qualitative research uses structured processes

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The word qualitative implies an emphasis on the qualities of entities and on processes and meanings that are not experimentally examined or measured [if measured at all] in terms of quantity, amount, intensity, or frequency. Qualitative researchers stress the socially constructed nature of reality, the intimate relationship between the researcher and what is studied, and the situational constraints that shape inquiry. Such researchers emphasize the value-laden nature of inquiry. They seek answers to questions that stress how social experience is created and given meaning. In contrast, quantitative studies emphasize the measurement and analysis of causal relationships between variables, not processes. Qualitative forms of inquiry are considered by many social and behavioral scientists to be as much a perspective on how to approach investigating a research problem as it is a method.

Denzin, Norman. K. and Yvonna S. Lincoln. “Introduction: The Discipline and Practice of Qualitative Research.” In The Sage Handbook of Qualitative Research . Norman. K. Denzin and Yvonna S. Lincoln, eds. 3 rd edition. (Thousand Oaks, CA: Sage, 2005), p. 10.

Characteristics of Qualitative Research

Below are the three key elements that define a qualitative research study and the applied forms each take in the investigation of a research problem.

• Naturalistic -- refers to studying real-world situations as they unfold naturally; non-manipulative and non-controlling; the researcher is open to whatever emerges [i.e., there is a lack of predetermined constraints on findings].
• Emergent -- acceptance of adapting inquiry as understanding deepens and/or situations change; the researcher avoids rigid designs that eliminate responding to opportunities to pursue new paths of discovery as they emerge.
• Purposeful -- cases for study [e.g., people, organizations, communities, cultures, events, critical incidences] are selected because they are “information rich” and illuminative. That is, they offer useful manifestations of the phenomenon of interest; sampling is aimed at insight about the phenomenon, not empirical generalization derived from a sample and applied to a population.

The Collection of Data

• Data -- observations yield a detailed, "thick description" [in-depth understanding]; interviews capture direct quotations about people’s personal perspectives and lived experiences; often derived from carefully conducted case studies and review of material culture.
• Personal experience and engagement -- researcher has direct contact with and gets close to the people, situation, and phenomenon under investigation; the researcher’s personal experiences and insights are an important part of the inquiry and critical to understanding the phenomenon.
• Empathic neutrality -- an empathic stance in working with study respondents seeks vicarious understanding without judgment [neutrality] by showing openness, sensitivity, respect, awareness, and responsiveness; in observation, it means being fully present [mindfulness].
• Dynamic systems -- there is attention to process; assumes change is ongoing, whether the focus is on an individual, an organization, a community, or an entire culture, therefore, the researcher is mindful of and attentive to system and situational dynamics.

The Analysis

• Unique case orientation -- assumes that each case is special and unique; the first level of analysis is being true to, respecting, and capturing the details of the individual cases being studied; cross-case analysis follows from and depends upon the quality of individual case studies.
• Inductive analysis -- immersion in the details and specifics of the data to discover important patterns, themes, and inter-relationships; begins by exploring, then confirming findings, guided by analytical principles rather than rules.
• Holistic perspective -- the whole phenomenon under study is understood as a complex system that is more than the sum of its parts; the focus is on complex interdependencies and system dynamics that cannot be reduced in any meaningful way to linear, cause and effect relationships and/or a few discrete variables.
• Context sensitive -- places findings in a social, historical, and temporal context; researcher is careful about [even dubious of] the possibility or meaningfulness of generalizations across time and space; emphasizes careful comparative case study analysis and extrapolating patterns for possible transferability and adaptation in new settings.
• Voice, perspective, and reflexivity -- the qualitative methodologist owns and is reflective about her or his own voice and perspective; a credible voice conveys authenticity and trustworthiness; complete objectivity being impossible and pure subjectivity undermining credibility, the researcher's focus reflects a balance between understanding and depicting the world authentically in all its complexity and of being self-analytical, politically aware, and reflexive in consciousness.

Berg, Bruce Lawrence. Qualitative Research Methods for the Social Sciences . 8th edition. Boston, MA: Allyn and Bacon, 2012; Denzin, Norman. K. and Yvonna S. Lincoln. Handbook of Qualitative Research . 2nd edition. Thousand Oaks, CA: Sage, 2000; Marshall, Catherine and Gretchen B. Rossman. Designing Qualitative Research . 2nd ed. Thousand Oaks, CA: Sage Publications, 1995; Merriam, Sharan B. Qualitative Research: A Guide to Design and Implementation . San Francisco, CA: Jossey-Bass, 2009.

Basic Research Design for Qualitative Studies

Unlike positivist or experimental research that utilizes a linear and one-directional sequence of design steps, there is considerable variation in how a qualitative research study is organized. In general, qualitative researchers attempt to describe and interpret human behavior based primarily on the words of selected individuals [a.k.a., “informants” or “respondents”] and/or through the interpretation of their material culture or occupied space. There is a reflexive process underpinning every stage of a qualitative study to ensure that researcher biases, presuppositions, and interpretations are clearly evident, thus ensuring that the reader is better able to interpret the overall validity of the research. According to Maxwell (2009), there are five, not necessarily ordered or sequential, components in qualitative research designs. How they are presented depends upon the research philosophy and theoretical framework of the study, the methods chosen, and the general assumptions underpinning the study. Goals Describe the central research problem being addressed but avoid describing any anticipated outcomes. Questions to ask yourself are: Why is your study worth doing? What issues do you want to clarify, and what practices and policies do you want it to influence? Why do you want to conduct this study, and why should the reader care about the results? Conceptual Framework Questions to ask yourself are: What do you think is going on with the issues, settings, or people you plan to study? What theories, beliefs, and prior research findings will guide or inform your research, and what literature, preliminary studies, and personal experiences will you draw upon for understanding the people or issues you are studying? Note to not only report the results of other studies in your review of the literature, but note the methods used as well. If appropriate, describe why earlier studies using quantitative methods were inadequate in addressing the research problem. Research Questions Usually there is a research problem that frames your qualitative study and that influences your decision about what methods to use, but qualitative designs generally lack an accompanying hypothesis or set of assumptions because the findings are emergent and unpredictable. In this context, more specific research questions are generally the result of an interactive design process rather than the starting point for that process. Questions to ask yourself are: What do you specifically want to learn or understand by conducting this study? What do you not know about the things you are studying that you want to learn? What questions will your research attempt to answer, and how are these questions related to one another? Methods Structured approaches to applying a method or methods to your study help to ensure that there is comparability of data across sources and researchers and, thus, they can be useful in answering questions that deal with differences between phenomena and the explanation for these differences [variance questions]. An unstructured approach allows the researcher to focus on the particular phenomena studied. This facilitates an understanding of the processes that led to specific outcomes, trading generalizability and comparability for internal validity and contextual and evaluative understanding. Questions to ask yourself are: What will you actually do in conducting this study? What approaches and techniques will you use to collect and analyze your data, and how do these constitute an integrated strategy? Validity In contrast to quantitative studies where the goal is to design, in advance, “controls” such as formal comparisons, sampling strategies, or statistical manipulations to address anticipated and unanticipated threats to validity, qualitative researchers must attempt to rule out most threats to validity after the research has begun by relying on evidence collected during the research process itself in order to effectively argue that any alternative explanations for a phenomenon are implausible. Questions to ask yourself are: How might your results and conclusions be wrong? What are the plausible alternative interpretations and validity threats to these, and how will you deal with these? How can the data that you have, or that you could potentially collect, support or challenge your ideas about what’s going on? Why should we believe your results? Conclusion Although Maxwell does not mention a conclusion as one of the components of a qualitative research design, you should formally conclude your study. Briefly reiterate the goals of your study and the ways in which your research addressed them. Discuss the benefits of your study and how stakeholders can use your results. Also, note the limitations of your study and, if appropriate, place them in the context of areas in need of further research.

Chenail, Ronald J. Introduction to Qualitative Research Design. Nova Southeastern University; Heath, A. W. The Proposal in Qualitative Research. The Qualitative Report 3 (March 1997); Marshall, Catherine and Gretchen B. Rossman. Designing Qualitative Research . 3rd edition. Thousand Oaks, CA: Sage, 1999; Maxwell, Joseph A. "Designing a Qualitative Study." In The SAGE Handbook of Applied Social Research Methods . Leonard Bickman and Debra J. Rog, eds. 2nd ed. (Thousand Oaks, CA: Sage, 2009), p. 214-253; Qualitative Research Methods. Writing@CSU. Colorado State University; Yin, Robert K. Qualitative Research from Start to Finish . 2nd edition. New York: Guilford, 2015.

Strengths of Using Qualitative Methods

The advantage of using qualitative methods is that they generate rich, detailed data that leave the participants' perspectives intact and provide multiple contexts for understanding the phenomenon under study. In this way, qualitative research can be used to vividly demonstrate phenomena or to conduct cross-case comparisons and analysis of individuals or groups.

Among the specific strengths of using qualitative methods to study social science research problems is the ability to:

• Obtain a more realistic view of the lived world that cannot be understood or experienced in numerical data and statistical analysis;
• Provide the researcher with the perspective of the participants of the study through immersion in a culture or situation and as a result of direct interaction with them;
• Allow the researcher to describe existing phenomena and current situations;
• Develop flexible ways to perform data collection, subsequent analysis, and interpretation of collected information;
• Yield results that can be helpful in pioneering new ways of understanding;
• Respond to changes that occur while conducting the study ]e.g., extended fieldwork or observation] and offer the flexibility to shift the focus of the research as a result;
• Provide a holistic view of the phenomena under investigation;
• Respond to local situations, conditions, and needs of participants;
• Interact with the research subjects in their own language and on their own terms; and,
• Create a descriptive capability based on primary and unstructured data.

Anderson, Claire. “Presenting and Evaluating Qualitative Research.” American Journal of Pharmaceutical Education 74 (2010): 1-7; Denzin, Norman. K. and Yvonna S. Lincoln. Handbook of Qualitative Research . 2nd edition. Thousand Oaks, CA: Sage, 2000; Merriam, Sharan B. Qualitative Research: A Guide to Design and Implementation . San Francisco, CA: Jossey-Bass, 2009.

Limitations of Using Qualitative Methods

It is very much true that most of the limitations you find in using qualitative research techniques also reflect their inherent strengths . For example, small sample sizes help you investigate research problems in a comprehensive and in-depth manner. However, small sample sizes undermine opportunities to draw useful generalizations from, or to make broad policy recommendations based upon, the findings. Additionally, as the primary instrument of investigation, qualitative researchers are often embedded in the cultures and experiences of others. However, cultural embeddedness increases the opportunity for bias generated from conscious or unconscious assumptions about the study setting to enter into how data is gathered, interpreted, and reported.

Some specific limitations associated with using qualitative methods to study research problems in the social sciences include the following:

• Drifting away from the original objectives of the study in response to the changing nature of the context under which the research is conducted;
• Arriving at different conclusions based on the same information depending on the personal characteristics of the researcher;
• Replication of a study is very difficult;
• Research using human subjects increases the chance of ethical dilemmas that undermine the overall validity of the study;
• An inability to investigate causality between different research phenomena;
• Difficulty in explaining differences in the quality and quantity of information obtained from different respondents and arriving at different, non-consistent conclusions;
• Data gathering and analysis is often time consuming and/or expensive;
• Requires a high level of experience from the researcher to obtain the targeted information from the respondent;
• May lack consistency and reliability because the researcher can employ different probing techniques and the respondent can choose to tell some particular stories and ignore others; and,
• Generation of a significant amount of data that cannot be randomized into manageable parts for analysis.

Research Tip

Human Subject Research and Institutional Review Board Approval

Almost every socio-behavioral study requires you to submit your proposed research plan to an Institutional Review Board. The role of the Board is to evaluate your research proposal and determine whether it will be conducted ethically and under the regulations, institutional polices, and Code of Ethics set forth by the university. The purpose of the review is to protect the rights and welfare of individuals participating in your study. The review is intended to ensure equitable selection of respondents, that you have met the requirements for obtaining informed consent , that there is clear assessment and minimization of risks to participants and to the university [read: no lawsuits!], and that privacy and confidentiality are maintained throughout the research process and beyond. Go to the USC IRB website for detailed information and templates of forms you need to submit before you can proceed. If you are  unsure whether your study is subject to IRB review, consult with your professor or academic advisor.

Chenail, Ronald J. Introduction to Qualitative Research Design. Nova Southeastern University; Labaree, Robert V. "Working Successfully with Your Institutional Review Board: Practical Advice for Academic Librarians." College and Research Libraries News 71 (April 2010): 190-193.

Another Research Tip

Finding Examples of How to Apply Different Types of Research Methods

SAGE publications is a major publisher of studies about how to design and conduct research in the social and behavioral sciences. Their SAGE Research Methods Online and Cases database includes contents from books, articles, encyclopedias, handbooks, and videos covering social science research design and methods including the complete Little Green Book Series of Quantitative Applications in the Social Sciences and the Little Blue Book Series of Qualitative Research techniques. The database also includes case studies outlining the research methods used in real research projects. This is an excellent source for finding definitions of key terms and descriptions of research design and practice, techniques of data gathering, analysis, and reporting, and information about theories of research [e.g., grounded theory]. The database covers both qualitative and quantitative research methods as well as mixed methods approaches to conducting research.

SAGE Research Methods Online and Cases

NOTE :  For a list of online communities, research centers, indispensable learning resources, and personal websites of leading qualitative researchers, GO HERE .

For a list of scholarly journals devoted to the study and application of qualitative research methods, GO HERE .

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Qualitative Studies

Qualitative Research Studies: Introduction

Introduction

Research design decides how research materials will be collected. One or more research methods, for example -- experiment, survey, interview, etc. -- are chosen depending on the research objectives. In some research contexts, a survey may be suitable. In other instances, interviews or case studies or observation might be more appropriate. Research design actually provides insights into “how” to conduct research using a particular research methodology. Basically, every researcher has a list of research questions that need to be assessed that can be done with research design.

So research design can be defined as a framework of research methods and techniques applied by a researcher to incorporate different elements & components of research in a systematic manner. Most significantly, research design provides insights into how to Conduct Research using a particular research methodology. 

Qualitative Methods try to gather detailed, rich data allowing for an in-depth understanding of research phenomena.  Seeks the “why” rather than the “how.”

Qualitative Data Collection

Data obtained using qualitative data collection methods can be used to find new ideas, opportunities, and problems, test their value and accuracy, formulate predictions, explore a certain field in more detail, and explain the numbers obtained using quantitative data collection techniques.

Since qualitative data collection methods usually do not involve numbers and mathematical calculations, qualitative data is often seen as more subjective, but at the same time, it allows a greater depth of understanding.

Aspers, P., Corte, U. What is Qualitative in Qualitative Research .  Qual Sociol   42 , 139–160 (2019). 

Types of Qualitative Studies

Qualitative study methods are semi-structured or unstructured, usually involve small sample sizes and lack strong scientific controls.

Qualitative Study Methods

Qualitative study methods employ many of the same methods as quantitative data collection, except that instead of structured or closed, they are semi- or unstructured and open-ended.  Some of the most common qualitative  study techniques include open-ended surveys and questionnaires, interviews, focus groups, observation, case studies, and so on.

There is generally five types of qualitative data collection:

• Ethnography research: Involves semi-structure or unstructured interviews with open-ended questions; participant and non-participant observation; collected materials including documents, books, papers, audio, images, videos etc.
• Phenomenological research : I n-depth interviewing which involves conducting intensive individual interviews with a small number of respondents to explore their perspectives on a particular idea, program, or situation.  The participant interviews may be structured, semi-structured or unstructured; it also includes reflective journals; written oral self-reports; and participant’s aesthetic expressions.
• Grounded theory research: Data collection methods often include in-depth interviews using open-ended questions. Questions can be adjusted as theory emerges. Participant observation and focus groups may also be used as well as collecting and studying …  including documents, books, papers, audio, images, artifacts; videos etc. used by participants in their daily lives.
• Narrative: Participant or non-participant interview, aesthetic expressions; one’s own and other’s observation; storytelling; letter writing; autobiographic writing; collected materials …..; personal information such as values. Narrative analysis focuses on different elements to make diverse but equally substantial and meaningful interpretations and conclusions. It is a genre of analytical frames used by researchers to interpret information with the context of research shared by all in daily life. 
• Case study : Focus groups; semi-structured or unstructured interviews with open-ended questions; participant and non-participant observation; collected materials

Nayar, S., & Stanley, D. M. (Eds.). (2015).  Qualitative research methodologies for occupational science and therapy . London: Routledge.

Frank, G., & Polkinghorne, D. (2010). Qualitative Research in Occupational Therapy: From the First to the Second Generation . OTJR (Thorofare, N.J.), 30(2), 51-57.

How To Search for Qualitative Studies

Databases categorize their records using subject terms or controlled vocabularies. These Subject Headings vary for each database.

Medline/PubMed : MeSH Subject Headings

• Qualitative Research : Any type of research that employs nonnumeric information to explore individual or group characteristics, producing findings not arrived at by statistical procedures or other quantitative means.  Includes Document Analysis & Hermaneutics.
• Interviews as Topic:  Works about conversations with an individual or individuals held in order to obtain information about their background and other personal biographical data, their attitudes and opinions, etc. It includes works about school admission or job interviews.
• Focus Groups : A method of data collection and a QUALITATIVE RESEARCH tool in which a small group of individuals are brought together and allowed to interact in a discussion of their opinions about topics, issues, or questions.
• Grounded Theory : The generation of theories from analysis of empirical data.
• Nursing Methodology Research :  Research carried out by nurses concerning techniques and methods to implement projects and to document information, including methods of interviewing patients, collecting data, and forming inferences. The concept includes exploration of methodological issues such as human subjectivity and human experience.
• Anecdotes As Topic : Works about brief accounts or narratives of an incident or event.
• Narration : The act, process, or an instance of narrating, i.e., telling a story. In the context of MEDICINE or ETHICS, narration includes relating the particular and the personal in the life story of an individual.
• Personal Narratives As Topic:  Works about accounts of individual experience in relation to a particular field or of participation in related activities.
• Observational Studies As Topic : Works about clinical studies in which participants may receive diagnostic, therapeutic, or other types of interventions, but the investigator does not assign participants to specific interventions (as in an interventional study).

CINAHL (Cumulative Index to Nursing & Allied Health) : CINAHL Subject Headings 

• Action Research: Research in which problem definition, data collection, factor formulation, planned change, data analysis, and problem redefinition continue in an ongoing cycle.
• Ethnographic Research: Research which seeks to uncover the symbols and categories that members of a given culture use to interpret their world.
• Ethnological Research: Comparison and contrasting of cultures and societies as a whole.
• Ethnonursing Research: The study and analysis of a designated culture's viewpoints, beliefs, and practices about nursing care behavior.
• Grounded Theory: A qualitative method developed by Glaser and Strauss to unite theory construction and data analysis.
• Naturalist Inquiry: The use of the natural setting in research to enable understanding the whole rather than only part of the reality being studied.
• Phenomenological Research: Research designed to discover and understand the meaning of human life experiences.
• Focus Groups : Small groups of individuals brought together to discuss their opinions regarding specific issues, topics, and questions.
• Interviews:  Face-to-face or telephone meetings with subjects for the purpose of gathering information.
• Narratives : Descriptions or interpretations of events, usually in an informal manner. Often used as a data collection method for research. Do not confuse with STORYTELLING, a form of literature or telling a real or imagined story to an audience or listener.
• Descriptive Research : Research studies that have as their main objective the accurate portrayal of the characteristics of persons, situations, or groups, and the frequency with which certain phenomena occur.
• Observational Methods:  Methods of data collection in which the investigator witnesses and records behaviors of interest.
• Projective Techniques : A variety of methods for measuring by providing respondents with unstructured stimuli to which to respond.

In CINHAL, on the Advanced Search page, there are Search Options.  Scroll down to the Clinical Queries drop down box and choose to limit the search to  Qualitative-High Sensitivity; Qualitative-High Specificity ; Qualitative-Best Balance . High Sensitivity is the broadest search, to include ALL relevant material, but may also include less relevant materials. High Specificity is the most targeted search to include only the most relevant result set, but may miss some relevant materials. Best Balance retrieves the best balance between Sensitivity and Specificity.

PsycINFO: Subject Headings

• Grounded Theory
• Narrative Analysis
• Thematic Analysis : A qualitative research strategy for identifying, analyzing, and reporting identifiable patterns or clusters within data.
• Focus Grou p
• Focus Group Interview
• Semi-Structured Interview
• Interpretive Phenomenological Analysis : A systematic qualitative approach in which a researcher explores how individual's make sense of particular experiences, events, and states, primarily through the analysis of data from structured and semi-structured interviews.
• Qualitative Measures : Measures or tests employing qualitative methods and/or data, such as narratives, interviews, and focus groups.

As with CINAHL, you can limit to Methodology.  Click on Additional Limits, scroll down to "Methodology" and choose "Qualitative Study", "Focus Groups" or "Interview".

NOTE!: Be aware of  Inconsistent indexing. The above subject headings as not always indexed (i.e. added to articles) for qualitative research nor is the publication type/methodology.  So, to successfully find qualitative articles you also need to add keywords to your search strategy or if you are getting too few results, leave off the Clinical Queries or Methodology filters.

Free text keywords

Use selective free text keywords to search in Titles, Abstracts or Keywords of records held in the databases to identify Qualitative Research.  Examples:

When searching, do a combination of subject terms and keywords depending on the type of qualitative study you are looking for:

Qualitative Research [MeSH] OR (qualitative AND (research OR study OR method))

(Grounded Theory[MeSH] OR "grounded theory")

then combine it with your topic of interest

post-traumatic stress disorder OR PTSD

brain injury, OR BTI OR "traumatic, brain injury"

How to Critically Analyze Qualitative Studies

 A critical analysis of a qualitative study considers the “fit” of the research question with the qualitative method used in the study. There are many checklists available for the assessment of qualitative research studies.  Here are a few:

• The Johanna Briggs Institute: The Joanna Briggs Institute Critical Appraisal tools  for use in JBI Systematic Reviews Checklist for  Qualitative Research  
• CASP:  CASP Checklist: 10 questions to help you make sense of a Qualitative research
• McMaster University:  Guidelines for Critical Review Form:  Qualitative Studies (Version 2.0) © Letts, L., Wilkins, S., Law, M., Stewart, D., Bosch, J., & Westmorland, M., 2007  

NOTE:  When using these checklists, be sure to use them critically and with careful consideration of the research context.  In other words, use the checklists as the beginning point in assessing the article and then re-assess the article based on whether the findings can be applied in your setting/population/disease/condition.

Additional Resources

Moorley, C., & Cathala, X. (2019). How to appraise qualitative research .  Evidence-Based Nursing ,  22 (1), 10-13.    ( open access)

Stenfors, T., Kajamaa, A. and Bennett, D. (2020), How to … assess the quality of qualitative research . Clin Teach, 17: 596-599.

Greenhalgh, T., & Taylor, R. (1997). How to read a paper: Papers that go beyond numbers (qualitative research).   BMj ,  315 (7110), 740-743. 

Jeanfreau, S. G., & Jack, L., Jr (2010). Appraising qualitative research in health education: guidelines for public health educators.   Health promotion practice ,  11 (5), 612–617. 

Research Series - Critical appraisal of qualitative research when reading papers Jul 22, 2022 Virtual Tutor; Research Series (Elsevier Health Education) YouTube Video 10:04 min [ This episode Professor Dall'Ora will be looking at qualitative research in more detail. In particular how to critically appraise qualitative studies.]

Hanes K. Chapter 4: Critical appraisal of qualitative research. In: Noyes J, Booth A, Hannes K, Harden A, Harris J, Lewin S, Lockwood C (editors), Supplementary Guidance for Inclusion of Qualitative Research in Cochrane Systematic Reviews of Interventions. Version 1 (updated August 2011). Cochrane Collaboration Qualitative Methods Group, 2011. 

David Tod, Andrew Booth & Brett Smith (2022)  Critical appraisal ,  International Review of Sport and Exercise Psychology, 15:1, 52-72  (open access)

Validity & Reliability in Qualitative Studies

Validity & Reliability

Validity in qualitative research means the “appropriateness” of the tools, processes, and data -- are the tools, processes and data measuring what it is intended to measure to answer the research question?  Assessing for validity is looking to see if the research question is "valid" for the desired outcome -- whether the choice of of the methodology used was appropriate for answering the research question, was the study design valid for the methodology, were the appropriate sampling and data analysis used and finally, were the results and conclusions valid for the sample and within the context of the research question. 

In contrast, reliability concerns the degree of consistency in the results if the study, using the same methodology, can be repeated over and over.

The Basics of Validity and Reliability in Research by Joe O'Brian & Anders Orn, Research Collective.com

Brewer, M., & Crano, W. (2014). Research Design and Issues of Validity. In H. Reis & C. Judd (Eds.),  Handbook of Research Methods in Social and Personality Psychology  (pp. 11-26). Cambridge: Cambridge University Press. 

Golafshani, N. (2003). Understanding Reliability and Validity in Qualitative Research.   The Qualitative Report ,  8 (4), 597-606. 

Cypress, Brigitte S. EdD, RN, CCRN. Rigor or Reliability and Validity in Qualitative Research: Perspectives, Strategies, Reconceptualization, and Recommendations . Dimensions of Critical Care Nursing 36(4):p 253-263, 7/8 2017. 

Leung L. (2015). Validity, reliability, and generalizability in qualitative research .  Journal of family medicine and primary care ,  4 (3), 324–327. 

Understanding Reliability and Validity . Writing@CSU

Rosumeck, S., Wagner, M., Wallraf, S., & Euler, U. (2020). A validation study revealed differences in design and performance of search filters for qualitative research in PsycINFO and CINAHL.   Journal of clinical epidemiology ,  128 , 101–108. 

Wagner, M., Rosumeck, S., Küffmeier, C., Döring, K., & Euler, U. (2020). A validation study revealed differences in design and performance of MEDLINE search filters for qualitative research .  Journal of clinical epidemiology ,  120 , 17–24.

Franzel, B., Schwiegershausen, M., Heusser, P.  et al.   How to locate and appraise qualitative research in complementary and alternative medicine.   BMC Complement Altern Med   13 , 125 (2013). 

Finfgeld-Connett, D. and Johnson, E.D. (2013), Literature search strategies for conducting knowledge-building and theory-generating qualitative systematic reviews. Journal of Advanced Nursing, 69: 194-204. 

Rogers, M, Bethel, A, Abbott, R.  Locating qualitative studies in dementia on MEDLINE, EMBASE, CINAHL, and PsycINFO: A comparison of search strategies.   Res Syn Meth . 2018; 9: 579– 586. 

Booth, A. Searching for qualitative research for inclusion in systematic reviews: a structured methodological review .  Syst Rev   5 , 74 (2016). 

Noyes, J., Hannes, K., Booth, A., Harris, J., Harden, A., Popay, J., ... & Pantoja, T. (2015). Qualitative research and Cochrane reviews .

Citing Sources

Citations are brief notations in the body of a research paper that point to a source in the bibliography or references cited section.

If your paper quotes, paraphrases, summarizes the work of someone else, you need to use citations.

Citation style guides such as APA, Chicago and MLA provide detailed instructions on how citations and bibliographies should be formatted.

Health Sciences Research Toolkit

Resources, tips, and guidelines to help you through the research process., finding information.

Library Research Checklist Helpful hints for starting a library research project.

Search Strategy Checklist and Tips Helpful tips on how to develop a literature search strategy.

Boolean Operators: A Cheat Sheet Boolean logic (named after mathematician George Boole) is a system of logic to designed to yield optimal search results. The Boolean operators, AND, OR, and NOT, help you construct a logical search. Boolean operators act on sets -- groups of records containing a particular word or concept.

Literature Searching Overview and tips on how to conduct a literature search.

Health Statistics and Data Sources Health related statistics and data sources are increasingly available on the Internet. They can be found already neatly packaged, or as raw data sets. The most reliable data comes from governmental sources or health-care professional organizations.

Evaluating Information

Primary, Secondary and Tertiary Sources in the Health Sciences Understand what are considered primary, secondary and tertiary sources.

Scholarly vs Popular Journals/Magazines How to determine what are scholarly journals vs trade or popular magazines.

Identifying Peer-Reviewed Journals A “peer-reviewed” or “refereed” journal is one in which the articles it contains have been examined by people with credentials in the article’s field of study before it is published.

Evaluating Web  Resources When searching for information on the Internet, it is important to be aware of the quality of the information being presented to you. Keep in mind that anyone can host a web site. To be sure that the information you are looking at is credible and of value.

Conducting Research Through An Anti-Racism Lens This guide is for students, staff, and faculty who are incorporating an anti-racist lens at all stages of the research life cycle.

Understanding Research Study Designs Covers case studies, randomized control trials, systematic reviews and meta-analysis.

Qualitative Studies Overview of what is a qualitative study and how to recognize, find and critically appraise.

Writing and Publishing

Citing Sources Citations are brief notations in the body of a research paper that point to a source in the bibliography or references cited section.

Structure of a Research Paper Reports of research studies usually follow the IMRAD format. IMRAD (Introduction, Methods, Results, [and] Discussion) is a mnemonic for the major components of a scientific paper. These elements are included in the overall structure of a research paper.

Top Reasons for Non-Acceptance of Scientific Articles Avoid these mistakes when preparing an article for publication.

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Qualitative Study

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• 1 University of Nebraska Medical Center
• 2 GDB Research and Statistical Consulting
• 3 GDB Research and Statistical Consulting/McLaren Macomb Hospital
• PMID: 29262162
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Qualitative research is a type of research that explores and provides deeper insights into real-world problems. Instead of collecting numerical data points or intervene or introduce treatments just like in quantitative research, qualitative research helps generate hypotheses as well as further 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 stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and application of qualitative research.

Qualitative research at its core, ask 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 at hand, qualitative research design is often not linear in the same way quantitative design is. 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 difficult to accurately capture quantitatively, whereas a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a certain 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 important 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, qualitative and quantitative work are not necessarily opposites nor are they incompatible. While qualitative and quantitative approaches are different, they are not necessarily opposites, and they are 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 that there is 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 together.

Examples of Qualitative Research Approaches

Ethnography

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

Grounded Theory

Grounded Theory is the “generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior.” As opposed to quantitative research which is deductive and tests or verifies an existing theory, grounded theory research is inductive and therefore lends itself to research that is aiming to study social interactions or experiences. In essence, Grounded Theory’s goal is to explain for example how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.

Phenomenology

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

Narrative Research

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

Research Paradigm

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

Positivist vs Postpositivist

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

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

Constructivist

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

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

Data Sampling

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

Purposive sampling- selection based on the researcher’s rationale in terms of being the most informative.

Criterion sampling-selection based on pre-identified factors.

Convenience sampling- selection based on availability.

Snowball sampling- the selection is by referral from other participants or people who know potential participants.

Extreme case sampling- targeted selection of rare cases.

Typical case sampling-selection based on regular or average participants.

Data Collection and Analysis

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

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or in the environment of the participants, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed which may then be coded manually or with the use of Computer Assisted Qualitative Data Analysis Software or CAQDAS such as ATLAS.ti or NVivo.

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

Dissemination

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

Examples of Application

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

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

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

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

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

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

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

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

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

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

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Qualitative Research – Methods, Analysis Types and Guide

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Qualitative Research

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

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

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

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

Focus Groups

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

Ethnographic Studies

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

Text Analysis

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

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

Process of Observation

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

Record Keeping

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

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

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

Qualitative Research Analysis Methods

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

Thematic Analysis

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

Content Analysis

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

Discourse Analysis

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

Grounded Theory Analysis

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

Narrative Analysis

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

Phenomenological Analysis

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

Comparative Analysis

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

Applications of Qualitative Research

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

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

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

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

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

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

Purpose of Qualitative Research

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

Qualitative research can serve multiple purposes, including:

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

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

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

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

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

Advantages of Qualitative Research

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

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

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

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

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Article Contents

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Trustworthiness

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

Credibility

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

Applicability

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

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

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

Consistency

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

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

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

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

The authors have no conflicts of interest to declare.

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Qualitative Research: Characteristics, Design, Methods & Examples

Lauren McCall

MSc Health Psychology Graduate

MSc, Health Psychology, University of Nottingham

Lauren obtained an MSc in Health Psychology from The University of Nottingham with a distinction classification.

Learn about our Editorial Process

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

“Not everything that can be counted counts, and not everything that counts can be counted“ (Albert Einstein)

Qualitative research is a process used for the systematic collection, analysis, and interpretation of non-numerical data (Punch, 2013). 

Qualitative research can be used to: (i) gain deep contextual understandings of the subjective social reality of individuals and (ii) to answer questions about experience and meaning from the participant’s perspective (Hammarberg et al., 2016).

Unlike quantitative research, which focuses on gathering and analyzing numerical data for statistical analysis, qualitative research focuses on thematic and contextual information.

Characteristics of Qualitative Research 

Reality is socially constructed.

Qualitative research aims to understand how participants make meaning of their experiences – individually or in social contexts. It assumes there is no objective reality and that the social world is interpreted (Yilmaz, 2013). 

The primacy of subject matter 

The primary aim of qualitative research is to understand the perspectives, experiences, and beliefs of individuals who have experienced the phenomenon selected for research rather than the average experiences of groups of people (Minichiello, 1990).

Variables are complex, interwoven, and difficult to measure

Factors such as experiences, behaviors, and attitudes are complex and interwoven, so they cannot be reduced to isolated variables , making them difficult to measure quantitatively.

However, a qualitative approach enables participants to describe what, why, or how they were thinking/ feeling during a phenomenon being studied (Yilmaz, 2013). 

Emic (insider’s point of view)

The phenomenon being studied is centered on the participants’ point of view (Minichiello, 1990).

Emic is used to describe how participants interact, communicate, and behave in the context of the research setting (Scarduzio, 2017).

Why Conduct Qualitative Research? 

In order to gain a deeper understanding of how people experience the world, individuals are studied in their natural setting. This enables the researcher to understand a phenomenon close to how participants experience it. 

Qualitative research allows researchers to gain an in-depth understanding, which is difficult to attain using quantitative methods. 

An in-depth understanding is attained since qualitative techniques allow participants to freely disclose their experiences, thoughts, and feelings without constraint (Tenny et al., 2022). 

This helps to further investigate and understand quantitative data by discovering reasons for the outcome of a study – answering the why question behind statistics. 

The exploratory nature of qualitative research helps to generate hypotheses that can then be tested quantitatively (Busetto et al., 2020).

To design hypotheses, theory must be researched using qualitative methods to find out what is important in order to begin research. 

For example, by conducting interviews or focus groups with key stakeholders to discover what is important to them. 

Examples of qualitative research questions include: 

• How does stress influence young adults’ behavior?
• What factors influence students’ school attendance rates in developed countries?
• How do adults interpret binge drinking in the UK?
• What are the psychological impacts of cervical cancer screening in women?
• How can mental health lessons be integrated into the school curriculum? 

Collecting Qualitative Data

There are four main research design methods used to collect qualitative data: observations, interviews,  focus groups, and ethnography.

Observations

This method involves watching and recording phenomena as they occur in nature. Observation can be divided into two types: participant and non-participant observation.

In participant observation, the researcher actively participates in the situation/events being observed.

In non-participant observation, the researcher is not an active part of the observation and tries not to influence the behaviors they are observing (Busetto et al., 2020). 

Observations can be covert (participants are unaware that a researcher is observing them) or overt (participants are aware of the researcher’s presence and know they are being observed).

However, awareness of an observer’s presence may influence participants’ behavior. 

Interviews give researchers a window into the world of a participant by seeking their account of an event, situation, or phenomenon. They are usually conducted on a one-to-one basis and can be distinguished according to the level at which they are structured (Punch, 2013). 

Structured interviews involve predetermined questions and sequences to ensure replicability and comparability. However, they are unable to explore emerging issues.

Informal interviews consist of spontaneous, casual conversations which are closer to the truth of a phenomenon. However, information is gathered using quick notes made by the researcher and is therefore subject to recall bias. 

Semi-structured interviews have a flexible structure, phrasing, and placement so emerging issues can be explored (Denny & Weckesser, 2022).

The use of probing questions and clarification can lead to a detailed understanding, but semi-structured interviews can be time-consuming and subject to interviewer bias. 

Focus groups 

Similar to interviews, focus groups elicit a rich and detailed account of an experience. However, focus groups are more dynamic since participants with shared characteristics construct this account together (Denny & Weckesser, 2022).

A shared narrative is built between participants to capture a group experience shaped by a shared context. 

The researcher takes on the role of a moderator, who will establish ground rules and guide the discussion by following a topic guide to focus the group discussions.

Typically, focus groups have 4-10 participants as a discussion can be difficult to facilitate with more than this, and this number allows everyone the time to speak.

Ethnography

Ethnography is a methodology used to study a group of people’s behaviors and social interactions in their environment (Reeves et al., 2008).

Data are collected using methods such as observations, field notes, or structured/ unstructured interviews.

The aim of ethnography is to provide detailed, holistic insights into people’s behavior and perspectives within their natural setting. In order to achieve this, researchers immerse themselves in a community or organization. 

Due to the flexibility and real-world focus of ethnography, researchers are able to gather an in-depth, nuanced understanding of people’s experiences, knowledge and perspectives that are influenced by culture and society.

In order to develop a representative picture of a particular culture/ context, researchers must conduct extensive field work. 

This can be time-consuming as researchers may need to immerse themselves into a community/ culture for a few days, or possibly a few years.

Qualitative Data Analysis Methods

Different methods can be used for analyzing qualitative data. The researcher chooses based on the objectives of their study. 

The researcher plays a key role in the interpretation of data, making decisions about the coding, theming, decontextualizing, and recontextualizing of data (Starks & Trinidad, 2007). 

Grounded theory

Grounded theory is a qualitative method specifically designed to inductively generate theory from data. It was developed by Glaser and Strauss in 1967 (Glaser & Strauss, 2017).

 This methodology aims to develop theories (rather than test hypotheses) that explain a social process, action, or interaction (Petty et al., 2012). To inform the developing theory, data collection and analysis run simultaneously. 

There are three key types of coding used in grounded theory: initial (open), intermediate (axial), and advanced (selective) coding. 

Throughout the analysis, memos should be created to document methodological and theoretical ideas about the data. Data should be collected and analyzed until data saturation is reached and a theory is developed. 

Content analysis

Content analysis was first used in the early twentieth century to analyze textual materials such as newspapers and political speeches.

Content analysis is a research method used to identify and analyze the presence and patterns of themes, concepts, or words in data (Vaismoradi et al., 2013). 

This research method can be used to analyze data in different formats, which can be written, oral, or visual. 

The goal of content analysis is to develop themes that capture the underlying meanings of data (Schreier, 2012). 

Qualitative content analysis can be used to validate existing theories, support the development of new models and theories, and provide in-depth descriptions of particular settings or experiences.

The following six steps provide a guideline for how to conduct qualitative content analysis.

• Define a Research Question : To start content analysis, a clear research question should be developed.
• Identify and Collect Data : Establish the inclusion criteria for your data. Find the relevant sources to analyze.
• Define the Unit or Theme of Analysis : Categorize the content into themes. Themes can be a word, phrase, or sentence.
• Develop Rules for Coding your Data : Define a set of coding rules to ensure that all data are coded consistently.
• Code the Data : Follow the coding rules to categorize data into themes.
• Analyze the Results and Draw Conclusions : Examine the data to identify patterns and draw conclusions in relation to your research question.

Discourse analysis

Discourse analysis is a research method used to study written/ spoken language in relation to its social context (Wood & Kroger, 2000).

In discourse analysis, the researcher interprets details of language materials and the context in which it is situated.

Discourse analysis aims to understand the functions of language (how language is used in real life) and how meaning is conveyed by language in different contexts. Researchers use discourse analysis to investigate social groups and how language is used to achieve specific communication goals.

Different methods of discourse analysis can be used depending on the aims and objectives of a study. However, the following steps provide a guideline on how to conduct discourse analysis.

• Define the Research Question : Develop a relevant research question to frame the analysis.
• Gather Data and Establish the Context : Collect research materials (e.g., interview transcripts, documents). Gather factual details and review the literature to construct a theory about the social and historical context of your study.
• Analyze the Content : Closely examine various components of the text, such as the vocabulary, sentences, paragraphs, and structure of the text. Identify patterns relevant to the research question to create codes, then group these into themes.
• Review the Results : Reflect on the findings to examine the function of the language, and the meaning and context of the discourse. 

Thematic analysis

Thematic analysis is a method used to identify, interpret, and report patterns in data, such as commonalities or contrasts. 

Although the origin of thematic analysis can be traced back to the early twentieth century, understanding and clarity of thematic analysis is attributed to Braun and Clarke (2006).

Thematic analysis aims to develop themes (patterns of meaning) across a dataset to address a research question. 

In thematic analysis, qualitative data is gathered using techniques such as interviews, focus groups, and questionnaires. Audio recordings are transcribed. The dataset is then explored and interpreted by a researcher to identify patterns. 

This occurs through the rigorous process of data familiarisation, coding, theme development, and revision. These identified patterns provide a summary of the dataset and can be used to address a research question.

Themes are developed by exploring the implicit and explicit meanings within the data. Two different approaches are used to generate themes: inductive and deductive. 

An inductive approach allows themes to emerge from the data. In contrast, a deductive approach uses existing theories or knowledge to apply preconceived ideas to the data.

Phases of Thematic Analysis

Braun and Clarke (2006) provide a guide of the six phases of thematic analysis. These phases can be applied flexibly to fit research questions and data. 

Template analysis

Template analysis refers to a specific method of thematic analysis which uses hierarchical coding (Brooks et al., 2014).

Template analysis is used to analyze textual data, for example, interview transcripts or open-ended responses on a written questionnaire.

To conduct template analysis, a coding template must be developed (usually from a subset of the data) and subsequently revised and refined. This template represents the themes identified by researchers as important in the dataset. 

Codes are ordered hierarchically within the template, with the highest-level codes demonstrating overarching themes in the data and lower-level codes representing constituent themes with a narrower focus.

A guideline for the main procedural steps for conducting template analysis is outlined below.

• Familiarization with the Data : Read (and reread) the dataset in full. Engage, reflect, and take notes on data that may be relevant to the research question.
• Preliminary Coding : Identify initial codes using guidance from the a priori codes, identified before the analysis as likely to be beneficial and relevant to the analysis.
• Organize Themes : Organize themes into meaningful clusters. Consider the relationships between the themes both within and between clusters.
• Produce an Initial Template : Develop an initial template. This may be based on a subset of the data.
• Apply and Develop the Template : Apply the initial template to further data and make any necessary modifications. Refinements of the template may include adding themes, removing themes, or changing the scope/title of themes. 
• Finalize Template : Finalize the template, then apply it to the entire dataset. 

Frame analysis

Frame analysis is a comparative form of thematic analysis which systematically analyzes data using a matrix output.

Ritchie and Spencer (1994) developed this set of techniques to analyze qualitative data in applied policy research. Frame analysis aims to generate theory from data.

Frame analysis encourages researchers to organize and manage their data using summarization.

This results in a flexible and unique matrix output, in which individual participants (or cases) are represented by rows and themes are represented by columns. 

Each intersecting cell is used to summarize findings relating to the corresponding participant and theme.

Frame analysis has five distinct phases which are interrelated, forming a methodical and rigorous framework.

• Familiarization with the Data : Familiarize yourself with all the transcripts. Immerse yourself in the details of each transcript and start to note recurring themes.
• Develop a Theoretical Framework : Identify recurrent/ important themes and add them to a chart. Provide a framework/ structure for the analysis.
• Indexing : Apply the framework systematically to the entire study data.
• Summarize Data in Analytical Framework : Reduce the data into brief summaries of participants’ accounts.
• Mapping and Interpretation : Compare themes and subthemes and check against the original transcripts. Group the data into categories and provide an explanation for them.

Preventing Bias in Qualitative Research

To evaluate qualitative studies, the CASP (Critical Appraisal Skills Programme) checklist for qualitative studies can be used to ensure all aspects of a study have been considered (CASP, 2018).

The quality of research can be enhanced and assessed using criteria such as checklists, reflexivity, co-coding, and member-checking. 

Co-coding 

Relying on only one researcher to interpret rich and complex data may risk key insights and alternative viewpoints being missed. Therefore, coding is often performed by multiple researchers.

A common strategy must be defined at the beginning of the coding process  (Busetto et al., 2020). This includes establishing a useful coding list and finding a common definition of individual codes.

Transcripts are initially coded independently by researchers and then compared and consolidated to minimize error or bias and to bring confirmation of findings. 

Member checking

Member checking (or respondent validation) involves checking back with participants to see if the research resonates with their experiences (Russell & Gregory, 2003).

Data can be returned to participants after data collection or when results are first available. For example, participants may be provided with their interview transcript and asked to verify whether this is a complete and accurate representation of their views.

Participants may then clarify or elaborate on their responses to ensure they align with their views (Shenton, 2004).

This feedback becomes part of data collection and ensures accurate descriptions/ interpretations of phenomena (Mays & Pope, 2000). 

Reflexivity in qualitative research

Reflexivity typically involves examining your own judgments, practices, and belief systems during data collection and analysis. It aims to identify any personal beliefs which may affect the research. 

Reflexivity is essential in qualitative research to ensure methodological transparency and complete reporting. This enables readers to understand how the interaction between the researcher and participant shapes the data.

Depending on the research question and population being researched, factors that need to be considered include the experience of the researcher, how the contact was established and maintained, age, gender, and ethnicity.

These details are important because, in qualitative research, the researcher is a dynamic part of the research process and actively influences the outcome of the research (Boeije, 2014). 

Reflexivity Example

Who you are and your characteristics influence how you collect and analyze data. Here is an example of a reflexivity statement for research on smoking. I am a 30-year-old white female from a middle-class background. I live in the southwest of England and have been educated to master’s level. I have been involved in two research projects on oral health. I have never smoked, but I have witnessed how smoking can cause ill health from my volunteering in a smoking cessation clinic. My research aspirations are to help to develop interventions to help smokers quit.

Establishing Trustworthiness in Qualitative Research

Trustworthiness is a concept used to assess the quality and rigor of qualitative research. Four criteria are used to assess a study’s trustworthiness: credibility, transferability, dependability, and confirmability.

Credibility in Qualitative Research

Credibility refers to how accurately the results represent the reality and viewpoints of the participants.

To establish credibility in research, participants’ views and the researcher’s representation of their views need to align (Tobin & Begley, 2004).

To increase the credibility of findings, researchers may use data source triangulation, investigator triangulation, peer debriefing, or member checking (Lincoln & Guba, 1985). 

Transferability in Qualitative Research

Transferability refers to how generalizable the findings are: whether the findings may be applied to another context, setting, or group (Tobin & Begley, 2004).

Transferability can be enhanced by giving thorough and in-depth descriptions of the research setting, sample, and methods (Nowell et al., 2017). 

Dependability in Qualitative Research

Dependability is the extent to which the study could be replicated under similar conditions and the findings would be consistent.

Researchers can establish dependability using methods such as audit trails so readers can see the research process is logical and traceable (Koch, 1994).

Confirmability in Qualitative Research

Confirmability is concerned with establishing that there is a clear link between the researcher’s interpretations/ findings and the data.

Researchers can achieve confirmability by demonstrating how conclusions and interpretations were arrived at (Nowell et al., 2017).

This enables readers to understand the reasoning behind the decisions made. 

Audit Trails in Qualitative Research

An audit trail provides evidence of the decisions made by the researcher regarding theory, research design, and data collection, as well as the steps they have chosen to manage, analyze, and report data. 

The researcher must provide a clear rationale to demonstrate how conclusions were reached in their study.

A clear description of the research path must be provided to enable readers to trace through the researcher’s logic (Halpren, 1983).

Researchers should maintain records of the raw data, field notes, transcripts, and a reflective journal in order to provide a clear audit trail. 

Discovery of unexpected data

Open-ended questions in qualitative research mean the researcher can probe an interview topic and enable the participant to elaborate on responses in an unrestricted manner.

This allows unexpected data to emerge, which can lead to further research into that topic. 

Flexibility

Data collection and analysis can be modified and adapted to take the research in a different direction if new ideas or patterns emerge in the data.

This enables researchers to investigate new opportunities while firmly maintaining their research goals. 

Naturalistic settings

The behaviors of participants are recorded in real-world settings. Studies that use real-world settings have high ecological validity since participants behave more authentically. 

Limitations

Time-consuming .

Qualitative research results in large amounts of data which often need to be transcribed and analyzed manually.

Even when software is used, transcription can be inaccurate, and using software for analysis can result in many codes which need to be condensed into themes. 

Subjectivity 

The researcher has an integral role in collecting and interpreting qualitative data. Therefore, the conclusions reached are from their perspective and experience.

Consequently, interpretations of data from another researcher may vary greatly. 

Limited generalizability

The aim of qualitative research is to provide a detailed, contextualized understanding of an aspect of the human experience from a relatively small sample size.

Despite rigorous analysis procedures, conclusions drawn cannot be generalized to the wider population since data may be biased or unrepresentative.

Therefore, results are only applicable to a small group of the population. 

Extraneous variables

Qualitative research is often conducted in real-world settings. This may cause results to be unreliable since extraneous variables may affect the data, for example:

• Situational variables : different environmental conditions may influence participants’ behavior in a study. The random variation in factors (such as noise or lighting) may be difficult to control in real-world settings.
• Participant characteristics : this includes any characteristics that may influence how a participant answers/ behaves in a study. This may include a participant’s mood, gender, age, ethnicity, sexual identity, IQ, etc.
• Experimenter effect : experimenter effect refers to how a researcher’s unintentional influence can change the outcome of a study. This occurs when (i) their interactions with participants unintentionally change participants’ behaviors or (ii) due to errors in observation, interpretation, or analysis. 

What sample size should qualitative research be?

The sample size for qualitative studies has been recommended to include a minimum of 12 participants to reach data saturation (Braun, 2013).

Are surveys qualitative or quantitative?

Surveys can be used to gather information from a sample qualitatively or quantitatively. Qualitative surveys use open-ended questions to gather detailed information from a large sample using free text responses.

The use of open-ended questions allows for unrestricted responses where participants use their own words, enabling the collection of more in-depth information than closed-ended questions.

In contrast, quantitative surveys consist of closed-ended questions with multiple-choice answer options. Quantitative surveys are ideal to gather a statistical representation of a population.

What are the ethical considerations of qualitative research?

Before conducting a study, you must think about any risks that could occur and take steps to prevent them. Participant Protection : Researchers must protect participants from physical and mental harm. This means you must not embarrass, frighten, offend, or harm participants. Transparency : Researchers are obligated to clearly communicate how they will collect, store, analyze, use, and share the data. Confidentiality : You need to consider how to maintain the confidentiality and anonymity of participants’ data.

What is triangulation in qualitative research?

Triangulation refers to the use of several approaches in a study to comprehensively understand phenomena. This method helps to increase the validity and credibility of research findings. 

Types of triangulation include method triangulation (using multiple methods to gather data); investigator triangulation (multiple researchers for collecting/ analyzing data), theory triangulation (comparing several theoretical perspectives to explain a phenomenon), and data source triangulation (using data from various times, locations, and people; Carter et al., 2014).

Why is qualitative research important?

Qualitative research allows researchers to describe and explain the social world. The exploratory nature of qualitative research helps to generate hypotheses that can then be tested quantitatively.

In qualitative research, participants are able to express their thoughts, experiences, and feelings without constraint.

Additionally, researchers are able to follow up on participants’ answers in real-time, generating valuable discussion around a topic. This enables researchers to gain a nuanced understanding of phenomena which is difficult to attain using quantitative methods.

What is coding data in qualitative research?

Coding data is a qualitative data analysis strategy in which a section of text is assigned with a label that describes its content.

These labels may be words or phrases which represent important (and recurring) patterns in the data.

This process enables researchers to identify related content across the dataset. Codes can then be used to group similar types of data to generate themes.

What is the difference between qualitative and quantitative research?

Qualitative research involves the collection and analysis of non-numerical data in order to understand experiences and meanings from the participant’s perspective.

This can provide rich, in-depth insights on complicated phenomena. Qualitative data may be collected using interviews, focus groups, or observations.

In contrast, quantitative research involves the collection and analysis of numerical data to measure the frequency, magnitude, or relationships of variables. This can provide objective and reliable evidence that can be generalized to the wider population.

Quantitative data may be collected using closed-ended questionnaires or experiments.

What is trustworthiness in qualitative research?

Trustworthiness is a concept used to assess the quality and rigor of qualitative research. Four criteria are used to assess a study’s trustworthiness: credibility, transferability, dependability, and confirmability. 

Credibility refers to how accurately the results represent the reality and viewpoints of the participants. Transferability refers to whether the findings may be applied to another context, setting, or group.

Dependability is the extent to which the findings are consistent and reliable. Confirmability refers to the objectivity of findings (not influenced by the bias or assumptions of researchers).

What is data saturation in qualitative research?

Data saturation is a methodological principle used to guide the sample size of a qualitative research study.

Data saturation is proposed as a necessary methodological component in qualitative research (Saunders et al., 2018) as it is a vital criterion for discontinuing data collection and/or analysis. 

The intention of data saturation is to find “no new data, no new themes, no new coding, and ability to replicate the study” (Guest et al., 2006). Therefore, enough data has been gathered to make conclusions.

Why is sampling in qualitative research important?

In quantitative research, large sample sizes are used to provide statistically significant quantitative estimates.

This is because quantitative research aims to provide generalizable conclusions that represent populations.

However, the aim of sampling in qualitative research is to gather data that will help the researcher understand the depth, complexity, variation, or context of a phenomenon. The small sample sizes in qualitative studies support the depth of case-oriented analysis.

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• Published: 05 October 2018

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

• P. Gill 1 &
• J. Baillie 2  

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

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

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

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

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

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Introduction

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

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

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

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

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

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

Overview of qualitative research

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

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

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

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

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

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

Types of interview

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

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

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

Conducting an interview

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

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

Greeting and explaining the project/interview

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

Asymmetry between the researcher and participant talking

Expressing interest and cultural ignorance

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

Creating hypothetical situations

Asking friendly questions

Knowing when to leave.

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

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

Box 1: Example of a topic guide

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

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

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

Why did you start cleaning their teeth at that point?

How often do you brush their teeth?

What do you use to brush their teeth and why?

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

Do you find anything difficult?

What makes cleaning their teeth easier for you?

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

Has it become easier or harder?

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

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

What do they enjoy about having their teeth cleaned?

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

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

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

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

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

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

Focus groups

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

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

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

Focus group considerations

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

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

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

Focus group management

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

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

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

Discussions within the group are confidential to the group

Only one person can speak at a time

All participants should have sufficient opportunity to contribute

There should be no unnecessary interruptions while someone is speaking

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

Challenging contrary opinions is appropriate, but ridiculing is not.

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

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

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

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

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

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

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Issue Date : 12 October 2018

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The qualitative research process, end-to-end

.css-1nrevy2{position:relative;display:inline-block;} The qualitative research process: step by step guide

Although research processes may vary by methodology or project team, some fundamentals exist across research projects. Below outlines the collective experience that qualitative researchers undertake to conduct research.

Step 1: Determine what to research

Once a researcher has determined a list of potential projects to tackle, they will prioritize projects based on the business's impact, available resourcing, timelines & dependencies to create a research roadmap. For each project, they will also identify the key questions they need to answer in the research.

The researcher should identify the participants they plan to research, and any key attributes that are a 'must-have' or 'nice to have' as these can be influential in determining the research approach (e.g. a niche group may require a longer timeline to recruit).

Researchers will generally aim for a mix of project types. Some may be more tactical or requests from stakeholders, and some will be projects that the researcher has proactively identified as opportunities for strategic research.

Step 2: Identify how to research it

Once the researcher has finalized the research project, they will need to figure out how they will do the work.

Firstly, the researcher will look through secondary data and research (e.g. analytics, previous research reports). Secondary analysis will help determine if there are existing answers to any of the open questions, ensuring that any net-new study doesn't duplicate current work (unless previous research is out of date).

After scoping the research, researchers will determine if the research input needs to be  attitudinal  (i.e. what someone says) or  behavioral  (i.e. what someone does); as well as if they need to  explore  a problem space or  evaluate  a product – these help determine the methodology to use. There are many methodologies out there, but the main ones you generally will find from a qualitative perspective are:

Interviews [Attitudinal / Exploratory]  – semi-structured conversation with a participant focused on a small set of topics. Runs for 30-60 minutes.

Contextual Inquiry [Behavioral / Exploratory]  – observation of a participant in their environment. Probing questions may be asked during the observation. Runs for 2-3 hours.

Survey [Attitudinal / Evaluative]  – gathering structured information from a sample of people, traditionally to generalize the results to a larger population. Surveys should generally not take participants more than 10 minutes to complete.

Usability Test [Behavioral / Evaluative]  – evaluating how representative users are, or are not, able to achieve critical tasks within an experience.

Check out these articles for more information about different methodologies:

When to Use Which User-Experience Research Methods

UX Research Cheat Sheet

Usability.gov

Design Research Kit

Step 3: Get buy-in and alignment from others

Once a researcher has determined what they will be researching and how they will research it, they will generally write up a research plan that includes additional information about the research goals, participant scope, timelines, and dependencies. The plan is typically either a document or presentation shared with stakeholders depending on the company and how they work.

After the research plan is complete, researchers will share the plan for feedback and input from their stakeholders to ensure that the stakeholders have the right expectations going into the research. Stakeholders may ask for additional question topics to be added, ensure that research will be executed against specific timelines, or provide recommendations on how the study will help make product decisions.

At organizations where there is a research team, researchers may also share their plan with other researchers informally or through a 'crit' process. Generally, researchers will provide feedback on the research craft, such as methodologies, participant mixes, and the research goals or questions.

Once the researcher feels confident in their plan, they will either begin to plan the research, or in the case of more junior researchers, get approval from their manager to begin the study.

Step 4: Prepare research

This step is where the researcher will get all of their ducks in a row to execute the research. Preparation activities include:

Equipment: Booking venues, labs, observation rooms, and procuring any appropriate equipment needed to run the study (e.g. cameras, mobile devices).

Participants: Sourcing participants from internal / external databases, reaching out/scheduling participants, managing schedule changes.

Incentives: Find budget, identify incentive type (e.g. Amazon gift card? customer credit? gift baskets), and purchasing.

Assets: Building relevant designs / prototypes (with design or design technologists), creating interview / observation guides and other research tools needed for sessions (e.g. physical cards for in-person card sorts).

Legal & Procurement: Participant waivers or NDAs preparation to ensure they are sent in advance of the research session to participants, vendor procurement, and management.

If Research Operations exists within an organization, they will generally take on most of the load in this area. The researcher will focus on assets required for executing research, such as interview guides.

In some cases, vendors may be engaged for some of these requirements (e.g. labs, participants, and incentive management) if resourcing is not available internally or if a researcher wants a blinded study (i.e. the participant doesn't know what company is running the research). In this case, additional time is incorporated to brief, onboard, and get approvals to work with the vendor.

Step 5: Execute research

Now the researcher gets to research!

Researchers will generally aim to execute research activities for 1–2 weeks, depending on the methodology to ensure they can be efficient in execution. In some more longitudinal methods (e.g., diary studies), or if a participant type is harder to recruit, it may take longer.

In consumer research, there will usually be back up participants available in case of no shows. However, in business or enterprise research, researchers will engage will all recruited participants as participants will generally have relationships with other parts of the company (e.g. sales). It is essential to maintain those relationships post-research.

During sessions, in a perfect world, there is one facilitator (principal researcher). In some cases, a secondary attendee who takes notes – this can be a stakeholder or a more junior researcher who can then learn soft skills from the primary researcher. By delegating note-taking, the principal researcher can focus on driving and managing the participant's conversation.

However, in most cases (especially if there is a "research team of one"), researchers will try to have to do both facilitation and documentation – this can lead to a clunkier conversation as the facilitator attempts to quickly write notes between trying to think of the next question. If a researcher decides to record a session instead, they will have to spend additional time after the research listening to the full recordings and writing notes.

In qualitative research, researchers may begin to  see patterns in the findings after five sessions . They may start to tailor the research questions to be more specific to gaps in their understanding.

Researchers may also set up an observation room for stakeholders (or share links to remote sessions) to attend live. Generally, researchers will have a backchannel (e.g., slack, chat, or SMS), so if a stakeholder has a follow-up question to an answer, the researcher can dig deeper. In some cases, researchers will give stakeholders an input form to take their notes that can be shared with the researcher afterward - this can be useful for the researcher to understand how the stakeholder views the research and what the stakeholder perceives as necessary to the research insights.

Step 6: Synthesize and find insights

Once the research capture is complete, the researcher will then aggregate findings to begin to look for common themes (in exploratory) or success rates (in evaluative). Both of these will then lead to insight generation that researchers will then look to tie back to the project's original research goals.

As analysis can be one of the most high-effort tasks in research, researchers will lean towards how to be efficient in their study, generally using digital tools, hacks, or workarounds. Researchers will usually create the analysis process they refine throughout their careers to help them become more efficient.

In cases where researchers are looking to get buy-in for research or capture stakeholder input, they may seem to more visual approaches (e.g. post-it affinity analysis) in war rooms. This process can take longer to process (especially if there is a high volume of data). Still, there can be a higher impact on analyzing research in this way – especially if the researcher is looking to get buy-in for future projects.

Step 7: Create research outputs

After a researcher identifies the key themes and insights, the researcher will reframe these findings to a relevant research output to ensure that stakeholders understand and buy-in to the outcomes. Outputs may include:

Report: Outlines vital findings from research in a document or presentation format. Will most likely include an executive summary, insight themes, and supporting evidence.

Videos: A highlight reel of supporting evidence from crucial findings. Generally seen as more useful and engaging compared to just a report. In most cases, the video will help the research report.

Personas : A written representation of a product's intended users to understand different types of user goals, needs, and behaviors. Also used to help stakeholders build empathy for the end-user of the product.

Journey Map : A visualization of the process that a person goes through to accomplish a goal. Generally created in conjunction with a persona.

Concepts / Wireframes / Designs: If research is evaluative, designs can visualize recommendations.

Storyboarding

Before a researcher makes the output, researchers will spend time planning the structure and storyboarding. Storyboarding is incredibly essential to help researchers define information requirements and ensure they present their findings in the most impactful way to stakeholders.

Having a point of view in outputs

Historically, researchers have tried to stay neutral to the data and not try to have a strong opinion or perspective to let the data speak. However, as researchers become more embedded in the industry, this has shifted to stakeholders wanting a strong point of view or recommendations from researchers that can help other stakeholders (especially product managers and designers) decide the knowledge captured as part of the research.

Having a strong perspective helps researchers have a seat at the table and appear as a trusted advisor/partner in cross-functional settings.

Step 8: Share and follow up on findings

After the research outputs are complete, some researchers will do a "pre-share" or walkthrough with key stakeholders or potential detractors to the research. The purpose of these meetings is to align with stakeholders' expectations and find potential 'watch-outs' (things that may derail a presentation).

Researchers will generally have to share their findings out multiple times to different stakeholder groups and tailor them for each audience. For example, executive meetings will be more higher level than a meeting with a product manager.

After sharing, researchers will follow up with key stakeholders (especially those who provided input to the research) to confirm they understand the findings and identify next steps. Next steps may include incorporating results in product strategy documents, proposals / PRDs, or user stories to ensure that the recommendations or findings have been reflected or sourced.

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• Harvard Library
• Research Guides
• Faculty of Arts & Sciences Libraries

Library Support for Qualitative Research

• Interview Research
• Resources for Methodology
• Remote Research & Virtual Fieldwork

Resources for Research Interviewing

Nih-funded qualitative research.

• Oral History
• Data Management & Repositories
• Campus Access

Types of Interviews

• Engaging Participants

Interview Questions

• Conducting Interviews
• Transcription
• Coding and Analysis
• Managing & Finding Interview Data
• UX & Market Research Interviews

Textbooks, Guidebooks, and Handbooks  

• The Ethnographic Interview by James P. Spradley  “Spradley wrote this book for the professional and student who have never done ethnographic fieldwork (p. 231) and for the professional ethnographer who is interested in adapting the author’s procedures (p. iv). Part 1 outlines in 3 chapters Spradley’s version of ethnographic research, and it provides the background for Part 2 which consists of 12 guided steps (chapters) ranging from locating and interviewing an informant to writing an ethnography. Most of the examples come from the author’s own fieldwork among U.S. subcultures . . . Steps 6 and 8 explain lucidly how to construct a domain and a taxonomic analysis” (excerpted from book review by James D. Sexton, 1980).  
• Fundamentals of Qualitative Research by Johnny Saldana (Series edited by Patricia Leavy)  Provides a soup-to-nuts overview of the qualitative data collection process, including interviewing, participant observation, and other methods.  
• InterViews by Steinar Kvale  Interviewing is an essential tool in qualitative research and this introduction to interviewing outlines both the theoretical underpinnings and the practical aspects of the process. After examining the role of the interview in the research process, Steinar Kvale considers some of the key philosophical issues relating to interviewing: the interview as conversation, hermeneutics, phenomenology, concerns about ethics as well as validity, and postmodernism. Having established this framework, the author then analyzes the seven stages of the interview process - from designing a study to writing it up.  
• Practical Evaluation by Michael Quinn Patton  Surveys different interviewing strategies, from, a) informal/conversational, to b) interview guide approach, to c) standardized and open-ended, to d) closed/quantitative. Also discusses strategies for wording questions that are open-ended, clear, sensitive, and neutral, while supporting the speaker. Provides suggestions for probing and maintaining control of the interview process, as well as suggestions for recording and transcription.  
• The SAGE Handbook of Interview Research by Amir B. Marvasti (Editor); James A. Holstein (Editor); Jaber F. Gubrium (Editor); Karyn D. McKinney (Editor)  The new edition of this landmark volume emphasizes the dynamic, interactional, and reflexive dimensions of the research interview. Contributors highlight the myriad dimensions of complexity that are emerging as researchers increasingly frame the interview as a communicative opportunity as much as a data-gathering format. The book begins with the history and conceptual transformations of the interview, which is followed by chapters that discuss the main components of interview practice. Taken together, the contributions to The SAGE Handbook of Interview Research: The Complexity of the Craft encourage readers simultaneously to learn the frameworks and technologies of interviewing and to reflect on the epistemological foundations of the interview craft.  
• The SAGE Handbook of Online Research Methods by Nigel G. Fielding, Raymond M. Lee and Grant Blank (Editors) Bringing together the leading names in both qualitative and quantitative online research, this new edition is organised into nine sections: 1. Online Research Methods 2. Designing Online Research 3. Online Data Capture and Data Collection 4. The Online Survey 5. Digital Quantitative Analysis 6. Digital Text Analysis 7. Virtual Ethnography 8. Online Secondary Analysis: Resources and Methods 9. The Future of Online Social Research

ONLINE RESOURCES, COMMUNITIES, AND DATABASES  

• Interviews as a Method for Qualitative Research (video) This short video summarizes why interviews can serve as useful data in qualitative research.  
• Companion website to Bloomberg and Volpe's  Completing Your Qualitative Dissertation: A Road Map from Beginning to End,  4th ed Provides helpful templates and appendices featured in the book, as well as links to other useful dissertation resources.
• International Congress of Qualitative Inquiry Annual conference hosted by the International Center for Qualitative Inquiry at the University of Illinois at Urbana-Champaign, which aims to facilitate the development of qualitative research methods across a wide variety of academic disciplines, among other initiatives.  
• METHODSPACE ​​​​​​​​An online home of the research methods community, where practicing researchers share how to make research easier.  
• SAGE researchmethods ​​​​​​​Researchers can explore methods concepts to help them design research projects, understand particular methods or identify a new method, conduct their research, and write up their findings. A "methods map" facilitates finding content on methods.

The decision to conduct interviews, and the type of interviewing to use, should flow from, or align with, the methodological paradigm chosen for your study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these).

Structured:

• Structured Interview. Entry in The SAGE Encyclopedia of Social Science Research Methodsby Floyd J. Fowler Jr., Editors: Michael S. Lewis-Beck; Alan E. Bryman; Tim Futing Liao (Editor)  A concise article noting standards, procedures, and recommendations for developing and testing structured interviews. For an example of structured interview questions, you may view the Current Population Survey, May 2008: Public Participation in the Arts Supplement (ICPSR 29641), Apr 15, 2011 at https://doi.org/10.3886/ICPSR29641.v1 (To see the survey questions, preview the user guide, which can be found under the "Data and Documentation" tab. Then, look for page 177 (attachment 8).

Semi-Structured:

• Semi-Structured Interview. Entry in The SAGE Encyclopedia of Qualitative Research Methodsby Lioness Ayres; Editor: Lisa M. Given  The semi-structured interview is a qualitative data collection strategy in which the researcher asks informants a series of predetermined but open-ended questions. The researcher has more control over the topics of the interview than in unstructured interviews, but in contrast to structured interviews or questionnaires that use closed questions, there is no fixed range of responses to each question.

Unstructured:

• Unstructured Interview. Entry in The SAGE Encyclopedia of Qualitative Research Methodsby Michael W. Firmin; Editor: Lisa M. Given  Unstructured interviews in qualitative research involve asking relatively open-ended questions of research participants in order to discover their percepts on the topic of interest. Interviews, in general, are a foundational means of collecting data when using qualitative research methods. They are designed to draw from the interviewee constructs embedded in his or her thinking and rationale for decision making. The researcher uses an inductive method in data gathering, regardless of whether the interview method is open, structured, or semi-structured. That is, the researcher does not wish to superimpose his or her own viewpoints onto the person being interviewed. Rather, inductively, the researcher wishes to understand the participant's perceptions, helping him or her to articulate percepts such that they will be understood clearly by the journal reader.

Genres and Uses

Focus groups:.

• "Focus Groups." Annual Review of Sociology 22 (1996): 129-1524.by David L. Morgan  Discusses the use of focus groups and group interviews as methods for gathering qualitative data used by sociologists and other academic and applied researchers. Focus groups are recommended for giving voice to marginalized groups and revealing the group effect on opinion formation.  
• Qualitative Research Methods: A Data Collector's Field Guide (See Module 4: "Focus Groups")by Mack, N., et al.  This field guide is based on an approach to doing team-based, collaborative qualitative research that has repeatedly proven successful in research projects sponsored by Family Health International (FHI) throughout the developing world. With its straightforward delivery of information on the main qualitative methods being used in public health research today, the guide speaks to the need for simple yet effective instruction on how to do systematic and ethically sound qualitative research. The aim of the guide is thus practical. In bypassing extensive discussion on the theoretical underpinnings of qualitative research, it distinguishes itself as a how-to guide to be used in the field.

In-Depth (typically One-on-One):

• A Practical Introduction to in-Depth Interviewingby Alan Morris  Are you new to qualitative research or a bit rusty and in need of some inspiration? Are you doing a research project involving in-depth interviews? Are you nervous about carrying out your interviews? This book will help you complete your qualitative research project by providing a nuts and bolts introduction to interviewing. With coverage of ethics, preparation strategies and advice for handling the unexpected in the field, this handy guide will help you get to grips with the basics of interviewing before embarking on your research. While recognising that your research question and the context of your research will drive your approach to interviewing, this book provides practical advice often skipped in traditional methods textbooks.  
• Qualitative Research Methods: A Data Collector's Field Guide (See Module 3: "In-Depth Interviews")by Mack, N., et al.  This field guide is based on an approach to doing team-based, collaborative qualitative research that has repeatedly proven successful in research projects sponsored by Family Health International (FHI) throughout the developing world. With its straightforward delivery of information on the main qualitative methods being used in public health research today, the guide speaks to the need for simple yet effective instruction on how to do systematic and ethically sound qualitative research. The aim of the guide is thus practical. In bypassing extensive discussion on the theoretical underpinnings of qualitative research, it distinguishes itself as a how-to guide to be used in the field.

Folklore Research and Oral Histories:

In addition to the following resource, see the  Oral History   page of this guide for helpful resources on Oral History interviewing.

American Folklife Center at the Library of Congress. Folklife and Fieldwork: A Layman’s Introduction to Field Techniques Interviews gathered for purposes of folklore research are similar to standard social science interviews in some ways, but also have a good deal in common with oral history approaches to interviewing. The focus in a folklore research interview is on documenting and trying to understand the interviewee's way of life relative to a culture or subculture you are studying. This guide includes helpful advice and tips for conducting fieldwork in folklore, such as tips for planning, conducting, recording, and archiving interviews.

An interdisciplinary scientific program within the Institute for Quantitative Social Science which encourages and facilitates research and instruction in the theory and practice of survey research. The primary mission of PSR is to provide survey research resources to enhance the quality of teaching and research at Harvard.

• Internet, Phone, Mail, and Mixed-Mode Surveysby Don A. Dillman; Jolene D. Smyth; Leah Melani Christian  The classic survey design reference, updated for the digital age. The new edition is thoroughly updated and revised, and covers all aspects of survey research. It features expanded coverage of mobile phones, tablets, and the use of do-it-yourself surveys, and Dillman's unique Tailored Design Method is also thoroughly explained. This new edition is complemented by copious examples within the text and accompanying website. It includes: Strategies and tactics for determining the needs of a given survey, how to design it, and how to effectively administer it. How and when to use mail, telephone, and Internet surveys to maximum advantage. Proven techniques to increase response rates. Guidance on how to obtain high-quality feedback from mail, electronic, and other self-administered surveys. Direction on how to construct effective questionnaires, including considerations of layout. The effects of sponsorship on the response rates of surveys. Use of capabilities provided by newly mass-used media: interactivity, presentation of aural and visual stimuli. The Fourth Edition reintroduces the telephone--including coordinating land and mobile.

User Experience (UX) and Marketing:

• See the  "UX & Market Research Interviews"  tab on this guide, above. May include  Focus Groups,  above.

Screening for Research Site Selection:

• Research interviews are used not only to furnish research data for theoretical analysis in the social sciences, but also to plan other kinds of studies. For example, interviews may allow researchers to screen appropriate research sites to conduct empirical studies (such as randomized controlled trials) in a variety of fields, from medicine to law. In contrast to interviews conducted in the course of social research, such interviews do not typically serve as the data for final analysis and publication.

ENGAGING PARTICIPANTS

Research ethics  .

• Human Subjects (IRB) The Committee on the Use of Human Subjects (CUHS) serves as the Institutional Review Board for the University area which includes the Cambridge and Allston campuses at Harvard. Find your IRB  contact person , or learn about  required ethics training.  You may also find the  IRB Lifecycle Guide  helpful. This is the preferred IRB portal for Harvard graduate students and other researchers. IRB forms can be downloaded via the  ESTR Library  (click on the "Templates and Forms" tab, then navigate to pages 2 and 3 to find the documents labelled with “HUA” for the Harvard University Area IRB. Nota bene: You may use these forms only if you submit your study to the Harvard University IRB). The IRB office can be reached through email at [email protected] or by telephone at (617) 496-2847.  
• Undergraduate Research Training Program (URTP) Portal The URTP at Harvard University is a comprehensive platform to create better prepared undergraduate researchers. The URTP is comprised of research ethics training sessions, a student-focused curriculum, and an online decision form that will assist students in determining whether their project requires IRB review. Students should examine the  URTP's guide for student researchers: Introduction to Human Subjects Research Protection.  
• Ethics reports From the Association of Internet Researchers (AoIR)  
• Respect, Beneficence, and Justice: QDR General Guidance for Human Participants If you are hoping to share your qualitative interview data in a repository after it has been collected, you will need to plan accordingly via informed consent, careful de-identification procedures, and data access controls. Consider  consulting with the Qualitative Research Support Group at Harvard Library  and consulting with  Harvard's Dataverse contacts  to help you think through all of the contingencies and processes.  
• "Conducting a Qualitative Child Interview: Methodological Considerations." Journal of Advanced Nursing 42/5 (2003): 434-441 by Kortesluoma, R., et al.  The purpose of this article is to illustrate the theoretical premises of child interviewing, as well as to describe some practical methodological solutions used during interviews. Factors that influence data gathered from children and strategies for taking these factors into consideration during the interview are also described.  
• "Crossing Cultural Barriers in Research Interviewing." Qualitative Social Work 63/3 (2007): 353-372 by Sands, R., et al.  This article critically examines a qualitative research interview in which cultural barriers between a white non-Muslim female interviewer and an African American Muslim interviewee, both from the USA, became evident and were overcome within the same interview.  
• Decolonizing Methodologies: Research and Indigenous Peoples by Linda Tuhiwai Smith  This essential volume explores intersections of imperialism and research - specifically, the ways in which imperialism is embedded in disciplines of knowledge and tradition as 'regimes of truth.' Concepts such as 'discovery' and 'claiming' are discussed and an argument presented that the decolonization of research methods will help to reclaim control over indigenous ways of knowing and being. The text includes case-studies and examples, and sections on new indigenous literature and the role of research in indigenous struggles for social justice.  

This resource, sponsored by University of Oregon Libraries, exemplifies the use of interviewing methodologies in research that foregrounds traditional knowledge. The methodology page summarizes the approach.

• Ethics: The Need to Tread Carefully. Chapter in A Practical Introduction to in-Depth Interviewing by Alan Morris  Pay special attention to the sections in chapter 2 on "How to prevent and respond to ethical issues arising in the course of the interview," "Ethics in the writing up of your interviews," and "The Ethics of Care."  
• Handbook on Ethical Issues in Anthropology by Joan Cassell (Editor); Sue-Ellen Jacobs (Editor)  This publication of the American Anthropological Association presents and discusses issues and sources on ethics in anthropology, as well as realistic case studies of ethical dilemmas. It is meant to help social science faculty introduce discussions of ethics in their courses. Some of the topics are relevant to interviews, or at least to studies of which interviews are a part. See chapters 3 and 4 for cases, with solutions and commentary, respectively.  
• Research Ethics from the Chanie Wenjack School for Indigenous Studies, Trent University  (Open Access) An overview of Indigenous research ethics and protocols from the across the globe.  
• Resources for Equity in Research Consult these resources for guidance on creating and incorporating equitable materials into public health research studies that entail community engagement.

The SAGE Handbook of Qualitative Research Ethics by Ron Iphofen (Editor); Martin Tolich (Editor)  This handbook is a much-needed and in-depth review of the distinctive set of ethical considerations which accompanies qualitative research. This is particularly crucial given the emergent, dynamic and interactional nature of most qualitative research, which too often allows little time for reflection on the important ethical responsibilities and obligations. Contributions from leading international researchers have been carefully organized into six key thematic sections: Part One: Thick Descriptions Of Qualitative Research Ethics; Part Two: Qualitative Research Ethics By Technique; Part Three: Ethics As Politics; Part Four: Qualitative Research Ethics With Vulnerable Groups; Part Five: Relational Research Ethics; Part Six: Researching Digitally. This Handbook is a one-stop resource on qualitative research ethics across the social sciences that draws on the lessons learned and the successful methods for surmounting problems - the tried and true, and the new.

RESEARCH COMPLIANCE AND PRIVACY LAWS

Research Compliance Program for FAS/SEAS at Harvard : The Faculty of Arts and Sciences (FAS), including the School of Engineering and Applied Sciences (SEAS), and the Office of the Vice Provost for Research (OVPR) have established a shared Research Compliance Program (RCP). An area of common concern for interview studies is international projects and collaboration . RCP is a resource to provide guidance on which international activities may be impacted by US sanctions on countries, individuals, or entities and whether licenses or other disclosure are required to ship or otherwise share items, technology, or data with foreign collaborators.

• Harvard Global Support Services (GSS) is for students, faculty, staff, and researchers who are studying, researching, or working abroad. Their services span safety and security, health, culture, outbound immigration, employment, financial and legal matters, and research center operations. These include travel briefings and registration, emergency response, guidance on international projects, and managing in-country operations.

Generative AI: Harvard-affiliated researchers should not enter data classified as confidential ( Level 2 and above ), including non-public research data, into publicly-available generative AI tools, in accordance with the University’s Information Security Policy. Information shared with generative AI tools using default settings is not private and could expose proprietary or sensitive information to unauthorized parties.

Privacy Laws: Be mindful of any potential privacy laws that may apply wherever you conduct your interviews. The General Data Protection Regulation is a high-profile example (see below):

• General Data Protection Regulation (GDPR) This Regulation lays down rules relating to the protection of natural persons with regard to the processing of personal data and rules relating to the free movement of personal data. It protects fundamental rights and freedoms of natural persons and in particular their right to the protection of personal data. The free movement of personal data within the Union shall be neither restricted nor prohibited for reasons connected with the protection of natural persons with regard to the processing of personal data. For a nice summary of what the GDPR requires, check out the GDPR "crash course" here .

SEEKING CONSENT  

If you would like to see examples of consent forms, ask your local IRB, or take a look at these resources:

• Model consent forms for oral history, suggested by the Centre for Oral History and Digital Storytelling at Concordia University  
• For NIH-funded research, see this  resource for developing informed consent language in research studies where data and/or biospecimens will be stored and shared for future use.

POPULATION SAMPLING

If you wish to assemble resources to aid in sampling, such as the USPS Delivery Sequence File, telephone books, or directories of organizations and listservs, please contact our  data librarian  or write to  [email protected] .

• Research Randomizer   A free web-based service that permits instant random sampling and random assignment. It also contains an interactive tutorial perfect for students taking courses in research methods.  
• Practical Tools for Designing and Weighting Survey Samples by Richard Valliant; Jill A. Dever; Frauke Kreuter  Survey sampling is fundamentally an applied field. The goal in this book is to put an array of tools at the fingertips of practitioners by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This book serves at least three audiences: (1) Students seeking a more in-depth understanding of applied sampling either through a second semester-long course or by way of a supplementary reference; (2) Survey statisticians searching for practical guidance on how to apply concepts learned in theoretical or applied sampling courses; and (3) Social scientists and other survey practitioners who desire insight into the statistical thinking and steps taken to design, select, and weight random survey samples. Several survey data sets are used to illustrate how to design samples, to make estimates from complex surveys for use in optimizing the sample allocation, and to calculate weights. Realistic survey projects are used to demonstrate the challenges and provide a context for the solutions. The book covers several topics that either are not included or are dealt with in a limited way in other texts. These areas include: sample size computations for multistage designs; power calculations related to surveys; mathematical programming for sample allocation in a multi-criteria optimization setting; nuts and bolts of area probability sampling; multiphase designs; quality control of survey operations; and statistical software for survey sampling and estimation. An associated R package, PracTools, contains a number of specialized functions for sample size and other calculations. The data sets used in the book are also available in PracTools, so that the reader may replicate the examples or perform further analyses.  
• Sampling: Design and Analysis by Sharon L. Lohr  Provides a modern introduction to the field of sampling. With a multitude of applications from a variety of disciplines, the book concentrates on the statistical aspects of taking and analyzing a sample. Overall, the book gives guidance on how to tell when a sample is valid or not, and how to design and analyze many different forms of sample surveys.  
• Sampling Techniques by William G. Cochran  Clearly demonstrates a wide range of sampling methods now in use by governments, in business, market and operations research, social science, medicine, public health, agriculture, and accounting. Gives proofs of all the theoretical results used in modern sampling practice. New topics in this edition include the approximate methods developed for the problem of attaching standard errors or confidence limits to nonlinear estimates made from the results of surveys with complex plans.  
• "Understanding the Process of Qualitative Data Collection" in Chapter 13 (pp. 103–1162) of 30 Essential Skills for the Qualitative Researcher by John W. Creswell  Provides practical "how-to" information for beginning researchers in the social, behavioral, and health sciences with many applied examples from research design, qualitative inquiry, and mixed methods.The skills presented in this book are crucial for a new qualitative researcher starting a qualitative project.  
• Survey Methodology by Robert M. Groves; Floyd J. Fowler; Mick P. Couper; James M. Lepkowski; Eleanor Singer; Roger Tourangeau; Floyd J. Fowler  coverage includes sampling frame evaluation, sample design, development of questionnaires, evaluation of questions, alternative modes of data collection, interviewing, nonresponse, post-collection processing of survey data, and practices for maintaining scientific integrity.

The way a qualitative researcher constructs and approaches interview questions should flow from, or align with, the methodological paradigm chosen for the study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these).

Constructing Your Questions

Helpful texts:.

• "Developing Questions" in Chapter 4 (pp. 98–108) of Becoming Qualitative Researchers by Corrine Glesne  Ideal for introducing the novice researcher to the theory and practice of qualitative research, this text opens students to the diverse possibilities within this inquiry approach, while helping them understand how to design and implement specific research methods.  
• "Learning to Interview in the Social Sciences" Qualitative Inquiry, 9(4) 2003, 643–668 by Roulston, K., deMarrais, K., & Lewis, J. B. See especially the section on "Phrasing and Negotiating Questions" on pages 653-655 and common problems with framing questions noted on pages 659 - 660.  
• Qualitative Research Interviewing: Biographic Narrative and Semi-Structured Methods (See sections on “Lightly and Heavily Structured Depth Interviewing: Theory-Questions and Interviewer-Questions” and “Preparing for any Interviewing Sequence") by Tom Wengraf  Unique in its conceptual coherence and the level of practical detail, this book provides a comprehensive resource for those concerned with the practice of semi-structured interviewing, the most commonly used interview approach in social research, and in particular for in-depth, biographic narrative interviewing. It covers the full range of practices from the identification of topics through to strategies for writing up research findings in diverse ways.  
• "Scripting a Qualitative Purpose Statement and Research Questions" in Chapter 12 (pp. 93–102) of 30 Essential Skills for the Qualitative Researcher by John W. Creswell  Provides practical "how-to" information for beginning researchers in the social, behavioral, and health sciences with many applied examples from research design, qualitative inquiry, and mixed methods.The skills presented in this book are crucial for a new qualitative researcher starting a qualitative project.  
• Some Strategies for Developing Interview Guides for Qualitative Interviews by Sociology Department, Harvard University Includes general advice for conducting qualitative interviews, pros and cons of recording and transcription, guidelines for success, and tips for developing and phrasing effective interview questions.  
• Tip Sheet on Question Wording by Harvard University Program on Survey Research

Let Theory Guide You:

The quality of your questions depends on how you situate them within a wider body of knowledge. Consider the following advice:

A good literature review has many obvious virtues. It enables the investigator to define problems and assess data. It provides the concepts on which percepts depend. But the literature review has a special importance for the qualitative researcher. This consists of its ability to sharpen his or her capacity for surprise (Lazarsfeld, 1972b). The investigator who is well versed in the literature now has a set of expectations the data can defy. Counterexpectational data are conspicuous, readable, and highly provocative data. They signal the existence of unfulfilled theoretical assumptions, and these are, as Kuhn (1962) has noted, the very origins of intellectual innovation. A thorough review of the literature is, to this extent, a way to manufacture distance. It is a way to let the data of one's research project take issue with the theory of one's field.

McCracken, G. (1988), The Long Interview, Sage: Newbury Park, CA, p. 31

When drafting your interview questions, remember that everything follows from your central research question. Also, on the way to writing your "operationalized" interview questions, it's  helpful to draft broader, intermediate questions, couched in theory. Nota bene:  While it is important to know the literature well before conducting your interview(s), be careful not to present yourself to your research participant(s) as "the expert," which would be presumptuous and could be intimidating. Rather, the purpose of your knowledge is to make you a better, keener listener.

If you'd like to supplement what you learned about relevant theories through your coursework and literature review, try these sources:

• Annual Reviews   Review articles sum up the latest research in many fields, including social sciences, biomedicine, life sciences, and physical sciences. These are timely collections of critical reviews written by leading scientists.  
• HOLLIS - search for resources on theories in your field   Modify this example search by entering the name of your field in place of "your discipline," then hit search.  
• Oxford Bibliographies   Written and reviewed by academic experts, every article in this database is an authoritative guide to the current scholarship in a variety of fields, containing original commentary and annotations.  
• ProQuest Dissertations & Theses (PQDT)   Indexes dissertations and masters' theses from most North American graduate schools as well as some European universities. Provides full text for most indexed dissertations from 1990-present.  
• Very Short Introductions   Launched by Oxford University Press in 1995, Very Short Introductions offer concise introductions to a diverse range of subjects from Climate to Consciousness, Game Theory to Ancient Warfare, Privacy to Islamic History, Economics to Literary Theory.

CONDUCTING INTERVIEWS

Equipment and software:  .

• Lamont Library  loans microphones and podcast starter kits, which will allow you to capture audio (and you may record with software, such as Garage Band). 
• Cabot Library  loans digital recording devices, as well as USB microphones.

If you prefer to use your own device, you may purchase a small handheld audio recorder, or use your cell phone.

• Audio Capture Basics (PDF)  - Helpful instructions, courtesy of the Lamont Library Multimedia Lab.
• Getting Started with Podcasting/Audio:  Guidelines from Harvard Library's Virtual Media Lab for preparing your interviewee for a web-based recording (e.g., podcast, interview)
• ​ Camtasia Screen Recorder and Video Editor
• Zoom: Video Conferencing, Web Conferencing
• Visit the Multimedia Production Resources guide! Consult it to find and learn how to use audiovisual production tools, including: cameras, microphones, studio spaces, and other equipment at Cabot Science Library and Lamont Library.
• Try the virtual office hours offered by the Lamont Multimedia Lab!

TIPS FOR CONDUCTING INTERVIEWS

Quick handout:  .

• Research Interviewing Tips (Courtesy of Dr. Suzanne Spreadbury)

Remote Interviews:  

• For Online or Distant Interviews, See "Remote Research & Virtual Fieldwork" on this guide .  
• Deborah Lupton's Bibliography: Doing Fieldwork in a Pandemic

Seeking Consent:

Books and articles:  .

• "App-Based Textual Interviews: Interacting With Younger Generations in a Digitalized Social Reallity."International Journal of Social Research Methodology (12 June 2022). Discusses the use of texting platforms as a means to reach young people. Recommends useful question formulations for this medium.  
• "Learning to Interview in the Social Sciences." Qualitative Inquiry, 9(4) 2003, 643–668 by Roulston, K., deMarrais, K., & Lewis, J. B. See especially the section on "Phrasing and Negotiating Questions" on pages 653-655 and common problems with framing questions noted on pages 659-660.  
• "Slowing Down and Digging Deep: Teaching Students to Examine Interview Interaction in Depth." LEARNing Landscapes, Spring 2021 14(1) 153-169 by Herron, Brigette A. and Kathryn Roulston. Suggests analysis of videorecorded interviews as a precursor to formulating one's own questions. Includes helpful types of probes.  
• Using Interviews in a Research Project by Nigel Joseph Mathers; Nicholas J Fox; Amanda Hunn; Trent Focus Group.  A work pack to guide researchers in developing interviews in the healthcare field. Describes interview structures, compares face-to-face and telephone interviews. Outlines the ways in which different types of interview data can be analysed.  
• “Working through Challenges in Doing Interview Research.” International Journal of Qualitative Methods, (December 2011), 348–66 by Roulston, Kathryn.  The article explores (1) how problematic interactions identified in the analysis of focus group data can lead to modifications in research design, (2) an approach to dealing with reported data in representations of findings, and (3) how data analysis can inform question formulation in successive rounds of data generation. Findings from these types of examinations of interview data generation and analysis are valuable for informing both interview practice as well as research design.

Videos:  

The way a qualitative researcher transcribes interviews should flow from, or align with, the methodological paradigm chosen for the study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these).

TRANSCRIPTION

Before embarking on a transcription project, it's worthwhile to invest in the time and effort necessary to capture good audio, which will make the transcription process much easier. If you haven't already done so, check out the  audio capture guidelines from Harvard Library's Virtual Media Lab , or  contact a media staff member  for customized recommendations. First and foremost, be mindful of common pitfalls by watching this short video that identifies  the most common errors to avoid!

SOFTWARE:  

• Adobe Premiere Pro Speech-To-Text  automatically generates transcripts and adds captions to your videos. Harvard affiliates can download Adobe Premiere in the Creative Cloud Suite.  
• GoTranscript  provides cost-effective human-generated transcriptions.  
• pyTranscriber  is an app for generating automatic transcription and/or subtitles for audio and video files. It uses the Google Cloud Speech-to-Text service, has a friendly graphical user interface, and is purported to work nicely with Chinese.   
• Otter  provides a new way to capture, store, search and share voice conversations, lectures, presentations, meetings, and interviews. The startup is based in Silicon Valley with a team of experienced Ph.Ds and engineers from Google, Facebook, Yahoo and Nuance (à la Dragon). Free accounts available. This is the software that  Zoom  uses to generate automated transcripts, so if you have access to a Zoom subscription, you have access to Otter transcriptions with it (applicable in several  languages ). As with any automated approach, be prepared to correct any errors after the fact, by hand.  
• Panopto  is available to Harvard affiliates and generates  ASR (automated speech recognition) captions . You may upload compatible audio files into it. As with any automatically generated transcription, you will need to make manual revisions. ASR captioning is available in several  languages . Panopto maintains robust security practices, including strong authentication measures and end-to-end encryption, ensuring your content remains private and protected.  
• REV.Com  allows you to record and transcribe any calls on the iPhone, both outgoing and incoming. It may be useful for recording phone interviews. Rev lets you choose whether you want an AI- or human-generated transcription, with a fast turnaround. Rev has Service Organization Controls Type II (SOC2) certification (a SOC2 cert looks at and verifies an organization’s processing integrity, privacy practices, and security safeguards).   
• Scribie Audio/Video Transcription  provides automated or manual transcriptions for a small fee. As with any transcription service, some revisions will be necessary after the fact, particularly for its automated transcripts.  
• Sonix  automatically transcribes, translates, and helps to organize audio and video files in over 40 languages. It's fast and affordable, with good accuracy. The free trial includes 30 minutes of free transcription.  
• TranscriptionWing  uses a human touch process to clean up machine-generated transcripts so that the content will far more accurately reflect your audio recording.   
• Whisper is a tool from OpenAI that facilitates transcription of sensitive audiovisual recordings (e.g., of research interviews) on your own device. Installation and use depends on your operating system and which version you install. Important Note: The Whisper API, where audio is sent to OpenAI to be processed by them and then sent back (usually through a programming language like Python) is NOT appropriate for sensitive data. The model should be downloaded with tools such as those described in this FAQ , so that audio is kept to your local machine. For assistance, contact James Capobianco .

EQUIPMENT:  

• Transcription pedals  are in circulation and available to borrow from the Circulation desk at Lamont, or use at Lamont Library's Media Lab on level B. For hand-transcribing your interviews, they work in conjunction with software such as  Express Scribe , which is loaded on Media Lab computers, or you may download for free on your own machine (Mac or PC versions; scroll down the downloads page for the latter). The pedals are plug-and-play USB, allow a wide range of playback speeds, and have 3 programmable buttons, which are typically set to rewind/play/fast-forward. Instructions are included in the bag that covers installation and set-up of the software, and basic use of the pedals.

NEED HELP?  

• Try the virtual office hours offered by the Lamont Multimedia Lab!    
• If you're creating podcasts, login to  Canvas  and check out the  Podcasting/Audio guide . 

Helpful Texts:  

• "Transcription as a Crucial Step of Data Analysis" in Chapter 5 of The SAGE Handbook of Qualitative Data Analysisby Uwe Flick (Editor)  Covers basic terminology for transcription, shares caveats for transcribers, and identifies components of vocal behavior. Provides notation systems for transcription, suggestions for transcribing turn-taking, and discusses new technologies and perspectives. Includes a bibliography for further reading.  
• "Transcribing the Oral Interview: Part Art, Part Science " on p. 10 of the Centre for Community Knowledge (CCK) newsletter: TIMESTAMPby Mishika Chauhan and Saransh Srivastav

QUALITATIVE DATA ANALYSIS

Software  .

• Free download available for Harvard Faculty of Arts and Sciences (FAS) affiliates
• Desktop access at Lamont Library Media Lab, 3rd floor
• Desktop access at Harvard Kennedy School Library (with HKS ID)
• Remote desktop access for Harvard affiliates from  IQSS Computer Labs . Email them at  [email protected] and ask for a new lab account and remote desktop access to NVivo.
• Virtual Desktop Infrastructure (VDI) access available to Harvard T.H. Chan School of Public Health affiliates

CODING AND THEMEING YOUR DATA

Data analysis methods should flow from, or align with, the methodological paradigm chosen for your study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these). Some established methods include Content Analysis, Critical Analysis, Discourse Analysis, Gestalt Analysis, Grounded Theory Analysis, Interpretive Analysis, Narrative Analysis, Normative Analysis, Phenomenological Analysis, Rhetorical Analysis, and Semiotic Analysis, among others. The following resources should help you navigate your methodological options and put into practice methods for coding, themeing, interpreting, and presenting your data.

• Users can browse content by topic, discipline, or format type (reference works, book chapters, definitions, etc.). SRM offers several research tools as well: a methods map, user-created reading lists, a project planner, and advice on choosing statistical tests.  
• Abductive Coding: Theory Building and Qualitative (Re)Analysis by Vila-Henninger, et al.  The authors recommend an abductive approach to guide qualitative researchers who are oriented towards theory-building. They outline a set of tactics for abductive analysis, including the generation of an abductive codebook, abductive data reduction through code equations, and in-depth abductive qualitative analysis.  
• Analyzing and Interpreting Qualitative Research: After the Interview by Charles F. Vanover, Paul A. Mihas, and Johnny Saldana (Editors)   Providing insight into the wide range of approaches available to the qualitative researcher and covering all steps in the research process, the authors utilize a consistent chapter structure that provides novice and seasoned researchers with pragmatic, "how-to" strategies. Each chapter author introduces the method, uses one of their own research projects as a case study of the method described, shows how the specific analytic method can be used in other types of studies, and concludes with three questions/activities to prompt class discussion or personal study.   
• "Analyzing Qualitative Data." Theory Into Practice 39, no. 3 (2000): 146-54 by Margaret D. LeCompte   This article walks readers though rules for unbiased data analysis and provides guidance for getting organized, finding items, creating stable sets of items, creating patterns, assembling structures, and conducting data validity checks.  
• "Coding is Not a Dirty Word" in Chapter 1 (pp. 1–30) of Enhancing Qualitative and Mixed Methods Research with Technology by Shalin Hai-Jew (Editor)   Current discourses in qualitative research, especially those situated in postmodernism, represent coding and the technology that assists with coding as reductive, lacking complexity, and detached from theory. In this chapter, the author presents a counter-narrative to this dominant discourse in qualitative research. The author argues that coding is not necessarily devoid of theory, nor does the use of software for data management and analysis automatically render scholarship theoretically lightweight or barren. A lack of deep analytical insight is a consequence not of software but of epistemology. Using examples informed by interpretive and critical approaches, the author demonstrates how NVivo can provide an effective tool for data management and analysis. The author also highlights ideas for critical and deconstructive approaches in qualitative inquiry while using NVivo. By troubling the positivist discourse of coding, the author seeks to create dialogic spaces that integrate theory with technology-driven data management and analysis, while maintaining the depth and rigor of qualitative research.   
• The Coding Manual for Qualitative Researchers by Johnny Saldana   An in-depth guide to the multiple approaches available for coding qualitative data. Clear, practical and authoritative, the book profiles 32 coding methods that can be applied to a range of research genres from grounded theory to phenomenology to narrative inquiry. For each approach, Saldaña discusses the methods, origins, a description of the method, practical applications, and a clearly illustrated example with analytic follow-up. Essential reading across the social sciences.  
• Flexible Coding of In-depth Interviews: A Twenty-first-century Approach by Nicole M. Deterding and Mary C. Waters The authors suggest steps in data organization and analysis to better utilize qualitative data analysis technologies and support rigorous, transparent, and flexible analysis of in-depth interview data.  
• From the Editors: What Grounded Theory is Not by Roy Suddaby Walks readers through common misconceptions that hinder grounded theory studies, reinforcing the two key concepts of the grounded theory approach: (1) constant comparison of data gathered throughout the data collection process and (2) the determination of which kinds of data to sample in succession based on emergent themes (i.e., "theoretical sampling").  
• “Good enough” methods for life-story analysis, by Wendy Luttrell. In Quinn N. (Ed.), Finding culture in talk (pp. 243–268). Demonstrates for researchers of culture and consciousness who use narrative how to concretely document reflexive processes in terms of where, how and why particular decisions are made at particular stages of the research process.   
• The Ethnographic Interview by James P. Spradley  “Spradley wrote this book for the professional and student who have never done ethnographic fieldwork (p. 231) and for the professional ethnographer who is interested in adapting the author’s procedures (p. iv) ... Steps 6 and 8 explain lucidly how to construct a domain and a taxonomic analysis” (excerpted from book review by James D. Sexton, 1980). See also:  Presentation slides on coding and themeing your data, derived from Saldana, Spradley, and LeCompte Click to request access.  
• Qualitative Data Analysis by Matthew B. Miles; A. Michael Huberman   A practical sourcebook for researchers who make use of qualitative data, presenting the current state of the craft in the design, testing, and use of qualitative analysis methods. Strong emphasis is placed on data displays matrices and networks that go beyond ordinary narrative text. Each method of data display and analysis is described and illustrated.  
• "A Survey of Qualitative Data Analytic Methods" in Chapter 4 (pp. 89–138) of Fundamentals of Qualitative Research by Johnny Saldana   Provides an in-depth introduction to coding as a heuristic, particularly focusing on process coding, in vivo coding, descriptive coding, values coding, dramaturgical coding, and versus coding. Includes advice on writing analytic memos, developing categories, and themeing data.   
• "Thematic Networks: An Analytic Tool for Qualitative Research." Qualitative Research : QR, 1(3), 385–405 by Jennifer Attride-Stirling Details a technique for conducting thematic analysis of qualitative material, presenting a step-by-step guide of the analytic process, with the aid of an empirical example. The analytic method presented employs established, well-known techniques; the article proposes that thematic analyses can be usefully aided by and presented as thematic networks.  
• Using Thematic Analysis in Psychology by Virginia Braun and Victoria Clark Walks readers through the process of reflexive thematic analysis, step by step. The method may be adapted in fields outside of psychology as relevant. Pair this with One Size Fits All? What Counts as Quality Practice in Reflexive Thematic Analysis? by Virginia Braun and Victoria Clark

TESTING OR GENERATING THEORIES

The quality of your data analysis depends on how you situate what you learn within a wider body of knowledge. Consider the following advice:

Once you have coalesced around a theory, realize that a theory should  reveal  rather than  color  your discoveries. Allow your data to guide you to what's most suitable. Grounded theory  researchers may develop their own theory where current theories fail to provide insight.  This guide on Theoretical Models  from Alfaisal University Library provides a helpful overview on using theory.

MANAGING & FINDING INTERVIEW DATA

Managing your elicited interview data, general guidance:  .

• Research Data Management @ Harvard A reference guide with information and resources to help you manage your research data. See also: Harvard Research Data Security Policy , on the Harvard University Research Data Management website.  
• Data Management For Researchers: Organize, Maintain and Share Your Data for Research Success by Kristin Briney. A comprehensive guide for scientific researchers providing everything they need to know about data management and how to organize, document, use and reuse their data.  
• Open Science Framework (OSF) An open-source project management tool that makes it easy to collaborate within and beyond Harvard throughout a project's lifecycle. With OSF you can manage, store, and share documents, datasets, and other information with your research team. You can also publish your work to share it with a wider audience. Although data can be stored privately, because this platform is hosted on the Internet and designed with open access in mind, it is not a good choice for highly sensitive data.  
• Free cloud storage solutions for Harvard affiliates to consider include:  Google Drive ,  DropBox , or  OneDrive ( up to DSL3 )  

Data Confidentiality and Secure Handling:  

• Data Security Levels at Harvard - Research Data Examples This resource provided by Harvard Data Security helps you determine what level of access is appropriate for your data. Determine whether it should be made available for public use, limited to the Harvard community, or be protected as either "confidential and sensitive," "high risk," or "extremely sensitive." See also:  Harvard Data Classification Table  
• Harvard's Best Practices for Protecting Privacy and  Harvard Information Security Collaboration Tools Matrix Follow the nuts-and-bolts advice for privacy best practices at Harvard. The latter resource reveals the level of security that can be relied upon for a large number of technological tools and platforms used at Harvard to conduct business, such as email, Slack, Accellion Kiteworks, OneDrive/SharePoint, etc.  
• “Protecting Participant Privacy While Maintaining Content and Context: Challenges in Qualitative Data De‐identification and Sharing.” Proceedings of the ASIST Annual Meeting 57 (1) (2020): e415-420 by Myers, Long, and Polasek Presents an informed and tested protocol, based on the De-Identification guidelines published by the Qualitative Data Repository (QDR) at Syracuse University. Qualitative researchers may consult it to guide their data de-identification efforts.  
• QDS Qualitative Data Sharing Toolkit The Qualitative Data Sharing (QDS) project and its toolkit was funded by the NIH National Human Genome Research Institute (R01HG009351). It provides tools and resources to help researchers, especially those in the health sciences, share qualitative research data while protecting privacy and confidentiality. It offers guidance on preparing data for sharing through de-identification and access control. These health sciences research datasets in ICPSR's Qualitative Data Sharing (QDS) Project Series were de-identified using the QuaDS Software and the project’s QDS guidelines.  
• Table of De-Identification Techniques  
• Generative AI Harvard-affiliated researchers should not enter data classified as confidential ( Level 2 and above ), including non-public research data, into publicly-available generative AI tools, in accordance with the University’s Information Security Policy. Information shared with generative AI tools using default settings is not private and could expose proprietary or sensitive information to unauthorized parties.  
• Harvard Information Security Quick Reference Guide Storage guidelines, based on the data's security classification level (according to its IRB classification) is displayed on page 2, under "handling."  
• Email Encryption Harvard Microsoft 365 users can now send encrypted messages and files directly from the Outlook web or desktop apps. Encrypting an email adds an extra layer of security to the message and its attachments (up to 150MB), and means only the intended recipient (and their inbox delegates with full access) can view it. Message encryption in Outlook is approved for sending high risk ( level 4 ) data and below.  

Sharing Qualitative Data:  

• Repositories for Qualitative Data If you have cleared this intention with your IRB, secured consent from participants, and properly de-identified your data, consider sharing your interviews in one of the data repositories included in the link above. Depending on the nature of your research and the level of risk it may present to participants, sharing your interview data may not be appropriate. If there is any chance that sharing such data will be desirable, you will be much better off if you build this expectation into your plans from the beginning.  
• Guide for Sharing Qualitative Data at ICPSR The Inter-university Consortium for Political and Social Research (ICPSR) has created this resource for investigators planning to share qualitative data at ICPSR. This guide provides an overview of elements and considerations for archiving qualitative data, identifies steps for investigators to follow during the research life cycle to ensure that others can share and reuse qualitative data, and provides information about exemplars of qualitative data  

International Projects:

• Research Compliance Program for FAS/SEAS at Harvard The Faculty of Arts and Sciences (FAS), including the School of Engineering and Applied Sciences (SEAS), and the Office of the Vice Provost for Research (OVPR) have established a shared Research Compliance Program (RCP). An area of common concern for interview studies is international projects and collaboration . RCP is a resource to provide guidance on which international activities may be impacted by US sanctions on countries, individuals, or entities and whether licenses or other disclosure are required to ship or otherwise share items, technology, or data with foreign collaborators.

Finding Extant Interview Data

Finding journalistic interviews:  .

• Academic Search Premier This all-purpose database is great for finding articles from magazines and newspapers. In the Advanced Search, it allows you to specify "Document Type":  Interview.  
• Guide to Newspapers and Newspaper Indexes Use this guide created to Harvard Librarians to identify newspapers collections you'd like to search. To locate interviews, try adding the term  "interview"  to your search, or explore a database's search interface for options to  limit your search to interviews.  Nexis Uni  and  Factiva  are the two main databases for current news.   
• Listen Notes Search for podcast episodes at this podcast aggregator, and look for podcasts that include interviews. Make sure to vet the podcaster for accuracy and quality! (Listen Notes does not do much vetting.)  
• NPR  and  ProPublica  are two sites that offer high-quality long-form reporting, including journalistic interviews, for free.

Finding Oral History and Social Research Interviews:  

• To find oral histories, see the Oral History   page of this guide for helpful resources on Oral History interviewing.  
• Repositories for Qualitative Data It has not been a customary practice among qualitative researchers in the social sciences to share raw interview data, but some have made this data available in repositories, such as the ones listed on the page linked above. You may find published data from structured interview surveys (e.g., questionnaire-based computer-assisted telephone interview data), as well as some semi-structured and unstructured interviews.  
• If you are merely interested in studies interpreting data collected using interviews, rather than finding raw interview data, try databases like  PsycInfo ,  Sociological Abstracts , or  Anthropology Plus , among others. 

Finding Interviews in Archival Collections at Harvard Library:

In addition to the databases and search strategies mentioned under the  "Finding Oral History and Social Research Interviews" category above,  you may search for interviews and oral histories (whether in textual or audiovisual formats) held in archival collections at Harvard Library.

• HOLLIS searches all documented collections at Harvard, whereas HOLLIS for Archival Discovery searches only those with finding aids. Although HOLLIS for Archival Discovery covers less material, you may find it easier to parse your search results, especially when you wish to view results at the item level (within collections). Try these approaches:

Search in  HOLLIS :  

• To retrieve items available online, do an Advanced Search for  interview* OR "oral histor*" (in Subject), with Resource Type "Archives/Manuscripts," then refine your search by selecting "Online" under "Show Only" on the right of your initial result list.  Revise the search above by adding your topic in the Keywords or Subject field (for example:  African Americans ) and resubmitting the search.  
•  To enlarge your results set, you may also leave out the "Online" refinement; if you'd like to limit your search to a specific repository, try the technique of searching for  Code: Library + Collection on the "Advanced Search" page .   

Search in  HOLLIS for Archival Discovery :  

• To retrieve items available online, search for   interview* OR "oral histor*" limited to digital materials . Revise the search above by adding your topic (for example:  artist* ) in the second search box (if you don't see the box, click +).  
• To preview results by collection, search for  interview* OR "oral histor*" limited to collections . Revise the search above by adding your topic (for example:  artist* ) in the second search box (if you don't see the box, click +). Although this method does not allow you to isolate digitized content, you may find the refinement options on the right side of the screen (refine by repository, subject or names) helpful.  Once your select a given collection, you may search within it  (e.g., for your topic or the term interview).

UX & MARKET RESEARCH INTERVIEWS

Ux at harvard library  .

• User Experience and Market Research interviews can inform the design of tangible products and services through responsive, outcome-driven insights. The  User Research Center  at Harvard Library specializes in this kind of user-centered design, digital accessibility, and testing. They also offer guidance and  resources  to members of the Harvard Community who are interested in learning more about UX methods. Contact [email protected] or consult the URC website for more information.

Websites  

• User Interviews: The Beginner’s Guide (Chris Mears)  
• Interviewing Users (Jakob Nielsen)

Books  

• Interviewing Users: How to Uncover Compelling Insights by Steve Portigal; Grant McCracken (Foreword by)  Interviewing is a foundational user research tool that people assume they already possess. Everyone can ask questions, right? Unfortunately, that's not the case. Interviewing Users provides invaluable interviewing techniques and tools that enable you to conduct informative interviews with anyone. You'll move from simply gathering data to uncovering powerful insights about people.  
• Rapid Contextual Design by Jessamyn Wendell; Karen Holtzblatt; Shelley Wood  This handbook introduces Rapid CD, a fast-paced, adaptive form of Contextual Design. Rapid CD is a hands-on guide for anyone who needs practical guidance on how to use the Contextual Design process and adapt it to tactical projects with tight timelines and resources. Rapid Contextual Design provides detailed suggestions on structuring the project and customer interviews, conducting interviews, and running interpretation sessions. The handbook walks you step-by-step through organizing the data so you can see your key issues, along with visioning new solutions, storyboarding to work out the details, and paper prototype interviewing to iterate the design all with as little as a two-person team with only a few weeks to spare *Includes real project examples with actual customer data that illustrate how a CD project actually works.

Videos  

Instructional Presentations on Interview Skills  

• Interview/Oral History Research for RSRA 298B: Master's Thesis Reading and Research (Spring 2023) Slideshow covers: Why Interviews?, Getting Context, Engaging Participants, Conducting the Interview, The Interview Guide, Note Taking, Transcription, File management, and Data Analysis.  
• Interview Skills From an online class on February 13, 2023:  Get set up for interview research. You will leave prepared to choose among the three types of interviewing methods, equipped to develop an interview schedule, aware of data management options and their ethical implications, and knowledgeable of technologies you can use to record and transcribe your interviews. This workshop complements Intro to NVivo, a qualitative data analysis tool useful for coding interview data.

NIH Data Management & Sharing Policy (DMSP) This policy, effective January 25, 2023, applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of  scientific data , including NIH-funded qualitative research. Click here to see some examples of how the DMSP policy has been applied in qualitative research studies featured in the 2021 Qualitative Data Management Plan (DMP) Competition . As a resource for the community, NIH has developed a resource for developing informed consent language in research studies where data and/or biospecimens will be stored and shared for future use. It is important to note that the DMS Policy does NOT require that informed consent obtained from research participants must allow for broad sharing and the future use of data (either with or without identifiable private information). See the FAQ for more information.

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Except where otherwise noted, this work is subject to a Creative Commons Attribution 4.0 International License , which allows anyone to share and adapt our material as long as proper attribution is given. For details and exceptions, see the Harvard Library Copyright Policy ©2021 Presidents and Fellows of Harvard College.

What is Qualitative in Qualitative Research

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

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• Patrik Aspers 1 , 2 &
• Ugo Corte 3  

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

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

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

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

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

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

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

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

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

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

Towards a Definition of Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Analysis – What is Qualitative Research?

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

Qualitative and Quantitative

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

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

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

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

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

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

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

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

Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

Grounded Theory

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

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

Defining Qualitative Research

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

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

Distinctions

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

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

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

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

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

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

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

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

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

Improved Understanding

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

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

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

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

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

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

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

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

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

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

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

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

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

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Acknowledgements

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

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How does the external context affect an implementation processes? A qualitative study investigating the impact of macro-level variables on the implementation of goal-oriented primary care

• Ine Huybrechts   ORCID: orcid.org/0000-0003-0288-1756 1 , 2 ,
• Anja Declercq 3 , 4 ,
• Emily Verté 1 , 2 ,
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Although the importance of context in implementation science is not disputed, knowledge about the actual impact of external context variables on implementation processes remains rather fragmented. Current frameworks, models, and studies merely describe macro-level barriers and facilitators, without acknowledging their dynamic character and how they impact and steer implementation. Including organizational theories in implementation frameworks could be a way of tackling this problem. In this study, we therefore investigate how organizational theories can contribute to our understanding of the ways in which external context variables shape implementation processes. We use the implementation process of goal-oriented primary care in Belgium as a case.

A qualitative study using in-depth semi-structured interviews was conducted with actors from a variety of primary care organizations. Data was collected and analyzed with an iterative approach. We assessed the potential of four organizational theories to enrich our understanding of the impact of external context variables on implementation processes. The organizational theories assessed are as follows: institutional theory, resource dependency theory, network theory, and contingency theory. Data analysis was based on a combination of inductive and deductive thematic analysis techniques using NVivo 12.

Institutional theory helps to understand mechanisms that steer and facilitate the implementation of goal-oriented care through regulatory and policy measures. For example, the Flemish government issued policy for facilitating more integrated, person-centered care by means of newly created institutions, incentives, expectations, and other regulatory factors. The three other organizational theories describe both counteracting or reinforcing mechanisms. The financial system hampers interprofessional collaboration, which is key for GOC. Networks between primary care providers and health and/or social care organizations on the one hand facilitate GOC, while on the other hand, technology to support interprofessional collaboration is lacking. Contingent variables such as the aging population and increasing workload and complexity within primary care create circumstances in which GOC is presented as a possible answer.

Conclusions

Insights and propositions that derive from organizational theories can be utilized to expand our knowledge on how external context variables affect implementation processes. These insights can be combined with or integrated into existing implementation frameworks and models to increase their explanatory power.

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Knowledge on how external context variables affect implementation processes tends to be rather fragmented. Insights on external context in implementation research often remain limited to merely describing macro-context barriers and facilitators.

Organizational theories contribute to our understanding on the impact of external context to an implementation process by explaining the complex interactions between organizations and their environments.

Findings can be utilized to help explain the mechanism of change in an implementation process and can be combined with or integrated into existing implementation frameworks and models to gain a broader picture on how external context affects implementation processes.

In this study, we integrate organizational theories to provide a profound analysis on how external context influences the implementation of complex interventions. There is a growing recognition that the context in which an intervention takes place highly influences implementation outcomes [ 1 , 2 ]. Despite its importance, researchers are challenged by the lack of a clear definition of context. Most implementation frameworks and models do not define context as such, but describe categories or elements of context, without capturing it as a whole [ 2 , 3 ]. Studies often distinguish between internal and external context: micro- and meso-level internal context variables are specific to a person, team, or organization. Macro-level external context variables consist of variables on a broader, socio-economic and policy level that are beyond one’s control [ 4 ].

Overall, literature provides a rather fragmented and limited perspective on how external context influences the implementation process of a complex intervention. Attempts are made to define, categorize, and conceptualize external context [ 5 , 6 ]. Certain implementation frameworks and models specifically mention external context, such as the conceptual model of evidence-based practice implementation in public service sectors [ 7 ], the Consolidated Framework for Implementation Research [ 8 ], or the i-PARiHS framework [ 9 ]. However, they remain limited to identifying and describing external context variables. Few studies are conducted that specifically point towards the actual impact of macro-level barriers and facilitators [ 10 , 11 , 12 ] but only provide limited insights in how these shape an implementation process. Nonetheless, external contextual variables can be highly disruptive for an organization’s implementation efforts, for example, when fluctuations in funding occur or when new legislation or technology is introduced [ 13 ]. In order to build a more comprehensive view on external context influences, we need an elaborative theoretical perspective.

Organizational theories as a frame of reference

To better understand how the external context affects the implementation process of a primary care intervention, we build upon research of Birken et al. [ 13 ] who demonstrate the explanatory power of organizational theories. Organizational theories can help explain the complex interactions between organizations and their environments [ 13 ], providing understanding on the impact of external context on the mechanism of change in an implementation process. We focus on three of the theories Birken et al. [ 8 ] put forward: institutional theory, resource dependency theory, and contingency theory. We also include network theory in recognition of the importance of interorganizational context and social ties between various actors, especially in primary care settings which are characterized by a multitude of diverse actors (meaning: participants of a process).

These four organizational theories demonstrate the ways in which organizations interact with their external environment in order to sustain and fulfill their core activities. All four of them do this with a different lens. Institutional theory states that an organization will aim to fulfil the expectations, values, or norms that are posed upon them in order to achieve a fit with their environment [ 14 ]. This theory helps to understand the relationships between organizations and actors and the institutional context in which they operate. Institutions can broadly be defined as a set of expectations for social or organizational behavior that can take the form formal structures such as regulatory entities, legislation, or procedures [ 15 ]. Resource dependency theory explains actions and decisions of organizations in terms of their dependence on critical and important resources. It postulates that organizations will respond to their external environment to secure the resources they need to operate [ 16 , 17 ]. This theory helps to gain insight in how fiscal variables can shape the adoption of an innovation. Contingency theory presupposes that an organizations’ effectiveness depends on the congruence between situational factors and organizational characteristics [ 18 ]. External context variables such as social and economic change and pressure can impact the way in which an innovation will be integrated. Lastly, network theory in its broader sense underlines the strength of networks: collaborating in networks can establish an effectiveness in which outcomes are achieved that could not be realized by individual organizations acting independently. Networks are about connecting or sharing information, resources, activities, and competences of three or more organizations aiming to achieve a shared goal or outcome [ 19 , 20 ]. Investigating networks helps to gain understanding of the importance of the interorganizational context and how social ties between organizations affect the implementation process of a complex intervention.

Goal-oriented care in Flanders as a case

In this study, we focus on the implementation of the approach goal-oriented care (GOC) in primary care in Flanders, the Dutch-speaking region in Belgium. Primary care is a highly institutionalized and regulated setting with a high level of professionalism. Healthcare organizations can be viewed as complex adaptive systems that are increasingly interdependent [ 21 ]. The primary care landscape in Flanders is characterized by many primary care providers (PCPs) being either self-employed or working in group practices or community health centers. They are organized and financed at different levels (federal, regional, local). In 2015–2019, a primary care reform was initiated in Flanders in which the region was geographically divided into 60 primary care zones that are governed by care councils. The Flemish Institute of Primary Care was created as a supporting institution aiming to strengthen the collaboration between primary care health and welfare actors. The complex and multisectoral nature of primary care in Flanders forms an interesting setting to gain understanding in how macro-level context variables affect implementation processes.

The concept of GOC implies a paradigm shift [ 22 ] that shifts away from a disease or problem-oriented focus towards a person-centered focus that departs from “what matters to the patient.” Boeykens et al. [ 23 ] state in their concept analysis that GOC could be described as a healthcare approach encompassing a multifaceted, dynamic, and iterative process underpinned by the patient’s context and values. The process is characterized by three stages: goal elicitations, goal setting, and goal evaluation in which patients’ needs and preferences form the common thread. It is an approach in which PCPs and patients collaborate to identify personal life goals and to align care with those goals [ 23 ]. An illustration of how this manifests at individual level can be found in Table 1 . The concept of GOC was incorporated in Flemish policies and included in the primary care reform in 2015–2019. It has gained interest in research and policy as a potential catalyst for integrated care [ 24 ]. As such, the implementation of GOC in Flanders provides an opportunity to investigate the external context of a complex primary care intervention. Our main research question is as follows: what can organizational theories tell us about the influence of external context variables on the implementation process of GOC?

We assess the potential of four organizational theories to enrich our understanding of the impact of external context variables on implementation processes. The organizational theories assessed are as follows: institutional theory, resource dependency theory, network theory, and contingency theory. Qualitative research methods are most suitable to investigate such complex matters, as they can help answer “how” and “why” questions on implementation [ 25 ]. We conducted online, semi-structured in-depth interviews with various primary care actors. These actors all had some level of experience at either meso- or micro-level with GOC implementation efforts.

Sample selection

For our purposive sample, we used the following inclusion criteria: 1) working in a Flemish health/social care context in which initiatives are taken to implement GOC and 2) having at least 6 months of experience. For recruitment, we made an overview of all possible stakeholders that are active in GOC by calling upon the network of the Primary Care Academy (PCA) Footnote 1 . Additionally, a snowballing approach was used in which respondents could refer to other relevant stakeholders at the end of each interview. This leads to respondents with different backgrounds (not only medical) and varying roles, such as being a staff member, project coordinator, or policy maker. We aimed at a maximum variation in the type of organizations which were represented by respondents, such as different governmental institutions and a variety of healthcare/social care organizations. In some cases, paired interviews were conducted [ 26 ] if the respondents were considered complementary in terms of expertise, background, and experience with the topic. An information letter and a request to participate was send to each stakeholder by e-mail. One reminder was sent in case of nonresponse.

Data collection

Interviews were conducted between January and June 2022 by a sociologist trained in qualitative research methods. Interviewing took place online using the software Microsoft Teams and were audio-recorded and transcribed verbatim. A semi-structured interview guide was used, which included (1) an exploration of the concept of GOC and how the respondent relates to this topic, (2) questions on how GOC became a topic of interest and initiatives within the respondent’s setting, and (3) the perceived barriers and facilitators for implementation. An iterative approach was used between data collection and data analysis, meaning that the interview guide underwent minor adjustments based on proceeding insights from earlier interviews in order to get richer data.

Data analysis

All data were thematically analyzed, both inductively and deductively, supported by the software NVivo 12©. For the inductive part, implicit and explicit ideas within the qualitative data were identified and described [ 27 ]. The broader research team, with backgrounds in sociology, medical sciences, and social work, discussed these initial analyses and results. The main researcher then further elaborated this into a broad understanding. This was followed by a deductive part, in which characteristics and perspectives from organizational theories were used as sensitizing concepts, inspired by research from Birken et al. [ 13 ]. This provided a frame of reference and direction, adding interpretive value to our analysis [ 28 ]. These analyses were subject of peer debriefing with our cooperating research team to validate whether these results aligned with their knowledge of GOC processes. This enhances the trustworthiness and credibility of our results [ 29 , 30 ]. Data analysis was done in Dutch, but illustrative quotes were translated into English.

In-depth interviews were performed with n = 23 respondents (see Table 2 ): five interviews were duo interviews, and one interview took place with n = 3 respondents representing one organization. We had n = 6 refusals: n = 3 because of time restraints, n = 1 did not feel sufficiently knowledgeable about the topic, n = 1 changed professional function, and there was n = 1 nonresponse. Respondents had various ways in which they related towards the macro-context: we included actors that formed part of external context (e.g., the Flemish Agency of Care and Health), actors that facilitate and strengthen organizations in the implementation of GOC (e.g., the umbrella organization for community health centers), and actors that actively convey GOC inside and outside their setting (e.g., an autonomous and integral home care service). Interviews lasted between 47 and 72 min. Table 3 gives an overview on the main findings of our deductive analysis with their respective links to the propositions of each of the organizational theories that we applied as a lens.

Institutional theory: laying foundations for a shift towards GOC

For the implementation of GOC in primary care, looking at the data with an institutional theory lens helps us understand the way in which primary care organizations will respond to social structures surrounding them. Institutional theory describes the influence of institutions, which give shape to organizational fields: “organizations that, in the aggregate, constitute a recognized area of institutional life [ 31 ], p. 148. Prevailing institutions within primary care in Flanders can affect how organizations within such organizational fields fulfil their activities. Throughout our interviews, we recognized several dynamics that are being described in institutional theory.

First of all, the changing landscape of primary care in Flanders (see 1.2) was often brought up as a dynamic in which GOC is intertwined with other changes. Respondents mention an overall tendency to reform primary care to becoming more integrated and the ideas of person-centered care becoming more upfront. These expectations in how primary care should be approached seem to affect the organizational field of primary care: “You could tell that in people’s minds they are ready to look into what it actually means to put the patient, the person central. — INT01” Various policy actors are committed to further steer towards these approaches: “the government has called it the direction that we all have to move towards. — INT23” It was part of the foundations for the most recent primary care reform, leading to the creation of demographic primary care zones governed by care councils and the Flemish Institute of Primary Care as supporting institution.

These newly established actors were viewed by our respondents as catalysts of GOC. They pushed towards the aims to depart from local settings and to establish connections between local actors. Overall, respondents emphasized their added value as they are close to the field and they truly connect primary care actors. “They [care councils] have picked up these concepts and have started working on it. At the moment they are truly the incubators and ecosystems, as they would call it in management slang. — INT04” For an innovation such as GOC to be diffused, they are viewed as the ideal actors who can function as a facilitator or conduit. They are uniquely positioned as they are closely in contact with the practice field and can be a top-down conduit for governmental actors but also are able to address the needs from bottom-up. “In this respect, people look at the primary care zones as the ideal partners. […] We can start bringing people together and have that helicopter view: what is it that truly connects you? — INT23” However, some respondents also mentioned their difficult governance structure due to representation of many disciplines and organizations.

Other regulatory factors were mentioned by respondents were other innovations or changes in primary care that were intentionally linked to GOC: e.g., the BelRAI Footnote 2 or Flemish Social Protection Footnote 3 . “The government also provides incentives. For example, family care services will gradually be obliged to work with the BelRAI screener. This way, you actually force them to start taking up GOC. — INT23” For GOC to be embedded in primary care, links with other regulatory requirements can steer PCPs towards GOC. Furthermore, it was sometimes mentioned that an important step would be for the policy level to acknowledge GOC as quality of care and to include the concept in quality standards. This would further formalize and enforce the institutional expectation to go towards person-centered care.

Currently, a challenge on institutional level as viewed by most respondents is that GOC is not or only to a limited extent incorporated in the basic education of most primary care disciplines. This leads to most of PCPs only having a limited understanding of GOC and different disciplines not having a shared language in this matter. “You have these primary health and welfare actors who each have their own approach, history and culture. To bring them together and to align them is challenging. — INT10” The absence of GOC as a topic in basic education is mentioned by various respondents as a current shortcoming in effectively implementing GOC in the wider primary care landscape.

Overall, GOC is viewed as our respondents as a topic that has recently gained a lot interest, both by individual PCPS, organizations, and governmental actors. The Flemish government has laid some foundations to facilitate this change with newly created institutions and incentives. However, other external context variables can interfere in how the concept of GOC is currently being picked up and what challenges arise.

Resource dependency theory: in search for a financial system that accommodates interprofessional collaboration

Another external context variable that affects how GOC can be introduced is the financial system that is at place. To analyze themes that were raised during the interviews with regard to finances, we utilized a resource dependency perspective. This theory presumes that organizations are dependent on financial resources and are seeking ways to ensure their continued functioning [ 16 , 17 ]. To a certain extent, this collides with the assumptions of institutional theory that foregrounds organization’s conformity to institutional pressures [ 32 ]. Resource dependency theory in contrast highlights differentiation of organizations that seek out competitive advantages [ 32 ].

In this context, respondents mention that their interest and willingness to move towards a GOC approach are held back by the current dominant system of pay for performance in the healthcare system. This financial system is experienced as restrictive, as it does not provide any incentive to PCPs for interprofessional collaboration, which is key for GOC. A switch to a flat fee system (in which a fixed fee is charged for each patient) or bundled payment was often mentioned as desirable. PCPs and health/social care organizations working in a context where they are financially rewarded for a trajectory or treatment of a patient in its entirety ensure that there is no tension with their necessity to obtain financial resources, as described in the resource dependency theory. Many of our respondents voice that community health centers are a good example. They cover different healthcare disciplines and operate with a fixed price per enrolled patient, regardless of the number of services for that patient. This promotes setting up preventive and health-promoting actions, which confirms our finding on the relevance of dedicated funding.

At the governmental level, the best way to finance and give incentives is said to be a point of discussion: “For years, we have been arguing about how to finance. Are we going to fund counsel coordination? Or counsel organization? Or care coordination? — INT04” Macro-level respondents do however mention financial incentives that are already in place to stimulate interprofessional collaboration: fees for multidisciplinary consultation being the most prominent. Other examples were given in which certain requirements were set for funding (e.g., Impulseo Footnote 4 , VIPA Footnote 5 ) that stimulate actors or settings in taking steps towards more interprofessional collaboration.

Nowadays, financial incentives to support organizations to engage in GOC tend to be project grants. However, a structural way to finance GOC approaches is currently lacking, according to our respondents. As a consequence, a long-term perspective for organizations is lacking; there is no stable financing and organizations are obliged to focus on projects instead of normalizing GOC in routine practice. According to a resource dependency perspective, the absence of financial incentives for practicing GOC hinders organizations in engaging with the approach, as they are focused on seeking out resources in order to fulfil their core activities.

A network-theory perspective: the importance of connectedness for the diffusion of an innovation

Throughout the interviews, interorganizational contextual elements were often addressed. A network theory lens states that collaborating in networks can lead to outcomes that could not be realized by individual organizations acting independently [ 19 , 20 ]. Networks consist of a set of actors such as PCPs or health/social care organizations along with a set of ties that link them [ 33 ]. These ties can be state-type ties (e.g., role based, cognitive) or event-type ties (e.g., through interactions, transactions). Both type of ties can enable a flow in which information or innovations can pass, as actors interact [ 33 ]. To analyze the implementation process of GOC and how this is diffused through various actors, a network theory perspective can help understand the importance of the connection between actors.

A first observation throughout the interviews in which we notice the importance of networks was in the mentioning of local initiatives that already existed before the creation of the primary care zones/care councils. In the area around Ghent, local multidisciplinary networks already organized community meetings, bringing together different PCPs on overarching topics relating to long-term care for patients with chronic conditions. These regions have a tradition of collaboration and connectedness of PCPs, which respondents mention to be highly valuable: “This ensures that we are more decisive, speaking from one voice with regards to what we want to stand for. — INT23” Respondents voice that the existence of such local networks has had a positive effect on the diffusion of ideas such as GOC, as trust between different actors was already established.

Further mentioning of the importance of networks could be found in respondents acknowledging one of the presumptions of network theory: working collaboratively towards a specific objective leads to outcomes that cannot be realized independently. This is especially true for GOC, an approach that in essence requires different disciplines to work together: “When only one GP, nurse or social worker starts working on it, it makes no sense. Everyone who is involved with that person needs to be on board. Actually, you need to finetune teams surrounding a person — INT11.” This is why several policy-level respondents mentioned that emphasis was placed on organizing GOC initiatives in a neighborhood-oriented way, in which accessible, inclusive care is aimed at by strengthening social cohesion. This way, different types of PCPs got to know each other through these sessions an GOC and would start to get aligned on what it means to provide GOC. However, in particular, self-employed PCPs are hard to reach. According to our respondents, occupational groups and care councils are suitable actors to engage these self-employed PCPs, but they are not always much involved in such a network .

To better connect PCPs and health/social care organizations, the absence of connectedness through the technological landscape is also mentioned. Current technological systems and platforms for documenting patient information do not allow for aligning and sharing between disciplines. In Flanders, there is a history of each discipline developing its own software, which lacks centralization or unification: “For years, they have decided to just leave it to the market, in such a way that you ended up with a proliferation of software, each discipline having its own package. — INT06” Most of the respondents mentioning this were aware that Flanders government is currently working on a unified digital care and support platform and were optimistic about its development.

Contingency theory: how environmental pressure can be a trigger for change

Our interviews were conducted during a rather dynamic and unique period of time in which the impact of social change and pressure was clearly visible: the Flemish primary care reform was ongoing which leads to the creation of care councils and VIVEL (see 3.1.1), and the COVID crisis impacted the functioning of these and other primary care actors. These observed effects of societal changes are reminiscent of the assumptions that are made in contingency theory. In essence, contingency theory presupposes that “organizational effectiveness results from fitting characteristics of the organization, such as its structure, to contingencies that reflect the situation of the organization [ 34 ], p. 1.” When it comes to the effects of the primary care reform and the COVID crisis, there were several mentions on how primary care actors reorganized their activities to adapt to these circumstances. Representatives of care councils/primary care zones whom we interviewed underlined that they were just at the point where they could again engage with their original action plans, not having to take up so many COVID-related tasks anymore. On the one hand, the COVID crisis had however forced them to immediately become functional and has also contributed that various primary care actors quickly got to know them. On the other hand, the COVID crisis has also kept them from their core activities for a while. On top of that, the crisis has also triggered a change the overall view towards data sharing. Some respondents mention a rather protectionist approach towards data sharing, while data sharing has become more normalized during the COVID crisis. This discussion was also relevant for the creation of a unified shared patient record in terms of documenting and sharing patient goals.

Other societal factors that were mentioned having an impact on the uptake of GOC are the demographic composition of a certain area. It was suggested that areas that are characterized by a patient population with more chronic care needs will be more likely to steer towards GOC as a way of coping with these complex cases. “You always have these GPs who blow it away immediately and question whether this is truly necessary. They will only become receptive to this when they experience needs for which GOC can be a solution — INT11.” On a macro-level, several respondents have mentioned how a driver for change is to have the necessity for change becoming very tangible. As PCPs are confronted with increasing numbers of patients with complex, chronic needs and their work becomes more demanding, the need for change becomes more acute. This finding is in line with what contingency theory underlines: changes in contingency (e.g., the population that is increasingly characterized by aging and multimorbidity) are an impetus for change for health/social care organizations to resolve this by adopting a structure that better fits the current environmental characteristics [ 34 ].

Our research demonstrates the applicability of organizational theories to help explain the impact that macro-level context variables have on an implementation process. These insights can be integrated into existing implementation frameworks and models to add the explanatory power of macro-level context variables, which is to date often neglected. The organizational theories demonstrate the ways in which organizations interact with their external environment in order to sustain and fulfill their core activities. As demonstrated in Fig. 1 , institutional theory largely explains how social expectations in the form of institutions lead towards the adoption or implementation of innovation, such as GOC. However, other organizational theories demonstrate how other macro-context elements on different areas can either strengthen or hamper the implementation process.

How organizational theories can help explain the way in which macro-level context variables affect implementation of an intervention

Departing from the mechanisms that are postulated by institutional theory, we observed that the shift towards GOC is part of a larger Flemish primary care reform in which and new institutions have been established and polices have been drawn up to go towards more integrated, person-centered care. To achieve this, governmental actors have placed emphasis on socialization of care, the local context, and establishing ties between organizations in order to become more complementary in providing primary health care [ 35 ]. With various initiatives surrounding this aim, the Flemish government is steering towards GOC. This is reminiscent of the mechanisms that are posed within institutional theory: organizations adapt to prevailing norms and expectations and mimic behaviors that are surrounding them [ 15 , 36 ].

Throughout our data, we came across concrete examples of how institutionalization takes place. DiMaggio and Powell [ 31 ] describe the subsequent process of isomorphism: organizations start to resemble each other as they are conforming to their institutional environment. A first mechanism through which this change occurs is coercive isomorphism and is clearly noticeable in our data. This type of isomorphism results from both formal and informal pressure coming from organizations from which a dependency relationship exists and from cultural expectations in the society [ 31 ]. Person-centered, GOC care is both formally propagated by governmental institutions and procedures and informally expected by current social tendencies. Care councils within primary care zones explicitly propagate and disseminate ideas and approaches that are desirable on policy level. Another form of isomorphism is professional isomorphism and relates to our finding that incorporation of GOC in basic education is currently lacking. The presumptions of professional isomorphism back up the importance of this: values, norms, and ideas that are developed during education are bound to find entrance within organizations as professionals start operating along these views.

Although many observations in our data back up the assumptions of institutional theory, it should be noticed that new initiatives such as the promotion of person-centered care and GOC can collide with earlier policy trends. Martens et al. [ 12 ] have examined the Belgian policy process relating three integrated care projects and concluded that although there is a strong support for a change towards a more patient-centered system, the current provider-driven system and institutional design complicate this objective. Furthermore, institutional theory tends to simplify actors as passive adopters of institutional norms and expectations and overlook the human agency and sensemaking that come with it [ 37 ]. For GOC, it is particularly true that PCPs will actively have to seek out their own style and fit the approach in their own way of working. Moreover, GOC was not just addressed as a governmental expectation but for many PCPs something they inherently stood behind.

Resources dependency theory poses that organizations are dependent on critical resources and adapt their way of working in response to those resources [ 17 ]. From our findings, it seems that the current financial system does not promote GOC, meaning that the mechanisms that are put forward in resources dependency theory are not set in motion. A macro-level analysis of barriers and facilitators in the implementation of integrated care in Belgium by Danhieux et al. [ 10 ] also points towards the financial system and data sharing as two of the main contextual determinants that affect implementation.

Throughout our data, the importance of a network approach was frequently mentioned. Interprofessional collaboration came forward as a prerequisite to make GOC happen, as well as active commitment on different levels. Burns, Nembhard, and Shortell [ 38 ] argue that research efforts on implementing person-centered, integrated care should have more focus on the use of social networks to study relational coordination. In terms of interprofessional collaboration, to date, Belgium has a limited tradition of working team-based with different disciplines [ 35 ]. However, when it comes to strengthening a cohesive primary care network, the recently established care councils have become an important facilitator. As a network governance structure, they resemble mostly a Network Administrative Organization (NAO): a separate, centralized administrative entity that is externally governed and not another member providing its own services [ 19 ]. According to Provan and Kenis [ 19 ], this type of governance form is most effective in a rather dense network with many participants, when the goal consensus is moderately high, characteristics that are indeed representative for the Flemish primary care landscape. This strengthens our observation that care councils have favorable characteristics and are well-positioned to facilitate the interorganizational context to implement GOC.

Lastly, the presumptions within contingency theory became apparent as respondents talked about how the need for change needs to become tangible for PCPs and organizations to take action, as they are increasingly faced with a shortage of time and means and more complex patient profiles. Furthermore, De Maeseneer [ 39 ] affirms our findings that the COVID-19 crisis could be employed as an opportunity to strengthen primary health care, as health becomes prioritized and its functioning becomes re-evaluated. Overall, contingency theory can help gain insight in how and why certain policy trends or decisions are made. A study of Bruns et al. [ 40 ] found that modifiable external context variables such as interagency collaboration were predictive for policy support for intervention adoption, while unmodifiable external context variable such as socio-economic composition of a region was more predictive for fiscal investments that are made.

Strengths and limitations

This study contributes to our overall understanding of implementation processes by looking into real-life implementation efforts for GOC in Flanders. It goes beyond a mere description of external context variables that affect implementation processes but aims to grasp which and how external context variables influence implementation processes. A variety of respondents from different organizations, with different backgrounds and perspectives, were interviewed, and results were analyzed by researchers with backgrounds in sociology, social work, and medical sciences. Results can not only be applied to further develop sustainable implementation plans for GOC but also enhance our understanding of how the external context influences and shapes implementation processes. As most research on contextual variables in implementation processes has until now mainly focused on internal context variables, knowledge on external context variables contributes to gaining a bigger picture of the mechanism of change.

However, this study is limited to the Flemish landscape, and external context variables and their dynamics might differ from other regions or countries. Furthermore, our study has examined and described how macro-level context variables affect the overall implementation processes of GOC. Further research is needed on the link between outer and inner contexts during implementation and sustainment, as explored by Lengninck-Hall et al. [ 41 ]. Another important consideration is that our sample only includes the “believers” in GOC and those who are already taking steps towards its implementation. It is possible that PCPs themselves or other relevant actors who are more skeptical about GOC have a different view on the policy and organizational processes that we explored. Furthermore, data triangulations in which this data is complemented with document analysis could have expanded our understanding and verified subjective perceptions of respondents.

Insights and propositions that derive from organizational theories can be utilized to expand our knowledge on how external context variables affect implementation processes. Our research demonstrates that the implementation of GOC in Flanders is steered and facilitated by regulatory and policy variables, which sets in motion mechanisms that are described in institutional theory. However, other external context variables interact with the implementation process and can further facilitate or hinder the overall implementation process. Assumptions and mechanisms explained within resource dependency theory, network theory, and contingency theory contribute to our understanding on how fiscal, technological, socio-economic, and interorganizational context variables affect an implementation process.

Availability of data and materials

The datasets generated and/or analyzed during the current study are not publicly available due to confidentiality guaranteed to participants but are available from the corresponding author on reasonable request.

The Primary Care Academy (PCA) is a research and teaching network of four Flemish universities, six university colleges, the White and Yellow Cross (an organization for home nursing), and patient representatives that have included GOC as one of their main research domains.

BelRAI, the Belgian implementation of the interRAI assessment tools; these are scientific, internationally validated instruments enabling an assessment of social, psychological, and physical needs and possibilities of individuals in different care settings. The data follows the person and is shared between care professionals and care organizations.

The Flemish Social Protection is a mandatory insurance established by the Flemish government to provide a range of concessions to individuals with long-term care and support needs due to illness or disability.

Impulseo, financial support for general practitioners who start an individual practice or join a group practice

VIPA, grants for the realization of sustainable, accessible, and affordable healthcare infrastructure

Abbreviations

• Goal-oriented care

Primary care provider

Primary Care Academy

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Acknowledgements

We are grateful for the partnership with the Primary Care Academy (academie-eerstelijn.be) and want to thank the King Baudouin Foundation and Fund Daniël De Coninck for the opportunity they offer us for conducting research and have impact on the primary care of Flanders, Belgium. The consortium of the Primary Care Academy consists of the following: lead author: Roy Remmen—[email protected]—Department of Primary Care and Interdisciplinary Care, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; Emily Verté—Department of Primary Care and Interdisciplinary Care, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium, and Department of Family Medicine and Chronic Care, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussel, Belgium; Muhammed Mustafa Sirimsi—Centre for Research and Innovation in Care, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; Peter Van Bogaert—Workforce Management and Outcomes Research in Care, Faculty of Medicine and Health Sciences, University of Antwerp, Belgium; Hans De Loof—Laboratory of Physio-Pharmacology, Faculty of Pharmaceutical Biomedical and Veterinary Sciences, University of Antwerp, Belgium; Kris Van den Broeck—Department of Primary Care and Interdisciplinary Care, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; Sibyl Anthierens—Department of Primary Care and Interdisciplinary Care, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; Ine Huybrechts—Department of Primary Care and Interdisciplinary Care, Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; Peter Raeymaeckers—Department of Sociology, Faculty of Social Sciences, University of Antwerp, Belgium; Veerle Bufel—Department of Sociology, Centre for Population, Family and Health, Faculty of Social Sciences, University of Antwerp, Belgium; Dirk Devroey—Department of Family Medicine and Chronic Care, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussel; Bert Aertgeerts—Academic Centre for General Practice, Faculty of Medicine, KU Leuven, Leuven, and Department of Public Health and Primary Care, Faculty of Medicine, KU Leuven, Leuven; Birgitte Schoenmakers—Department of Public Health and Primary Care, Faculty of Medicine, KU Leuven, Leuven, Belgium; Lotte Timmermans—Department of Public Health and Primary Care, Faculty of Medicine, KU Leuven, Leuven, Belgium; Veerle Foulon—Department of Pharmaceutical and Pharmacological Sciences, Faculty Pharmaceutical Sciences, KU Leuven, Leuven, Belgium; Anja Declercq—LUCAS-Centre for Care Research and Consultancy, Faculty of Social Sciences, KU Leuven, Leuven, Belgium; Dominique Van de Velde, Department of Rehabilitation Sciences, Occupational Therapy, Faculty of Medicine and Health Sciences, University of Ghent, Belgium, and Department of Occupational Therapy, Artevelde University of Applied Sciences, Ghent, Belgium; Pauline Boeckxstaens—Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, University of Ghent, Belgium; An De Sutter—Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, University of Ghent, Belgium; Patricia De Vriendt—Department of Rehabilitation Sciences, Occupational Therapy, Faculty of Medicine and Health Sciences, University of Ghent, Belgium, and Frailty in Ageing (FRIA) Research Group, Department of Gerontology and Mental Health and Wellbeing (MENT) Research Group, Faculty of Medicine and Pharmacy, Vrije Universiteit, Brussels, Belgium, and Department of Occupational Therapy, Artevelde University of Applied Sciences, Ghent, Belgium; Lies Lahousse—Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium; Peter Pype—Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, University of Ghent, Belgium, End-of-Life Care Research Group, Faculty of Medicine and Health Sciences, Vrije Universiteit Brussel and Ghent University, Ghent, Belgium; Dagje Boeykens—Department of Rehabilitation Sciences, Occupational Therapy, Faculty of Medicine and Health Sciences, University of Ghent, Belgium, and Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, University of Ghent, Belgium; Ann Van Hecke—Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, University of Ghent, Belgium, University Centre of Nursing and Midwifery, Faculty of Medicine and Health Sciences, University of Ghent, Belgium; Peter Decat—Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, University of Ghent, Belgium; Rudi Roose—Department of Social Work and Social Pedagogy, Faculty of Psychology and Educational Sciences, University Ghent, Belgium; Sandra Martin—Expertise Centre Health Innovation, University College Leuven-Limburg, Leuven, Belgium; Erica Rutten—Expertise Centre Health Innovation, University College Leuven-Limburg, Leuven, Belgium; Sam Pless—Expertise Centre Health Innovation, University College Leuven-Limburg, Leuven, Belgium; Anouk Tuinstra—Expertise Centre Health Innovation, University College Leuven-Limburg, Leuven, Belgium; Vanessa Gauwe—Department of Occupational Therapy, Artevelde University of Applied Sciences, Ghent, Belgium; Didier ReynaertE-QUAL, University College of Applied Sciences Ghent, Ghent, Belgium; Leen Van Landschoot—Department of Nursing, University of Applied Sciences Ghent, Ghent, Belgium; Maja Lopez Hartmann—Department of Welfare and Health, Karel de Grote University of Applied Sciences and Arts, Antwerp, Belgium; Tony Claeys—LiveLab, VIVES University of Applied Sciences, Kortrijk, Belgium; Hilde Vandenhoudt—LiCalab, Thomas University of Applied Sciences, Turnhout, Belgium; Kristel De Vliegher—Department of Nursing–Homecare, White-Yellow Cross, Brussels, Belgium; and Susanne Op de Beeck—Flemish Patient Platform, Heverlee, Belgium.

This research was funded by fund Daniël De Coninck, King Baudouin Foundation, Belgium. The funder had no involvement in this study. Grant number: 2019-J5170820-211,588.

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Peter Raeymaeckers and Sibyl Anthierens have contributed equally to this work and share senior last authorship.

Authors and Affiliations

Department of Family Medicine and Population Health, University of Antwerp, Doornstraat 331, 2610, Antwerp, Belgium

Ine Huybrechts, Emily Verté & Sibyl Anthierens

Department of Family Medicine and Chronic Care, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090, Jette/Brussels, Belgium

Ine Huybrechts & Emily Verté

LUCAS — Centre for Care Research and Consultancy, KU Leuven, Minderbroedersstraat 8/5310, 3000, Leuven, Belgium

Anja Declercq

Center for Sociological Research, Faculty of Social Sciences, KU Leuven, Parkstraat 45/3601, 3000, Leuven, Belgium

Department of Social Work, University of Antwerp, St-Jacobstraat 2, 2000, Antwerp, Belgium

Peter Raeymaeckers

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• , Emily Verté
• , Muhammed Mustafa Sirimsi
• , Peter Van Bogaert
• , Hans De Loof
• , Kris Van den Broeck
• , Sibyl Anthierens
• , Ine Huybrechts
• , Peter Raeymaeckers
• , Veerle Bufel
• , Dirk Devroey
• , Bert Aertgeerts
• , Birgitte Schoenmakers
• , Lotte Timmermans
• , Veerle Foulon
• , Anja Declerq
• , Dominique Van de Velde
• , Pauline Boeckxstaens
• , An De Sutter
• , Patricia De Vriendt
• , Lies Lahousse
• , Peter Pype
• , Dagje Boeykens
• , Ann Van Hecke
• , Peter Decat
• , Rudi Roose
• , Sandra Martin
• , Erica Rutten
• , Sam Pless
• , Anouk Tuinstra
• , Vanessa Gauwe
• , Leen Van Landschoot
• , Maja Lopez Hartmann
• , Tony Claeys
• , Hilde Vandenhoudt
• , Kristel De Vliegher
•  & Susanne Op de Beeck

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IH wrote the main manuscript text. AD, EV, PR, and SA contributed to the different steps of the making of this manuscript. All authors reviewed the manuscript.

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Correspondence to Ine Huybrechts .

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The study protocol was approved by the Medical Ethics Committee of the University of Antwerp/Antwerp University Hospital (reference: 2021-1690). All participants received verbal and written information about the purpose and methods of the study and gave written informed consent.

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Huybrechts, I., Declercq, A., Verté, E. et al. How does the external context affect an implementation processes? A qualitative study investigating the impact of macro-level variables on the implementation of goal-oriented primary care. Implementation Sci 19 , 32 (2024). https://doi.org/10.1186/s13012-024-01360-0

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• Contingency theory
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‘Enough is enough’: a mixed methods study on the key factors driving UK NHS nurses’ decision to strike

• Daniel Sanfey 1  

BMC Nursing volume  23 , Article number:  247 ( 2024 ) Cite this article

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The UK National Health Service (NHS) is one of the largest employers in the world and employs around 360,000 registered nurses. Following a protracted pay dispute in December 2022 NHS nurses engaged in industrial action resulting in the largest nurse strikes in the 74-year history of the NHS. Initially it appeared these strikes were a direct consequence of pay disputes but evidence suggests that the situation was more complex. This study aimed to explore what the key factors were in driving UK NHS nurses’ decision to strike.

A convergent parallel mixed methods design was used. The study was conducted throughout the UK and involved participants who were nurses working for the NHS who voted in favour of strike action. Data collection involved the use of an online survey completed by 468 nurses and 13 semi-structured interviews. Descriptive and inferential statistics were used for quantitative data analysis and a process of inductive thematic analysis for the qualitative data. The quantitative and qualitative data were analysed separately and then integrated to generate mixed methods inferences.

The quantitative findings showed that patient safety, followed by staff shortages, pay, and unmanageable work demands were the most important factors encouraging nurses’ decision to strike. The qualitative findings served to further the understanding of these factors particularly in relation to participants’ perception of the NHS and the consequences of inadequate pay and staff shortages. Three overarching and overlapping themes represented the qualitative findings: Save our NHS, Money talks, and It’s untenable. Integration of the findings showed a high level of concordance between the two data sets and suggest that the factors involved are interconnected and inextricably linked.

Conclusions

The UK NHS is a challenging and demanding work environment in which the well-being of its patients is dependent on the well-being of those who care for them. Concerns relating to patient welfare, the nursing profession and the NHS played a large part in driving UK NHS nurses’ decision to strike. In order to address these concerns a focus on recruitment and retention of nurses in the NHS is needed.

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The United Kingdom National Health Service (NHS) is the seventh largest employer in the world [ 1 ] providing public health services for a population of around 67 million people [ 2 ]. Of the 1.4 million staff working for the NHS approximately a quarter of these are registered nurses [ 3 ]. Nurses are the backbone of the NHS providing hospital and community services and are often patients’ first and last point of contact when accessing care.

Nurses working for the NHS are paid according to a pre agreed pay and grading system decided upon by the UK Government with recommendations from an independent NHS pay review body. Research has shown that when taking inflation into account the average pay of NHS nurses has fallen in real terms by 8% between 2010/11 and 2021/22 [ 4 ], with the figure estimated at closer to 20% for more experienced nurses [ 5 ].

The Royal College of Nurses (RCN) is the largest nursing union in the world and represents around 405,000 registered nurses working in the UK [ 6 ]. Following a protracted pay dispute with the UK government, in October 2022 the RCN balloted its members working for the NHS on whether to take industrial action in the form of strikes. Despite the high threshold for success, with all ballots needing to be conducted by post and a 50% turnout and 40% vote in favour, the ballot was conclusive. NHS nurses voted in favour of strike action in the majority of NHS Trusts throughout the UK. Footnote 1 In December 2022, for the first time in the RCN’s 106-year history their members engaged in strike action. The largest nursing strike in the 74-year history of the NHS.

On the surface it appears clear. NHS nurses were striking to secure better pay. This is supported by the most recent NHS staff survey [ 7 ] which found that only 25.6% of staff were satisfied with their level of pay. However, the staff survey also highlighted a number of other factors that indicate a high level of discontent, portraying the NHS as a stressful, demanding and unsatisfactory work environment. Furthermore, increasing numbers of nurses are leaving the profession due to health reasons, burnout and exhaustion [ 8 ], with additional nurses voicing their intent to leave because of high workload pressures and feeling undervalued [ 9 ]. This leads to the question: what are the key factors that have driven UK NHS nurses’ decision to strike?

Answering this research question is particularly pertinent at this time as the UK NHS is currently experiencing some of the greatest pressures in its history [ 10 ]. Waiting times are at an all-time high and record numbers of patients are waiting for treatment [ 11 ]. Not only are nurses engaging in strike action but also a plethora of other professions within the NHS including doctors, radiologists and physiotherapists; all of which only serves to exacerbate what is widely considered as an NHS in crisis [ 12 ]. At a time of widespread industrial action throughout the UK in which 2022 saw the highest number of working days lost to strikes for more than 30 years [ 13 ], determining the key factors driving UK NHS nurses’ decision to strike may serve to inform those concerned with prolonged and future industrial action, not just within the nursing profession and the NHS, but also the wider UK workforce.

Literature review

A strike has been defined as ‘A temporary stoppage of work by a group of employees in order to express a grievance or enforce a demand’ (p.3) [ 14 ], Hyman [ 15 ] highlights that it is predominantly a calculated act and that the complete stoppage of work and its temporary and collective nature distinguish it from other forms of work-based protest.

Nursing strikes are a global phenomenon with incidences occurring in a diverse range of countries including America, Japan, Kenya, India, Australia and throughout Europe. In the UK nurses have a rich history of protest, but the incidences of strikes within the profession are few and far between. A limited number of empirical studies exist identifying factors that have driven nurses to go on strike. These include quantitative [ 16 , 17 , 18 ], qualitative [ 19 , 20 , 21 ], and mixed methods designs [ 22 , 23 ]. Within these, issues relating to pay and working conditions predominate, but other factors such as intimidation from unions, failures of healthcare systems and addressing public perceptions of nurses were also found. What is notable is that none of these studies focus solely on factors driving nurses’ decision to strike, instead collecting data on a broad range of topics. This diverse approach may explain to some extent why they fail to facilitate a thorough understanding of the key factors driving nurses’ decision to strike. At present, it appears that there are no existing empirical studies focusing on nurse strikes within the UK, signifying a gap in the literature.

In addition to existing empirical studies there is a wide body of literature in the form of retrospective accounts that document and provide theoretical interpretations of individual and country specific nurse strikes [ 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. By depicting the nurse strike within a historical, political, and professional context these accounts help to further illuminate the phenomenon and facilitate a much richer and deeper understanding. With this, we begin to appreciate the nurse strike as distinct from those within industrialised settings and as much a form of advocacy as that of self-preservation.

For any strike there are consequences. Whether they be for employers, workers, service users, the government, or for society at large. Within the healthcare environment there are concerns that a strike may have the additional consequence of compromising patient care. This has led some to denounce strikes by nurses citing them as immoral, unjustifiable [ 31 ] and wholly inappropriate [ 32 ]. Yet, it has been argued that such a stance fails to see the bigger picture and puts too much emphasis on the nurse/patient relationship [ 33 ].

Healthcare provision is a collective endeavour and whilst nurses have a professional responsibility to prioritise patient care and put the safety and wellbeing of those requiring care at the forefront of all they do [ 34 , 35 ]; governments, employers and health policy makers also have a responsibility to facilitate an environment conducive to such an approach [ 36 ]. In situations where this does not happen it can be argued that to not stand up and take appropriate action would in itself be unethical [ 37 ] and antithetical to the standards required. It has therefore been posited that concerns around patient safety and standards of care can now be seen as one of the key driving factors for nurse strikes [ 26 ].

The aim of this study is to explore what the key factors are driving UK NHS nurses’ decision to strike. The findings of this study can be used to inform government, employers, unions and health policy makers concerned with prolonged and future industrial action and stimulate a wider discussion around the demands of contemporary nursing and the challenges of working for the UK NHS.

Study design

A convergent parallel mixed methods design was used for the study to facilitate a detailed inquiry into the research question and enhance the validity of any inferences made. Quantitative and qualitative data were collected concurrently but separately, with equal importance given to each. The two data sets were then analysed independently, after which the results were merged and interpreted [ 38 ]. This approach helped to better understand the statistical trends associated with the nurse strikes whilst gaining a contextual understanding of the motivation and experiences that lay behind them. A summary of the study design can be seen in Fig.  1 . The study is deemed exploratory in nature due to the lack of previous research on the topic within the UK and also to allow a certain amount of creativity and flexibility within the research methods used [ 39 ].

Convergent parallel mixed methods design used for study

Study setting and sampling

The study took place within the United Kingdom across all four nations of England, Wales, Scotland and Northern Ireland. The eligibility criteria included registered nurses working for the UK NHS who were also members of the RCN and voted in favour of strike action in the ballots conducted in October/November 2022 and/or May June 2023.

Participants were recruited for the quantitative methods through a combination of voluntary and convenience sampling. Nurses were notified of the study and invited to participate via the use of online nursing forums related to the RCN, social media sites (including Facebook, Twitter and LinkedIn), networking, and word of mouth. In addition, following approval from the local research and development (R&D) boards the study was advertised within two large NHS trusts in the south of England. This was achieved by distributing flyers and posters amongst the hospital wards. An email notification was also sent by the R&D department in one of the trusts. Further sampling was achieved on the picket lines outside two hospitals in Wales during the strikes in June 2023 with nurses informed of the study in person and provided with a QR code to access a survey.

Over 300,000 nurses were balloted in the first ballot on strike action in October/November 2022 [ 40 ]. The number of ballots completed and the proportion of nurses who voted in favour of strike action were not released and were not provided on request. However, with UK law [ 41 ] requiring a 50% response rate and a minimum of 40% voting ‘yes’ for strike action to happen we can assume that the actual population of nurses voting for strike action was at the very least 60,000 Footnote 2 nurses. A sample size of 384 participants was therefore deemed necessary in order for the sample to be representative. This was calculated using a basic prevalence sample size calculator with a confidence level of 95% and a margin of error at 5% [ 42 ].

Purposive and voluntary sampling was used for the qualitative methods. Potential participants were identified by scanning social media platforms for posts by nurses that implied they were in favour of and passionate about the strikes. Those nurses were then contacted, informed of the study and invited to participate ( n 8). In addition, on hearing of the study a number of nurses came forward and volunteered their participation ( n 5).

Quantitative data collection and analysis

An online cross-sectional survey was designed and administered for the study (Additional file  1 ) and was made available via the digital survey platform Lamapoll [ 43 ]. Data was collected between the 21st April and 1st July 2023 and was analysed using IBM SPSS Statistics software v.29. Prior to data collection the survey was piloted and reviewed by 8 nurses who provided feedback. This resulted in minor adjustments in the wording for a single question and the subsequent removal of a sub-scale which was deemed unclear and lacking relevance.

The survey asked participants to select which factors they felt encouraged their decision to vote for strike action from a predetermined list. The list included seven factors which were compiled to reflect the most relevant points from the literature review, the stance of the RCN, and the current political climate within the UK. Descriptive statistics were used to depict how frequently each of the factors were chosen. In addition, participants were asked to rank those factors in order of importance. Means were calculated and compared. A one-way repeated measures ANOVA test was performed to determine whether the difference between the ranked levels of importance between factors was significant.

A number of the factors (staff shortages, pay and unmanageable work demands) were singled out for further exploration. This was done to try and gain an insight into the motivation lying behind each of those factors; that is, were those nurses more concerned with self-preservation and their own individual well-being ( self-motivation ), or were they more concerned with the well-being of the profession and the patients it cares for ( professional motivation ).

To determine the weighting towards the two constructs of self-motivation and professional motivation a series of Likert items were designed using a 5-point bipolar scale, ranging from strongly disagree to strongly agree . The items were divided into three subscales relating to each of the chosen factors. The three sub-scales combined had good reliability [ 44 , 45 ] for both the Professional motivation construct (Cronbach’s α = .88; 6 items) and the Self-motivation construct (Cronbach’s α = .86; 6 items). Measures of internal consistency for the individual sub-scales can be found in Table  1 . The order of questions within each sub-scale were varied to minimise acquiescent response bias [ 46 ]. The scales were numerically coded into interval data and grouped under their corresponding constructs. Paired t-tests were performed to determine whether the difference between the two constructs was statistically significant for each sub-scale.

Demographic data was obtained to inform what type of nurses participated in the survey and presented in tabular form using descriptive statistics.

Qualitative data collection and analysis

Semi-structured interviews were conducted using an interview guide consisting of a range of questions and probes designed to elicit rich and insightful responses (Additional file  2 ). An additional set of probes were used for responses that complimented the factors listed within the survey so as to facilitate congruence between the data sets (Additional file  3 ). To allow the inclusion of participants from a broad geographical range interviews took place online via the video conferencing platform Zoom. They were conducted between the 23rd May and the 23rd June 2023. Interviews were conducted until it was felt that saturation of data was achieved; meaning, new data appeared to be repeating what was previously collected and thus, it was felt that further data collection was unlikely to add to the findings. The mean length of the interviews was exactly 50 minutes.

Thematic analysis of the data was conducted using the methods outlined by Braun and Clarke [ 47 ] with the help of MAXQDA 2022 data analysis software. These methods involved a 6-phase process. Phase 1 – familiarisation, began by a single researcher conducting the interviews and transcribing them verbatim. This helped to facilitate familiarity with and immersion of the data. An inductive approach was used for phase 2 - generating initial codes, in which coding of the transcripts was guided by the content of the data rather than any preconceived theoretical or epistemological perspectives. This phase generated over 90 interrelated and often overlapping codes which were sorted and organised using a mind map. Organising the codes in this way helped to see the relations between them and formed the beginnings of phase 3 – searching for themes. Initially this phase took on a rather positivist approach that saw the inception of themes based on the prevalence of codes and their semantic level context. However, a more interactive and organic approach developed in phase 4 – reviewing themes, where the initial set of themes were revised to ensure they really represented the coded extracts, as well as the story being told across the entire data set. It is here that the researcher’s subjective interpretation began to play a more influential role. Themes developed not just based on the data within the codes but on how they were perceived and understood by the researcher. This process gained momentum in phase 5 – defining and naming themes where the essence of each theme, how they related to one another and the story that they told was fully realised. Phase 6 – producing the report saw the outcome of this process in which the qualitative results tell a story that reflects the coming together of the experiences, meaning and reality of participants with that of the understanding, values and skills of the researcher.

Mixed methods analysis

Quantitative and qualitative data were integrated at the interpretation and reporting level. The key findings of the quantitative data were presented alongside qualitative data using a joint display table. This approach helped to merge the data in a more direct way and facilitate a better understanding of the mixed methods meta-inferences [ 48 ].

Ethical considerations

Ethical approval was granted by the University of Freiburg’s ethical research committee (Application no. 23–1126-S2). All surveys were completed anonymously and informed consent gained from all participants. Participants who partook in the interviews were provided with a participant information sheet and asked to sign a consent form prior to being interviewed. The interviews were anonymised during transcription with all identifiable data subsequently deleted. All data was held and stored in accordance with the UK Data Protection Act of 2018. Participation was completely voluntary, and no financial incentives made.

Five hundred forty-four nurses responded to the survey. Those that did not fulfil the eligibility criteria or provided an insufficient amount of data were discarded, resulting in 468 completed surveys included in the analysis. Thirteen participants were recruited for the semi-structured interviews. The demographics and work-based characteristics for the quantitative and qualitative samples are displayed in Tables  2 and Table  3 respectively. Female nurses working in hospital settings with adult patients predominated. There was a broad range of experience across the two data sets with the majority of nurses having trained in the UK. Demographics for RCN membership were not available to draw comparisons with; however, the sample is broadly proportional to that of the UK nursing register with regards to age, gender and type of nursing. It is underrepresented by mental health nurses and those who trained outside of the UK [ 49 ].

Quantitative results

The factors that encouraged nurses’ decision to strike are displayed in Fig.  2 . The mode number of factors chosen was 5, in which Staff shortages and Patient safety were the most frequently cited.

Factors that encouraged participants’ decision to strike. Note .  N  = 468

Nurses indicated that patient safety, followed by staff shortages were the most important factors that encouraged their decision to strike. The ranked means and standard deviations for the level of importance ascribed to each factor are presented in Table  4 . A one-way repeated measures ANOVA found that the difference between the level of importance for the factors was significant at the .05 alpha level. Wilks’ Lambda = .04, F (6, 462) = 2149.69, p  < .001, multivariate partial eta squared = .97. However, post-hoc pairwise comparisons with a Bonferroni adjustment indicate that the difference was not significant between each level of ranking. Those that were significant are highlighted in Table 4 .

Responses to the Likert sub-scales and the level of agreement that nurses had to the individual items are presented in Fig.  3 . The results of the paired t-tests (Table  5 ) indicate that those who cited pay and unmanageable work demands as factors that encouraged their decision to strike were significantly more professionally motivated than self-motivated ( α  = .05). However, it should be noted that the effect size, whilst moderate for pay was small for unmanageable work demands. The difference between the level of professional motivation and self-motivation for those who cited staff shortages as a factor that encouraged their decision to strike was not statistically significant.

Likert sub-scales showing individual items and their relation to the constructs professional motivation and self-motivation. Note . Order of items presented to facilitate easy understanding of how the items relate to the constructs of Professional Motivation and Self-motivation. The order of items within the survey was different

Qualitative results

The process of thematic analysis identified three overarching and overlapping themes which were selected to represent the data. These themes included: Save our NHS, Money talks, and It’s untenable.

Save our NHS

The state of the NHS was reflected upon throughout the interviews. Participants were passionate about the NHS and its ability to provide high standards of safe and effective care, free at the point of need. However, there was a recognition that the NHS was failing as an institution, the injustice of which was palpable and articulated by the following comment:

I don't understand, genuinely don't understand why people aren't rioting because of the state of the NHS. We are going to lose this incredible thing… It's just, I mean, I feel quite emotional. It’s just shocking. It's just shocking that it's happening. Participant 2

Witnessing the decline of the NHS seemed to elicit a sense of loss and foreboding in participants. One nurse explained how this had evolved into a sense of shame at what it has become.

I was very proud going back years ago to put on a uniform, to enter that building and start my shift. And I was proud to tell people that I worked for the NHS. And I'm not anymore. I'm embarrassed by it. I'm embarrassed by the care that we give. I’m embarrassed by the treatment that some of the patients get. It's heart breaking, it really is. Participant 10.

And yet, these feelings seemed to stem, not from an idealistic view of what the NHS should be or how it should be run, but rather from the lived experience of providing frontline care on a day-to-day basis. This results in a visceral understanding that nurses are not just the providers of care but also the recipients of care, along with their families, loved ones, and the nation as a whole. For example, on reflecting on caring for a dying patient participant 6 acknowledged “That could be me one day.” In addition, whilst talking about the poor standards of care she had witnessed, participant 13 expressed “I’m worried about the care my parents are going to receive, I’m worried about the care I’m going to receive in the future!” Participant 5 spoke about living with a congenital heart condition, needing regular specialist review, extensive surgery and a costly hospital stay. He concluded “I’ve really benefited from the NHS, as an end user and also as an employee. I think it’s a great institution and I think it needs to continue.”

Nurses’ decision to strike could therefore be seen as a call to arms in response to the witnessed decline of the NHS and all that it entailed. The value and appreciation that nurses hold for the NHS comes with a real sense that it is worth fighting for. The decision to strike was seen to play an important part in that fight. Participant 12 highlighted this point in saying:

It really is about the health of all people in the UK and the future of what that's going to look like. And it's not looking good, you know, from where we're at just now. If we don't fight, I believe there's a real possibility we could lose the NHS.

Money talks

It was widely felt throughout the interviews that the rate of pay that nurses receive does not reflect their level of expertise, professional development, and the responsibility that comes with the job. The following nurse discussed this in relation to her own professional development.

If I did my nurse prescribing in a couple of years, which is a possibility, it's not going to get me any more pay. And the level of responsibility that comes with that… We're a very responsible profession, you know, breaking bad news, seeing things that the ordinary general public wouldn't even dream to see… And yet, we're not recognised financially, or with the respect as a profession that we deserve. Participant 11

Participants throughout the interviews felt that the nursing profession was undervalued and underappreciated, especially by the government and thus, their decision to strike was an attempt to highlight this. This sentiment was particularly pertinent in relation to the recent COVID pandemic. Participants reflected upon the sacrifices they made during the pandemic and the discrepancy of being hailed as heroes by the government one day, to receiving yet another below inflation pay rise the next. This served to exacerbate the feeling of being undervalued as highlighted in the following excerpts:

My husband had a heart attack during the pandemic, I couldn't visit him. But I was still going to work. I was in this building. But I couldn't go and see him. There are huge, huge sacrifices made by all of us. Four of my colleagues died, and we're not even worth a real time pay increase! Participant 2.

Yes, let's all stand out on our doorsteps and clap and bang our pans for the wonderful people who are doing a wonderful job. But actually, when you want a decent wage, we're not going to give that to you. Participant 5

The level of pay that nurses receive was therefore perceived as a measure of the value and appreciation ascribed to the profession. In addition, better pay was viewed as a vital tool in incentivising people to become nurses and to work in the NHS. This point was made by Participant 4 who explained:

I don't personally care about the pay. For me at least as an individual… But I do care about pay for my colleagues and the wider NHS, is it 47,000 nursing vacancies? They're not going to get filled with shoddy pay. There needs to be an incentive to be a nurse at the moment.

The pursuit of better pay was a key factor driving nurses’ decision to strike because better pay was seen as integral to addressing the ongoing recruitment and retention crisis of nurses within the NHS.

It’s untenable

The recruitment and retention crisis, and it’s resulting staff shortages was frequently cited by participants as being the root of the problem and fundamental to their decision to strike. Staff shortages result in nurses having to take on an additional workload to meet the needs of patients. As participant 7 explains, “It’s not doable. You’re having to work twice as hard… You’re having to do several people’s jobs.” Participants spoke of how staying late after work and working through their breaks to try and keep on top of the workload was an everyday occurrence. The relentless pressure and responsibility of the job is at times overwhelming and the impact on individual nurses seen as untenable. As participant 13 pointed out.

We're not designed to be in flight mode all the time, are we? And if we don't get respite, then we're in trouble and that's what we're seeing on our work force right now in terms of how people feel, burnout, wanting to leave, going off sick….

This was also reflected upon by participant 10 who spoke about her own experiences of being burnt out from work and how this impacted her.

I ended up being off for three months… I was at the point where I didn’t want to be a nurse anymore, I didn’t want to be in my marriage. I wanted to walk out of my home, my children, my…. I just wanted to pick-up and walk out of my life.

With this we see that the morale of nurses working in an environment that is chronically understaffed is persistently under threat. As participant 1 lamented, “it makes you feel inadequate. It makes you feel that you’re not doing your job as well as you should be.” A point further elaborated on by participant 11 who noted: “nurses can’t be the nurses that they want to be. You know, they’re feeling disappointed with themselves, they’re feeling let down, they feel that they have failed.” All of this results in more and more nurses leaving the NHS or the profession completely, which only serves to exacerbate the problem of staff shortages. The decision to strike was effectively a way of nurses saying, “enough is enough, this cannot go on!”

Despite the strains of the job, it is interesting to note however that participants largely considered the real consequences of staff shortages to be suffered by patients. With increasing workloads and high patient to nurse ratios nurses’ ability to provide even the most basic standards of care are compromised. They are often faced with difficult decisions on prioritising and allocating care; things get missed, mistakes happen, and treatments and care are not provided in a timely fashion. This compromises the safety of patients and results in them coming to harm. A point stressed by participant 13.

I have seen, and I have experienced patients having poor health outcomes, or poor experiences as a result of not being able to deliver the care that we know we can deliver. And that's because of circumstances such as short staffing, and people being off long-term sick with stress.

It seems then that nurses’ decision to strike was a cry for help, not just for nurses working within the NHS, but for the very patients it aims to serve.

Integration of quantitative and qualitative results

Integration of the quantitative and qualitative findings show a high level of concordance between the two data sets. Table  6 provides examples of how the qualitative findings not only confirmed the key quantitative findings ( confirmation ) but also served to expand the understanding of them ( expansion ). No incidences were found where the two sets of findings contradicted each other ( disconfirm ).

This mixed methods study offers valuable insights into the key factors driving UK NHS nurses’ decision to strike. The quantitative findings identify that patient safety, followed by staff shortages and pay were the most important factors. The qualitative findings support these findings and further enhance our understanding of them. Mixed methods inferences suggest that the factors driving UK NHS nurses’ decision to strike are complex, interconnected and inextricably linked.

What is notable from the findings was that two factors: perspectives of the RCN and/or my colleagues and other UK services going on strike were deemed the least important factors and cited by less than 10% of participants. In addition, they did not arise within the qualitative data. This suggests that the decision to strike by participants was made with a high level of autonomy and was largely independent of the widespread industrial action taking place within the UK during that time.

In contrast to other empirical studies conducted on nurse strikes outside of the UK [ 16 , 17 , 18 , 21 , 22 , 23 ] this study found that pay was not the most cited factor encouraging nurses’ decision to strike. Due to these studies varying considerably in their aims, context and methodological profiles it is difficult to draw any definitive conclusions as to why this difference occurs; however, it suggests that factors driving nurses’ decision to strike are context specific and reflective of differing cultural and economic environments.

Although pay was not found to be the most important factor, the qualitative findings indicate that it still plays an integral role in encouraging nurses’ decision to strike. In part, this is because it was seen as an indicator of how valued and appreciated the nursing profession is. West et al. [ 50 ] argue that this sense of value is essential for nurses’ well-being and their ability to deliver high-quality care. The finding that nurses perceive pay as a measure of value is supported by Clayton-Hathway et al. [ 51 ] who go on to suggest that the lack of value ascribed to the nursing profession, and its resulting low pay is rooted in the perception of nursing as ‘women’s work’ and indicative of the patriarchal society historically found within the UK. This concept of gender disparities in relation to pay is compelling and challenges the assumption that low pay is simply to do with a lack of funds. It suggests that further research on the qualitative determinants of nurses pay would be valuable.

Within this study it was found that there was a high level of both self and professional motivation behind the factors driving participants’ decision to strike, but it was the latter that predominated. The concept of professional motivation being a driving force in nurses’ decision to strike is supported by accounts of nurse strikes both within the UK [ 25 , 52 ] and outside [ 19 , 24 , 26 , 28 ]. Briskin [ 24 ] referred to it as ‘the politicisation of caring’, a theory closely aligned to Hart’s [ 25 ] ‘clinical militancy’. However, there is a danger in adopting such terminology that we are merely conforming to the stereotypes around industrial action and failing to adequately reflect the nuances of the nurse strike. The findings of this study indicate a softer, more considered approach by nurses that is deeply rooted in a sense of moral justice and duty of care. With this understanding one is compelled to rethink the depiction of the strike as a form of self-gratifying militancy, to that of a legitimate act of compassionate care [ 53 ].

The finding that professional motivation plays a significant role behind the factors driving UK NHS nurses’ decision to strike is important as it can be used to garner public support for future nurse strikes and better inform those in opposition to them. In addition, it can be used by the RCN to reflect upon their communication strategies and ensure they adequately reflect the perceptions of their membership; furthermore, it may serve to challenge those accounts by media outlets that portray the strikes to be driven solely by individual monetary gain. A suggestion for further research could therefore be to conduct a content analysis on the media coverage of the strikes and compare the findings with that of this study. This could provide valuable insights into the validity of the mainstream media’s interpretation of strikes and the role it plays in influencing public opinion.

The mixed methods inferences of this study help us to understand that the factors driving UK NHS nurses’ decision to strike are complex, multifaceted and inextricably linked. Figure  4 provides a conceptual model of these inferences and summarises the interconnected nature of the factors.

Interconnectedness of factors drawn from mixed methods inferences. Note . This model shows how factors encouraging nurses’ decision to strike lead into one another and are centred around staff shortages. The interplay of pay, staff shortages and unmanageable work demands creates a vicious cycle that manifests as a recruitment and retention crisis, resulting in compromised patient safety

Limitations

The findings of this study should be judged within the context of its limitations. First of all, it should be noted that this study was conducted by a single lone researcher who is also a registered nurse working for the UK NHS and a member of the RCN. Whilst every attempt was made to reduce bias and provide a true representation of participants perspectives the lack of investigator triangulation leaves the study susceptible to observer bias. In particular, the validity of the qualitative findings would have been enhanced by a second reviewer confirming the selection of and allocation of codes, and the generation of themes.

A further limitation can be found in the sampling methods used. The use of voluntary sampling means that the findings are likely to be subject to self-selection bias and thus less representative of those nurses who were less forthright about their decision to strike. Furthermore, a large proportion of participants were recruited via social media meaning that the study may not adequately reflect the views of those nurses who do not use social media. Data collection began approximately 5 months after the initial ballot in which nurses first voted to strike. It may have been that by this time there was an element of strike fatigue resulting in an unwillingness to participate and engage with the study. Had the data collection happened sooner it may have helped to minimise response bias and encourage greater participation.

This notion of strike fatigue may also explain to some extent why the RCN failed to secure a further strike mandate following the completion of this study. In focusing on the key factors that drove nurses’ decision to strike this study fails to adequately portray how those decisions, and the volition to strike may change over time.

Although the results of this study are compelling it is important to recognise that an element of social desirability bias may have played a part. Participants may have felt drawn toward emphasising those factors that portrayed them as striking for the greater good so as to uphold the reputation of the profession and justify the act. Although it is not possible to quantify to what extent social desirability bias played a role it should be taken into consideration when interpreting the results.

In keeping with the exploratory nature of this study a novel approach was used in the survey design. Due to the lack of previous research in this area and the absence of a strong theoretical foundation in relation to the constructs used, there is a danger that the survey lacks construct validity. The survey would therefore benefit from greater scrutiny in the form of expert opinion review, further research and refinement with the use of factor analysis.

This mixed methods study has facilitated an exploration into the key factors driving UK NHS nurses’ decision to strike leading up to and during the industrial action of 2022/23. The findings identify that factors relating to patient safety, staff shortages, pay and unmanageable work demands were key, and that there was a strong sense of professional motivation lying behind them; that is, participants concerns around the welfare of patients, the nursing profession and the NHS often came before that of their own.

In adopting a mixed methods design this study helps to highlight that the factors driving UK NHS nurses’ decision to strike do not stand in isolation and therefore, a holistic and multifactorial approach to addressing them is required. Nurses’ concerns around recruitment and retention and the implications of staff shortages need to be taken into consideration. Perhaps more importantly however, this study demonstrates that the NHS is a challenging and demanding work environment, and that the well-being of its patients is dependent on the well-being of those who care for them. If nobody cares for the carers the process of healthcare delivery breaks down. Thus, one can consider these nurse strikes as a movement, a movement toward putting the care back into care .

This study paves the way for future research on nurse strikes and could also be used to inform research into other healthcare related professions engaged in industrial action. Further research looking at the factors driving nurses’ decision to strike is required to confirm the validity of these findings and also to develop the constructs of self and professional motivation in relation to strikes. In addition, research looking into the perspectives of the mainstream media on nurse strikes and the determinants of nurses’ pay would offer valuable insights and increase our understanding of the nurse strike.

Availability of data and materials

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

NHS Trusts are organisations that provide healthcare services on behalf of the NHS within a given specialisation or geographical area. The majority of nurses working for the UK NHS are employed directly by an NHS Trust.

The actual figure is likely to be far higher but a further increase in population size does not influence the sample size calculation.

Abbreviations

Research and Development

Royal College of Nursing

• National Health Service
• United Kingdom

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Acknowledgements

Many thanks to Dr. Ercüment Çelik for overseeing this project and for his comments and suggestions relating to protocol development and write-up of the study. Thank you also to Urs A. Fichtner from University Hospital Freiburg Institute for Medical Biometry and Statistics for his advice and suggestions regarding the statistical analysis for the study. This study formed part of a Master’s in Global Urban Health at the University of Freiburg, Germany. Many thanks to Sonia Diaz-Monslave and the GUH master’s team for facilitating the process. Thank you also to the reviewers of the manuscript for their thoughtful and valuable comments and suggestions.

Open Access funding enabled and organized by Projekt DEAL. The author received no financial support for the research or authorship.

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The study was conducted in accordance with the Declaration of Helsinki. Informed consent was gained from all participants partaking in both the quantitative and qualitative methods. Ethical approval was granted by the University of Freiburg’s ethical research committee (Application no. 23–1126-S2). All data was held and stored in accordance with the UK Data Protection Act of 2018.

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Sanfey, D. ‘Enough is enough’: a mixed methods study on the key factors driving UK NHS nurses’ decision to strike. BMC Nurs 23 , 247 (2024). https://doi.org/10.1186/s12912-024-01793-4

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• http://orcid.org/0000-0002-8129-8376 Jane Ferguson 1 ,
• http://orcid.org/0000-0001-9325-3362 Gemma Stringer 2 ,
• http://orcid.org/0000-0002-0696-480X Kieran Walshe 2 ,
• http://orcid.org/0000-0002-2972-7911 Thomas Allen 3 , 4 ,
• http://orcid.org/0000-0003-1621-8648 Christos Grigoroglou 3 ,
• http://orcid.org/0000-0002-2958-915X Darren M Ashcroft 5 ,
• http://orcid.org/0000-0001-6450-5815 Evangelos Kontopantelis 6 , 7
• 1 Health Services Management Centre, School of Social Policy , University of Birmingham , Birmingham , UK
• 2 Alliance Manchester Business School , University of Manchester , Manchester , UK
• 3 Manchester Centre for Health Economics, Division of Population Health, Health Services Research and Primary Care , University of Manchester , Manchester , UK
• 4 Danish Centre for Health Economics , University of Southern Denmark , Odense , Denmark
• 5 NIHR Greater Manchester Patient Safety Research Collaboration (PSRC), Division of Pharmacy and Optometry, Faculty of Biology Medicine and Health , University of Manchester , Manchester , UK
• 6 Division of Informatics, Imaging and Data Sciences , University of Manchester , Manchester , UK
• 7 NIHR School for Primary Care Research, Centre for Primary Care, Division of Population Health, Health Services Research and Primary Care , University of Manchester , Manchester , UK
• Correspondence to Dr Jane Ferguson, Health Services Management Centre, University of Birmingham, Birmingham, UK; j.ferguson.1{at}bham.ac.uk

Background The use of temporary doctors, known as locums, has been common practice for managing staffing shortages and maintaining service delivery internationally. However, there has been little empirical research on the implications of locum working for quality and safety. This study aimed to investigate the implications of locum working for quality and safety.

Methods Qualitative semi-structured interviews and focus groups were conducted with 130 participants, including locums, patients, permanently employed doctors, nurses and other healthcare professionals with governance and recruitment responsibilities for locums across primary and secondary healthcare organisations in the English NHS. Data were collected between March 2021 and April 2022. Data were analysed using reflexive thematic analysis and abductive analysis.

Results Participants described the implications of locum working for quality and safety across five themes: (1) ‘familiarity’ with an organisation and its patients and staff was essential to delivering safe care; (2) ‘balance and stability’ of services reliant on locums were seen as at risk of destabilisation and lacking leadership for quality improvement; (3) ‘discrimination and exclusion’ experienced by locums had negative implications for morale, retention and patient outcomes; (4) ‘defensive practice’ by locums as a result of perceptions of increased vulnerability and decreased support; (5) clinical governance arrangements, which often did not adequately cover locum doctors.

Conclusion Locum working and how locums were integrated into organisations posed some significant challenges and opportunities for patient safety and quality of care. Organisations should take stock of how they work with the locum workforce to improve not only quality and safety but also locum experience and retention.

• Health services research
• Patient safety
• Qualitative research
• Quality improvement

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This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/bmjqs-2023-016699

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WHAT IS ALREADY KNOWN ON THIS TOPIC

Despite longstanding policy concerns about the implications of locum working for quality and safety, there has been little empirical research. Understanding how organisations engage, support and work with locums and how locum doctors integrate and interact with the complex and changing systems in which they work is essential if quality and safety are to be improved.

WHAT THIS STUDY ADDS

This qualitative study examines the perspectives of locums, patients and people who work with locums to identify the implications of temporary medical working for quality and safety.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Organisations should examine how they engage, support and work with locums. Organisations and locums need to reflect on whether their practices support a collective approach to patient safety and quality of care.

Introduction

Temporary doctors, often known as locums, are a vital resource that enable healthcare organisations to deliver care by flexing capacity and covering staffing gaps. In the United Kingdom, all doctors, other than those in their first year of training after qualifying, can work as a locum. Locum work can vary from very short-term (a single shift) to longer-term assignments (weeks, months or even sometimes years). Locums find work through various platforms, including locum agencies, online job platforms, professional networks or word of mouth. Locum agencies typically have some governance responsibilities (such as compliance with regulations and licensing requirements), but the extent of these responsibilities varies and the NHS in England has no oversight over how recruitment agencies operate. Despite concerns among policymakers, healthcare providers, professional associations and professional regulators about the implications of locum working for quality and safety and cost, 1–3 there is limited robust empirical research to evidence or support those concerns.

The workforce retention crisis is a significant challenge in healthcare internationally 4–6 and persistent understaffing poses a serious risk to patient safety. 7 8 In the UK, high doctor turnover has been linked to poorer service and health outcomes 9 and has led NHS trusts and general practices (GPs) to be ‘overly reliant’ 3 on temporary staff to fill rota gaps. 10 11 Expenditure on temporary staff in the NHS in England increased from £3.45 billion to £5.2 billion between 2021 and 2022. 3 12 The NHS Long Term Workforce Plan aims to reduce reliance on temporary staff and make substantive employment the most cost-effective and attractive option. 3 However, with the vacancy rate in the NHS projected to increase, 13 locums are likely to continue to be essential to maintaining service provision, especially in shortage specialities such as psychiatry. 14

An obvious implication of locum working is a reduced likelihood of organisational and team integration, 15 familiarity and a shared understanding of ‘the way things are done around here’. 16 Locums are likely to be less familiar with teams and other contextual factors relevant to providing safe and effective care 17 and more likely to be situated on the periphery of organisational structures, teams and governance systems 1 18 Teamwork represents a powerful process to improve patient care, 19 20 and trust, shared understanding, communication and collaboration have been associated with better patient outcomes. 21 22 The ability of healthcare teams to develop and maintain team situational awareness, or a shared perception, comprehension and subsequent projection of what is going on in complex and changing clinical environments, has been described as crucial for patient safety. 23 24 Through participation and working together, 25 teams gain an understanding of the roles, skills and competencies of others to demonstrate ‘collective competence’, 26 27 which is critical for healthcare delivery, 28 29 and existing research on locums suggests a need for better integration into teams to improve quality and safety. 30 31

Context matters for patient safety and quality improvement, 32 33 yet the limited evidence 17 relating to locums practice is largely ‘acontextual’ and tends to ignore the role of the organisation in the integration of temporary staff, focusing instead on the potential risks locums present as individual clinicians, 17 30 which is perhaps unsurprising given the liminal space locums occupy. In the UK, responsibility for the quality and safety of healthcare services is shared primarily between organisations and the individual professionals working within them. 34 Organisations are responsible for creating systems and environments that promote and protect clinical governance and enable all doctors to meet their professional obligations, while doctors are expected to participate in the systems and processes put in place by regulators and organisations to protect and improve patient care. 35 However, NHS trusts and primary care organisations procure the services of locum doctors without assuming the responsibilities normally associated with an employer–employee relationship 30 and locums often struggle to participate in teams and governance systems that were designed for doctors working in conventional employment relationships. 18 36

There is longstanding debate about the role of individual accountability in patient safety and how responsibility is distributed between organisations and individuals. 37 A systems approach reasons that adverse events are likely to occur as a result of system failures rather than individual failures, 38 and patients are protected from mistakes by well designed systems and environments that promote safety cultures. 39 But locums are often positioned at the periphery of these systems, 30 and doctors who are new to and also peripheral to organisations, and organisations who are inexperienced with and unsupportive of locums are unlikely to be able to perform optimally. 40

The aim of this research was to provide evidence on how locum working arrangements impact quality and safety and the implications of locum working for patients, locums and health service organisations in primary and secondary care in the English NHS. Locum doctors are an essential and growing part of the healthcare workforce 1 who have been largely ignored in healthcare workforce research. This research addresses a gap in the empirical evidence base on how locum doctor working arrangements affect quality and safety, and provides, for the first time, an in-depth exploration that includes perspectives from patients, locums and the people they work with.

Study design and setting

A qualitative semi-structured interview and focus group study was conducted with locums, people working with locums, and patients with experience of being treated by locums. Participants were purposively sampled through 11 organisations, including NHS trusts, primary care practices, statutory NHS bodies and locum agencies. Locum doctor participants were recruited through these organisations, locum recruitment agencies and networks. We used purposive, snowball and convenience sampling, drawing on intelligence from stakeholders, including our project advisory group, to identify and recruit organisations and participants. Patient participants were recruited through patient and contributor forums. The forum involved active partnership between patients and researchers in the research process to develop research which is relevant and useful to patient and public needs. Participant demographics were monitored to ensure representation across a broad range of roles in primary and secondary care and to increase diversity in terms of gender and ethnicity (see table 1 ).

• View inline

Characteristics of study participants

Data collection

Three semi-structured interview and focus group guides were developed for use with locums, people working with locums and patients with experience of being treated by locums (as shown in online supplemental files 1-3 ). Our previous review of the literature relating to quality and safety and locum work 17 informed the schedules as well as the initial coding and thematic development. Schedules were also refined and informed by our patient and public involvement (PPI) forum and our project advisory group. Each schedule was intended to explore locum doctor working arrangements with a particular focus on understanding how locum doctor working may affect the safety and quality of care and what strategies or systems organisations and individuals used to assure or improve quality and safety. The topic guides for locums and people working with locums also covered governance and support, the impact of the COVID pandemic and policies and initiatives used to support locums.

Supplemental material

Interviews and focus groups were transcribed verbatim by a professional transcription company and organised into codes and themes using the software package NVivo. 41 Reflexive thematic analysis (RTA) 42 was used and involved familiarisation with the data by reading and re-reading the transcripts and field notes; coding the dataset and collating all relevant data extracts; generating initial themes by examining the codes and collated data to identify significant broader patterns of meaning across the dataset; reviewing themes by questioning whether themes answered the research question and told a convincing story of the data and combining, splitting and discarding themes as necessary; defining and naming themes by developing a detailed analysis of each theme; and finally the analytical write up which positioned the analysis in relation to existing literature. 43 RTA acknowledges the active role of researchers in knowledge production and the researcher’s subjectivity as the analytic resource. 42 RTA recognises interpretive variability between researchers based on differences in their knowledge and skills, theoretical assumptions and differences in how they responded to the dataset is acknowledged and expected. 42 The research team worked reflexively discussing their personal biases and their potential impact on the research at regular meetings throughout the data collection and analysis period. Our PPI forum were also involved in data collection and analysis, and offered a form of triangulation to enhance rigour, challenge and alternative interpretations of the findings. 44 Analysis adopted a constructionist epistemology, in that while we acknowledged the importance of recurrence in generating themes, meaning and meaningfulness were the central criteria in the coding process. 42

After themes were developed, an abductive approach was taken to position findings against a background of existing theory and knowledge. 17 30 This provided a way of constructing empirically based theorisations without confining theory to predefined concepts. 45 This approach integrated inductive data-driven coding with deductive theory-driven interpretation; aiming to find a middle ground between inductive and deductive methods and the most logical solution and useful explanation for phenomena. 45

We conducted 130 interviews with 88 participants who worked in healthcare and 42 patients took part in focus groups and one-to-one interviews. Participants included locums, permanently employed doctors; nurses and other health professionals; medical directors/clinical leaders; responsible officers (ROs are accountable for local clinical governance processes and focus on the performance of doctors) and appraisers; leads for medical staffing and clinical governance and practice managers (see table 2 ). Three experienced qualitative researchers (JF, GS and KW) and two members of the PPI forum (MM and MS) carried out five focus groups with 30 patients, and JF and GS carried out 12 one-to-one interviews. Data were collected between March 2021 and April 2022 during the COVID pandemic using video conferencing software (n=126) or over the phone (n=4) at a time convenient to participants. Interviews and focus groups ranged in length from 23 to 171 min, with the average interview being 59 min.

Healthcare organisations and participant roles

Thematic framework

Our findings are presented under five broad and interrelated themes that examine how locum work relates to and impacts quality and safety: ‘familiarity’ with an organisation and its patients and staff; ‘balance and stability’ in services with lots of locums; ‘discrimination and exclusion’ towards locums and their effects; ‘defensive practice’ by locums; and the positioning of locums outside clinical governance arrangements.

Familiarity: knowing who, where and how

Locums described often working in unfamiliar environments, sometimes with minimal induction and varying levels of support. Unfamiliarity, lack of access to or other restrictions on computer systems, policies, procedures and buildings meant that locums were not always able to do their job safely, productively or effectively.

That’s probably the biggest sort of safety aspect that sticks in my mind, is that it is unbelievably frustrating to have to learn a whole new set of patients from day to day … when I was signed up to four different hospitals, plus the locum agencies, I very quickly realised that not only is it the fact that you don’t know the patients from day to day, if you’re chopping and changing site the whole time, then store cupboards are laid out differently, ways of contacting relevant staff members are different, you’ve got to recognise what code to put in to bleep someone that’s different at every single site. (Interview 23, locum, secondary care)

Locum working sometimes created extra work for permanent staff who were responsible for inducting, training and supervising locums. The amount of additional workload was dependent on contextual factors, such as the experience of the locum, organisational support and length of placement, access to systems and what terms and conditions locums or organisations had negotiated. Locum reliance on permanent staff meant that care could be delayed, partially completed or not completed at all, which sometimes caused resentment.

Some of the things that we don’t … like, for example, procedures of limited clinical value that we don’t refer in for, they won’t know about those in our areas … So they’ll do referrals that we then will get pulled on. They’ll maybe prescribe medications that are not first line medications within our own formulary. So we see quite a bit of that, you know, there’s quite a lot of tidying up to be done afterwards or work. They generate that. So whilst we meet the patient numbers, they create a lot of work for the rest of the team. (Interview 3, practice manager, primary care)

Locums mitigated risks related to working in unfamiliar environments by avoiding organisations considered chaotic or unsafe, working below their grade to avoid having responsibility in unfamiliar organisations where they may not be supported or included in the team or working in a limited number of organisations to increase familiarity.

Most locums take jobs, locum work below their grade. So a person who’s at a registrar level would take a locum work as an SHO (senior house officer), because they don't know the trust that well. (Interview 55, locum, secondary care)

However, lack of familiarity and discontinuity could at times be beneficial for patients and organisations as fresh perspectives offered by locums led to different routes of treatment or management, and could alter organisational cultures or practices.

So that [locum] doctor, through that line of questioning and not having any sort of prior history … ordered the right tests and didn’t feel constrained in that practice about what tests that they could order. And someone subsequently … because when you get referred to hospital, the consultant said that that doctor was very much on the ball. And, of course, that’s a change to lifelong medication. And literally within a month of the medication kicking in, it transformed my life. (Focus group A, patient 1)

Balance and stability

The balance between locum and permanent staff had implications for quality and safety, organisational leadership, long-term planning and governance. Locums were often employed to deliver immediate services and consequently were less likely to be involved in team and organisational development. Locums recognised that having ‘an NHS run by locums’ was detrimental to quality and safety, and some avoided organisations that were locum dependent for this reason. Well functioning established teams were regarded as better able to incorporate a small number of locums without being significantly impacted.

Locum work, my view on it is they’re there to fill a gap. They shouldn’t be relied upon to deliver a service Monday to Friday, day in, day out, week in, week out. And unfortunately my trust see it as that, though, that’s my worry that they feel they’re not just plugging a gap, they’re almost as a workforce … (Interview 84, lead GP, primary and secondary care)

Departments that were disproportionately locum dependent were often perceived to lack clinical leadership and direction. An absence of consistent medical leadership meant that quality improvement was slower or less likely to happen, and trusting relationships between staff were harder to establish.

If you get a department that is disproportionately locum dependent, then it stagnates, it doesn't progress. Things like implementation of new NICE guidance, for example, that sort of thing tends not to happen or happen less well, less quickly. (Interview 30, responsible officer, secondary care)

Discrimination and exclusion

Most locums described negative behaviours and attitudes from staff and some patients, which impacted their involvement, inclusion and experiences in organisations. Negative attitudes and behaviours towards locums could affect turnover, locum well-being, team dynamics and potentially patient safety. Perceived disparities between pay, workload, competence and organisational and team commitment between locums and permanent staff could be sources of resentment and influenced how locums were treated and viewed. This compromised staff communication and reduced the sharing of important patient information.

I guess like any temporary post really, you struggle to invest in them, don't necessarily see them as being part of the team. Not very positive about them, particularly junior staff, particularly in the acute trusts. We'd have locums refusing to come back because of the treatment of the midwives. (Interview 86, clinical lead, secondary care)

Negative perceptions of competency and safety meant that locums were often stigmatised, marginalised and excluded. The identity of locum intersected and overlapped with other identities and was described as ‘layering up’ with ethnicity and gender to further exacerbate discrimination.

Oh, doctors coming over from Germany. There was one locum … that administered a dose of something and the patient died, and then there’s this whole layer of extra negativity attached to locum doctors in general because of what one doctor did, and that doctor happened to be someone from a different ethnicity … As a UK born and qualified doctor I can see that those overseas get it but I can also see that I have experienced that as well. So yeah, it can layer up with the whole locum thing. (Interview 59, locum GP, primary care)

A sense of othering and being seen as less was particularly evident during the COVID pandemic when resources were limited. Some locums described how they were not afforded the same protections as permanent members of staff and were sometimes expected to take on riskier work.

I’ve worked in another practice where, because they live on locums and they live on ad hoc locums, you’re a piece of dirt under the shoe. You don’t get gloves, you didn’t have aprons, you didn’t have a face visor, you didn’t have safety specs, you have to ask for a mask. Not only are you not treated as a service provider, you’re not treated as a colleague, someone with knowledge. (Interview 44, locum GP)

Defensive practice by locums

Locums recognised that they were likely to be scapegoated if things went wrong, and some locums described being more likely to practice defensively. Defensive practice has been defined as deviation from standard practice to avoid litigation, complaints or criticism. 46 Participants reported instances of defensive practice which involved providing services (eg, tests, referrals) or avoiding high-risk decisions, usually to reduce the risk of adverse outcomes such as patient complaints or potential termination of contract at short notice. Locums described practicing defensively because they were attempting to practice as safely as possible in complex unfamiliar environments where they were professionally isolated and perceived negatively. Permanent members of staff could perceive that locums practiced defensively because they lacked confidence in their abilities. The diversion of resources away from more clinically relevant activities placed additional burden on teams, who were already facing significant workload challenges.

Being risk averse and practising defensive medicine usually means more tests, more referrals, whereas holding risk tends to be disadvantageous for you as a locum because what’s the benefit to you of not doing that. You’re benefiting the system by rationing resource, the patient won’t thank you. (Interview 35, locum GP)

Locums described avoiding making decisions when risks to employment or medical licenses were perceived as high. Locums felt they were more vulnerable to criticisms of their clinical competence and disempowered to make decisions. Others felt that some locums were simply avoiding work and evaded responsibility for patients by pushing work onto others or into the future.

You don’t interfere, very simple. Over time locums have learned that if you interfere, if you participate in the team, you participate in patient care, [and this] is when you get into trouble … Well most of the locums that I know will just say, okay, there’s already somebody else who’s made a decision, it’s not my job to make a decision, I just follow through. If things go wrong, call the senior person and be done with it, that’s the end of my role. Actually doing something to protect a patient is not important for a locum because the risk is too high. (Interview 55, locum, secondary care)

Locums fall outside clinical governance arrangements

Governance practices in relation to locums varied widely and were not generally regarded as being as robust in comparison to permanently employed doctors. Responsibility for involving locum doctors in performance feedback, supervision, educational opportunities, appraisal and quality improvement was unclear. While some organisations included locums in their governance activities, others regarded locum work as transactional; where the locum was there to provide a finite service and the organisation assumed no responsibilities for their performance, development or oversight. There were concerns that governance structures were modelled on and designed for permanently employed doctors and did not work for locums. When deficits in performance were undetected or unaddressed, doctor performance and patient safety could be jeopardised.

I think it’s a remote world. It’s like a cloud, you know, it’s like the cloud. We talk about the cloud when it comes to storing information. And I think locum world is a bit like that … And I don’t know the doctors anywhere like as much as I did when I was an RO in the NHS, I knew them all personally. If I used to have a problem, I used to get them in my office there and then, chat it all through, sort it. Can’t do that in locum world, it might take me four days to get hold of the doctor, some of them won’t respond immediately … They don’t know me and I don’t know them. (Interview 51, responsible officer, locum agency)

The absence of typical recruitment processes (involving meeting a doctor, carrying out an interview and following up on references) meant that healthcare organisations were reliant on partial information from locum agencies, which made it difficult to determine competency, scope of practice and suitability for a role. However, staff shortages and a requirement to meet safe staffing ratios meant that organisational leaders had little recourse of action if they were unsure about a doctor’s capability, which caused anxiety and frustration. This suggests that the provision of healthcare superseded ensuring safety standards and necessitated accepting one of two objectionable alternatives; accepting gaps in staffing that may jeopardise patient safety or accepting unknown doctors; each of which may compromise patient safety.

If a locum turns up and I have serious doubts about their ability to do the job to the required standard, I don’t have any recourse … And therefore I’m in a position where either I accept this locum or I don’t. There’s not much in the way of middle ground. Not accepting them is a really unpalatable choice because if I say look, I’m sorry, I don’t think you’re up to this, I think you should go home, that leaves me with a gap. (Interview 30, consultant and responsible officer, secondary care)

Similar governance and information sharing problems were described by locum agencies and NHS organisations; both described difficulties in gathering and sharing feedback. When concerns were raised, participants were often uncertain as to what happened to the information they provided and whether it was shared or acted on. Locums often did not get to hear about concerns raised about them, meaning learning opportunities were missed.

It would give you more confidence if you heard back. And sometimes I'll pick up the phone and you try to do the best you can to make sure this information gets passed on. But I just have this nagging doubt that I'm not always convinced it does. (Interview 30, responsible officer, secondary care)

There was also a perception from some locum agency responsible officers that while most locum doctors were excellent, there were some locums who were isolated and in need of organisational and professional support.

You have to accept that whilst within the agency world, 80 per cent of the doctors we place are excellent, and have no problems, and do a great job, perhaps 20 per cent are those that have shaken down to that 20 per cent in the agency world, because they’ve not succeeded in the NHS, they’ve not got a substantive place, they are lost souls. And they are less able to cope with the vicissitudes of busy clinical life and professional life within a large organisation such as the NHS. (Interview 47, responsible officer, locum agency)

Our findings provide some profound and concerning insights for patient safety and quality of care. The ways in which locums were recruited, inducted, deployed and integrated, and supported by organisations undoubtedly affected quality and safety. Our findings indicate that regardless of their level of experience, it was unlikely that locum doctors would be able to function optimally in unfamiliar environments; and organisations who had poor supportive infrastructure and governance mechanisms for locums were less likely to deliver high-quality safe services.

Locums were often regarded as organisational outsiders—positioned at the periphery of the team and the organisation. The implications of transience and peripheral participation were weaker relationships with organisations, teams, peers and patients, leading some to suggest locum working is better suited to experienced doctors. 47 Consistent with previous research, 48 frequent variation in process, systems and equipment, combined with disruption in relationships and a lack of mutual awareness of team skills and competencies, decreased collective competence, placed additional burden on the wider healthcare team and reduced patient safety. As others have found in research on safe staffing and nursing, 49 temporary staff are not effective substitutes for staff who regularly work in the organisation. Safe medical staffing is not just achieved by filling rota gaps, but also team composition and doctors’ familiarity with the team and organisation must be taken into account. Regulatory agencies should consider locum usage in their inspections and perhaps be particularly concerned when organisations have ‘services run on locums’.

Our research found, as others have, 18 that organisations and doctors sometimes struggled to meet their governance obligations and that governance activities differed based on contractual status and organisational policies and norms, with systems being less robust for locums. This research has highlighted that much still needs to be done to develop governance systems that promote and protect the interests of patients and create an environment which supports locum doctors in meeting their professional obligations.

More positively, locum doctors are a potentially valuable source of information about safety concerns, faulty systems or poor conduct. 50 Locums move between organisations, have broad systems knowledge and are perhaps better placed to identify some quality and safety issues than permanent doctors. However, findings indicate opportunities for shared learning were often missed. Locums recognised their precarity and vulnerability when offering second opinions, sharing improvement ideas or voicing safety concerns; meaning opinions were not always offered and concerns were not always raised. Failure to voice concerns is a persistent problem in healthcare, 51 and locums may be even less inclined to offer potentially valuable information about safety concerns because of their perceptions of unsupportive organisational climates.

Our findings shed light on how temporary doctors fit into the enduring debate 37 around how responsibility between organisational systems and individual professionals is distributed. Locums appear to represent a subsection of the medical profession for whom the wider paradigm shift from a focus on individual blame to a systems approach 52 appeared not to have been made. Locums were often not regarded as a part of the organisation, and therefore the system, and not afforded the same protections as permanent staff when things went wrong. Blaming locums when things go wrong and punishing or sanctioning individuals who make errors in contexts that were not designed to incorporate temporary workers may divert attention from understanding inadequately designed, poorly functioning systems, or indeed the individual practice of other doctors. While we should take into account systemic factors that impede locums from performing safely, we should expect high standards of healthcare professionals, be cognisant of individual agency and recognise the distinction between blaming someone and holding them responsible. 53

Strengths and limitations

This large qualitative study explores locum working and quality and safety in an under-researched, yet growing area of the medical workforce. However, sites were all based in England, which means caution should be taken when extrapolating findings. Similar research in other countries and contexts to understand more about locum doctor working and quality and safety is therefore important. It is possible that our sample may have been skewed towards locums, healthcare professionals and patients who had more negative perceptions and experiences, although accounts resonate with previous research 30 and patient perspectives were generally positive. Our data were collected during the COVID pandemic, which may have affected findings as there was a reduction in locum working during that time 10 11 ; it also meant we were unable to carry out observations, which would have strengthened our findings and mitigated some of the inherent limitations of interviews, such as recall bias. We used both one-to-one interviews and focus groups in data collection. Although flexibility in data collection meant that participants had the option to take part in an interview or a focus group, these methods are used for different reasons and produce different data. There may have been differences in what participants disclosed depending on the method

Our findings show that the way in which doctors who worked on a temporary basis were integrated into organisations posed some significant challenges and opportunities for patient safety and quality of care, and that both organisations and locums had a part to play in improvement. Doctors working as locums are a heterogeneous group with differing backgrounds, experiences, skills and capabilities that likely reflect the variability seen in the wider population of doctors. Locums are working in the same pressured and imperfect systems as other health workers; it is vital that systemic problems are not mistaken for problems about individuals and important to recognise that a locum is not a type of doctor but a way of working. Our findings are a call to action for organisations to take stock of how they engage, support and work with locums, and asks both locums and organisations to reflect on whether their practices support a collective approach to patient safety and quality of care.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

This study involves human participants and was approved by the Health Research Authority North West—Haydock Research Ethics Committee 20/NW/0386. Participants gave informed consent to participate in the study before taking part.

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Supplementary materials

Supplementary data.

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• Data supplement 1
• Data supplement 2
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• Data supplement 4

Twitter @janefergo, @@kieran_walshe

Contributors JF, KW, DA, TA and EK conceived the study. Recruitment was led by JF and supported by GS. JF, GS and KW conducted the interviews, reviewed and analysed the transcripts, and JF wrote the first version of the manuscript. Two members of the patient and public involvement (PPI) forum also assisted with focus groups. JF conducted data analysis with input from KW and GS, the PPI forum, and review by all authors. JF and KW were involved in initial critical review and revision of the manuscript, followed by all authors. All authors read and approved the final version of the manuscript. JF is the guarantor.

Funding This study was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR128349), and the NIHR Greater Manchester Patient Safety Research Collaboration (PSRC). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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How to do qualitative research?

Elaine denny.

1 Faculty of Health, Education and Life Sciences, Birmingham City University, Birmingham UK

Annalise Weckesser

Associated data.

Not applicable

Learning points

• The main methods used in qualitative research are interview, focus group and observation.
• Recruitment is purposive, or strategic, in that the aim is to achieve a sample that is relevant to the research question.
• Data are collected until saturation of themes and insights is reached.

Qualitative research begins with one or more relatively broad research questions that may be revised iteratively as the research is carried out to narrow the research aim or purpose. This is different from quantitative research, where a narrow research question is set at the start and remains fixed. For example, the aim of a study may be to explore the experiences of women who are pregnant while living with epilepsy. The initial research question may be ‘How do women with epilepsy experience pregnancy?’ However, from preliminary findings this may change to ‘How do women manage their epilepsy during pregnancy?’

There are three main methods used in qualitative research.

The first and most commonly used is interviewing. Semi‐structured interviews contain pre‐set, open‐ended questions, with further questions emerging from the discussion. Unstructured interviews cover a few issues in great depth, for example they can be used for life history narratives.

Focus groups are group discussions facilitated by a researcher, who will have guidelines to focus the group. Data collection consists of group interaction as well as discussion content. They can be stand alone, but more commonly are used to clarify or extend data collected by other methods.

Both interviews and focus groups tend to be flexible and non‐standardised, with greater interest in the participants' perspectives and experience than for quantitative research. However, it is important that flexibility does not result in asking leading questions.

Another method is observation, which is the act of watching social phenomena in real‐world settings, recording what people do, rather than what they profess to do. The observer may be part of the scene being observed (participant observation) or stand outside it (non‐participant).

Sampling for qualitative research tends to be purposive (that is recruitment on the basis of a shared experience that is relevant to the research question), convenience (based for example on accessibility or cost) or snowballing (where a few individuals from the target population will connect the researcher with their network). In the example above, women were purposefully recruited as pregnant, living with epilepsy and willing to be interviewed about how this impacted upon their lives (Weckesser & Denny. Soc Sci Med 2017:185;210–17).

The amount of data collected in qualitative research is not fixed or calculable, but continues until saturation is reached. That is, data are collected until emerging concepts have been explored and additional data are not producing fresh insights (Bryman. Social Research Methods , 3rd edn. Oxford: Oxford University Press; 2008). Generally speaking, the study sample size tends to be much smaller when compared with quantitative research.

Interviews and focus group discussions are usually audio‐recorded, with the consent of participants, and then transcribed verbatim. Written notes may also be made by the researcher for use in analysis. For the method of observation, extensive field notes are recorded during and after the event. Copious data are usually generated, which need to be organised for analysis, which is the focus of the next article in this series.

CONFLICT OF INTEREST

None declared. Completed disclosure of interests form available to view online as supporting information.

AUTHOR CONTRIBUTION

Elaine Denny and Annalise Weckesser contributed equally to the paper.

USEFUL RESOURCES

Britten N. Qualitative research: qualitative interviews in medical research. BMJ 1995;311:251–3.

Kitzinger J. Qualitative research: introducing focus groups. BMJ 1995;311:229.

Savage J. Participative observation: standing in the shoes of others? Qual Health Res 2000;3:324–39.

Supporting information

Appendix S1

Appendix S2

Denny E, Weckesser A. How to do qualitative research? . BJOG . 2022; 129 :1166–1167. 10.1111/1471-0528.17150 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

DATA AVAILABILITY STATEMENT