing students) will master some EBN basic knowledge and technical skills , and then be able to apply these methods and competences in practice.” (Participant 2 , Academic nurse) .

Increased EBN projects

The EBN knowledge and skills would be improved for undergraduate nursing students after participating in APPs-EBN course. Undergraduate nursing students may conduct more EBNP projects in clinical nursing in the future.

“They (nursing undergraduate students) will have the skills to conduct EBNP projects in the future , especially the project of evidence implementation. This is the EBNP skill they need to possess after working in clinical nursing in the future.” (Participant 9 , Academic nurse) . “The long-term goal is that undergraduate nursing students can conduct EBNP projects in clinical nursing in the future , and to improve their existing clinical nursing practices.” (Participant 5 , Academic nurse) .

Improved quality of nursing care

Participants considered that undergraduate nursing students would conduct EBNP projects in clinical nursing, which was beneficial for improving patient satisfaction and quality of nursing care.

“Maybe these (EBNP) projects will bring some benefits to patients and improve the quality of nursing care.” (Participant 9 , Academic nurse) . “In the long-term goal , it may be that undergraduate nursing students could apply the methods of EBN into clinical nursing in clinical nursing in the future. These results of EBNP projects may improve the quality of nursing care and patients’ satisfaction.” (Participant 6 , Academic nurse) .

Improved professional identity

Participants mentioned that undergraduate nursing students would have professional identity improvement after conducting EBNP projects. “After conducting EBNP projects , many of undergraduate nursing students actually have a sense of feedback and value. Therefore , it may also enhance their professional identity and their own sense of value” (Participant 9 , Academic nurse) .

This study aimed to explore the academic and clinical nurses’ perceptions on APPs-EBN course for undergraduate nursing students based on practice-academic partnership logic model. In this study, the specific contents of inputs, activities, outputs, and outcomes could further enriching the theoretical framework for developing APPs-EBN education and provide the details for developing of APPs-EBN course for undergraduate nursing students [ 22 ].

The specific content of inputs in this study validates and supplements the results of this scoping review (including key stakeholder commitment, shared mission, time, instructional design, mutual trust, leadership support) [ 22 ]. The results of this study indicated the significance of EBN training and incentives in facilitating the implementation of APPs-EBN course for undergraduate nursing students, which was similar with existing study conducted by Dr. Chen [ 20 ]. Notably, most academic nurses a lack of nursing care experience, leading to a limited understanding of specific process and challenges associated with EBNP projects [ 36 ]. Some clinical nurses a lack of theoretical knowledge of EBN, others were inadequately prepared to engage in teaching EBN courses [ 5 , 31 , 37 , 38 , 39 ], potentially impacting the learning outcomes of undergraduate nursing students participated in EBN courses [ 40 , 41 ]. Therefore, strengthening the training of academic nurses in EBNP and clinical nurses in EBN theoretical knowledge was crucial for improving their basic knowledge, competences, and teaching quality of EBN course.

Developing and conducting of an APPs-EBN course for undergraduate nursing students requires active participation from both academic and clinical nurses in the teaching of APPs-EBN course [ 31 , 42 ]. Sufficient incentives have promoting effect on the participation of academic and clinical nurses in the teaching of APPs-EBN course, which similar with the results of existing research [ 20 , 43 ]. Academic and clinical institutions should develop incentives such as professional title promotion and performance rewards for academic and clinical nurses to promote partnerships in developing and implementing APPs-EBN course for undergraduate nursing students. Effective incentives may help academic and clinical nurses overcome obstacles related to develop APPs-EBN course for undergraduate nursing students, such as lack of time [ 20 ].

The results of this study indicated that developing and conducting APPs-EBN course for undergraduate nursing students needed academic and clinical nurses conduct activities of ongoing communication and share decision making, which was consistent with the results of a scoping review [ 22 ]. Academic and clinical nurses participate in developing APPs-EBN course and conduct ongoing communication and shared decision making through meetings or group discussions during the stages of course planning, course commencement, and evaluation are crucial for refining APPs-EBN course [ 44 ]. Continuous activities between both sides can also promote partnerships between academic and clinical nurses, which may strengthen the connection between academic and clinical sides [ 20 ].

EBNP projects and EBN manuals were the outputs in this study, which was similar with the results of the EBNP quality improvement initiative from the perspective of APPs-EBN [ 45 ]. After conducting APPs-EBN course for undergraduate nursing students, academic and clinical nurses would establish stable cooperative relationships and more nursing undergraduate students have the awareness and ability to conduct EBNP projects. This may lead to more EBNP projects conducted by academic nurses, clinical nurses, and nursing undergraduate students in the future [ 20 ]. In addition, academic and clinical nurses could create EBN manuals related to APPs-EBN courses for undergraduate nursing students based on teaching experiences and insights gained from conducting this course. EBN manuals may provide a theoretical foundation, enabling more nursing schools domestically and internationally to conduct APPs-EBN course for undergraduate nursing students.

Conducting APPs-EBN course for undergraduate nursing students could yield various positive outcomes, aligning with the results of the scoping review [ 22 ]. Short-term goals of APPs-EBN course for undergraduate nursing students may include improved EBN awareness and improved EBN, as high-quality EBN education stands as a crucial measure to attain these goals [ 8 ]. Undergraduate nursing students who possess awareness of and competence in EBN are better prepared to incorporate EBN methodologies into nursing practice. This preparation is crucial for advancing long-term goals such as increasing EBN projects, enhancing the quality of nursing care, and strengthening professional identity [ 46 , 47 ]. Therefore, it is recommended that nursing educators to provide comprehensive inputs and actively participate in activities when conducting APPs-EBN course for undergraduate nursing students. This approach could lead to the generation of outputs and realization of desired outcomes.

Strength and limitation

The participants involved in this study came from four distinct regions in China, all of them with different educational features. This diversity contributes to the universality of the results of this study.

The limitation of this study was that not all participants have experience in APPs-EBN. This is primarily from the scarcity of nursing colleges in China providing EBN courses for undergraduate students. Consequently, it becomes challenging to recruit academic and clinical nurses with sufficient experience in APPs-EBN to participate in this study. In addition, all of the clinical nurses in this study have master’s degree, primarily because the study was conducted in China. Most nursing schools at various universities in China have developed EBN courses only for graduate students, while undergraduate nursing students typically do not receive systematic EBN course [ 48 ]. In the future, it would be beneficial to target recruitment towards both academic and clinical nurses with adequate experience in APPs-EBN and varying education levels for further interviews. This approach aims to garner additional insights and refine the theoretical framework and specific APPs-EBN course.

In addition, the interviews were conducted through online videoconferencing meetings or face-to-face meetings due to the limitations of time and space. For the online videoconferencing meeting, we turned on the camera during the online interview and recorded it with the informed consent of the participants. However, the continuity and fluency of the interview were affected to some certain extent due to network interruption.

Conclusions

Developing and conducting of APPs-EBN course for undergraduate nursing students involves investing inputs (Key stakeholder commitment, Shared mission, EBN training, Time, Instructional design, Incentive, Mutual trust, Leadership support) and conducting activities (Ongoing communication and Share decision-making) may lead to outputs (Educational resource) and outcomes (Improved EBN awareness, Improved EBN competence, Increased EBN projects, Improved quality of nursing care, Improved professional identity).

Data availability

All the original data were shown in the results section of the maunscript.

Melnyk BM, et al. Evidence-based Practice Culture and Mentorship Predict EBP implementation, nurse job satisfaction, and intent to stay: support for the ARCC(©) model. Worldviews Evid Based Nurs. 2021;18(4):272–81.

Article   PubMed   Google Scholar  

Alqahtani N, et al. Nurses’ evidence-based practice knowledge, attitudes and implementation: a cross-sectional study. J Clin Nurs. 2020;29(1–2):274–83.

Dagne AH, et al. Implementation of evidence-based practice and associated factors among nurses and midwives working in Amhara Region government hospitals: a cross-sectional study. Reprod Health. 2021;18(1):36.

Article   PubMed   PubMed Central   Google Scholar  

Wu Y, et al. Do educational interventions aimed at nurses to support the implementation of evidence-based practice improve patient outcomes? A systematic review. Nurse Educ Today. 2018;70:109–14.

Yoo JY, et al. Clinical nurses’ beliefs, knowledge, organizational readiness and level of implementation of evidence-based practice: the first step to creating an evidence-based practice culture. PLoS ONE. 2019;14(12):e0226742.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Lv Y, Geng L, Zeng Y, Wang H. Qualitative study on the difficulties experienced by nursing managers during evidence-based nursing practice. J Nurs Sci (China). 2021;36(11):60–2. https://doi.org/10.3870/j.issn.1001-4152.2021.11.060 .

Article   Google Scholar  

Zhao J, et al. Evidence-based practice implementation in healthcare in China: a living scoping review. Lancet Reg Health West Pac. 2022;20:100355.

PubMed   PubMed Central   Google Scholar  

González LMP, Fonseca DA, Bermeo RNZ. Evidence-based practice competences in nursing students at a university in Colombia. Nurse Educ Today. 2021;107:105094.

Hou R. (2013). The Construction of Access Indicator System of Undergraduate Nursing—Students’Clinical Teacher in Henan Province. (Master) Zhengzhou University (China).

Institute of Medicine Committee on the Robert Wood Johnson Foundation Initiative on. The future of nursing, a.t.I.o.M. The future of nursing: leading change, advancing Health. National Academies Press (US); 2011.

Mthiyane GN, Habedi DS. The experiences of nurse educators in implementing evidence-based practice in teaching and learning. Health SA. 2018;23:1177.

Xu J, Guan Y, Shi H, Zhang Y, Zheng J, Wu C. Evidence-based practice education in undergraduate nursing students: a scoping review. Chin Jouranl Nurs Educ (China). 2022;19(3):277–83. https://doi.org/10.3761/j.issn.1672-9234.2022.03.01613 .

Keib CN, et al. Changes in nursing students’ perceptions of research and evidence-based practice after completing a research course. Nurse Educ Today. 2017;54:37–43.

Kim JS, Gu MO, Chang H. Effects of an evidence-based practice education program using multifaceted interventions: a quasi-experimental study with undergraduate nursing students. BMC Med Educ. 2019;19(1):71.

Cardoso D et al. The Effectiveness of an Evidence-Based Practice (EBP) Educational Program on Undergraduate Nursing Students’ EBP Knowledge and Skills: A Cluster Randomized Control Trial. Int J Environ Res Public Health, 2021. 18(1).

Rholdon R, et al. An embedded EBP project: Effect on student nurses’ practice, attitude, and knowledge. Teach Learn Nurs. 2021;16(2):110–5.

Chen Q et al. Differences in evidence-based nursing practice competencies of clinical and academic nurses in China and opportunities for complementary collaborations: a cross-sectional study. J Clin Nurs, 2022.

Ramis MA, et al. Theory-based strategies for teaching evidence-based practice to undergraduate health students: a systematic review. BMC Med Educ. 2019;19(1):267.

Beal JA. Academic-service partnerships in nursing: an integrative review Nurs Res Pract, 2012. 2012: p. 501564.

Chen Q et al. Academic and Clinical Nurses’ Perceptions and Experiences on Academic-Practice Partnership in Evidence-Based Practice: An Interpretive Description Journal of Nursing Management, 2023. 2023.

McClinton TD. A guided search: formulating a PICOT from assigned areas of inquiry. Volume 19. WORLDVIEWS ON EVIDENCE-BASED NURSING; 2022. pp. 426–7. 5.

Xia Y, et al. Academic-practice partnerships in evidence-based nursing education: a theory-guided scoping review. Nurse Educ Pract. 2023;73:103839.

Zhao Q, et al. Non-pharmacological interventions to prevent and treat delirium in older people: an overview of systematic reviews. Int J Nurs Stud. 2023;148:104584.

Rycroft-Malone J, et al. Collaboration and co-production of knowledge in Healthcare: opportunities and challenges. Int J Health Policy Manag. 2016;5(4):221–3.

De Geest S, et al. Academic service partnerships: what do we learn from around the globe? A systematic literature review. Nurs Outlook. 2013;61(6):447–57.

MacPhee M. Developing a practice-academic partnership logic model. Nurs Outlook. 2009;57(3):143–7.

Blum ER, Stenfors T, Palmgren PJ. Benefits of massive Open Online Course participation: deductive thematic analysis. J Med Internet Res. 2020;22(7):e17318.

Buus N, Perron A. The quality of quality criteria: replicating the development of the Consolidated Criteria for Reporting Qualitative Research (COREQ). Int J Nurs Stud. 2020;102:103452.

Su JJ, et al. Defining compassionate nursing care. Nurs Ethics. 2020;27(2):480–93.

Lasater K, Atherton IM, Kyle RG. Population health as a ‘platform’ for nurse education: a qualitative study of nursing leaders. Nurse Educ Today. 2020;86:104313.

Pedregosa S, et al. Effective academic-practice partnership models in nursing students’ clinical placement: a systematic literature review. Nurse Educ Today. 2020;95:104582.

Sukkarieh-Haraty O, Hoffart N. Integrating evidence-based practice into a Lebanese nursing baccalaureate program: challenges and successes. Int J Nurs Educ Scholarsh, 2017. 14(1).

Li S, Cao M, Zhu X. Evidence-based practice: knowledge, attitudes, implementation, facilitators, and barriers among community nurses-systematic review. Med (Baltim). 2019;98(39):e17209.

Wakibi S et al. Teaching evidence-based nursing practice to student nurses in developing countries: strategies for novice nurse educators. Int J Nurs Educ Scholarsh, 2020. 17(1).

Alving BE, Christensen JB, Thrysøe L. Hospital nurses’ information retrieval behaviours in relation to evidence based nursing: a literature review. Health Info Libr J. 2018;35(1):3–23.

Orta R, et al. Knowledge and competency of nursing Faculty regarding evidence-based practice. J Contin Educ Nurs. 2016;47(9):409–19.

Saunders H, et al. Practicing Healthcare professionals’ evidence-based practice competencies: an overview of systematic reviews. Worldviews Evid Based Nurs. 2019;16(3):176–85.

Camargo FC, et al. Competences and barriers for the evidence-based practice in nursing: an integrative review. Rev Bras Enferm. 2018;71(4):2030–8.

Cleary-Holdforth J. Evidence-based practice in nursing and midwifery: we are talking the talk, but are we walking the Walk? Worldviews Evid Based Nurs. 2020;17(2):94–7.

Lam CK, Schubert CF, Herron EK. Evidence-based practice competence in nursing students preparing to transition to practice. Worldviews Evid Based Nurs. 2020;17(6):418–26.

Lam CK, Schubert C. Evidence-based practice competence in nursing students: an exploratory study with important implications for educators. Worldviews Evid Based Nurs. 2019;16(2):161–8.

Gilliss CL, et al. Academic/clinical nursing integration in academic health systems. Nurs Outlook. 2021;69(2):234–42.

Speroni KG, McLaughlin MK, Friesen MA. Use of evidence-based Practice Models and Research Findings in Magnet-designated hospitals across the United States: National Survey results. Worldviews Evid Based Nurs. 2020;17(2):98–107.

Amaral C, et al. Patient Safety Training Programs for Health Care professionals: a scoping review. J Patient Saf. 2023;19(1):48–58.

PubMed   Google Scholar  

Otts JA, et al. Academic-practice Partnership to prevent and manage pressure injuries: an evidence-based Quality Improvement Initiative. J Wound Ostomy Cont Nurs. 2023;50(6):463–73.

Fu L, et al. Evidence-based practice competency and related factors among nurses working in Public hospitals. Inquiry. 2020;57:46958020927876.

André B, Aune AG, Brænd JA. Embedding evidence-based practice among nursing undergraduates: results from a pilot study. Nurse Educ Pract. 2016;18:30–5.

Jiao Y. Study on the status quo of evidence-based nursing quality of clinical undergraduate nurses and the construction of training contents (Master). Shanxi Medical University (China); 2017.

Download references

Acknowledgements

Not Application.

This work was supported by the Natural Science Foundation of Hunan Province (No.2022JJ40642) and the National Natural Science Foundation of China (No. 72104250).

Author information

Authors and affiliations.

School of Nursing, Shandong Xiehe University, Jinan, China

Guiyun Wang

Xiangya School of Nursing, Central South University, Changsha, China

Yuting Xia, Qirong Chen & Xirongguli Halili

The Third Xiangya Hospital, Central South University, Changsha, China

You can also search for this author in PubMed   Google Scholar

Contributions

Study design: YX, HH, QC; Literature searching: YX, XH; Quality Appraisal: YX, HH, QC; Data extraction: YX, GW, QC; Study supervision: QC, GW, HH; Manuscript drafting: YX; Critical revisions for important intellectual content: YX, QC, HH, GW.

Corresponding authors

Correspondence to Yuting Xia or Hui Huang .

Ethics declarations

Ethics approval and consent to participate.

This study was approved by the Ethics Committee of school of nursing of Central South university, China (review number: E202313). Detailed explanations were provided concerning the recording procedures, and the interviewees were requested to sign an informed consent form before the interviews officially commenced, including the recording process.

Consent for publication

Competing interests.

The authors declare no competing interests.

Additional information

Publisher’s note.

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

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ .

Reprints and permissions

About this article

Cite this article.

Wang, G., Xia, Y., Chen, Q. et al. Exploring academic and clinical nurses’ perspectives on evidence-based nursing course for undergraduates from perspectives of academic-practice partnerships: a qualitative study. BMC Nurs 23 , 657 (2024). https://doi.org/10.1186/s12912-024-02223-1

Download citation

Received : 16 April 2024

Accepted : 02 August 2024

Published : 15 September 2024

DOI : https://doi.org/10.1186/s12912-024-02223-1

Share this article

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

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

Provided by the Springer Nature SharedIt content-sharing initiative

• Academic-practice partnerships
• Evidence-based nursing
• Undergraduate nursing students
• Perceptions

BMC Nursing

ISSN: 1472-6955

• General enquiries: [email protected]

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 17 September 2024

Exploring the impact of perceived early marriage on women’s education and employment in Bangladesh through a mixed-methods study

• Md. Nuruzzaman Khan 1 , 2 ,
• Shimlin Jahan Khanam 1 ,
• Md. Mostaured Ali Khan 3 ,
• Md Arif Billah 4 &
• Shahinoor Akter 5  

Scientific Reports volume  14 , Article number:  21683 ( 2024 ) Cite this article

Metrics details

• Epidemiology
• Medical research

Child marriage negatively affects women’s socio-economic empowerment, particularly in education and employment. This study aimed to explore women’ perspectives on the timing of their marriages, considering their educational and employment status at the time. It also sought to identify factors influencing early married women’s perception of their marriages as timely. We analyzed both quantitative and qualitative data. The quantitative data included a sample of 5,596 women aged 15–24 from the 2017/18 Bangladesh Demographic and Health Survey. Additionally, we collected qualitative data through six in-depth interviews, two focus group discussions, and 13 key informant interviews. We used a multilevel mixed-effects Poisson regression model to examine the relationship between women’s formal employment, education, and child marriage. Thematic analysis was employed for the qualitative data. Around 62% of the total women analysed reported their married occurred early with the mean age at marriage was 15.2 years. Approximately 55% of the total early married women believed their marriages occurred at the right time, especially among those who were employed at the time of their marriage. Among this subset, we also noticed a higher likelihood of discontinuing work and education following marriage. Qualitative findings revealed reasons behind this perception, such as escaping poverty, safety concerns, limited job prospects, and the impact of non-marital relationship and societal norms. While many early-married women perceived their marriage as timely, particularly those initially employed, this decision often coincides with a subsequent withdrawal from work and education. This underscores the pressing need for policies and programs aimed at educating women about the legal age for marriage and the negative consequences associated with early marriage while also equipping them with knowledge and resources for informed decision-making.

Introduction

Child marriage is a pervasive issue in low- and middle-income countries (LMICs), especially in South Asia and sub-Saharan Africa 1 . The 2022 UNICEF report on child marriage revealed that approximately 12 million girls in LMICs are married before the age of 18 each year, which translates to one in every five girls in those settings 2 . In Bangladesh, the situation is even more alarming, with recent estimates indicating that about 59% of women aged 20–24 years were married before turning 18 3 , and 22% were married before the age of 15 4 . The rate is further higher in rural areas, particularly those with widespread poverty, low education enrolment and significant concerns about family’s reputation 4 , 5 , 6 .

Child marriage can have devastating consequences for girls and their families, as it often leads to a cycle of poverty and disempowerment 7 . Girls who are forced into early marriage are often forced to drop out of school, which reduces and restricts their opportunities for education and limits their economic prospects 8 . Additionally, child marriage has been associated with higher rates of domestic violence and divorce, which can have significant negative impacts on girls’ physical and mental health, hampering the development and wellbeing of girls 9 , 10 . Moreover, child marriage has serious implications for maternal health. Child brides are more likely to experience complications during pregnancy and childbirth, such as obstetric fistula and maternal mortality 11 , 12 . Children born to child brides are also at a higher risk of mortality and malnutrition 13 . This leads to an intergenerational effect because malnourished children are often more likely to drop out of school and subsequently become child brides themselves 14 . These adverse consequences associated with child marriage, coupled with the high number of girls affected, highlight a significant burden in LMICs 1 . Therefore, it poses challenges to achieving Sustainable Development Goals (SDGs) related to health and well-being (SDG 3), gender equality (SDG 5), education (SDG 4), and poverty reduction (SDG 1) 15 .

Socio-demographic factors associated with child marriage have been extensively studied in LMICs, including Bangladesh 16 , 17 , 18 , 19 . Although such observational studies played a crucial role in developing relevant policies and programs to reduce the occurrence of child marriage, they fall short comprehensively addressing the issue. Girls’ views over their marriage along with marriage age can carry a significant weight and override all socio-demographic factors by mediating their roles 20 . It is commonly assumed that every child marriage occurs on parental wishes and is not desired by the girls. However, this is not always the case in reality. The underlying reasons for girls choosing to marry at an early age instead of continuing education and work has remained understudied 21 . Therefore, it is crucial to explore the percentage of girls who perceive their marital age as appropriate or not, as this can inform the development of more effective policies and programs. However, undertaking this requires comprehensive research, integrating determinant factors of early marriage and perceptions of those who marry early. Unfortunately, such information is largely absent in existing literature due to the nature of available data in LMICs, including Bangladesh, where DHS surveys serve as primary data sources 16 , 17 , 18 , 19 , 22 . The survey provides important information on prevalence of early marriage and its socio-demographic predictors, however, lacking content related to girls’ views over early marriage as it typically requires qualitative study. This indicates a need for mixed-methods studies, which are mostly lacking in LMICs, with none conducted in Bangladesh 23 , 24 , 25 , 26 . To address these limitations, we aimed to investigate women’s perceptions of getting married at an earlier age, taking into account their education and employment status at the time of marriage. We also sought to identify the factors that influenced earlier-aged women to perceive their marriages as occurring at the right age.

Study design

The study applied a sequential explanatory mixed-methods design where analysis of secondary quantitative data were followed by the collection and analysis of qualitative data 27 . The qualitative findings, therefore, aimed to explain and interpret the findings of the quantitative study.

Quantitative study

Data source and sampling.

This study analysed data of most recent 2017/18 Bangladesh Demography and Health Survey (BDHS). The survey employed a two-stage stratified random sampling method to select the respondents. In the first stage, 672 Primary Sampling Units (PSUs) were selected from a list of 293,579 PSUs generated during the 2011 National Population Census of Bangladesh, excluding three PSUs due to extreme floods. In the second stage, 30 households were randomly selected from each of the PSUs, using probability proportional to PSU size. This generated a list of 20,160 households, and 19,457 of these households were interviewed. There were 20,376 respondents eligible in the selected households with the eligibility criteria: (i) being a married woman of reproductive age and (ii) spent the previous night of the survey day in the selected households. Of them data were collected from 20,127 women. Details of the BDHS survey procedure were published elsewhere 3 . A sub-sample, 5,596 women aged 15–24, of them was analysed in this study selected based on the following two inclusion criteria: (i) aged 15–24 years (to ensure inclusion of only recently married women following the recommendation of global literature 2 , 6 , 7 , 9 , 24 , 28 ) and (ii) married at the time of survey.

Outcome variable

The focus of our quantitative study was child marriage, which we defined as a binary outcome variable (yes or no). To collect this data, the BDHS asked women to report the age at which they first began living with their spouse or first spouse in case of more than one marriage. We categorized responses as either child marriage (1, if the marriage occurred before the woman turned 18) or normal-aged marriage (0, if the marriage occurred at age 18 or later) according to the universal recommendation which is also followed in Bangladesh 2 .

Exposure variables

Working status and educational status of respondents at the time of their marriage as well as following marriage were our primary exposure variables. The BDHS collected this data by asking whether the respondents were working or studying in school just before they got married. If the response was affirmative, the respondents were then asked two follow-up questions to determine their work or education continuity and the number of years of continuity. These follow-up questions were: (i) Did you continue working/studying after marriage? and (ii) If yes, for how long? Based on the responses, we created four variables: (i) study before marriage (yes, no), (ii) work before marriage (yes, no), (iii) after marriage study (no, continue less than a year, continue less than five years), and (iv) after marriage work (no, continue less than a year, less than five years). We also considered additional exposure variables by reviewing the available literature for Bangladesh and other LMICs 16 , 17 , 18 , 19 . These variables included respondents’ age, education level, partner’s education level, partner’s occupation, wealth quintile, place of residence, and region of residence.

Statistical analysis

Descriptive statistics, including frequency and percentage, were used to describe the characteristics of the respondents. Multilevel mixed-effect Poisson regression model was utilized to explore the association between early marriage and the working and studying status of the respondents, as well as the continuity of their working and studying status following child marriage. The reason for using a multilevel Poisson regression model was higher prevalence of child marriage (> 10%) and the clustering structure of the BDHS data. Previous studies have found that simple logistic regression analysis produces less precise findings when the prevalence of the outcome variable is high and the data come from a clustered structure 29 . Both adjusted and unadjusted models were run, where one particular exposure variable was considered with the child marriage variable in the unadjusted model, and other factors were adjusted in the adjusted model. Multicollinearity was checked before running each model. Results were reported as unadjusted or adjusted Prevalence Ratios (PRs) and corresponding 95% confidence intervals. Stata version 18.0 was used for data analysis.

Qualitative exploration

In our quantitative study, we identified a higher prevalence of child marriage among working women. To explore why working women get married at an early age, we conducted a qualitative study during January 2023 and January 2024 as this information was not available in the BDHS survey data. The Gazipur district of Dhaka division was purposively selected as the study area. This area has a higher concentration of ready-made garments and small-scale industries where the majority of workers are women and married 30 . Two focus group discussions (FGDs) involving 16 participants (8 in each FGD), six in-depth interviews (IDIs), and 13 key informant interviews (KIIs) were conducted using two pre-developed interview topic guides. The topic guides covered several areas, including marriage experience, perceptions at the time of marriage, education and employment after marriage, respondents’ perspectives on marriage over time, and community and religious norms related to early marriage. The length of these interviews ranged from 75 to 90 min.

The participants included in the FGD and IDI were selected purposively selected based on the following criteria: (i) currently aged between 15 and 24 years, (ii) married before their 18th birthday, (iii) involved in either work or education just before marriage, and (iv) currently either continuing education or work or have left them to become housewives. These criteria aimed to ensure that the qualitative study participants were similar to those in the quantitative study. To recruit the participants, data collectors first approached them by sharing the details of the study plan and collected data on their preferred date. To protect privacy of the participants and ensure limited interruption during interview process, the participant and interviewer choose a private location. Prior to the qualitative data collection, participants were again briefed about its objectives and assured of the confidentiality of their responses. Informed consent was obtained from participants above 18 years old, while for participants under 18, informed consent was obtained from their legal guardians (father or husband).

Additionally, 13 key informant interviews (KIIs, male = 9; female = 4) were conducted with managers of ready-made garment factories ( n  = 2), small-scale industries ( n  = 1), local leaders (members of the Pourosova, n  = 3 [male = 2, female = 1]), the Upazila Nirbahi officer ( n  = 1, female), and parents of girls who married at an early age ( n  = 6 [male = 4, female = 2]). Their perspectives on early marriage were sought due to their significant involvement in the issue, including shaping cultural norms and exerting social pressures that perpetuate early marriage practices.

Participation was completely voluntary, and no participants were provided with any gifts or incentives to participate in this study. Experienced social researchers were involved in the qualitative data collection. The FGDs and IDIs were conducted by a female interviewer (second author). The KIIs were conducted by two male interviewers (first and third author). All conversations during FDGs, IDIs and KIIs were audio recorded with consent. The recorded audio files were subsequently reviewed and translated into English by the respective research team members. Relevant sections on the reasons behind early marriage and its impact on work and educational pursuits were extracted and discussed among the team to ensure accurate interpretation and presentation of the data. Qualitative data were thematically analysed 31 , using Nvivo version 12.10 32 . Key themes identified in the analyses were synthesized and presented as study findings. Ethical approval for the qualitative study was obtained from the Institutional Review Board of the University of Rajshahi.

Background characteristics of the respondents

Table  1 presents the background characteristics of the respondents included in the quantitative exploration. The mean age at marriage was 15.2 years (SD, ± 1.41) and the mean years of education were 6.9 years (SD, ± 2.95). About 32.8% of the respondents reported being engaged in a formal job. Of the respondents analyzed, 61.7% reported their marriage occurred before reaching their age 18 years. Over half of the (55.1%) total 61.7% who reported being married before 18 years reported that their marriage occurred at the right time, while 44.9% of them felt that they should have delayed their marriage.

Respondents’ perception about their marriage timing

Table  2 illustrates the distribution of respondents’ perception about their marriage timing as per their socio-demographic characteristics. Among the respondents who believed that their marriage occurred earlier, and they should delay, 49.8% were aged between 15 and 19 years, and 41.2% were aged between 20 and 24 years. Earlier-aged married women who believe their marriage occurred earlier and should be delayed, 36.6% were illiterate. This number was half to 63.4% of illiterate women who thought their marriage occurred at right age.

How women’s education and employment status before marriage influences their perception of marriage age

The unadjusted associations suggest that earlier-married women who thought their marriage occurred at the right time were more likely to have worked before marriage (PR = 1.88, 95% CI = 1.34–2.64) and less likely to have studied before marriage (PR = 0.55, 95% CI = 0.47–0.66) compared to women who thought they should delay their marriage (Table  3 ). After adjusting for confounding variables, the associations remain significant, but the effect sizes are attenuated. Earlier aged women who thought their marriage occurred at the right time were still more likely to have worked before marriage (aPR = 1.47, 95% CI = 1.01–2.18), but the association was no longer significant. However, adjusted likelihood of early marriage was found lower among studying girls (aPR = 0.43, 95% CI = 0.35–0.53).

Impact of early marriage on the continuation of education and employment

Table  4 presents the results of the analysis of the association between the women’s perception of their marriage timing and their continuation of education and work after marriage. In the unadjusted analysis, earlier aged women who think that their marriage occurred at right time were more likely to report continuation of their education up to five years (PR = 1.73, 95% CI 1.31–2.28) as compared to the women who did not continue their education. However, this association was not significant for those who continued their education for less than one year. In the adjusted analysis, the association between continuing education and women’s perception of their marriage timing was attenuated, with women who continued their education for less than five years having a non-significant lower likelihood of perceiving their marriage as occurring at the right time (aPR = 0.92, 95% CI 0.65–1.28). The association between continuing work and women’s perception of their marriage timing remained non-significant in the adjusted analysis.

Through qualitative investigation, we conducted an extensive exploration into the reasons why working women who married at an earlier age believed that their marriage took place at the right time, and also examined why studying women who married at an earlier age perceived their marriage as occurring earlier, as revealed in our quantitative analysis. The characteristics of the participants participated in qualitative interviews are presented in supplementary Tables 1 , 2 and 3 . Our comprehensive findings have uncovered a multitude of factors that can be categorized into distinct thematic patterns (supplementary Table 4). These include: (i) getting married is a way to recover from poverty, (ii) marriage was perceived as a means to ensure the safety and security of young unmarried girls, (iii) less hope for job prospects, and (iv) intimate relationships and social norms.

Getting married way to recover from poverty

Participants reported that a common influencing factor behind early marriage among young girls was their perception that it would help them escape poverty.

“I had dreams of studying and becoming a government service holder, but poverty choked those dreams before they could bloom. Marriage was the only path open to me, even if it means leaving those dreams behind.” (IDI participant 3, age 20). “My parents couldn’t afford to keep me in school anymore, and marriage seemed like the only way to have a roof over my head and food on the table.” (IDI participant 2, age 19).

Most female participants reported that they entered the labour market before reaching their 18th birthday. Since their families were from lower socio-economic backgrounds, they started looking for a job to support their families. They often engaged in low-wage occupations, such as house cleaning or garment factories.

“I worked in house cleaning before my marriage and received a very low wage, which was not enough for my living. As a result, I could not send money to my parents, even though they expected me to do so.” (FGD 1 participant, age 19).

According to them, like many young girls, they also moved to the city from rural areas leaving their families behind in search of jobs and started living in rental accommodations. The income derived from these jobs proved insufficient to meet their daily expenses, including paying for food, rent and utilities while providing financial assistance to their families. This issue was also highlighted in the KIIs. One ready-made garment manager reported that young female ready-made garment factory workers’ wages are not enough to support themselves and their parents. Therefore, they usually decide or agree to get married at an early age to overcome their financial struggles.

“Girls who started working here usually work on a daily basis and earn only 150–200 BDT (1.5-2 USD) per day, which is not enough to maintain their daily expenses. What’s even worse is that many of these girls migrated from rural areas to work here, meaning they have to pay for their rent and other associated costs. It’s no surprise that many of them end up choosing to get married, as it seems like the only way out of this financial struggle”. (Ready-garment manager, male, age 45).

Marriage was perceived as a means to ensure the safety and security of young unmarried girls

In the context of working girls who opt for early marriage, safety and security emerge as crucial factors. Participants reported that young girls working in different industries (such as ready-made garments factories) usually work alongside male workers. Due to the demands of their jobs, they usually spend prolonged hours working together at workplace. The nature of their joint work and spending prolonged hours at workplace often create tensions and a sense of insecurity among themselves and within their families. They fear being exposed to physical and sexual abuse and/or violence at workplace, thereby reinforcing the inclination towards early marriage.

“My parents were concerned about the potential risks of sexual and physical abuse when working outside the home, especially during evening hours and interacting with male colleagues. I would hold the same belief and take similar precautions if I had a young daughter engaged in employment, as there are multiple reasons to support this perspective”. (FGD 1 participant, age 18). “Living alone as a young woman in this city felt dangerous. Marriage, even if it’s not ideal, meant having someone to protect me and a family to belong to.” (IDI participant 2, age 20).

This fear also reflected in the KIIs with fathers. Families of young girls working in ready-made garment factories tend to marry off their young girls to protect their daughters or girls from any future risks of abuse.

“Soon after starting working at age 15, I arranged her marriage. Although it was not my intention, we did not feel secure leaving my young daughter outside the house, as she could be at risk of rape or harassment from strangers. My neighbours also suggested that I do so”. (Father of a married and working young girl, age 55).

One key informant, a supervisor of a ready-made garments industry, also confirmed that young girls working in the industries often become victims of physical and sexual harassments. He also added that the prevalence of sexual violence and harassment had been underreported like in other sectors in Bangladesh and remained a concerning reality. However, the families of the young girls are aware of these risks, even if based on limited evidence, which significantly influenced marry off their girls at a young age against the law.

“A significant number of girls who start working at a young age face violence from their male counterparts, including sexual violence. We are aware of this, and our organization has very strict laws against it. However, these incidents often go unreported, similar to other sectors in Bangladesh”. (A supervisor of a garment factory, male, age 38).

Even parents of young school or college-going girls also voiced their concern regarding their daughters’ safety while traveling to school or college. Sometimes local boys or men harassed these young girls on the way to home or college, and parents of these young girls usually perceived that marrying the young girls off was the only solution.

“I wanted my daughter to continue her education. However, a mischievous boy started following her to school. I contacted his parents and asked them to discipline their son and prevent him from following my daughter, but it did not work. Eventually, I had to marry off my daughter when she was only 16 years old”. (Father of earlier aged girls who marry off while studying, age 38).

However, during the FGDs, female participants expressed their viewpoints that the claims regarding safety concerns and incidents of violence were not always accurate. They argued that this phenomenon might stem from parents’ genuine apprehensions regarding the safety and their desire to uphold societal prestige, their parents mostly forced them to get married at an early age against their will. This highlights the need to delve deeper into the complexities surrounding early marriage and the factors that shape this decision.

“I started working as a house cleaner when I was 15 and got married at age 16. I wasn’t intending to get married at that time, but my parents pressured me to do so. They had heard that young girls working as house cleaners often face sexual and physical violence from homeowners. Though my homeowners treated me like their daughter. Therefore, they were strict in their decision to marry me off”. (FGD 2 participant, age 20).

Less hope for job prospects

Several female participants highlighted the interconnectedness between school dropout, limited employment opportunities for people with lower educational attainment, early entry into workforce, and early marriage. According to them, education could not guarantee job prospects in Bangladesh. Securing a job could be more challenging for individuals with low academic achievements. Therefore, they perceived that entering the job market early would be more worthwhile for them and their families than continuing their education, as it required financial resources.

“Studying seemed pointless when I knew there were barely any jobs at the end. Marriage offered a chance at some stability, even if it wasn’t the kind I hoped for.” (IDI participant 5, age 21).

One FGD participant reported that she perceived that she did not have the necessary qualities to compete in the increasingly competitive job market. She felt early employment would give her practical work experience, opening opportunities for better job prospects. Hence, she decided to dropout from school. Other FGD participants agreed with her, indicating they shared similar perceptions.

“Obtaining a job after completing education is only possible for highly meritorious students. I did not fall into that category. Hence, I decided to start working with the hope that by the time I finished my education, I would have accumulated several years of work experience, which would undoubtedly enhance my chances of securing a comparatively better job”. (FGD 2 participant, age 19).

Some guardians of young school or college-going girls also perceived that education would not guarantee any employment for their daughters and married them off at an earlier age.

“Why would I continue my daughter’s education? What hope was there? Even many educated and meritorious students are now unemployed. Therefore, I married off my daughter when she was only 15, and she is now leading her own life. I have no concern now”. (Father of earlier aged girls who marry off while studying, age 40).

Intimate relationships and social norms

Several female participants revealed that working girls were found to be more susceptible to developing relationships with their colleagues. These close bonds often evolve into sexual relationships, contributing to early marriage among working girls.

“Shortly after I began working, I entered into a relationship with one of my colleagues, which later turned into a sexual relationship. We then decided to marry, although our parents were unhappy with our decision. However, we did it without their approval because we knew what we did was not right according to our religion”. (FGD 1 participant, age 18).

The issue of having a relationship at the workplace without parents’ permission was identified as a growing concern for early marriage, even in the absence of an intimate relationship.

“Parents of the earlier-aged working girls are mostly uneducated and strongly influenced by the social norms and misconceptions. They believe female and male could not be co-worker. Therefore, they prefer to marry off their daughters earlier”. (Upazila Nirbahi officer, age 38).

Importantly, this perception was found to be common among parents of both working and studying girls. However, it does not pose a significant concern for the parents of studying girls. This is because their awareness of the negative effects of child marriage motivates them to prioritize the education of their daughters and prioritize their daughters’ safety above all else.

“I had concerns about the possibility of my school-going daughters engaging in intimate relationships, which have become more common due to modernization. However, my intention was not to abruptly end her education and arrange her marriage solely based on this risk. I believed she was young and had a promising future ahead. Eventually, I did make the decision to marry her, but it was primarily motivated by the opportunity to find a comparatively better groom within my family lineage”. (Father of earlier aged girls who marry off while studying, age 38).

Social norms were highlighted as significant reasons for early marriage among the women who married at a younger age.

“Marriage is a way to uphold our traditions, to show respect to our families and ancestors. Even if I had doubts, I knew I had to follow the path laid out for me.” (IDI participant 4, age 22).

One participant mentioned that she felt she did not belong in her society and remained a minor in society’s eyes when she found many of peers were getting married at an earlier age than her.

“Everyone around me was getting married young, building families. It felt like I was the only one left behind, stuck in a childhood that was no longer fitting. Marriage was a way to belong, to be seen as a responsible adult.” (IDI participant 5, age 21).

Another participant explicitly mentioned why marriage was important for them to become important in the society.

“Marriage is a social currency here. It defines your status, your worth. Choosing a career over marriage felt like choosing shame over acceptance, a path less traveled and less understood.” (IDI participant 3, age 19).

The primary objective of this study was to explore the perspectives of girls regarding the timing of their own marriages, taking into consideration their educational and employment backgrounds at the time of marriage. Furthermore, we aimed to investigate the factors that influenced earlier-aged women to perceive their marriages as occurring at the appropriate time. Our findings indicate that among the total population of earlier-aged women, 55% believe that their marriages took place at the right time, with a higher percentage observed among women who were employed at the time of marriage. Among those who held this perception, there was a notable trend of discontinuing work and education after getting married. Through qualitative analysis, we gained insights into the underlying reasons why these women considered their marriages to be timely, including the desire to escape poverty, concerns regarding safety and security, and the influence of intimate relationships and societal norms.

The study findings convey three significant messages concerning early marriage in the country. Firstly, a substantial portion of early marriages are a result of girls’ choice. Secondly, the engagement of girls in formal employment contributes to an increase in early marriage rates, unless measures are implemented to ensure economic security and safety. Lastly, early-married girls who believe that their marriages occurred at the right time are more likely to discontinue their education and withdraw from the workforce.

The perception of working girls who marry early that their marriage occurred at the right time can be understood from two distinct directions. Firstly, these girls may lack awareness regarding the appropriate age for marriage and the potential negative consequences associated with marrying at a young age. Secondly, their working environment and the challenges they face may have influenced their decision to marry early, despite being aware of the adverse outcomes of early marriage. This may include parental pressure for marriage once girls start working, especially if they work alongside male colleagues or develop intimate relationships with them, which can conflict with societal norms 33 . Traditional patriarchal values in Bangladesh further reinforce these pressures 33 . Regardless of the direction, these perceptions indicate a failure of policies and programs, which can result in long-term burdens for the country.

If the first direction holds true, it suggests that a portion of women have not received the message regarding the correct age for marriage at early ages and consequences of early marriage. Factors such as early dropout from education to enter the workforce and limited exposure to mass media due to work obligations may contribute to this lower level of awareness 28 , 29 , 34 . These directions are influenced by various socio-demographic and socio-cultural factors. While leaving the parental home to enter the workforce can indicate a degree of freedom for girls, this is not always the case in many LMICs, including Nepal and India 8 , 18 . In these contexts, girls who start working early, often without continuing their education, typically come from low-income families where they are expected to support their families. Early marriage remains a long-standing norm in these communities, perpetuated by the fact that their mothers and grandmothers also married at a young age. Furthermore, these girls often move from their parental homes to their workplace, which is often seen as opposite of social norms in Bangladesh as well as other LMICs 35 .

On the other hand, if the second directions is true, it indicates a failure of long-standing governmental priorities to ensure continuing girls’ education and prevent child labour, as well as a failure to ensure the safety of working girls 18 . Though Bangladesh has made remarkable progress in reducing violence against women, incidents still occur frequently with one in three women faces it 36 . Importantly, any such incidents are usually spread widely with additional rumours, causing concern for the girls’ security and motivating their parents to marry them off early. However, the above explanations may not be true for the girls who continue education. They are usually better aware off about the right age of marriage and risk of early marriage as well as usually stay at home with less security issue. They are also from a comparatively better family status.

In this study, we have also found that there is a lower likelihood of continuing work after marriage. This change is mainly due to the presence of family pressure or intention to have a child, as well as the desire to give more time to the family 37 , 38 . Moreover, we found that while women are employed, their wages in the factories are very low. This financial constraint limits their opportunities, often pushing them towards early marriage or leading them to leave work altogether to assume traditional roles as wives, mothers, and homemakers 39 . However, this practice can have several adverse consequences on women’s economic flexibility, empowerment and decision making abilities in the family 40 , 41 . For instance, stopping work can lead to face earlier aged pregnancy, which is associated with various adverse maternal and child health outcomes, including lower utilization of maternal healthcare services, pregnancy complications, and maternal and child mortality 40 , 42 . Furthermore, this trend indicates a significant dropout rate of girls from continuing their education and working status, which negatively affects women’s empowerment and decision-making abilities 40 , 41 . These consequences can lead to higher household poverty, greater sensitivity to economic shocks, and less income diversification 41 . These factors, in turn, can have significant intergenerational impacts, resulting in poorer health among children and lower investment in education and other forms of human capital accumulation 43 , 44 . All of these factors increase the likelihood of early marriage in subsequent generations 43 .

Regardless of the explanation provided, these findings indicate challenges for the country to achieve relevant SDG’s targets related to the improvement of sexual and reproductive health rights as well as equity. This highlights the need for policies and programs to educate and raise awareness among studying and working girls about the correct age of marriage and the adverse effects of early marriage. Increasing the wages of working girls at the initial level is also important. Nevertheless, the existing initiatives remain ineffective unless appropriate engagement of multiple stakeholders including girl’s parents and local leaders for implementation of target-oriented policies and programs to reduce early marriage. Reducing gender-based violence and improving their safety in the workplace are also crucial to reducing early marriage.

This study exhibits several notable strengths as well as a few limitations. It stands as the first investigation in Bangladesh and other LMICs that delves into women’s perceptions of their marriage age, accounting for their educational and employment statuses, and utilizing nationally representative quantitative survey data. Additionally, the qualitative survey findings offer insight into the motivating factors behind the marriage decisions of working and educated girls. The qualitative interviews were conducted by the authors of this study, who have extensive experience in academia and public health research. They hold postgraduate degrees in population science, public health, and anthropology, and possess substantial expertise in conducting research in LMICs, including Bangladesh. All authors agreed on and approved the interpretation presented in the manuscript. The study employed appropriate statistical modelling techniques to analyze the data, incorporating a diverse range of confounding variables. As a result, the reported findings possess sufficient robustness to inform national-level policies and programs. However, one key limitation of this study is that the quantitative data analyzed in this study were derived from a cross-sectional survey, which restricts the ability to establish causal relationships. While the study explored cultural factors associated with early marriage through qualitative analysis, these factors were not adjusted for in the quantitative analysis due to their unavailability within the survey. We were also unable to account for other important factors, such as spousal age differences and the extent of early marriage within the women’s families, due to a lack of data, despite their relevance to the occurrence of early marriage. Furthermore, the women’s age of marriage was self-reported, introducing the potential for recall bias. Nevertheless, any such bias is expected to be random in nature and should not significantly skew the reported results in any particular direction. Conducting qualitative study was another strength of this study, where representation of women (in IDIs and FGDs) and men (in the KIIs) allowed us to capture diverse perspectives on this complex issue. We conducted the qualitative study in a purposively selected district and utilized data to explain and interpret findings from the nationally representative quantitative data. However, this comparison may introduce errors due to different social norms and cultural issues regarding early marriage in various parts of the country. Moreover, the perception of early marriage among this group of women might differ slightly from that of women in other regions and rural areas due to factors such as their relocation, economic stability, community engagement, and relatively higher decision-making autonomy. This indicates a need for qualitative interviews to be conducted in different regions of the country. However, we were unable to do so due to a lack of funding. It is worth noting that although participants included in our qualitative survey were from only one district, a significant portion of them reported their origins as being from different parts of the country, including rural areas, rather than their present location. They had moved to this district for employment, given that ready-made garment and small-scale industries are predominantly located in this area. Moreover, we conducted qualitative interviews in 2023–2024, while the quantitative data we analysed was collected in 2017–2018. Comparing data from different time points may introduce some distortion in the reported associations and conclusions. However, we could not address this issue further as the quantitative survey data we analysed is the most recent available in Bangladesh.

Our findings revealed that approximately 55% of women who married at an early age believed that their marriage took place at the right time. Among early-married women, those who were employed at the time of their marriage were more likely to perceive their marriage as timely, whereas those who were pursuing studies at the time of their marriage were more inclined to view their marriage as occurring too early and should have been delayed. Multiple factors emerged as influential in shaping the perception of earlier-aged married women regarding the timing of their marriage, including the desire to escape poverty, concerns related to safety and security, and the influence of intimate relationships and societal norms. These findings highlight that a significant proportion of early-married women believe their marriage occurred at the right time, indicating a gap in policies and programs designed to raise awareness about the risks of early marriage and early childbearing. It is crucial for policies and programs to prioritize comprehensive education for all girls and those around them, including parents, to ensure they are informed about the appropriate age for marriage and the potential consequences of early marriage. Additionally, those involved in decision-making and upholding social norms around early marriage should receive extensive counselling on its adverse effects. This focus should particularly target working girls, who may be more vulnerable to early marriage.

Data availability

“The data that support the findings of this study are available from The DHS Program, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are, however, available from the corresponding author upon reasonable request and with permission of The DHS Program. To proceed, researchers are required to submit a research proposal via the website (https://dhsprogram.com/data/available-datasets.cfm). Subsequently, the designated individual will review the proposal and approve access for data download. We are unable to share the qualitative interview data due to restrictions imposed by the ethical review committee”.

Abbreviations

Low- and middle-income countries

Demographic Health Survey

Bangladesh Demographic Health Survey

adjusted odds ratio

Confidence interval

Sustainable development goal

National Institute of Population Research and Training

Primary sampling unit

Subramanee, S. D. et al. Child marriage in South Asia: a systematic review. Int. J. Environ. Res. Public Health 19 (22), 15138 (2022).

PubMed   PubMed Central   Google Scholar  

UNICEF. UN General Assembly Resolutions on Child Marriage . https://www.unicef.org/protection/child-marriage (2022).

National Institute of Population Research and Training (NIPORT). Bangladesh Demographic and Health Survey 2017–2018 (2020).

Bangladesh Bureau of Statistics (BBS) & UNICEF Bangladesh Progotir Pathey, Bangladesh Multiple Indicator Cluster Survey 2019, Survey Findings Report (2019).

Marphatia, A. A., Ambale, G. S. & Reid, A. M. Women’s marriage age matters for public health: a review of the broader health and social implications in South Asia. Front. Public Health 5 , 269 (2017).

UNICEF. Ending Child Marriage: A Profile of Progress in Ethiopia (UNICEF, 2018).

Scolaro, E. et al. Child marriage legislation in the Asia-Pacific region. Rev. Faith Int. Affairs 13 (3), 23–31 (2015).

Google Scholar  

Sekine, K. & Hodgkin, M. E. Effect of child marriage on girls’ school dropout in Nepal: analysis of data from the multiple Indicator Cluster Survey 2014. PLoS ONE 12 (7), e0180176 (2017).

Islam, M. M. Child marriage, marital disruption, and marriage thereafter: evidence from a national survey. BMC Women’s Health 485 , 22485 (2022).

Naved, R. T. et al. Impact of Tipping Point Initiative, a Social Norms Intervention, in Addressing Child Marriage and Other Adolescent Health and Behavioral Outcomes in a Northern District of Bangladesh (2022).

Dadras, O., Khampaya, T. & Nakayama, T. Child marriage, reproductive outcomes, and service utilization among young Afghan women: findings from a nationally Representative Survey in Afghanistan. Stud. Fam. Plann. 53 (3), 417–431 (2022).

PubMed   Google Scholar  

Fan, S. & Koski, A. The health consequences of child marriage: a systematic review of the evidence. BMC Public Health 22 (1), 1–17 (2022).

Hossain, M. M. et al. Child marriage and its association with morbidity and mortality of under-5 years old children in Bangladesh. PLoS ONE 17 (2), e0262927 (2022).

CAS   PubMed   PubMed Central   Google Scholar  

Khanam, S. J. & Khan, M. N. Effects of parental migration on early childhood development of left-behind children in Bangladesh: evidence from a nationally representative survey. PLoS ONE 18 (11), e0287828 (2023).

Julitta Onabanjo, M. M. M. F. Urgent Action Needed to Meet SDG to End Child Marriage by 2030 (UNICEF, 2022).

Kamal, S. M. et al. Child marriage in Bangladesh: trends and determinants. J. Biosoc. Sci. 47 (1), 120–139 (2015).

MathSciNet   PubMed   Google Scholar  

MacQuarrie, K., Juan, C. & Fish, T. D. Trends, Inequalities, and Contextual Determinants of Child Marriage in Asia (ICF, 2019).

Billah, M. A. et al. Spatial Pattern and Influential Factors for Early Marriage: Evidence from Bangladesh Demographic Health Survey Data 2017–2018 (2023).

Modak, P. Determinants of girl-child marriage in high prevalence states in India. J. Int. Women’s Stud. 20 (7), 374–394 (2019).

Boertien, D. & Härkönen, J. Why does women’s education stabilize marriages? The role of marital attraction and barriers to divorce. Demogr. Res. 38 , 1241–1276 (2018).

Mourtada, R., Schlecht, J. & DeJong, J. A qualitative study exploring child marriage practices among Syrian conflict-affected populations in Lebanon. Confl. Health 11 (1), 53–65 (2017).

Biswas, R. K., Khan, J. R. & Kabir, E. Trend of child marriage in Bangladesh: a reflection on significant socioeconomic factors. Child Youth Serv. Rev. 104 , 104382 (2019).

Saleh, A. M. et al. Exploring Iraqi people’s perception about early marriage: a qualitative study. BMC Women’s Health 22 (1), 393 (2022).

UNICEF. Child marriage knowledge, attitudes, and perceptions among affected communities in Albania. UNICEF 1 , 1–101 (2018).

Seta, R. Child marriage and its impact on health: a study of perceptions and attitudes in Nepal. J. Glob. Health Rep. 7 , e2023073 (2023).

Mardi, A. et al. Perceptions of teenage women about marriage in adolescence in an Iranian setting: a qualitative study. Electron. Phys. 10 (2), 6292 (2018).

Maxwell, J. A. Qualitative Research Design: An Interactive Approach (Sage, 2012).

UNICEF. Child Marriage, Aolescent Pregnancy and School Dropout in South Asia . https://www.unicef.org/rosa/reports/child-marriage-adolescent-pregnancy-and-school-dropout-south-asia (2022).

Barros, A. J. & Hirakata, V. N. Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio. BMC Med. Res. Methodol. 3 (1), 1–13 (2003).

Swazan, I. S. & Das, D. Bangladesh’s emergence as a ready-made garment export leader: an examination of the competitive advantages of the garment industry. Int. J. Glob. Bus. Competitive. 17 (2), 162–174 (2022).

Clarke, V. & Braun, V. Thematic analysis. J. Posit. Psychol. 12 (3), 297–298 (2017).

Dhakal, K. NVivo J. Med. Libr. Assoc. 110 (2), 270 (2022).

Ferdous, D. S., Saha, P. & Yeasmin, F. Preventing Child, Early and Forced Marriage in Bangladesh: Understanding Socio-economic Drivers and Legislative Gaps (2019).

Bajracharya, A., Psaki, S. & Sadiq, M. Child Marriage, Adolescent Pregnancy and School Dropout in South Asia (Report by the Population Council for the United Nations Children’s Fund Regional Office for South Asia, 2019).

Jayachandran, S. Social norms as a barrier to women’s employment in developing countries. IMF Econ. Rev. 69 (3), 576–595 (2021).

MathSciNet   Google Scholar  

Shahen, M. A. Gender-based violence in Bangladesh: a critical analysis. Int. J. Qual. Res. 1 (2), 127–139 (2021).

Bhowmik, J., Biswas, R. K. & Hossain, S. Child marriage and adolescent motherhood: a nationwide vulnerability for women in Bangladesh. Int. J. Environ. Res. Public Health 18 (8), 4030 (2021).

Daily & Star From Early Marriage to Risky Pregnancy: We Must Break the Cycle (Dhaka, 2022).

Nagata, H. Female workers’ skills, wages, and householding in Bangladesh’s readymade garment industry: the case of a Japanese multinational company. J. Interdiscp. Econ. 32 (1), 47–74 (2020).

Ahinkorah, B. O. et al. Girl child marriage and its association with maternal healthcare services utilization in sub-saharan Africa. BMC Health Serv. Res. 22 (1), 777 (2022).

Abera, M. et al. Early marriage and women’s empowerment: the case of child-brides in Amhara National Regional State, Ethiopia. BMC Int. Health Hum. Rights 20 (1), 1–16 (2020).

Li, C., Cheng, W. & Shi, H. Early Marriage and Maternal Health care Utilisation: Evidence from sub-Saharan Africa 101054 (Economics & Human Biology, 2021).

Sekhri, S. & Debnath, S. Intergenerational consequences of early age marriages of girls: Effect on children’s human capital. J. Dev. Stud. 50 (12), 1670–1686 (2014).

Otoo-Oyortey, N. & Pobi, S. Early marriage and poverty: exploring links and key policy issues. Gend. Dev. 11 (2), 42–51 (2003).

Download references

Acknowledgements

We are thankful to MEASURE DHS for the data support and also grateful to icddr, b where the data for this study was analysed. We are also acknowledged the Governments of Bangladesh, Canada, Sweden and the UK for providing core/unrestricted support for to run icddr, b. The authors also acknowledge the support of Health System and Population Studies Division of icddr, b and Department of Population Science of Jatiya Kabi Kazi Nazrul Islam University, where this study was designed and conducted.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and affiliations.

Department of Population Science, Jatiya Kabi Kazi Nazrul Islam University, Namapara, Mymensingh, 2220, Bangladesh

Md. Nuruzzaman Khan & Shimlin Jahan Khanam

Nossal Institute for Global Health, Melbourne School of Population and Global health, The University of Melbourne, Melbourne, 3010, Australia

Md. Nuruzzaman Khan

Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), 68 Shaheed Tajuddin Ahmed Sarani, Mohakhali, Dhaka, 1212, Bangladesh

Md. Mostaured Ali Khan

Health System and Population Studies Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), 68 Shaheed Tajuddin Ahmed Sarani, Mohakhali, Dhaka, 1212, Bangladesh

Md Arif Billah

La Trobe Rural Health School, John Richards Centre for Rural Ageing Research, La Trobe University, Melbourne, VIC, 3689, Australia

Shahinoor Akter

You can also search for this author in PubMed   Google Scholar

Contributions

“Khan MN designed the study. Khan MN, Khanam SJ and Khan MMA collected qualitative data. Khan MN and Billah MA analysed quantitative data while all authors analysed qualitative data. Khan MN, Khan MMA, Billah MA and Khanam SJ wrote the first draft of this manuscript. Akter S critically reviewed and edited the previous versions of this manuscript. All authors approved this final version of the manuscript”.

Corresponding author

Correspondence to Md. Nuruzzaman Khan .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Ethical approval

The quantitative data analysed in this study was extracted from the survey which was approved by the institutional review board of ICF macro (Inner City Fund) and the National Research Ethics Committee of the Bangladesh Medical Research Council. Informed consent was obtained from all participants. All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. No separate ethical approval was required to conduct this study. We obtained permission to access this survey and conduct this research. All methods were performed in accordance with the relevant guidelines and regulations. Ethical approval for conducting the qualitative survey was obtained from the Institutional Review Board of the University of Rajshahi (123/430/IAMEBBC/IBSc), ensuring compliance with ethical guidelines and protocols. Informed consent was obtained from all participants who were 18 years of age or older. For participants who were under 18 years of age, their legal guardian, such as their husband or father, provided informed consent on their behalf. This process ensured that all participants had a clear understanding of the survey’s purpose, procedures, and potential risks, and voluntarily agreed to participate. So that this applies to illiterate respondents as well.

Additional information

Publisher’s note.

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

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ .

Reprints and permissions

About this article

Cite this article.

Khan, M.N., Khanam, S.J., Khan, M.M.A. et al. Exploring the impact of perceived early marriage on women’s education and employment in Bangladesh through a mixed-methods study. Sci Rep 14 , 21683 (2024). https://doi.org/10.1038/s41598-024-73137-w

Download citation

Received : 15 February 2024

Accepted : 13 September 2024

Published : 17 September 2024

DOI : https://doi.org/10.1038/s41598-024-73137-w

Share this article

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

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

Provided by the Springer Nature SharedIt content-sharing initiative

• Child marriage
• Working status
• Educational status

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

The PMC website is updating on October 15, 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Can J Hosp Pharm
• v.68(3); May-Jun 2015

Qualitative Research: Data Collection, Analysis, and Management

Introduction.

In an earlier paper, 1 we presented an introduction to using qualitative research methods in pharmacy practice. In this article, we review some principles of the collection, analysis, and management of qualitative data to help pharmacists interested in doing research in their practice to continue their learning in this area. Qualitative research can help researchers to access the thoughts and feelings of research participants, which can enable development of an understanding of the meaning that people ascribe to their experiences. Whereas quantitative research methods can be used to determine how many people undertake particular behaviours, qualitative methods can help researchers to understand how and why such behaviours take place. Within the context of pharmacy practice research, qualitative approaches have been used to examine a diverse array of topics, including the perceptions of key stakeholders regarding prescribing by pharmacists and the postgraduation employment experiences of young pharmacists (see “Further Reading” section at the end of this article).

In the previous paper, 1 we outlined 3 commonly used methodologies: ethnography 2 , grounded theory 3 , and phenomenology. 4 Briefly, ethnography involves researchers using direct observation to study participants in their “real life” environment, sometimes over extended periods. Grounded theory and its later modified versions (e.g., Strauss and Corbin 5 ) use face-to-face interviews and interactions such as focus groups to explore a particular research phenomenon and may help in clarifying a less-well-understood problem, situation, or context. Phenomenology shares some features with grounded theory (such as an exploration of participants’ behaviour) and uses similar techniques to collect data, but it focuses on understanding how human beings experience their world. It gives researchers the opportunity to put themselves in another person’s shoes and to understand the subjective experiences of participants. 6 Some researchers use qualitative methodologies but adopt a different standpoint, and an example of this appears in the work of Thurston and others, 7 discussed later in this paper.

Qualitative work requires reflection on the part of researchers, both before and during the research process, as a way of providing context and understanding for readers. When being reflexive, researchers should not try to simply ignore or avoid their own biases (as this would likely be impossible); instead, reflexivity requires researchers to reflect upon and clearly articulate their position and subjectivities (world view, perspectives, biases), so that readers can better understand the filters through which questions were asked, data were gathered and analyzed, and findings were reported. From this perspective, bias and subjectivity are not inherently negative but they are unavoidable; as a result, it is best that they be articulated up-front in a manner that is clear and coherent for readers.

THE PARTICIPANT’S VIEWPOINT

What qualitative study seeks to convey is why people have thoughts and feelings that might affect the way they behave. Such study may occur in any number of contexts, but here, we focus on pharmacy practice and the way people behave with regard to medicines use (e.g., to understand patients’ reasons for nonadherence with medication therapy or to explore physicians’ resistance to pharmacists’ clinical suggestions). As we suggested in our earlier article, 1 an important point about qualitative research is that there is no attempt to generalize the findings to a wider population. Qualitative research is used to gain insights into people’s feelings and thoughts, which may provide the basis for a future stand-alone qualitative study or may help researchers to map out survey instruments for use in a quantitative study. It is also possible to use different types of research in the same study, an approach known as “mixed methods” research, and further reading on this topic may be found at the end of this paper.

The role of the researcher in qualitative research is to attempt to access the thoughts and feelings of study participants. This is not an easy task, as it involves asking people to talk about things that may be very personal to them. Sometimes the experiences being explored are fresh in the participant’s mind, whereas on other occasions reliving past experiences may be difficult. However the data are being collected, a primary responsibility of the researcher is to safeguard participants and their data. Mechanisms for such safeguarding must be clearly articulated to participants and must be approved by a relevant research ethics review board before the research begins. Researchers and practitioners new to qualitative research should seek advice from an experienced qualitative researcher before embarking on their project.

DATA COLLECTION

Whatever philosophical standpoint the researcher is taking and whatever the data collection method (e.g., focus group, one-to-one interviews), the process will involve the generation of large amounts of data. In addition to the variety of study methodologies available, there are also different ways of making a record of what is said and done during an interview or focus group, such as taking handwritten notes or video-recording. If the researcher is audio- or video-recording data collection, then the recordings must be transcribed verbatim before data analysis can begin. As a rough guide, it can take an experienced researcher/transcriber 8 hours to transcribe one 45-minute audio-recorded interview, a process than will generate 20–30 pages of written dialogue.

Many researchers will also maintain a folder of “field notes” to complement audio-taped interviews. Field notes allow the researcher to maintain and comment upon impressions, environmental contexts, behaviours, and nonverbal cues that may not be adequately captured through the audio-recording; they are typically handwritten in a small notebook at the same time the interview takes place. Field notes can provide important context to the interpretation of audio-taped data and can help remind the researcher of situational factors that may be important during data analysis. Such notes need not be formal, but they should be maintained and secured in a similar manner to audio tapes and transcripts, as they contain sensitive information and are relevant to the research. For more information about collecting qualitative data, please see the “Further Reading” section at the end of this paper.

DATA ANALYSIS AND MANAGEMENT

If, as suggested earlier, doing qualitative research is about putting oneself in another person’s shoes and seeing the world from that person’s perspective, the most important part of data analysis and management is to be true to the participants. It is their voices that the researcher is trying to hear, so that they can be interpreted and reported on for others to read and learn from. To illustrate this point, consider the anonymized transcript excerpt presented in Appendix 1 , which is taken from a research interview conducted by one of the authors (J.S.). We refer to this excerpt throughout the remainder of this paper to illustrate how data can be managed, analyzed, and presented.

Interpretation of Data

Interpretation of the data will depend on the theoretical standpoint taken by researchers. For example, the title of the research report by Thurston and others, 7 “Discordant indigenous and provider frames explain challenges in improving access to arthritis care: a qualitative study using constructivist grounded theory,” indicates at least 2 theoretical standpoints. The first is the culture of the indigenous population of Canada and the place of this population in society, and the second is the social constructivist theory used in the constructivist grounded theory method. With regard to the first standpoint, it can be surmised that, to have decided to conduct the research, the researchers must have felt that there was anecdotal evidence of differences in access to arthritis care for patients from indigenous and non-indigenous backgrounds. With regard to the second standpoint, it can be surmised that the researchers used social constructivist theory because it assumes that behaviour is socially constructed; in other words, people do things because of the expectations of those in their personal world or in the wider society in which they live. (Please see the “Further Reading” section for resources providing more information about social constructivist theory and reflexivity.) Thus, these 2 standpoints (and there may have been others relevant to the research of Thurston and others 7 ) will have affected the way in which these researchers interpreted the experiences of the indigenous population participants and those providing their care. Another standpoint is feminist standpoint theory which, among other things, focuses on marginalized groups in society. Such theories are helpful to researchers, as they enable us to think about things from a different perspective. Being aware of the standpoints you are taking in your own research is one of the foundations of qualitative work. Without such awareness, it is easy to slip into interpreting other people’s narratives from your own viewpoint, rather than that of the participants.

To analyze the example in Appendix 1 , we will adopt a phenomenological approach because we want to understand how the participant experienced the illness and we want to try to see the experience from that person’s perspective. It is important for the researcher to reflect upon and articulate his or her starting point for such analysis; for example, in the example, the coder could reflect upon her own experience as a female of a majority ethnocultural group who has lived within middle class and upper middle class settings. This personal history therefore forms the filter through which the data will be examined. This filter does not diminish the quality or significance of the analysis, since every researcher has his or her own filters; however, by explicitly stating and acknowledging what these filters are, the researcher makes it easer for readers to contextualize the work.

Transcribing and Checking

For the purposes of this paper it is assumed that interviews or focus groups have been audio-recorded. As mentioned above, transcribing is an arduous process, even for the most experienced transcribers, but it must be done to convert the spoken word to the written word to facilitate analysis. For anyone new to conducting qualitative research, it is beneficial to transcribe at least one interview and one focus group. It is only by doing this that researchers realize how difficult the task is, and this realization affects their expectations when asking others to transcribe. If the research project has sufficient funding, then a professional transcriber can be hired to do the work. If this is the case, then it is a good idea to sit down with the transcriber, if possible, and talk through the research and what the participants were talking about. This background knowledge for the transcriber is especially important in research in which people are using jargon or medical terms (as in pharmacy practice). Involving your transcriber in this way makes the work both easier and more rewarding, as he or she will feel part of the team. Transcription editing software is also available, but it is expensive. For example, ELAN (more formally known as EUDICO Linguistic Annotator, developed at the Technical University of Berlin) 8 is a tool that can help keep data organized by linking media and data files (particularly valuable if, for example, video-taping of interviews is complemented by transcriptions). It can also be helpful in searching complex data sets. Products such as ELAN do not actually automatically transcribe interviews or complete analyses, and they do require some time and effort to learn; nonetheless, for some research applications, it may be a valuable to consider such software tools.

All audio recordings should be transcribed verbatim, regardless of how intelligible the transcript may be when it is read back. Lines of text should be numbered. Once the transcription is complete, the researcher should read it while listening to the recording and do the following: correct any spelling or other errors; anonymize the transcript so that the participant cannot be identified from anything that is said (e.g., names, places, significant events); insert notations for pauses, laughter, looks of discomfort; insert any punctuation, such as commas and full stops (periods) (see Appendix 1 for examples of inserted punctuation), and include any other contextual information that might have affected the participant (e.g., temperature or comfort of the room).

Dealing with the transcription of a focus group is slightly more difficult, as multiple voices are involved. One way of transcribing such data is to “tag” each voice (e.g., Voice A, Voice B). In addition, the focus group will usually have 2 facilitators, whose respective roles will help in making sense of the data. While one facilitator guides participants through the topic, the other can make notes about context and group dynamics. More information about group dynamics and focus groups can be found in resources listed in the “Further Reading” section.

Reading between the Lines

During the process outlined above, the researcher can begin to get a feel for the participant’s experience of the phenomenon in question and can start to think about things that could be pursued in subsequent interviews or focus groups (if appropriate). In this way, one participant’s narrative informs the next, and the researcher can continue to interview until nothing new is being heard or, as it says in the text books, “saturation is reached”. While continuing with the processes of coding and theming (described in the next 2 sections), it is important to consider not just what the person is saying but also what they are not saying. For example, is a lengthy pause an indication that the participant is finding the subject difficult, or is the person simply deciding what to say? The aim of the whole process from data collection to presentation is to tell the participants’ stories using exemplars from their own narratives, thus grounding the research findings in the participants’ lived experiences.

Smith 9 suggested a qualitative research method known as interpretative phenomenological analysis, which has 2 basic tenets: first, that it is rooted in phenomenology, attempting to understand the meaning that individuals ascribe to their lived experiences, and second, that the researcher must attempt to interpret this meaning in the context of the research. That the researcher has some knowledge and expertise in the subject of the research means that he or she can have considerable scope in interpreting the participant’s experiences. Larkin and others 10 discussed the importance of not just providing a description of what participants say. Rather, interpretative phenomenological analysis is about getting underneath what a person is saying to try to truly understand the world from his or her perspective.

Once all of the research interviews have been transcribed and checked, it is time to begin coding. Field notes compiled during an interview can be a useful complementary source of information to facilitate this process, as the gap in time between an interview, transcribing, and coding can result in memory bias regarding nonverbal or environmental context issues that may affect interpretation of data.

Coding refers to the identification of topics, issues, similarities, and differences that are revealed through the participants’ narratives and interpreted by the researcher. This process enables the researcher to begin to understand the world from each participant’s perspective. Coding can be done by hand on a hard copy of the transcript, by making notes in the margin or by highlighting and naming sections of text. More commonly, researchers use qualitative research software (e.g., NVivo, QSR International Pty Ltd; www.qsrinternational.com/products_nvivo.aspx ) to help manage their transcriptions. It is advised that researchers undertake a formal course in the use of such software or seek supervision from a researcher experienced in these tools.

Returning to Appendix 1 and reading from lines 8–11, a code for this section might be “diagnosis of mental health condition”, but this would just be a description of what the participant is talking about at that point. If we read a little more deeply, we can ask ourselves how the participant might have come to feel that the doctor assumed he or she was aware of the diagnosis or indeed that they had only just been told the diagnosis. There are a number of pauses in the narrative that might suggest the participant is finding it difficult to recall that experience. Later in the text, the participant says “nobody asked me any questions about my life” (line 19). This could be coded simply as “health care professionals’ consultation skills”, but that would not reflect how the participant must have felt never to be asked anything about his or her personal life, about the participant as a human being. At the end of this excerpt, the participant just trails off, recalling that no-one showed any interest, which makes for very moving reading. For practitioners in pharmacy, it might also be pertinent to explore the participant’s experience of akathisia and why this was left untreated for 20 years.

One of the questions that arises about qualitative research relates to the reliability of the interpretation and representation of the participants’ narratives. There are no statistical tests that can be used to check reliability and validity as there are in quantitative research. However, work by Lincoln and Guba 11 suggests that there are other ways to “establish confidence in the ‘truth’ of the findings” (p. 218). They call this confidence “trustworthiness” and suggest that there are 4 criteria of trustworthiness: credibility (confidence in the “truth” of the findings), transferability (showing that the findings have applicability in other contexts), dependability (showing that the findings are consistent and could be repeated), and confirmability (the extent to which the findings of a study are shaped by the respondents and not researcher bias, motivation, or interest).

One way of establishing the “credibility” of the coding is to ask another researcher to code the same transcript and then to discuss any similarities and differences in the 2 resulting sets of codes. This simple act can result in revisions to the codes and can help to clarify and confirm the research findings.

Theming refers to the drawing together of codes from one or more transcripts to present the findings of qualitative research in a coherent and meaningful way. For example, there may be examples across participants’ narratives of the way in which they were treated in hospital, such as “not being listened to” or “lack of interest in personal experiences” (see Appendix 1 ). These may be drawn together as a theme running through the narratives that could be named “the patient’s experience of hospital care”. The importance of going through this process is that at its conclusion, it will be possible to present the data from the interviews using quotations from the individual transcripts to illustrate the source of the researchers’ interpretations. Thus, when the findings are organized for presentation, each theme can become the heading of a section in the report or presentation. Underneath each theme will be the codes, examples from the transcripts, and the researcher’s own interpretation of what the themes mean. Implications for real life (e.g., the treatment of people with chronic mental health problems) should also be given.

DATA SYNTHESIS

In this final section of this paper, we describe some ways of drawing together or “synthesizing” research findings to represent, as faithfully as possible, the meaning that participants ascribe to their life experiences. This synthesis is the aim of the final stage of qualitative research. For most readers, the synthesis of data presented by the researcher is of crucial significance—this is usually where “the story” of the participants can be distilled, summarized, and told in a manner that is both respectful to those participants and meaningful to readers. There are a number of ways in which researchers can synthesize and present their findings, but any conclusions drawn by the researchers must be supported by direct quotations from the participants. In this way, it is made clear to the reader that the themes under discussion have emerged from the participants’ interviews and not the mind of the researcher. The work of Latif and others 12 gives an example of how qualitative research findings might be presented.

Planning and Writing the Report

As has been suggested above, if researchers code and theme their material appropriately, they will naturally find the headings for sections of their report. Qualitative researchers tend to report “findings” rather than “results”, as the latter term typically implies that the data have come from a quantitative source. The final presentation of the research will usually be in the form of a report or a paper and so should follow accepted academic guidelines. In particular, the article should begin with an introduction, including a literature review and rationale for the research. There should be a section on the chosen methodology and a brief discussion about why qualitative methodology was most appropriate for the study question and why one particular methodology (e.g., interpretative phenomenological analysis rather than grounded theory) was selected to guide the research. The method itself should then be described, including ethics approval, choice of participants, mode of recruitment, and method of data collection (e.g., semistructured interviews or focus groups), followed by the research findings, which will be the main body of the report or paper. The findings should be written as if a story is being told; as such, it is not necessary to have a lengthy discussion section at the end. This is because much of the discussion will take place around the participants’ quotes, such that all that is needed to close the report or paper is a summary, limitations of the research, and the implications that the research has for practice. As stated earlier, it is not the intention of qualitative research to allow the findings to be generalized, and therefore this is not, in itself, a limitation.

Planning out the way that findings are to be presented is helpful. It is useful to insert the headings of the sections (the themes) and then make a note of the codes that exemplify the thoughts and feelings of your participants. It is generally advisable to put in the quotations that you want to use for each theme, using each quotation only once. After all this is done, the telling of the story can begin as you give your voice to the experiences of the participants, writing around their quotations. Do not be afraid to draw assumptions from the participants’ narratives, as this is necessary to give an in-depth account of the phenomena in question. Discuss these assumptions, drawing on your participants’ words to support you as you move from one code to another and from one theme to the next. Finally, as appropriate, it is possible to include examples from literature or policy documents that add support for your findings. As an exercise, you may wish to code and theme the sample excerpt in Appendix 1 and tell the participant’s story in your own way. Further reading about “doing” qualitative research can be found at the end of this paper.

CONCLUSIONS

Qualitative research can help researchers to access the thoughts and feelings of research participants, which can enable development of an understanding of the meaning that people ascribe to their experiences. It can be used in pharmacy practice research to explore how patients feel about their health and their treatment. Qualitative research has been used by pharmacists to explore a variety of questions and problems (see the “Further Reading” section for examples). An understanding of these issues can help pharmacists and other health care professionals to tailor health care to match the individual needs of patients and to develop a concordant relationship. Doing qualitative research is not easy and may require a complete rethink of how research is conducted, particularly for researchers who are more familiar with quantitative approaches. There are many ways of conducting qualitative research, and this paper has covered some of the practical issues regarding data collection, analysis, and management. Further reading around the subject will be essential to truly understand this method of accessing peoples’ thoughts and feelings to enable researchers to tell participants’ stories.

Appendix 1. Excerpt from a sample transcript

The participant (age late 50s) had suffered from a chronic mental health illness for 30 years. The participant had become a “revolving door patient,” someone who is frequently in and out of hospital. As the participant talked about past experiences, the researcher asked:

• What was treatment like 30 years ago?
• Umm—well it was pretty much they could do what they wanted with you because I was put into the er, the er kind of system er, I was just on
• endless section threes.
• Really…
• But what I didn’t realize until later was that if you haven’t actually posed a threat to someone or yourself they can’t really do that but I didn’t know
• that. So wh-when I first went into hospital they put me on the forensic ward ’cause they said, “We don’t think you’ll stay here we think you’ll just
• run-run away.” So they put me then onto the acute admissions ward and – er – I can remember one of the first things I recall when I got onto that
• ward was sitting down with a er a Dr XXX. He had a book this thick [gestures] and on each page it was like three questions and he went through
• all these questions and I answered all these questions. So we’re there for I don’t maybe two hours doing all that and he asked me he said “well
• when did somebody tell you then that you have schizophrenia” I said “well nobody’s told me that” so he seemed very surprised but nobody had
• actually [pause] whe-when I first went up there under police escort erm the senior kind of consultants people I’d been to where I was staying and
• ermm so er [pause] I . . . the, I can remember the very first night that I was there and given this injection in this muscle here [gestures] and just
• having dreadful side effects the next day I woke up [pause]
• . . . and I suffered that akathesia I swear to you, every minute of every day for about 20 years.
• Oh how awful.
• And that side of it just makes life impossible so the care on the wards [pause] umm I don’t know it’s kind of, it’s kind of hard to put into words
• [pause]. Because I’m not saying they were sort of like not friendly or interested but then nobody ever seemed to want to talk about your life [pause]
• nobody asked me any questions about my life. The only questions that came into was they asked me if I’d be a volunteer for these student exams
• and things and I said “yeah” so all the questions were like “oh what jobs have you done,” er about your relationships and things and er but
• nobody actually sat down and had a talk and showed some interest in you as a person you were just there basically [pause] um labelled and you
• know there was there was [pause] but umm [pause] yeah . . .

This article is the 10th in the CJHP Research Primer Series, an initiative of the CJHP Editorial Board and the CSHP Research Committee. The planned 2-year series is intended to appeal to relatively inexperienced researchers, with the goal of building research capacity among practising pharmacists. The articles, presenting simple but rigorous guidance to encourage and support novice researchers, are being solicited from authors with appropriate expertise.

Previous articles in this series:

Bond CM. The research jigsaw: how to get started. Can J Hosp Pharm . 2014;67(1):28–30.

Tully MP. Research: articulating questions, generating hypotheses, and choosing study designs. Can J Hosp Pharm . 2014;67(1):31–4.

Loewen P. Ethical issues in pharmacy practice research: an introductory guide. Can J Hosp Pharm. 2014;67(2):133–7.

Tsuyuki RT. Designing pharmacy practice research trials. Can J Hosp Pharm . 2014;67(3):226–9.

Bresee LC. An introduction to developing surveys for pharmacy practice research. Can J Hosp Pharm . 2014;67(4):286–91.

Gamble JM. An introduction to the fundamentals of cohort and case–control studies. Can J Hosp Pharm . 2014;67(5):366–72.

Austin Z, Sutton J. Qualitative research: getting started. C an J Hosp Pharm . 2014;67(6):436–40.

Houle S. An introduction to the fundamentals of randomized controlled trials in pharmacy research. Can J Hosp Pharm . 2014; 68(1):28–32.

Charrois TL. Systematic reviews: What do you need to know to get started? Can J Hosp Pharm . 2014;68(2):144–8.

Competing interests: None declared.

Further Reading

Examples of qualitative research in pharmacy practice.

• Farrell B, Pottie K, Woodend K, Yao V, Dolovich L, Kennie N, et al. Shifts in expectations: evaluating physicians’ perceptions as pharmacists integrated into family practice. J Interprof Care. 2010; 24 (1):80–9. [ PubMed ] [ Google Scholar ]
• Gregory P, Austin Z. Postgraduation employment experiences of new pharmacists in Ontario in 2012–2013. Can Pharm J. 2014; 147 (5):290–9. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Marks PZ, Jennnings B, Farrell B, Kennie-Kaulbach N, Jorgenson D, Pearson-Sharpe J, et al. “I gained a skill and a change in attitude”: a case study describing how an online continuing professional education course for pharmacists supported achievement of its transfer to practice outcomes. Can J Univ Contin Educ. 2014; 40 (2):1–18. [ Google Scholar ]
• Nair KM, Dolovich L, Brazil K, Raina P. It’s all about relationships: a qualitative study of health researchers’ perspectives on interdisciplinary research. BMC Health Serv Res. 2008; 8 :110. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Pojskic N, MacKeigan L, Boon H, Austin Z. Initial perceptions of key stakeholders in Ontario regarding independent prescriptive authority for pharmacists. Res Soc Adm Pharm. 2014; 10 (2):341–54. [ PubMed ] [ Google Scholar ]

Qualitative Research in General

• Breakwell GM, Hammond S, Fife-Schaw C. Research methods in psychology. Thousand Oaks (CA): Sage Publications; 1995. [ Google Scholar ]
• Given LM. 100 questions (and answers) about qualitative research. Thousand Oaks (CA): Sage Publications; 2015. [ Google Scholar ]
• Miles B, Huberman AM. Qualitative data analysis. Thousand Oaks (CA): Sage Publications; 2009. [ Google Scholar ]
• Patton M. Qualitative research and evaluation methods. Thousand Oaks (CA): Sage Publications; 2002. [ Google Scholar ]
• Willig C. Introducing qualitative research in psychology. Buckingham (UK): Open University Press; 2001. [ Google Scholar ]

Group Dynamics in Focus Groups

• Farnsworth J, Boon B. Analysing group dynamics within the focus group. Qual Res. 2010; 10 (5):605–24. [ Google Scholar ]

Social Constructivism

• Social constructivism. Berkeley (CA): University of California, Berkeley, Berkeley Graduate Division, Graduate Student Instruction Teaching & Resource Center; [cited 2015 June 4]. Available from: http://gsi.berkeley.edu/gsi-guide-contents/learning-theory-research/social-constructivism/ [ Google Scholar ]

Mixed Methods

• Creswell J. Research design: qualitative, quantitative, and mixed methods approaches. Thousand Oaks (CA): Sage Publications; 2009. [ Google Scholar ]

Collecting Qualitative Data

• Arksey H, Knight P. Interviewing for social scientists: an introductory resource with examples. Thousand Oaks (CA): Sage Publications; 1999. [ Google Scholar ]
• Guest G, Namey EE, Mitchel ML. Collecting qualitative data: a field manual for applied research. Thousand Oaks (CA): Sage Publications; 2013. [ Google Scholar ]

Constructivist Grounded Theory

• Charmaz K. Grounded theory: objectivist and constructivist methods. In: Denzin N, Lincoln Y, editors. Handbook of qualitative research. 2nd ed. Thousand Oaks (CA): Sage Publications; 2000. pp. 509–35. [ Google Scholar ]

How to protect marketing research from fraud in the age of AI

As AI technology advances, so do the methods of those who seek to exploit it, making fraud an ever-growing concern for marketing researchers. Discover six strategies to protect your research from AI fraud.

AI in marketing research: Key strategies for success

Editor’s note: Arjun S is co-founder of qualitative research startup Metaforms AI, San Francisco.

Generative AI has brought significant changes to market research, providing powerful tools that make processes smoother and improve data analysis. However, with these advancements come new risks, particularly the threat of fraud. As we dive deeper into this AI-driven world, it’s crucial to not only take advantage of AI's benefits but also to protect the integrity of our research efforts from these growing risks. This article offers practical strategies to help you protect your research from AI-related fraud.

The rapid adoption of AI in market research has transformed the way we conduct studies and analyze data. From creating more advanced surveys to quickly processing large amounts of data, AI has made it possible to gain insights faster and more accurately. However, as these technologies progress, so do the tactics of those looking to misuse them, making fraud an increasingly important issue.

The fraud dilemma: How AI is misused in research

With the growing reliance on AI, fraudsters are finding novel ways to exploit the system. The anonymity and automation provided by AI tools make it easier for malicious actors to introduce fake data into research projects. This problem is particularly evident in survey responses and online forums, where AI can generate convincing but entirely fabricated answers.

In some cases, AI-generated content is used to respond to open-ended questions in a manner that seems authentic on the surface but lacks genuine participant insight. This not only distorts data but also complicates efforts to detect and eliminate fraudulent responses, posing a serious threat to the validity of research findings.

Six strategies to protect your research from AI fraud

To mitigate the risk of AI-driven fraud in your market research, it’s essential to implement robust strategies. Here are six approaches:

1. Deploy multilayered identity verification.

To safeguard the authenticity of your research participants, implement a multilayered verification process that goes beyond simple checks. Combine digital identity verification tools with human oversight, such as cross-referencing with social media profiles or conducting brief video interviews. This approach not only confirms the identity of participants but also deters bots and fraudulent respondents who rely on anonymity.

2. Incorporate behavioral analytics.

Fraudulent behavior often leaves subtle traces in participant interactions. By leveraging behavioral analytics, you can monitor patterns such as inconsistent response times, unusual answer choices or erratic navigation through the survey. These analytics can flag suspicious activity for further review, allowing you to filter out potentially fraudulent data before it skews your results.

3. Use AI to combat AI fraud.

Turn AI's capabilities against fraud by implementing adaptive questioning. This technique involves dynamically altering questions based on previous responses, making it difficult for AI-generated content to produce coherent answers. For example, follow-up questions that reference earlier responses can reveal inconsistencies that are typical of non-human respondents. This method adds an additional layer of complexity that AI-driven fraudsters find challenging to navigate.

4. Enhance the transparency of your research process.

Transparency can be a powerful deterrent against fraud. Clearly communicate to participants that your research includes sophisticated fraud detection methods and outline the steps you take to ensure data integrity. When respondents know their answers will be scrutinized, they are less likely to attempt fraudulent behavior. Additionally, sharing these practices with stakeholders can increase their confidence in the reliability of your findings.

5. Incorporate live interaction elements.

Adding live interaction components to your research – such as real-time video responses, live chat interviews or interactive polling – makes it harder for AI-generated bots to participate. These live elements require participants to engage in ways that AI cannot easily replicate, such as reacting to unexpected questions or demonstrating physical tasks. This strategy not only weeds out fraudulent respondents but also enriches the quality of the data collected.

6. Implement continuous data auditing.

Rather than relying solely on post-study audits, implement continuous data auditing throughout the research process. This involves regularly reviewing incoming data for anomalies, such as repetitive patterns or responses that mirror known AI-generated content. By conducting these audits in real-time, you can identify and address issues as they arise, ensuring that your final data set is as clean and accurate as possible.

Tackling AI Fraud in qualitative research

In an article for Quirk’s , my colleague Siddish Reddy highlighted the challenges posed by AI in qualitative research. He points out that AI-generated responses, while often polished and convincing, can be too good to be true, signaling potential fraud. Reddy emphasizes the need for researchers to use AI judiciously, ensuring that it enhances rather than undermines the research process. By combining AI with rigorous verification methods, researchers can maintain the quality and trustworthiness of their insights, even in an era where AI is increasingly used to automate responses.

As AI continues to revolutionize market research, safeguarding against fraud requires a strategic, multifaceted approach. By incorporating these six strategies into your research design, you can ensure that your findings remain credible and actionable in an increasingly AI-driven world.

Navigating AI, Innovation and Human-Centric Insights Related Categories: Consumers, Research Industry, Artificial Intelligence / AI Consumers, Research Industry, Artificial Intelligence / AI, Consumer Research, Innovation, Social Media Research

Harnessing AI: Marketing researchers are the new power players in business Related Categories: Consumers, Research Industry, Data Analysis, Data Quality, Artificial Intelligence / AI Consumers, Research Industry, Data Analysis, Data Quality, Artificial Intelligence / AI, Consumer Research, High-Tech, Information Technology (IT), Marketing Research-General

How does a country’s cultural profile influence consumer responses to new products? Related Categories: Consumers, Research Industry, Data Analysis Consumers, Research Industry, Data Analysis, Advertising Research, Concept Research, Consumer Research, Cultural Insights, Innovation, Market/Category Evaluations, Product Positioning Studies

Enhancing the virtual backroom experience Related Categories: Research Industry, Qualitative Research, Qualitative-Online Research Industry, Qualitative Research, Qualitative-Online, Focus Group-Videoconference, Marketing Research-General, One-on-One (Depth) Interviews, Online Research