qualitative research methods in english literature

Chapter Four: Theory, Methodologies, Methods, and Evidence

Research Methods

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This page discusses the following topics:

Research Goals

Research method types.

Before discussing research   methods , we need to distinguish them from  methodologies  and  research skills . Methodologies, linked to literary theories, are tools and lines of investigation: sets of practices and propositions about texts and the world. Researchers using Marxist literary criticism will adopt methodologies that look to material forces like labor, ownership, and technology to understand literature and its relationship to the world. They will also seek to understand authors not as inspired geniuses but as people whose lives and work are shaped by social forces.

Example: Critical Race Theory Methodologies

Critical Race Theory may use a variety of methodologies, including

• Interest convergence: investigating whether marginalized groups only achieve progress when dominant groups benefit as well
• Intersectional theory: investigating how multiple factors of advantage and disadvantage around race, gender, ethnicity, religion, etc. operate together in complex ways
• Radical critique of the law: investigating how the law has historically been used to marginalize particular groups, such as black people, while recognizing that legal efforts are important to achieve emancipation and civil rights
• Social constructivism: investigating how race is socially constructed (rather than biologically grounded)
• Standpoint epistemology: investigating how knowledge relates to social position
• Structural determinism: investigating how structures of thought and of organizations determine social outcomes

To identify appropriate methodologies, you will need to research your chosen theory and gather what methodologies are associated with it. For the most part, we can’t assume that there are “one size fits all” methodologies.

Research skills are about how you handle materials such as library search engines, citation management programs, special collections materials, and so on.

Research methods  are about where and how you get answers to your research questions. Are you conducting interviews? Visiting archives? Doing close readings? Reviewing scholarship? You will need to choose which methods are most appropriate to use in your research and you need to gain some knowledge about how to use these methods. In other words, you need to do some research into research methods!

Your choice of research method depends on the kind of questions you are asking. For example, if you want to understand how an author progressed through several drafts to arrive at a final manuscript, you may need to do archival research. If you want to understand why a particular literary work became a bestseller, you may need to do audience research. If you want to know why a contemporary author wrote a particular work, you may need to do interviews. Usually literary research involves a combination of methods such as  archival research ,  discourse analysis , and  qualitative research  methods.

Literary research methods tend to differ from research methods in the hard sciences (such as physics and chemistry). Science research must present results that are reproducible, while literary research rarely does (though it must still present evidence for its claims). Literary research often deals with questions of meaning, social conventions, representations of lived experience, and aesthetic effects; these are questions that reward dialogue and different perspectives rather than one great experiment that settles the issue. In literary research, we might get many valuable answers even though they are quite different from one another. Also in literary research, we usually have some room to speculate about answers, but our claims have to be plausible (believable) and our argument comprehensive (meaning we don’t overlook evidence that would alter our argument significantly if it were known).

A literary researcher might select the following:

Theory: Critical Race Theory

Methodology: Social Constructivism

Method: Scholarly

Skills: Search engines, citation management

Wendy Belcher, in  Writing Your Journal Article in 12 Weeks , identifies two main approaches to understanding literary works: looking at a text by itself (associated with New Criticism ) and looking at texts as they connect to society (associated with Cultural Studies ). The goal of New Criticism is to bring the reader further into the text. The goal of Cultural Studies is to bring the reader into the network of discourses that surround and pass through the text. Other approaches, such as Ecocriticism, relate literary texts to the Sciences (as well as to the Humanities).

The New Critics, starting in the 1940s,  focused on meaning within the text itself, using a method they called “ close reading .” The text itself becomes e vidence for a particular reading. Using this approach, you should summarize the literary work briefly and q uote particularly meaningful passages, being sure to introduce quotes and then interpret them (never let them stand alone). Make connections within the work; a sk  “why” and “how” the various parts of the text relate to each other.

Cultural Studies critics see all texts  as connected to society; the critic  therefore has to connect a text to at least one political or social issue. How and why does  the text reproduce particular knowledge systems (known as discourses) and how do these knowledge systems relate to issues of power within the society? Who speaks and when? Answering these questions helps your reader understand the text in context. Cultural contexts can include the treatment of gender (Feminist, Queer), class (Marxist), nationality, race, religion, or any other area of human society.

Other approaches, such as psychoanalytic literary criticism , look at literary texts to better understand human psychology. A psychoanalytic reading can focus on a character, the author, the reader, or on society in general. Ecocriticism  look at human understandings of nature in literary texts.

We select our research methods based on the kinds of things we want to know. For example, we may be studying the relationship between literature and society, between author and text, or the status of a work in the literary canon. We may want to know about a work’s form, genre, or thematics. We may want to know about the audience’s reading and reception, or about methods for teaching literature in schools.

Below are a few research methods and their descriptions. You may need to consult with your instructor about which ones are most appropriate for your project. The first list covers methods most students use in their work. The second list covers methods more commonly used by advanced researchers. Even if you will not be using methods from this second list in your research project, you may read about these research methods in the scholarship you find.

Most commonly used undergraduate research methods:

• Scholarship Methods:  Studies the body of scholarship written about a particular author, literary work, historical period, literary movement, genre, theme, theory, or method.
• Textual Analysis Methods:  Used for close readings of literary texts, these methods also rely on literary theory and background information to support the reading.
• Biographical Methods:  Used to study the life of the author to better understand their work and times, these methods involve reading biographies and autobiographies about the author, and may also include research into private papers, correspondence, and interviews.
• Discourse Analysis Methods:  Studies language patterns to reveal ideology and social relations of power. This research involves the study of institutions, social groups, and social movements to understand how people in various settings use language to represent the world to themselves and others. Literary works may present complex mixtures of discourses which the characters (and readers) have to navigate.
• Creative Writing Methods:  A literary re-working of another literary text, creative writing research is used to better understand a literary work by investigating its language, formal structures, composition methods, themes, and so on. For instance, a creative research project may retell a story from a minor character’s perspective to reveal an alternative reading of events. To qualify as research, a creative research project is usually combined with a piece of theoretical writing that explains and justifies the work.

Methods used more often by advanced researchers:

• Archival Methods: Usually involves trips to special collections where original papers are kept. In these archives are many unpublished materials such as diaries, letters, photographs, ledgers, and so on. These materials can offer us invaluable insight into the life of an author, the development of a literary work, or the society in which the author lived. There are at least three major archives of James Baldwin’s papers: The Smithsonian , Yale , and The New York Public Library . Descriptions of such materials are often available online, but the materials themselves are typically stored in boxes at the archive.
• Computational Methods:  Used for statistical analysis of texts such as studies of the popularity and meaning of particular words in literature over time.
• Ethnographic Methods:  Studies groups of people and their interactions with literary works, for instance in educational institutions, in reading groups (such as book clubs), and in fan networks. This approach may involve interviews and visits to places (including online communities) where people interact with literary works. Note: before you begin such work, you must have  Institutional Review Board (IRB)  approval “to protect the rights and welfare of human participants involved in research.”
• Visual Methods:  Studies the visual qualities of literary works. Some literary works, such as illuminated manuscripts, children’s literature, and graphic novels, present a complex interplay of text and image. Even works without illustrations can be studied for their use of typography, layout, and other visual features.

Regardless of the method(s) you choose, you will need to learn how to apply them to your work and how to carry them out successfully. For example, you should know that many archives do not allow you to bring pens (you can use pencils) and you may not be allowed to bring bags into the archives. You will need to keep a record of which documents you consult and their location (box number, etc.) in the archives. If you are unsure how to use a particular method, please consult a book about it. [1] Also, ask for the advice of trained researchers such as your instructor or a research librarian.

• What research method(s) will you be using for your paper? Why did you make this method selection over other methods? If you haven’t made a selection yet, which methods are you considering?
• What specific methodological approaches are you most interested in exploring in relation to the chosen literary work?
• What is your plan for researching your method(s) and its major approaches?
• What was the most important lesson you learned from this page? What point was confusing or difficult to understand?

Write your answers in a webcourse discussion page.

• Introduction to Research Methods: A Practical Guide for Anyone Undertaking a Research Project  by Catherine, Dr. Dawson
• Practical Research Methods: A User-Friendly Guide to Mastering Research Techniques and Projects  by Catherine Dawson
• Qualitative Inquiry and Research Design: Choosing Among Five Approaches  by John W. Creswell  Cheryl N. Poth
• Qualitative Research Evaluation Methods: Integrating Theory and Practice  by Michael Quinn Patton
• Research Design: Qualitative, Quantitative, and Mixed Methods Approaches  by John W. Creswell  J. David Creswell
• Research Methodology: A Step-by-Step Guide for Beginners  by Ranjit Kumar
• Research Methodology: Methods and Techniques  by C.R. Kothari

Strategies for Conducting Literary Research Copyright © 2021 by Barry Mauer & John Venecek is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Methodology

• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on June 19, 2020 by Pritha Bhandari . Revised on June 22, 2023.

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

• Flexibility

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

• Natural settings

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

• Meaningful insights

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

• Generation of new ideas

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

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

• Unreliability

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

• Subjectivity

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

• Limited generalizability

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

• Labor-intensive

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

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

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

Research bias

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

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

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

There are five common approaches to qualitative research :

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

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

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

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

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

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Criteria for Good Qualitative Research: A Comprehensive Review

• Regular Article
• Open access
• Published: 18 September 2021
• Volume 31 , pages 679–689, ( 2022 )

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This review aims to synthesize a published set of evaluative criteria for good qualitative research. The aim is to shed light on existing standards for assessing the rigor of qualitative research encompassing a range of epistemological and ontological standpoints. Using a systematic search strategy, published journal articles that deliberate criteria for rigorous research were identified. Then, references of relevant articles were surveyed to find noteworthy, distinct, and well-defined pointers to good qualitative research. This review presents an investigative assessment of the pivotal features in qualitative research that can permit the readers to pass judgment on its quality and to condemn it as good research when objectively and adequately utilized. Overall, this review underlines the crux of qualitative research and accentuates the necessity to evaluate such research by the very tenets of its being. It also offers some prospects and recommendations to improve the quality of qualitative research. Based on the findings of this review, it is concluded that quality criteria are the aftereffect of socio-institutional procedures and existing paradigmatic conducts. Owing to the paradigmatic diversity of qualitative research, a single and specific set of quality criteria is neither feasible nor anticipated. Since qualitative research is not a cohesive discipline, researchers need to educate and familiarize themselves with applicable norms and decisive factors to evaluate qualitative research from within its theoretical and methodological framework of origin.

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Good Qualitative Research: Opening up the Debate

Beyond qualitative/quantitative structuralism: the positivist qualitative research and the paradigmatic disclaimer.

What is Qualitative in Research

Avoid common mistakes on your manuscript.

Introduction

“… It is important to regularly dialogue about what makes for good qualitative research” (Tracy, 2010 , p. 837)

To decide what represents good qualitative research is highly debatable. There are numerous methods that are contained within qualitative research and that are established on diverse philosophical perspectives. Bryman et al., ( 2008 , p. 262) suggest that “It is widely assumed that whereas quality criteria for quantitative research are well‐known and widely agreed, this is not the case for qualitative research.” Hence, the question “how to evaluate the quality of qualitative research” has been continuously debated. There are many areas of science and technology wherein these debates on the assessment of qualitative research have taken place. Examples include various areas of psychology: general psychology (Madill et al., 2000 ); counseling psychology (Morrow, 2005 ); and clinical psychology (Barker & Pistrang, 2005 ), and other disciplines of social sciences: social policy (Bryman et al., 2008 ); health research (Sparkes, 2001 ); business and management research (Johnson et al., 2006 ); information systems (Klein & Myers, 1999 ); and environmental studies (Reid & Gough, 2000 ). In the literature, these debates are enthused by the impression that the blanket application of criteria for good qualitative research developed around the positivist paradigm is improper. Such debates are based on the wide range of philosophical backgrounds within which qualitative research is conducted (e.g., Sandberg, 2000 ; Schwandt, 1996 ). The existence of methodological diversity led to the formulation of different sets of criteria applicable to qualitative research.

Among qualitative researchers, the dilemma of governing the measures to assess the quality of research is not a new phenomenon, especially when the virtuous triad of objectivity, reliability, and validity (Spencer et al., 2004 ) are not adequate. Occasionally, the criteria of quantitative research are used to evaluate qualitative research (Cohen & Crabtree, 2008 ; Lather, 2004 ). Indeed, Howe ( 2004 ) claims that the prevailing paradigm in educational research is scientifically based experimental research. Hypotheses and conjectures about the preeminence of quantitative research can weaken the worth and usefulness of qualitative research by neglecting the prominence of harmonizing match for purpose on research paradigm, the epistemological stance of the researcher, and the choice of methodology. Researchers have been reprimanded concerning this in “paradigmatic controversies, contradictions, and emerging confluences” (Lincoln & Guba, 2000 ).

In general, qualitative research tends to come from a very different paradigmatic stance and intrinsically demands distinctive and out-of-the-ordinary criteria for evaluating good research and varieties of research contributions that can be made. This review attempts to present a series of evaluative criteria for qualitative researchers, arguing that their choice of criteria needs to be compatible with the unique nature of the research in question (its methodology, aims, and assumptions). This review aims to assist researchers in identifying some of the indispensable features or markers of high-quality qualitative research. In a nutshell, the purpose of this systematic literature review is to analyze the existing knowledge on high-quality qualitative research and to verify the existence of research studies dealing with the critical assessment of qualitative research based on the concept of diverse paradigmatic stances. Contrary to the existing reviews, this review also suggests some critical directions to follow to improve the quality of qualitative research in different epistemological and ontological perspectives. This review is also intended to provide guidelines for the acceleration of future developments and dialogues among qualitative researchers in the context of assessing the qualitative research.

The rest of this review article is structured in the following fashion: Sect.  Methods describes the method followed for performing this review. Section Criteria for Evaluating Qualitative Studies provides a comprehensive description of the criteria for evaluating qualitative studies. This section is followed by a summary of the strategies to improve the quality of qualitative research in Sect.  Improving Quality: Strategies . Section  How to Assess the Quality of the Research Findings? provides details on how to assess the quality of the research findings. After that, some of the quality checklists (as tools to evaluate quality) are discussed in Sect.  Quality Checklists: Tools for Assessing the Quality . At last, the review ends with the concluding remarks presented in Sect.  Conclusions, Future Directions and Outlook . Some prospects in qualitative research for enhancing its quality and usefulness in the social and techno-scientific research community are also presented in Sect.  Conclusions, Future Directions and Outlook .

For this review, a comprehensive literature search was performed from many databases using generic search terms such as Qualitative Research , Criteria , etc . The following databases were chosen for the literature search based on the high number of results: IEEE Explore, ScienceDirect, PubMed, Google Scholar, and Web of Science. The following keywords (and their combinations using Boolean connectives OR/AND) were adopted for the literature search: qualitative research, criteria, quality, assessment, and validity. The synonyms for these keywords were collected and arranged in a logical structure (see Table 1 ). All publications in journals and conference proceedings later than 1950 till 2021 were considered for the search. Other articles extracted from the references of the papers identified in the electronic search were also included. A large number of publications on qualitative research were retrieved during the initial screening. Hence, to include the searches with the main focus on criteria for good qualitative research, an inclusion criterion was utilized in the search string.

From the selected databases, the search retrieved a total of 765 publications. Then, the duplicate records were removed. After that, based on the title and abstract, the remaining 426 publications were screened for their relevance by using the following inclusion and exclusion criteria (see Table 2 ). Publications focusing on evaluation criteria for good qualitative research were included, whereas those works which delivered theoretical concepts on qualitative research were excluded. Based on the screening and eligibility, 45 research articles were identified that offered explicit criteria for evaluating the quality of qualitative research and were found to be relevant to this review.

Figure  1 illustrates the complete review process in the form of PRISMA flow diagram. PRISMA, i.e., “preferred reporting items for systematic reviews and meta-analyses” is employed in systematic reviews to refine the quality of reporting.

PRISMA flow diagram illustrating the search and inclusion process. N represents the number of records

Criteria for Evaluating Qualitative Studies

Fundamental criteria: general research quality.

Various researchers have put forward criteria for evaluating qualitative research, which have been summarized in Table 3 . Also, the criteria outlined in Table 4 effectively deliver the various approaches to evaluate and assess the quality of qualitative work. The entries in Table 4 are based on Tracy’s “Eight big‐tent criteria for excellent qualitative research” (Tracy, 2010 ). Tracy argues that high-quality qualitative work should formulate criteria focusing on the worthiness, relevance, timeliness, significance, morality, and practicality of the research topic, and the ethical stance of the research itself. Researchers have also suggested a series of questions as guiding principles to assess the quality of a qualitative study (Mays & Pope, 2020 ). Nassaji ( 2020 ) argues that good qualitative research should be robust, well informed, and thoroughly documented.

Qualitative Research: Interpretive Paradigms

All qualitative researchers follow highly abstract principles which bring together beliefs about ontology, epistemology, and methodology. These beliefs govern how the researcher perceives and acts. The net, which encompasses the researcher’s epistemological, ontological, and methodological premises, is referred to as a paradigm, or an interpretive structure, a “Basic set of beliefs that guides action” (Guba, 1990 ). Four major interpretive paradigms structure the qualitative research: positivist and postpositivist, constructivist interpretive, critical (Marxist, emancipatory), and feminist poststructural. The complexity of these four abstract paradigms increases at the level of concrete, specific interpretive communities. Table 5 presents these paradigms and their assumptions, including their criteria for evaluating research, and the typical form that an interpretive or theoretical statement assumes in each paradigm. Moreover, for evaluating qualitative research, quantitative conceptualizations of reliability and validity are proven to be incompatible (Horsburgh, 2003 ). In addition, a series of questions have been put forward in the literature to assist a reviewer (who is proficient in qualitative methods) for meticulous assessment and endorsement of qualitative research (Morse, 2003 ). Hammersley ( 2007 ) also suggests that guiding principles for qualitative research are advantageous, but methodological pluralism should not be simply acknowledged for all qualitative approaches. Seale ( 1999 ) also points out the significance of methodological cognizance in research studies.

Table 5 reflects that criteria for assessing the quality of qualitative research are the aftermath of socio-institutional practices and existing paradigmatic standpoints. Owing to the paradigmatic diversity of qualitative research, a single set of quality criteria is neither possible nor desirable. Hence, the researchers must be reflexive about the criteria they use in the various roles they play within their research community.

Improving Quality: Strategies

Another critical question is “How can the qualitative researchers ensure that the abovementioned quality criteria can be met?” Lincoln and Guba ( 1986 ) delineated several strategies to intensify each criteria of trustworthiness. Other researchers (Merriam & Tisdell, 2016 ; Shenton, 2004 ) also presented such strategies. A brief description of these strategies is shown in Table 6 .

It is worth mentioning that generalizability is also an integral part of qualitative research (Hays & McKibben, 2021 ). In general, the guiding principle pertaining to generalizability speaks about inducing and comprehending knowledge to synthesize interpretive components of an underlying context. Table 7 summarizes the main metasynthesis steps required to ascertain generalizability in qualitative research.

Figure  2 reflects the crucial components of a conceptual framework and their contribution to decisions regarding research design, implementation, and applications of results to future thinking, study, and practice (Johnson et al., 2020 ). The synergy and interrelationship of these components signifies their role to different stances of a qualitative research study.

Essential elements of a conceptual framework

In a nutshell, to assess the rationale of a study, its conceptual framework and research question(s), quality criteria must take account of the following: lucid context for the problem statement in the introduction; well-articulated research problems and questions; precise conceptual framework; distinct research purpose; and clear presentation and investigation of the paradigms. These criteria would expedite the quality of qualitative research.

How to Assess the Quality of the Research Findings?

The inclusion of quotes or similar research data enhances the confirmability in the write-up of the findings. The use of expressions (for instance, “80% of all respondents agreed that” or “only one of the interviewees mentioned that”) may also quantify qualitative findings (Stenfors et al., 2020 ). On the other hand, the persuasive reason for “why this may not help in intensifying the research” has also been provided (Monrouxe & Rees, 2020 ). Further, the Discussion and Conclusion sections of an article also prove robust markers of high-quality qualitative research, as elucidated in Table 8 .

Quality Checklists: Tools for Assessing the Quality

Numerous checklists are available to speed up the assessment of the quality of qualitative research. However, if used uncritically and recklessly concerning the research context, these checklists may be counterproductive. I recommend that such lists and guiding principles may assist in pinpointing the markers of high-quality qualitative research. However, considering enormous variations in the authors’ theoretical and philosophical contexts, I would emphasize that high dependability on such checklists may say little about whether the findings can be applied in your setting. A combination of such checklists might be appropriate for novice researchers. Some of these checklists are listed below:

The most commonly used framework is Consolidated Criteria for Reporting Qualitative Research (COREQ) (Tong et al., 2007 ). This framework is recommended by some journals to be followed by the authors during article submission.

Standards for Reporting Qualitative Research (SRQR) is another checklist that has been created particularly for medical education (O’Brien et al., 2014 ).

Also, Tracy ( 2010 ) and Critical Appraisal Skills Programme (CASP, 2021 ) offer criteria for qualitative research relevant across methods and approaches.

Further, researchers have also outlined different criteria as hallmarks of high-quality qualitative research. For instance, the “Road Trip Checklist” (Epp & Otnes, 2021 ) provides a quick reference to specific questions to address different elements of high-quality qualitative research.

Conclusions, Future Directions, and Outlook

This work presents a broad review of the criteria for good qualitative research. In addition, this article presents an exploratory analysis of the essential elements in qualitative research that can enable the readers of qualitative work to judge it as good research when objectively and adequately utilized. In this review, some of the essential markers that indicate high-quality qualitative research have been highlighted. I scope them narrowly to achieve rigor in qualitative research and note that they do not completely cover the broader considerations necessary for high-quality research. This review points out that a universal and versatile one-size-fits-all guideline for evaluating the quality of qualitative research does not exist. In other words, this review also emphasizes the non-existence of a set of common guidelines among qualitative researchers. In unison, this review reinforces that each qualitative approach should be treated uniquely on account of its own distinctive features for different epistemological and disciplinary positions. Owing to the sensitivity of the worth of qualitative research towards the specific context and the type of paradigmatic stance, researchers should themselves analyze what approaches can be and must be tailored to ensemble the distinct characteristics of the phenomenon under investigation. Although this article does not assert to put forward a magic bullet and to provide a one-stop solution for dealing with dilemmas about how, why, or whether to evaluate the “goodness” of qualitative research, it offers a platform to assist the researchers in improving their qualitative studies. This work provides an assembly of concerns to reflect on, a series of questions to ask, and multiple sets of criteria to look at, when attempting to determine the quality of qualitative research. Overall, this review underlines the crux of qualitative research and accentuates the need to evaluate such research by the very tenets of its being. Bringing together the vital arguments and delineating the requirements that good qualitative research should satisfy, this review strives to equip the researchers as well as reviewers to make well-versed judgment about the worth and significance of the qualitative research under scrutiny. In a nutshell, a comprehensive portrayal of the research process (from the context of research to the research objectives, research questions and design, speculative foundations, and from approaches of collecting data to analyzing the results, to deriving inferences) frequently proliferates the quality of a qualitative research.

Prospects : A Road Ahead for Qualitative Research

Irrefutably, qualitative research is a vivacious and evolving discipline wherein different epistemological and disciplinary positions have their own characteristics and importance. In addition, not surprisingly, owing to the sprouting and varied features of qualitative research, no consensus has been pulled off till date. Researchers have reflected various concerns and proposed several recommendations for editors and reviewers on conducting reviews of critical qualitative research (Levitt et al., 2021 ; McGinley et al., 2021 ). Following are some prospects and a few recommendations put forward towards the maturation of qualitative research and its quality evaluation:

In general, most of the manuscript and grant reviewers are not qualitative experts. Hence, it is more likely that they would prefer to adopt a broad set of criteria. However, researchers and reviewers need to keep in mind that it is inappropriate to utilize the same approaches and conducts among all qualitative research. Therefore, future work needs to focus on educating researchers and reviewers about the criteria to evaluate qualitative research from within the suitable theoretical and methodological context.

There is an urgent need to refurbish and augment critical assessment of some well-known and widely accepted tools (including checklists such as COREQ, SRQR) to interrogate their applicability on different aspects (along with their epistemological ramifications).

Efforts should be made towards creating more space for creativity, experimentation, and a dialogue between the diverse traditions of qualitative research. This would potentially help to avoid the enforcement of one's own set of quality criteria on the work carried out by others.

Moreover, journal reviewers need to be aware of various methodological practices and philosophical debates.

It is pivotal to highlight the expressions and considerations of qualitative researchers and bring them into a more open and transparent dialogue about assessing qualitative research in techno-scientific, academic, sociocultural, and political rooms.

Frequent debates on the use of evaluative criteria are required to solve some potentially resolved issues (including the applicability of a single set of criteria in multi-disciplinary aspects). Such debates would not only benefit the group of qualitative researchers themselves, but primarily assist in augmenting the well-being and vivacity of the entire discipline.

To conclude, I speculate that the criteria, and my perspective, may transfer to other methods, approaches, and contexts. I hope that they spark dialog and debate – about criteria for excellent qualitative research and the underpinnings of the discipline more broadly – and, therefore, help improve the quality of a qualitative study. Further, I anticipate that this review will assist the researchers to contemplate on the quality of their own research, to substantiate research design and help the reviewers to review qualitative research for journals. On a final note, I pinpoint the need to formulate a framework (encompassing the prerequisites of a qualitative study) by the cohesive efforts of qualitative researchers of different disciplines with different theoretic-paradigmatic origins. I believe that tailoring such a framework (of guiding principles) paves the way for qualitative researchers to consolidate the status of qualitative research in the wide-ranging open science debate. Dialogue on this issue across different approaches is crucial for the impending prospects of socio-techno-educational research.

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Yadav, D. Criteria for Good Qualitative Research: A Comprehensive Review. Asia-Pacific Edu Res 31 , 679–689 (2022). https://doi.org/10.1007/s40299-021-00619-0

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What is Qualitative Research? Methods, Types, Approaches and Examples

Qualitative research is a type of method that researchers use depending on their study requirements. Research can be conducted using several methods, but before starting the process, researchers should understand the different methods available to decide the best one for their study type. The type of research method needed depends on a few important criteria, such as the research question, study type, time, costs, data availability, and availability of respondents. The two main types of methods are qualitative research and quantitative research. Sometimes, researchers may find it difficult to decide which type of method is most suitable for their study. Keeping in mind a simple rule of thumb could help you make the correct decision. Quantitative research should be used to validate or test a theory or hypothesis and qualitative research should be used to understand a subject or event or identify reasons for observed patterns.  

Qualitative research methods are based on principles of social sciences from several disciplines like psychology, sociology, and anthropology. In this method, researchers try to understand the feelings and motivation of their respondents, which would have prompted them to select or give a particular response to a question. Here are two qualitative research examples :  

• Two brands (A & B) of the same medicine are available at a pharmacy. However, Brand A is more popular and has higher sales. In qualitative research , the interviewers would ideally visit a few stores in different areas and ask customers their reason for selecting either brand. Respondents may have different reasons that motivate them to select one brand over the other, such as brand loyalty, cost, feedback from friends, doctor’s suggestion, etc. Once the reasons are known, companies could then address challenges in that specific area to increase their product’s sales.  
• A company organizes a focus group meeting with a random sample of its product’s consumers to understand their opinion on a new product being launched.  

Table of Contents

What is qualitative research? 1

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data. The findings of qualitative research are expressed in words and help in understanding individuals’ subjective perceptions about an event, condition, or subject. This type of research is exploratory and is used to generate hypotheses or theories from data. Qualitative data are usually in the form of text, videos, photographs, and audio recordings. There are multiple qualitative research types , which will be discussed later.  

Qualitative research methods 2

Researchers can choose from several qualitative research methods depending on the study type, research question, the researcher’s role, data to be collected, etc.  

The following table lists the common qualitative research approaches with their purpose and examples, although there may be an overlap between some.  

Types of qualitative research 3,4

The data collection methods in qualitative research are designed to assess and understand the perceptions, motivations, and feelings of the respondents about the subject being studied. The different qualitative research types include the following:  

• In-depth or one-on-one interviews : This is one of the most common qualitative research methods and helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event. These interviews are usually conversational and encourage the respondents to express their opinions freely. Semi-structured interviews, which have open-ended questions (where the respondents can answer more than just “yes” or “no”), are commonly used. Such interviews can be either face-to-face or telephonic, and the duration can vary depending on the subject or the interviewer. Asking the right questions is essential in this method so that the interview can be led in the suitable direction. Face-to-face interviews also help interviewers observe the respondents’ body language, which could help in confirming whether the responses match.  
• Document study/Literature review/Record keeping : Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.  
• Focus groups : Usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic. Focus groups ensure constructive discussions to understand the why, what, and, how about the topic. These group meetings need not always be in-person. In recent times, online meetings are also encouraged, and online surveys could also be administered with the option to “write” subjective answers as well. However, this method is expensive and is mostly used for new products and ideas.  
• Qualitative observation : In this method, researchers collect data using their five senses—sight, smell, touch, taste, and hearing. This method doesn’t include any measurements but only the subjective observation. For example, “The dessert served at the bakery was creamy with sweet buttercream frosting”; this observation is based on the taste perception.  

Qualitative research : Data collection and analysis

• Qualitative data collection is the process by which observations or measurements are gathered in research.  
• The data collected are usually non-numeric and subjective and could be recorded in various methods, for instance, in case of one-to-one interviews, the responses may be recorded using handwritten notes, and audio and video recordings, depending on the interviewer and the setting or duration.  
• Once the data are collected, they should be transcribed into meaningful or useful interpretations. An experienced researcher could take about 8-10 hours to transcribe an interview’s recordings. All such notes and recordings should be maintained properly for later reference.  
• Some interviewers make use of “field notes.” These are not exactly the respondents’ answers but rather some observations the interviewer may have made while asking questions and may include non-verbal cues or any information about the setting or the environment. These notes are usually informal and help verify respondents’ answers.  

2. Qualitative data analysis 

• This process involves analyzing all the data obtained from the qualitative research methods in the form of text (notes), audio-video recordings, and pictures.  
• Text analysis is a common form of qualitative data analysis in which researchers examine the social lives of the participants and analyze their words, actions, etc. in specific contexts. Social media platforms are now playing an important role in this method with researchers analyzing all information shared online.   

There are usually five steps in the qualitative data analysis process: 5

• Prepare and organize the data  
• Transcribe interviews  
• Collect and document field notes and other material  
• Review and explore the data  
• Examine the data for patterns or important observations  
• Develop a data coding system  
• Create codes to categorize and connect the data  
• Assign these codes to the data or responses  
• Review the codes  
• Identify recurring themes, opinions, patterns, etc.  
• Present the findings  
• Use the best possible method to present your observations  

The following table 6 lists some common qualitative data analysis methods used by companies to make important decisions, with examples and when to use each. The methods may be similar and can overlap.  

Characteristics of qualitative research methods 4

• Unstructured raw data : Qualitative research methods use unstructured, non-numerical data , which are analyzed to generate subjective conclusions about specific subjects, usually presented descriptively, instead of using statistical data.  
• Site-specific data collection : In qualitative research methods , data are collected at specific areas where the respondents or researchers are either facing a challenge or have a need to explore. The process is conducted in a real-world setting and participants do not need to leave their original geographical setting to be able to participate.  
• Researchers’ importance : Researchers play an instrumental role because, in qualitative research , communication with respondents is an essential part of data collection and analysis. In addition, researchers need to rely on their own observation and listening skills during an interaction and use and interpret that data appropriately.  
• Multiple methods : Researchers collect data through various methods, as listed earlier, instead of relying on a single source. Although there may be some overlap between the qualitative research methods , each method has its own significance.  
• Solving complex issues : These methods help in breaking down complex problems into more useful and interpretable inferences, which can be easily understood by everyone.  
• Unbiased responses : Qualitative research methods rely on open communication where the participants are allowed to freely express their views. In such cases, the participants trust the interviewer, resulting in unbiased and truthful responses.  
• Flexible : The qualitative research method can be changed at any stage of the research. The data analysis is not confined to being done at the end of the research but can be done in tandem with data collection. Consequently, based on preliminary analysis and new ideas, researchers have the liberty to change the method to suit their objective.  

When to use qualitative research   4

The following points will give you an idea about when to use qualitative research .  

• When the objective of a research study is to understand behaviors and patterns of respondents, then qualitative research is the most suitable method because it gives a clear insight into the reasons for the occurrence of an event.  
• A few use cases for qualitative research methods include:  
• New product development or idea generation  
• Strengthening a product’s marketing strategy  
• Conducting a SWOT analysis of product or services portfolios to help take important strategic decisions  
• Understanding purchasing behavior of consumers  
• Understanding reactions of target market to ad campaigns  
• Understanding market demographics and conducting competitor analysis  
• Understanding the effectiveness of a new treatment method in a particular section of society  

A qualitative research method case study to understand when to use qualitative research 7

Context : A high school in the US underwent a turnaround or conservatorship process and consequently experienced a below average teacher retention rate. Researchers conducted qualitative research to understand teachers’ experiences and perceptions of how the turnaround may have influenced the teachers’ morale and how this, in turn, would have affected teachers’ retention.  

Method : Purposive sampling was used to select eight teachers who were employed with the school before the conservatorship process and who were subsequently retained. One-on-one semi-structured interviews were conducted with these teachers. The questions addressed teachers’ perspectives of morale and their views on the conservatorship process.  

Results : The study generated six factors that may have been influencing teachers’ perspectives: powerlessness, excessive visitations, loss of confidence, ineffective instructional practices, stress and burnout, and ineffective professional development opportunities. Based on these factors, four recommendations were made to increase teacher retention by boosting their morale.  

Advantages of qualitative research 1

• Reflects real-world settings , and therefore allows for ambiguities in data, as well as the flexibility to change the method based on new developments.  
• Helps in understanding the feelings or beliefs of the respondents rather than relying only on quantitative data.  
• Uses a descriptive and narrative style of presentation, which may be easier to understand for people from all backgrounds.  
• Some topics involving sensitive or controversial content could be difficult to quantify and so qualitative research helps in analyzing such content.  
• The availability of multiple data sources and research methods helps give a holistic picture.  
• There’s more involvement of participants, which gives them an assurance that their opinion matters, possibly leading to unbiased responses.   

Disadvantages of qualitative research 1

• Large-scale data sets cannot be included because of time and cost constraints.  
• Ensuring validity and reliability may be a challenge because of the subjective nature of the data, so drawing definite conclusions could be difficult.  
• Replication by other researchers may be difficult for the same contexts or situations.  
• Generalization to a wider context or to other populations or settings is not possible.  
• Data collection and analysis may be time consuming.  
• Researcher’s interpretation may alter the results causing an unintended bias.  

Differences between qualitative research and quantitative research 1

Frequently asked questions on qualitative research  

Q: how do i know if qualitative research is appropriate for my study  .

A: Here’s a simple checklist you could use:  

• Not much is known about the subject being studied.  
• There is a need to understand or simplify a complex problem or situation.  
• Participants’ experiences/beliefs/feelings are required for analysis.  
• There’s no existing hypothesis to begin with, rather a theory would need to be created after analysis.  
• You need to gather in-depth understanding of an event or subject, which may not need to be supported by numeric data.  

Q: How do I ensure the reliability and validity of my qualitative research findings?  

A: To ensure the validity of your qualitative research findings you should explicitly state your objective and describe clearly why you have interpreted the data in a particular way. Another method could be to connect your data in different ways or from different perspectives to see if you reach a similar, unbiased conclusion.   

To ensure reliability, always create an audit trail of your qualitative research by describing your steps and reasons for every interpretation, so that if required, another researcher could trace your steps to corroborate your (or their own) findings. In addition, always look for patterns or consistencies in the data collected through different methods.  

Q: Are there any sampling strategies or techniques for qualitative research ?   

A: Yes, the following are few common sampling strategies used in qualitative research :  

1. Convenience sampling  

Selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.  

2. Purposive sampling  

Participants are grouped according to predefined criteria based on a specific research question. Sample sizes are often determined based on theoretical saturation (when new data no longer provide additional insights).  

3. Snowball sampling  

Already selected participants use their social networks to refer the researcher to other potential participants.  

4. Quota sampling  

While designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.  

Q: What ethical standards need to be followed with qualitative research ?  

A: The following ethical standards should be considered in qualitative research:  

• Anonymity : The participants should never be identified in the study and researchers should ensure that no identifying information is mentioned even indirectly.  
• Confidentiality : To protect participants’ confidentiality, ensure that all related documents, transcripts, notes are stored safely.  
• Informed consent : Researchers should clearly communicate the objective of the study and how the participants’ responses will be used prior to engaging with the participants.  

Q: How do I address bias in my qualitative research ?  

  A: You could use the following points to ensure an unbiased approach to your qualitative research :  

• Check your interpretations of the findings with others’ interpretations to identify consistencies.  
• If possible, you could ask your participants if your interpretations convey their beliefs to a significant extent.  
• Data triangulation is a way of using multiple data sources to see if all methods consistently support your interpretations.  
• Contemplate other possible explanations for your findings or interpretations and try ruling them out if possible.  
• Conduct a peer review of your findings to identify any gaps that may not have been visible to you.  
• Frame context-appropriate questions to ensure there is no researcher or participant bias.

We hope this article has given you answers to the question “ what is qualitative research ” and given you an in-depth understanding of the various aspects of qualitative research , including the definition, types, and approaches, when to use this method, and advantages and disadvantages, so that the next time you undertake a study you would know which type of research design to adopt.  

References:  

• McLeod, S. A. Qualitative vs. quantitative research. Simply Psychology [Accessed January 17, 2023]. www.simplypsychology.org/qualitative-quantitative.html    
• Omniconvert website [Accessed January 18, 2023]. https://www.omniconvert.com/blog/qualitative-research-definition-methodology-limitation-examples/  
• Busetto L., Wick W., Gumbinger C. How to use and assess qualitative research methods. Neurological Research and Practice [Accessed January 19, 2023] https://neurolrespract.biomedcentral.com/articles/10.1186/s42466-020-00059  
• QuestionPro website. Qualitative research methods: Types & examples [Accessed January 16, 2023]. https://www.questionpro.com/blog/qualitative-research-methods/  
• Campuslabs website. How to analyze qualitative data [Accessed January 18, 2023]. https://baselinesupport.campuslabs.com/hc/en-us/articles/204305675-How-to-analyze-qualitative-data  
• Thematic website. Qualitative data analysis: Step-by-guide [Accessed January 20, 2023]. https://getthematic.com/insights/qualitative-data-analysis/  
• Lane L. J., Jones D., Penny G. R. Qualitative case study of teachers’ morale in a turnaround school. Research in Higher Education Journal . https://files.eric.ed.gov/fulltext/EJ1233111.pdf  
• Meetingsnet website. 7 FAQs about qualitative research and CME [Accessed January 21, 2023]. https://www.meetingsnet.com/cme-design/7-faqs-about-qualitative-research-and-cme     
• Qualitative research methods: A data collector’s field guide. Khoury College of Computer Sciences. Northeastern University. https://course.ccs.neu.edu/is4800sp12/resources/qualmethods.pdf  

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35 Qualitative Research

Dr. Neeru Tandon

The students will grasp the basic essentials about qualitative research in English language teaching. They will identify key issues regarding research in current English language studies and develop skills to search online and offline sources to carry out literature review. They will come to know various aspects of quantitative, qualitative, and mixed-methods research in English studies. Multiple-choice exercises will help them in assessing their knowledge and understanding of the work. Bibliography, list of websites and YouTube videos will help them in their in-depth study and further reading.

The chapter aims to enable students to:

• Understand various research paradigms and become aware of theoretical and practical issues related to humanities research especially in contemporary English language studies
• Review previously published work in the field; select an appropriate research topic with an awareness of principles in research design
• Demonstrate knowledge required to plan and conduct research with an understanding of appropriate research methods for a particular domain
• Familiarize themselves with skills to analyze different types of research data and explore various tools and software for the analyses
• Consolidate their research and academic skills to present research findings in both spoken and written forms.

INTRODUCTION

There are many approaches to dealing with research. Two of the most common are known as quantitative and qualitative, although this distinction is somewhat simplistic as the relationship is best thought of as a continuum of research types. The term qualitative research is an imprecise term that creates at least two problems. One problem arises because qualitative refers to a type of data, not a type of research design. This makes the idea of qualitative research illogical–even impossible since it ignores the possibility of triangulation using multiple types of data, some of which might be qualitative and some of which might be quantitative. Furthermore, the term assumes the type of data determines the type of research. Nevertheless, despite these problems, many researchers and editors continue to use the term qualitative to refer to a type of research instead of restricting its use to a type of data. A second and related problem is that the general term qualitative research can refer to any number of research designs, for example case study, ethnography, or grounded theory. In these research designs, none of the assumptions of experimental design, such as variables and hypothesis testing are operative.

DEFINING QUALITATIVE RESEARCH

One of the most common ways to classify research is by categorizing them according to the data (gathered and analyzed). According to the data gathered, research can be classified into two kinds: quantitative and qualitative research. To put it simply, quantitative research deals with numbers whereas qualitative research deals with words.

The term qualitative research is associated with a range of different methods, perspectives, and approaches. As Mason (1996) pointed out, “qualitative research—whatever it might be—

certainly does not represent a unified set of techniques or philosophies, and indeed has grown out of a wide range of intellectual and disciplinary traditions”.

To give a general definition of qualitative research in the second language field the term qualitative research can be taken to refer to research that is based on descriptive data that does not make (regular) use of statistical procedures.

Scollon (2001) argued that critical discourse analysis, a form of qualitative research, is “a program of social analysis that critically analyzes discourse—that is to say language in use—as a means of addressing social change”.

Describing quantitative research has been a relatively straightforward task because there is a general agreement amongst QUAN practitioners about the main features and principles of the approach. This is not at all the case with QUAL research. In a recent overview of the field, two of the most influential qualitative researchers, Denzin and Lincoln (2oo5a), concluded that ‘qualitative research is difficult to define clearly. It has no theory or paradigm that is distinctly shown. Nor does qualitative research have a: distinct set of methods or practices that are entirely its own, (p. 6-7). And later they added, ‘Qualitative research is many things to many people’ (p~ IO). Denzin and Lincoln’s view is not at all exaggerated and is shared throughout the profession. For example, another well-known proponent of qualitative research, Silverman (I997), expressed a similar conclusion when he stated that ‘there is no agreed doctrine underlying all qualitative social research’ (p. I4). Furthermore, Holliday (2004: 73I) has added that ‘boundaries in current qualitative research are crumbling, and researchers are increasingly doing whatever they can to find out what they want to know’. As seen earlier, the lack of uniformity goes back to the genesis of the qualitative approach when scholars of diverse beliefs united under the qualitative label in their fight against the quantitative paradigm. Luckily, the overall picture is not as gloomy and fragmented as the above quotes would suggest. Qualitative research is in fact a thriving discipline, and while it is true that some issues have been subject to a lot of, and sometimes heated, discussion, there exists a core set of features that would universally characterize a properly conducted qualitative study.

Brief Historical Overview

Research that can be considered ‘qualitative’ in retrospect has been around for about- a century in the social sciences. Qualitative-like methods were Research Methods in Applied Linguistics introduced into sociology at the end of the first decade of the twentieth century through the work of the Chicago School for the study of human group life, and during the first third of the century anthropology also produced some seminal qualitative studies by renowned scholars such as Boas and Malinowski, defining the outlines of the fieldwork method . Thus, the basic QUAL ideas and principles are not new at-all, yet the first text that tried to define ‘qualitative methodology’ -Glaser and Strauss’s (1967) The Discovery of Grounded Theory: Strategies for Qualitative Research – did not appear until the late sixties. In this highly influential book the authors described the use of qualitative procedures by the QUAL pointers as ‘nonsystematic and nonrigorous’, and opposed that early monographs based on qualitative data consisted of ‘lengthy, detailed descriptions, which resulted in very small amounts of theory, if any’. After the I930s and particularly after World War 1, quantitative research methodology produced substantial advances and qualitative research was relegated to preliminary, exploratory work whose role was seen to provide the ‘more serious’ quantitative studies with an adequate starting point. The middle of the twentieth century was undoubtedly subjugated by quantitative research, and the invaluable merit of Glaset’ and Strauss’f (1967) book was to offer a worthwhile challenge to this domination.

In applied linguistics there has been an increasing visibility and acceptance of qualitative research since the mid-I990s. This is related to the growing recognition that almost every aspect of language acquisition and use is determined or significantly shaped by social, cultural, and situational factors, and qualitative research is ideal for providing insights into such contextual conditions and influences. Accordingly, applied linguistics has been offering an increasingly level playing field for both QUAN and QUAL approaches.

Although the frequency of published QUAL studies is still relatively low, the impact of qualitative research in applied linguistics over the past three decades has been profound. Early case studies of the I970S and I980s generated many of the prevailing principles and models. With regard to contemporary research, we find qualitative studies focusing on topics across the whole research spectrum, even including core quantitative areas such as language testing, and several key areas of applied linguistics (for example, the study of gender, race, ethnicity, and identity) are being driven by qualitative research.

Ideally, qualitative researchers enter the research process with a completely open mind and without setting out to test preconceived hypotheses. In their seminal work, Glaser and Strauss (I967) actively encouraged qualitative researchers to ignore the literature before the investigation in order to assure that ‘the emergence of categories will not be contaminated by concepts more suited to different areas’.

The Nature of Qualitative Data

Qualitative research works with a wide range of data including recorded interviews, various types of texts (for example, field notes, journal and diary entries, and documents) and images. During data processing most data are transformed into a textual form (for example, interview recordings are transcribed) because most qualitative data analysis is done with words. Although qualitative data is not gathered with the purpose of being directly counted or measured in art objective way, subsequent analysis can define categories through which certain aspects of qualitative data can be quantified. Because the common objective of all the different types of qualitative methods is to make sense of a set of (cultural or personal) meanings in the observed phenomena, it is indispensable that the data should capture rich and complex details. Therefore, in order to achieve such a ‘thick’ description, almost any relevant information can be admitted as QUAL data.

Because of the QUAL objective to describe social phenomena as they occur naturally, qualitative research takes place in the natural setting, without any attempts to manipulate the situation under study.

Qualitative research is concerned with subjective opinions, experiences and feelings of individuals and thus the overt target of research is to discover the participants’ views of the situation being studied. This approach follows from the way qualitative researchers perceive meaning: it is a fundamental QUAL principle that human behaviour is based upon meanings which people attribute to and bring to situations (Punch 2005) and it is only the actual participants themselves who can reveal the meanings and interpretations of their experiences and actions. Therefore, qualitative researchers struggle to view social phenomena from the perspectives of the ‘insiders’ and the term ‘insider perspective’ has a special place in the qualitative dogma.

In quantitative study, data is usually analyzed using computer software (e.g. t-test) and presented in numerical forms (by using percentage, for example). Quantitative studies usually start with a (written) hypothesis that needs to be “tested” by conducting the research. In contrast, qualitative studies start with the assumption that the research topic must be understood “holistically”

(McKay, 2006, )

Interpretive analysis of Qualitative Research

Qualitative research is fundamentally interpretive, which means that the research outcome is ultimately the product of the researcher’s subjective interpretation of the data. Several alternative interpretations are possible for each dataset, and because QUAL studies utilize relatively limited harmonized equipment or diagnostic methods, finally the researcher will decide it. As Miles and Huberman (I994: 7) conclude, ‘The researcher is essentially the main “measurement device” in the study’. Accordingly, in qualitative research, the researcher’s own values, personal history, and ‘position’ on characteristics such as gender, culture, class, and age become integral part of the inquiry

(Haverkamp 2005).

One of the most challenging issues amongst qualitative researchers concerns the question as to whether researchers need to enter a QUAL project with only nominal background knowledge so as not to ‘contaminate’ the developing nature of the study. Glaser and Strauss (I967) were explicit about this requirement and it has ‘become one of the main tenets of the qualitative inquiry that the results ’emerge’ naturally, without any biased interference of the researcher. The researcher, therefore, needs to adopt a ‘tabula rasa’ orientation and Glaser and Strauss proposed that the researcher’s ‘theoretical sensitivity’ is only to appear when the data has already been collected and partially analyzed so that the concepts and hypotheses that have emerged from the data can be combined with existing knowledge.’ Miles and Huberman (I994) go one step further when they claim that it is the researchers’ background knowledge that helps them to see and decipher details, complexities, and subtleties, as well as to decide what kind of questions to ask or which incidents to attend to closely.

The topics of greatest interest for qualitative researchers are human behaviors and socio-cultural patterns and norms, which underlie the behaviors. Data are viewed in a “holistic” fashion, without attempting to separate them into their components, and preferably following the interpretations of the people who are the object of the research (“emic” interpretations) In data collection, ethnographic research (as the most typical and concrete example of qualitative research) doesn’t usually use “instruments,” rather “processes” that are supposedly free of bias and prior assumptions: free, prolonged observation, at times “participant observation,” open- ended interviews, “triangulation” of information and interpretation, “informant checking,” access to existing documents.

Strengths and Weaknesses of Qualitative Research: Qualitative research has traditionally been seen as a successful way of discovering new, unexplored spaces. If a fact is not so popular, the detailed study of a few cases is principally suitable because it does not depend on previous literature or first-hand findings received previously (Eisenhardt I989). Qualitative methods are useful for making sense of highly complex situations. In such cases there is a real danger for researchers in general to produce reduced and simplified interpretations that distort the bigger picture; the participant-sensitivity of qualitative research is very helpful in deciding what aspects of the data require special attention because it offers priority guidelines that are validated by the main actors themselves.

Qualitative vs. Quantitative research

Qualitative research can be best understood through the meanings in subjective experiences. The relation between subjective experience and language is a collaborative process; language is used to explain meaning, but the other way round, language influences how meaning is formed. Voicing experiences is a complex procedure as the meaning of experiences is often not completely comprehensible or user -friendly and difficult to express in language. Because interpretation and understanding meanings are central in qualitative research and text is the ‘vehicle’ with which meaning is ultimately transferred to the reader, language differences generate additional challenges that might hamper the transfer of meaning and might result in loss of meaning and thus loss of the authority of the qualitative study.

Qualitative research is often process-oriented or open ended. Qualitative researchers aim to study individuals and events in their natural settings (Tetnowski & Damico, 2001). That is, rather than trying to control circumstantial factors through the use of laboratories or other artificial environments, qualitative researchers tend to be more interested in presenting a natural and holistic picture of the phenomena being studied. In contrast, quantitative research usually begins with a carefully defined research question that guides the process of data collection and analysis. Thus, whereas quantitative researchers set out to test specific hypotheses, qualitative researchers tend to approach the research context with the purpose of observing whatever may be present there, and letting further questions occur from the context.

To capture the richness of experience in language, people commonly use narratives and metaphors (Polkinghorne 2005). Metaphors vary from culture to culture and are language- specific (Lakoff and Johnson 1980). Language also influences what can be expressed, and some linguists even state that social reality as experience is unique to one’s own language; those who speak different languages would perceive the world differently (Chapman 2006).Qualitative research is considered valid when the distance between the meanings as experienced by the participants and the meanings as interpreted in the findings is as close as possible (Polkinghorne 2007). The importance and utility of qualitative methods is increasingly being recognized in the field of second language research. Next, commonly used methods for gathering qualitative data are outlined, including case studies, ethnographies, interviews, observational techniques, verbal protocols, and diaries/journals.

Whereas most quantitative researchers consider impartiality to be a goal of their research, some qualitative researchers may consciously take ideological positions. This sort of research is sometimes described as ‘critical,’ meaning that the research may have particular social or political goals.

Quantitative research generally begins with an experimental design in which a hypothesis is followed by the quantification of data and statistical investigation. ‘The observations in quantitative research (whether tests, attitudes scales of the subjects observed, behaviors categorized and counted according to instruments, etc.) usually are based on an observation scheme or descriptive categories that have been developed prior to the research.’ Moreover, these observations are made in a planned way, according to an order determined by the design of the research, and with categories that cannot be changed once the research is ongoing.

Qualitative studies, on the other hand, generally are not set up as experiments; the data cannot be easily quantified, and the analysis is interpretive rather than statistical. Quantitative research can be conceptually divided into two types: associational and experimental. What is common in both types is that researchers are attempting to determine a relationship between or within variables. The goal of associational research is to determine whether a relationship exists between variables and, if so, the strength of that relationship. This is often tested statistically through correlations, which allow a researcher to determine how closely two variables (e.g., motivation and language ability) are related in a given population. Associational research is not concerned with causation, only with co-occurrence. In experimental studies, researchers deliberately manipulate one or more variables (independent variables) to determine the effect on another variable (dependent variable). Many types of experimental research involve a comparison of pretreatment and post treatment performance.

Despite the fact that dissimilarities can be drawn between qualitative and quantitative research, these two research types are by no means as dichotomous as they sometimes appear to be. Compounding this confusion, it is increasingly common for researchers to present and discuss both quantitative and qualitative data in the same report, or to use methods associated with both types of research in a process sometimes known as split methods or multiple methods.

For example, Sullivan and Pratt (1996) used both quantitative and qualitative methodologies to investigate the effects of computer technology on ESL student writers. The researchers used quantitative approaches to compare student essays in two types of writing environments (classes using computer technology and traditional oral classrooms); qualitative analyses were then used to compare the types and patterns of discourse in those environments.

By combining these approaches, Sullivan and Pratt were able to present a more detailed picture of how the computer technology affected the quality of the students’ writing, their patterns of discourse, and their perspectives on the value of the technology.

The growing practice of utilizing qualitative and quantitative data illustrates the fact that these two research approaches should not be viewed as opposing poles in a dichotomy, but rather as complementary means of investigating the complex phenomena at work in second language acquisition.

GATHERING QUALITATIVE DATA

A wide variety of different techniques are used in the collection of qualitative data. Each approach and method can be seen as contributing its own piece of the puzzle in qualitative researchers’ attempts to obtain rich, detailed, participant-oriented pictures of the phenomena under study. Murcott (1997) argues that the key questions for the qualitative methodology chapter are: How did you go about your research? What overall strategy did you adopt and why? What design and techniques did you use? Why those and not others?

The most commonly used qualitative data collection methods, include:

• Ethnographies
• Case studies
• Diaries/journals
• Observational techniques

Ethnographies: It can be said from a second language research perspective that ethnographic research aims “to describe and interpret the cultural behavior, including communicative behavior, of a group” (Johnson, 1992, p. 134) or, in other words, to carry out research from the participants’ point of view, using categories relevant to a particular group and cultural system. Another important principle of ethnographic research is the holistic approach taken to describing and explaining a particular pattern in relation to a whole system of patterns. One advantage of using an ethnographic approach is that the research questions employed in these studies can be dynamic, subject to constant revision, and refined as the research continues to uncover new knowledge. For example, an ethnographer studying second language writing classrooms may enter the research process with the aim of describing the patterns of interaction between teachers and students and illustrating how those patterns are related to the writing process. Ethnographic approaches are particularly valuable when not enough is known about the context or situation to establish narrowly defined questions or develop formal hypotheses. Because ethnographies typically employ multiple methods for gathering data, such as participant observations and open- ended interviews as well as written products, ethnographic research may be able to provide an holistic, culturally grounded, and emic (using categories of people studied) perspective of the phenomena under investigation.

In embarking on an ethnographic study, researchers need to be aware of some potential challenges and sensitive issues. First of all, ethnographies involve intensive research over an extended period of time. They require a commitment to long-term data collection, detailed and continuous record keeping, and repeated and careful analysis of data obtained from multiple sources. It is also important for the researcher to realize that ethnographic approaches to research may create potential conflicts between the researcher’s roles as an observer and a participant. If the researcher participates in an event he or she is observing, this may leave little time for the carefully detailed field notes that ethnographies may require. This can be rectified to a certain extent by audio and video tape recording. However, and more seriously, the researcher’s participation may change the nature of the event. Researchers thus need to be aware of how they can supplement and triangulate ethnographic data obtained through participant observation, and they must carefully consider how their dual roles might influence the data collected. In addition to these practical concerns, there are theoretical issues that the researcher should take into consideration. First of all, it has been argued that an ethnographer’s focus on describing a culture is problematic, because “there is no such thing as a social group that is not constantly destabilized by both outside influences and personal idiosyncrasy and agency” (Ramanathan & Atkinson, 1999, p. 45). In its strong form, this criticism implies that any attempt to describe a group is to some extent misguided on the part of the ethnographer. A second theoretical concern about ethnographies concerns the act of writing up the research. Because research reports adhere to certain (culturally influenced) standards of writing, the otherwise accurate picture an ethnographer has recorded may come out skewed. Finally, it is often difficult to generalize the findings of ethnographic research to other problems or settings because of the highly specific nature of such work.

Interviews A number of different interview types can be employed to gather data for qualitative research. Interviews are often associated with survey-based research, as well as being a technique used by many qualitative researchers. Structured interviews resemble verbal questionnaires and allow researchers to compare answers from different participants. Less rigid are semi-structured interviews, in which the researcher uses a written list of questions as a guide, while still having the freedom to digress and probe for more information. In unstructured interviews, on the other hand, no list of questions is used. Instead, interviewers develop and adapt their own questions, helping respondents to open up and express themselves in their own terms and at their own speed. Unstructured interviews are more similar to natural conversations, and the outcomes are not limited by the researcher’s preconceived ideas about the area of interest. Some interviews can also be based around a stimulus—for example, a completed questionnaire or a videotape of a lesson. Focus-group sessions are related to such interviews, and usually involve several participants in a group discussion, often with a facilitator whose goal it is to keep the group discussion targeted on specific topics, again often using a stimulus for discussion, such as a videotape or previously elicited data.

Interviews can allow researchers to investigate phenomena that are not directly observable, such as learners’ self-reported perceptions or attitudes. Also, because interviews are interactive, researchers can elicit additional data if initial answers are vague, incomplete, off-topic, or not specific enough. Another advantage of interviews is that they can be used to produce data from learners who are not comfortable in other modes. Depending on the research question and the resources available, interviews can also be conducted in the learner’s Ll, thus removing concerns about the proficiency of the learner impacting the quality and quantity of the data provided.

Researchers must also take note of the potential drawbacks of interviews. For example, Hall and Rist (1999) made the point that interviews may involve “selective recall, self-delusion, perceptual distortions, memory loss from the respondent, and subjectivity in the researcher’s recording and interpreting of the data”.

Multiple interviews —that is, interviewing the same subject more than once, or interviewing many different subjects—is one potential means of addressing such issues. Another concern is that good interviewing is a skill. It may not be easy for novice researchers to conduct unstructured interviews without practice and / or training in drawing participants out, encouraging them to express themselves, and gathering valuable data on the area of interest. Given that participants’ attitudes toward other people can impact what they say, there is also the danger of the so-called halo effect.

The following suggestions may be useful in interviewing:

• Be sensitive to (and / or match the interviewer’s characteristics with) the age, gender, and cultural background of the interviewee.
• Encourage open-ended discussion—for example, by keeping silent, or by saying ‘Anything else?” rather than accepting a first answer as the interviewee’s final and complete response to a question.
• Develop skills in anticipating and addressing communication problems.
• Try to make the interviewee as comfortable as possible. This can be done by conducting the interview in a familiar place, beginning with small talk to relax the interviewee, and/ or using the Ll if a communication problem arises or if the interviewee so prefers.
• Place the key questions in the middle of the interview, because the interviewee may be nervous in the beginning and tired by the end.
• Mirror the interviewee’s responses by repeating them neutrally to provide an opportunity for reflection and further input.

When appropriate qualitative research methods are chosen to address a particular problem, and when the proper standards of empirical rigor are met through triangulation of research perspectives, consideration of emic perspectives, and cyclical data collection and analysis, qualitative research can reliably help us to gain a deeper understanding of the nature of second language learning.

Case Studies Like ethnographies, case studies generally aim to provide a holistic description of language learning or use within a specific population and setting. However, whereas ethnographies focus on cultural patterns within groups, case studies tend to provide detailed descriptions of specific learners (or sometimes classes) within their learning setting. Case studies are also usually associated with a longitudinal approach, in which observations of the phenomena under investigation are made at periodic intervals for an extended period of time. Case studies have been used in a wide variety of second language research studies.

One main advantage of case studies is that they allow the researcher to focus on the individual in a way that is rarely possible in a group research. Case studies stand in sharp contrast to these approaches by providing insights into the complexities of particular cases in their particular contexts”. In addition, case studies can be conducted with more than one individual learner or more than one existing group of learners for the purpose of comparing and contrasting their behaviors within their particular context. Case studies clearly have the potential for rich contextualization that can shed light on the complexities of the second language learning process.

In the opening sections of reports, qualitative and quantitative research can be quite similar. However, qualitative and quantitative research can be different in their final stages insofar as qualitative research reports can be more varied in terms of organization and in terms of the specific sections. They also demand persuasive and skilled writing in order to effectively summarize large amounts of data and to communicate the significance of the research to the reader.

Qualitative research must also address many other elements that are inherent to non-quantitative research, as Different paradigms of qualitative research potentially involve distinct standards for reporting and stylistic elements. Qualitative research can involve a range of data collection methods, including, for instance, structured and unstructured classroom observations, structured and unstructured informal interviews, case studies, introspective analyses, and diary studies. Because it seems that acceptable reports vary based on the research paradigm and methods that the qualitative researcher adopts, qualitative researchers must decide how to organize their reports so that their ideas are best communicated to the intended audience. Heath (1997) suggested that qualitative reports include introduction, research paradigm, and research method sections, and that they address preliminary biases, suppositions, and hypotheses. The introduction to qualitative reports might begin with a quotation or a vignette before describing the research question and situating it within a theoretical context. The research design section should be used to represent the epistemological, conceptual foundations and assumptions of the qualitative research paradigm chosen and should contain citations of authors who have defined the paradigm, thus increasing the validity of the design. The research methods section should include sufficient detail in order to increase its verisimilitude (i.e., authenticity and credibility). As such, the instrumentation used to collect the data, as well as the specific procedures followed, should be described. Reports should clearly state how the researcher gained access to participants and what kind of relationship was established between the researcher and participants. The nature of the data and how they were collected should also be clearly stated.

Particularly important for qualitative research is the inclusion of information about procedures such as how decision-making was carried out and how the researcher implemented data reduction and reconstruction. It is also important for researchers to provide a clear sense of how much data were collected (e.g., how many interviews, and of what length, how many hours of observation, and over what period of time), because this is vital in assessing the strength of the research overall.

The boundaries of the case study must also be clearly described and motivated—for instance, why a particular case was selected, and how and in what contexts data were collected. In addition, although generalizations are seldom made based on case studies, the researcher should not only report findings but also draw conclusions that contribute to an overall understanding of a phenomenon within a theoretical framework. Like case studies of individuals, classroom observation research should make the role of the researcher in the classroom explicit. If surveys or questionnaires are employed to supplement and triangulate qualitative data, the researcher should report issues such as what the response rates were, whether or not there was a nonresponse bias, how analyses were performed, and whether any generalizations can be drawn from the results. It is also common to include copies of survey or interview questions in the appendixes. In summary, then, each qualitative research paradigm requires a unique consideration of its crucial elements when a report is written, in part because there are different research paradigms and many means of collecting and analyzing data. Because of this, researchers need to take particular care to detail (and justify) how they collected and analyzed their data. When reporting the results of a qualitative study, researchers should also take into account the importance of rich or thick description. If the purpose of the research is to describe and classify the observed data, rich description is often utilized. The evidence reported should be detailed, multilayered, and comprehensive. Rather than reporting a limited number of anecdotes that support the conclusions, researchers should try to provide detail about a systematic selection of the data that represents both the central tendencies and variations.

The purpose of some qualitative research, such as ethnographies, is to go beyond mere description and attribute observations to underlying constructs and systems of meaning. An important question in qualitative research write-ups is how much interpretation of the data the writer should provide. Many qualitative researchers suggest that although writers may offer their own interpretations, they should also provide an adequate basis for their readers to construct their own independent interpretations. This may be accomplished by separating presentation of data (e.g., vignettes, interview excepts, etc.) from discussion and analysis.

SUMMING UP :MIXED METHOD: It is becoming the case that quantitative and qualitative research methods are not viewed as dichotomous. Also, survey-based research methods like questionnaires, are often used to triangulate both more quantitative and more qualitatively oriented data. However methods are classified, second language researchers are increasingly taking into account the fact that data can be collected using a wide range and combination of methods. When included in a primarily quantitative report, qualitative data or analytic techniques may provide unique insights that would escape both the researcher and the reader if statistical counts and analyses were used in isolation. For example, graphs representing the data frequency distribution, measures of central tendencies (means, modes, or medians), and range and standard deviation characteristics of the data can help confirm the validity of any trends, patterns, or groupings that the researcher has identified through a qualitative analysis. Hence, it may be best if researchers, even if they identify their research as primarily qualitative or quantitative, not rule out the inclusion of both types of data in their reports. In reporting their studies, researchers need to consider all elements and requirements that will best explain the data to the audience.

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• Savignon, S.J. (2007). Beyond communicative language teaching: What’s ahead? Journal of Pragmatics, 39 (1), 207-220.
• Wallwork, A. (2011). English for writing research papers. New York: Springer.

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4.2 Definitions and Characteristics of Qualitative Research

Qualitative research aims to uncover the meaning and understanding of phenomena that cannot be broken down into measurable elements. It is based on naturalistic, interpretative and humanistic notions. 5 This research method seeks to discover, explore, identify or describe subjective human experiences using non-statistical methods and develops themes from the study participants’ stories. 5 Figure 4.1 depicts major features/ characteristics of qualitative research. It utilises exploratory open-ended questions and observations to search for patterns of meaning in collected data (e.g. observation, verbal/written narrative data, photographs, etc.) and uses inductive thinking (from specific observations to more general rules) to interpret meaning. 6 Participants’ voice is evident through quotations and description of the work. 6 The context/ setting of the study and the researcher’s reflexivity (i.e. “reflection on and awareness of their bias”, the effect of the researcher’s experience on the data and interpretations) are very important and described as part of data collection. 6 Analysis of collected data is complex, often involves inductive data analysis (exploration, contrasts, specific to general) and requires multiple coding and development of themes from participant stories. 6

Reflexivity- avoiding bias/Role of the qualitative researcher

Qualitative researchers generally begin their work with the recognition that their position (or worldview) has a significant impact on the overall research process. 7 Researcher worldview shapes the way the research is conducted, i.e., how the questions are formulated, methods are chosen, data are collected and analysed, and results are reported. Therefore, it is essential for qualitative researchers to acknowledge, articulate, reflect on and clarify their own underlying biases and assumptions before embarking on any research project. 7 Reflexivity helps to ensure that the researcher’s own experiences, values, and beliefs do not unintentionally bias the data collection, analysis, and interpretation. 7 It is the gold standard for establishing trustworthiness and has been established as one of the ways qualitative researchers should ensure rigour and quality in their work. 8 The following questions in Table 4.1 may help you begin the reflective process. 9

Table 4.1: Questions to aid the reflection process

Philosophical underpinnings to qualitative research

Qualitative research uses an inductive approach and stems from interpretivism or constructivism and assumes that realities are multiple, socially constructed, and holistic. 10 According to this philosophical viewpoint, humans build reality through their interactions with the world around them. 10 As a result, qualitative research aims to comprehend how individuals make sense of their experiences and build meaning in their lives. 10 Because reality is complex/nuanced and context-bound, participants constantly construct it depending on their understanding. Thus, the interactions between the researcher and the participants are considered necessary to offer a rich description of the concept and provide an in-depth understanding of the phenomenon under investigation. 11

An Introduction to Research Methods for Undergraduate Health Profession Students Copyright © 2023 by Faith Alele and Bunmi Malau-Aduli is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on 4 April 2022 by Pritha Bhandari . Revised on 30 January 2023.

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

• Flexibility

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

• Natural settings

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

• Meaningful insights

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

• Generation of new ideas

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

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

• Unreliability

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

• Subjectivity

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

• Limited generalisability

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

• Labour-intensive

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

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

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

There are five common approaches to qualitative research :

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

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

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

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

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

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This timely book will guide researchers on how to apply qualitative research methods to explore English-medium instruction (EMI) issues, such as classroom interactions, teachers’ and students’ perceptions on language and pedagogical challenges, and stakeholders’ views on the implementation of EMI. Each chapter focuses on a specific type of qualitative research methodology, beginning with an overview of the research and the method used, before presenting a unique case study. Chapters will also identify the process that EMI researchers went through to conduct their research, the key dilemmas they faced, and focus particularly on the methodological issues they encountered. By exploring these issues and providing up-to-date insights in contexts across the globe, this book informs theory or the lack thereof, underlying research into the phenomenon of EMI. This text will be indispensable for researchers who want to learn and acquire skills in conducting qualitative research in EMI, as well as undergraduate and postgraduate students reading in the fields of applied linguistics and language education.

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How to use and assess qualitative research methods

Loraine busetto.

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

Wolfgang Wick

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

Christoph Gumbinger

Associated data.

Not applicable.

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

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

What is qualitative research?

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

Why conduct qualitative research?

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

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

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

How to conduct qualitative research?

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

Iterative research process

While it is not always explicitly addressed, qualitative methods reflect a different underlying research paradigm than quantitative research (e.g. constructivism or interpretivism as opposed to positivism). The choice of methods can be based on the respective underlying substantive theory or theoretical framework used by the researcher [ 2 ].

Data collection

The methods of qualitative data collection most commonly used in health research are document study, observations, semi-structured interviews and focus groups [ 1 , 14 , 16 , 17 ].

Document study

Document study (also called document analysis) refers to the review by the researcher of written materials [ 14 ]. These can include personal and non-personal documents such as archives, annual reports, guidelines, policy documents, diaries or letters.

Observations

Observations are particularly useful to gain insights into a certain setting and actual behaviour – as opposed to reported behaviour or opinions [ 13 ]. Qualitative observations can be either participant or non-participant in nature. In participant observations, the observer is part of the observed setting, for example a nurse working in an intensive care unit [ 18 ]. In non-participant observations, the observer is “on the outside looking in”, i.e. present in but not part of the situation, trying not to influence the setting by their presence. Observations can be planned (e.g. for 3 h during the day or night shift) or ad hoc (e.g. as soon as a stroke patient arrives at the emergency room). During the observation, the observer takes notes on everything or certain pre-determined parts of what is happening around them, for example focusing on physician-patient interactions or communication between different professional groups. Written notes can be taken during or after the observations, depending on feasibility (which is usually lower during participant observations) and acceptability (e.g. when the observer is perceived to be judging the observed). Afterwards, these field notes are transcribed into observation protocols. If more than one observer was involved, field notes are taken independently, but notes can be consolidated into one protocol after discussions. Advantages of conducting observations include minimising the distance between the researcher and the researched, the potential discovery of topics that the researcher did not realise were relevant and gaining deeper insights into the real-world dimensions of the research problem at hand [ 18 ].

Semi-structured interviews

Hijmans & Kuyper describe qualitative interviews as “an exchange with an informal character, a conversation with a goal” [ 19 ]. Interviews are used to gain insights into a person’s subjective experiences, opinions and motivations – as opposed to facts or behaviours [ 13 ]. Interviews can be distinguished by the degree to which they are structured (i.e. a questionnaire), open (e.g. free conversation or autobiographical interviews) or semi-structured [ 2 , 13 ]. Semi-structured interviews are characterized by open-ended questions and the use of an interview guide (or topic guide/list) in which the broad areas of interest, sometimes including sub-questions, are defined [ 19 ]. The pre-defined topics in the interview guide can be derived from the literature, previous research or a preliminary method of data collection, e.g. document study or observations. The topic list is usually adapted and improved at the start of the data collection process as the interviewer learns more about the field [ 20 ]. Across interviews the focus on the different (blocks of) questions may differ and some questions may be skipped altogether (e.g. if the interviewee is not able or willing to answer the questions or for concerns about the total length of the interview) [ 20 ]. Qualitative interviews are usually not conducted in written format as it impedes on the interactive component of the method [ 20 ]. In comparison to written surveys, qualitative interviews have the advantage of being interactive and allowing for unexpected topics to emerge and to be taken up by the researcher. This can also help overcome a provider or researcher-centred bias often found in written surveys, which by nature, can only measure what is already known or expected to be of relevance to the researcher. Interviews can be audio- or video-taped; but sometimes it is only feasible or acceptable for the interviewer to take written notes [ 14 , 16 , 20 ].

Focus groups

Focus groups are group interviews to explore participants’ expertise and experiences, including explorations of how and why people behave in certain ways [ 1 ]. Focus groups usually consist of 6–8 people and are led by an experienced moderator following a topic guide or “script” [ 21 ]. They can involve an observer who takes note of the non-verbal aspects of the situation, possibly using an observation guide [ 21 ]. Depending on researchers’ and participants’ preferences, the discussions can be audio- or video-taped and transcribed afterwards [ 21 ]. Focus groups are useful for bringing together homogeneous (to a lesser extent heterogeneous) groups of participants with relevant expertise and experience on a given topic on which they can share detailed information [ 21 ]. Focus groups are a relatively easy, fast and inexpensive method to gain access to information on interactions in a given group, i.e. “the sharing and comparing” among participants [ 21 ]. Disadvantages include less control over the process and a lesser extent to which each individual may participate. Moreover, focus group moderators need experience, as do those tasked with the analysis of the resulting data. Focus groups can be less appropriate for discussing sensitive topics that participants might be reluctant to disclose in a group setting [ 13 ]. Moreover, attention must be paid to the emergence of “groupthink” as well as possible power dynamics within the group, e.g. when patients are awed or intimidated by health professionals.

Choosing the “right” method

As explained above, the school of thought underlying qualitative research assumes no objective hierarchy of evidence and methods. This means that each choice of single or combined methods has to be based on the research question that needs to be answered and a critical assessment with regard to whether or to what extent the chosen method can accomplish this – i.e. the “fit” between question and method [ 14 ]. It is necessary for these decisions to be documented when they are being made, and to be critically discussed when reporting methods and results.

Let us assume that our research aim is to examine the (clinical) processes around acute endovascular treatment (EVT), from the patient’s arrival at the emergency room to recanalization, with the aim to identify possible causes for delay and/or other causes for sub-optimal treatment outcome. As a first step, we could conduct a document study of the relevant standard operating procedures (SOPs) for this phase of care – are they up-to-date and in line with current guidelines? Do they contain any mistakes, irregularities or uncertainties that could cause delays or other problems? Regardless of the answers to these questions, the results have to be interpreted based on what they are: a written outline of what care processes in this hospital should look like. If we want to know what they actually look like in practice, we can conduct observations of the processes described in the SOPs. These results can (and should) be analysed in themselves, but also in comparison to the results of the document analysis, especially as regards relevant discrepancies. Do the SOPs outline specific tests for which no equipment can be observed or tasks to be performed by specialized nurses who are not present during the observation? It might also be possible that the written SOP is outdated, but the actual care provided is in line with current best practice. In order to find out why these discrepancies exist, it can be useful to conduct interviews. Are the physicians simply not aware of the SOPs (because their existence is limited to the hospital’s intranet) or do they actively disagree with them or does the infrastructure make it impossible to provide the care as described? Another rationale for adding interviews is that some situations (or all of their possible variations for different patient groups or the day, night or weekend shift) cannot practically or ethically be observed. In this case, it is possible to ask those involved to report on their actions – being aware that this is not the same as the actual observation. A senior physician’s or hospital manager’s description of certain situations might differ from a nurse’s or junior physician’s one, maybe because they intentionally misrepresent facts or maybe because different aspects of the process are visible or important to them. In some cases, it can also be relevant to consider to whom the interviewee is disclosing this information – someone they trust, someone they are otherwise not connected to, or someone they suspect or are aware of being in a potentially “dangerous” power relationship to them. Lastly, a focus group could be conducted with representatives of the relevant professional groups to explore how and why exactly they provide care around EVT. The discussion might reveal discrepancies (between SOPs and actual care or between different physicians) and motivations to the researchers as well as to the focus group members that they might not have been aware of themselves. For the focus group to deliver relevant information, attention has to be paid to its composition and conduct, for example, to make sure that all participants feel safe to disclose sensitive or potentially problematic information or that the discussion is not dominated by (senior) physicians only. The resulting combination of data collection methods is shown in Fig.  2 .

Possible combination of data collection methods

Attributions for icons: “Book” by Serhii Smirnov, “Interview” by Adrien Coquet, FR, “Magnifying Glass” by anggun, ID, “Business communication” by Vectors Market; all from the Noun Project

The combination of multiple data source as described for this example can be referred to as “triangulation”, in which multiple measurements are carried out from different angles to achieve a more comprehensive understanding of the phenomenon under study [ 22 , 23 ].

Data analysis

To analyse the data collected through observations, interviews and focus groups these need to be transcribed into protocols and transcripts (see Fig.  3 ). Interviews and focus groups can be transcribed verbatim , with or without annotations for behaviour (e.g. laughing, crying, pausing) and with or without phonetic transcription of dialects and filler words, depending on what is expected or known to be relevant for the analysis. In the next step, the protocols and transcripts are coded , that is, marked (or tagged, labelled) with one or more short descriptors of the content of a sentence or paragraph [ 2 , 15 , 23 ]. Jansen describes coding as “connecting the raw data with “theoretical” terms” [ 20 ]. In a more practical sense, coding makes raw data sortable. This makes it possible to extract and examine all segments describing, say, a tele-neurology consultation from multiple data sources (e.g. SOPs, emergency room observations, staff and patient interview). In a process of synthesis and abstraction, the codes are then grouped, summarised and/or categorised [ 15 , 20 ]. The end product of the coding or analysis process is a descriptive theory of the behavioural pattern under investigation [ 20 ]. The coding process is performed using qualitative data management software, the most common ones being InVivo, MaxQDA and Atlas.ti. It should be noted that these are data management tools which support the analysis performed by the researcher(s) [ 14 ].

From data collection to data analysis

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

How to report qualitative research?

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

How to combine qualitative with quantitative research?

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

Three common mixed methods designs

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

How to assess qualitative research?

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

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

Reflexivity

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

Sampling and saturation

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

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

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

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

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

Member checking

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

Stakeholder involvement

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

How not to assess qualitative research

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

Protocol adherence

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

Sample size

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

Randomisation

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

Interrater reliability, variability and other “objectivity checks”

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

Not being quantitative research

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

The main take-away points of this paper are summarised in Table ​ Table1. 1 . We aimed to show that, if conducted well, qualitative research can answer specific research questions that cannot to be adequately answered using (only) quantitative designs. Seeing qualitative and quantitative methods as equal will help us become more aware and critical of the “fit” between the research problem and our chosen methods: I can conduct an RCT to determine the reasons for transportation delays of acute stroke patients – but should I? It also provides us with a greater range of tools to tackle a greater range of research problems more appropriately and successfully, filling in the blind spots on one half of the methodological spectrum to better address the whole complexity of neurological research and practice.

Take-away-points

Acknowledgements

Abbreviations.

Authors’ contributions

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

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Qualitative Research Methods in English Medium Instruction for Emerging Researchers

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This timely book will guide researchers on how to apply qualitative research methods to explore English-medium instruction (EMI) issues, such as classroom interactions, teachers’ and students’ perceptions on language and pedagogical challenges, and stakeholders’ views on the implementation of EMI.

Each chapter focuses on a specific type of qualitative research methodology, beginning with an overview of the research and the method used, before presenting a unique case study. Chapters will also identify the process that EMI researchers went through to conduct their research, the key dilemmas they faced, and focus particularly on the methodological issues they encountered. By exploring these issues and providing up-to-date insights in contexts across the globe, this book informs theory or the lack thereof, underlying research into the phenomenon of EMI.

This text will be indispensable for researchers who want to learn and acquire skills in conducting qualitative research in EMI, as well as undergraduate and postgraduate students reading in the fields of applied linguistics and language education.

Introduction: qualitative research methods in English-medium instruction for emerging researchers   1. Using Q methodology to better understand subjectivity in EMI  2. How to conduct a multimodal classroom discourse analysis  3. The use of epistemic network analysis in analysing classroom discourse in EMI-science classrooms  4. Using corpus linguistics and grounded theory to explore EMI stakeholders' discourse  5. Affordances of conversation analysis for investigating EMI classroom talk  6. Moving beyond language in EMI research: a multimodal and multichannel analytical framework to visualise classroom practices  7. A narrative enquiry into EMI instructors’ linguistic and pedagogical needs  8. Engaged methodological approach in the study of language ideologies in EMI policies

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Article Contents

Introduction, challenging some common methodological assumptions about online qualitative surveys, ten practical tips for designing, implementing and analysing online qualitative surveys, acknowledgements, conflict of interest statement, data availability, ethical approval.

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Methodological and practical guidance for designing and conducting online qualitative surveys in public health

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Samantha L Thomas, Hannah Pitt, Simone McCarthy, Grace Arnot, Marita Hennessy, Methodological and practical guidance for designing and conducting online qualitative surveys in public health, Health Promotion International , Volume 39, Issue 3, June 2024, daae061, https://doi.org/10.1093/heapro/daae061

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Online qualitative surveys—those surveys that prioritise qualitative questions and interpretivist values—have rich potential for researchers, particularly in new or emerging areas of public health. However, there is limited discussion about the practical development and methodological implications of such surveys, particularly for public health researchers. This poses challenges for researchers, funders, ethics committees, and peer reviewers in assessing the rigour and robustness of such research, and in deciding the appropriateness of the method for answering different research questions. Drawing and extending on the work of other researchers, as well as our own experiences of conducting online qualitative surveys with young people and adults, we describe the processes associated with developing and implementing online qualitative surveys and writing up online qualitative survey data. We provide practical examples and lessons learned about question development, the importance of rigorous piloting strategies, use of novel techniques to prompt detailed responses from participants, and decisions that are made about data preparation and interpretation. We consider reviewer comments, and some ethical considerations of this type of qualitative research for both participants and researchers. We provide a range of practical strategies to improve trustworthiness in decision-making and data interpretation—including the importance of using theory. Rigorous online qualitative surveys that are grounded in qualitative interpretivist values offer a range of unique benefits for public health researchers, knowledge users, and research participants.

Public health researchers are increasingly using online qualitative surveys.

There is still limited practical and methodological information about the design and implementation of these studies.

Building on Braun and Clarke (2013) , Terry and Braun (2017) and Braun et al . (2021) , we reflect on the methodological and practical lessons we have learnt from our own experience with conducting online qualitative surveys.

We provide guidance and practical examples about the design, implementation and analysis processes.

We argue that online qualitative surveys have rich potential for public health researchers and can be an empowering and engaging way to include diverse populations in qualitative research.

Public health researchers mostly engage in experiential (interpretive) qualitative approaches ( Braun and Clarke, 2013 ). These approaches are ‘centred on the exploration of participants’ subjective experiences and sense-making’ [( Braun and Clarke, 2021c ), p. 39]. Given the strong focus in public health on social justice, power and inequality, researchers proactively use the findings from these qualitative studies—often in collaboration with lived experience experts and others who are impacted by key decisions ( Reed et al ., 2024 )—to advocate for changes to public health policy and practice. There is also an important level of theoretical, methodological and empirical reflection that is part of the public health researcher’s role. For example, as qualitative researchers actively construct and interpret meaning from data, they constantly challenge their assumptions, their way of knowing and their way of ‘doing’ research ( Braun and Clarke, 2024 ). This reflexive practice also includes considering how to develop more inclusive opportunities for people to participate in research and to share their opinions and experiences about the issues that matter to them.

While in-depth interviews and focus groups provide rich and detailed narratives that are central to understanding people’s lives, these forms of data collection may sometimes create practical barriers for both researchers and participants. For example, they can be time consuming, and the power dynamics associated with face-to-face interviews (even in online settings) may make them less accessible for groups that are marginalized or stigmatized ( Edwards and Holland, 2020 ). While some population subgroups (and contexts) may suit (or require) face-to-face qualitative data collection approaches, others may lend themselves to different forms of data collection. Young people, for example, may be keen to be civically involved in research about the issues that matter to them, such as the climate crisis, but they may find it more convenient and comfortable using anonymized digital technologies to do so ( Arnot et al ., 2024b ). As such, part of our reflexive practice as public health researchers must be to explore, and be open to, a range of qualitative methodological approaches that could be more convenient, less intimidating and more engaging for a diverse range of population subgroups. This includes thinking about pragmatic ways of operationalizing qualitative data collection methods. How can we develop methods and engagement strategies that enable us to gain insights from a diverse range of participants about new issues or phenomenon that may pose threats to public health, or look at existing issues in new ways?

Advancements in online data collection methods have also created new options for researchers and participants about how they can be involved in qualitative studies ( Hensen et al ., 2021 ; Chen, 2023 ; Fan et al ., 2024 ). Online qualitative surveys—those surveys that prioritize qualitative values and questions—have rich potential for qualitative researchers. Braun and Clarke (2013 , p. 135) state that qualitative surveys:

…consist of a series of open-ended questions about a topic, and participants type or hand-write their responses to each question. They are self-administered; a researcher-administered qualitative survey would basically be an interview.

While these types of studies are increasingly utilized in public health, researchers have highlighted that there is still relatively limited discussion about the methodological and practical implications of these surveys ( Braun and Clarke, 2013 ; Terry and Braun, 2017 ; Braun et al ., 2021 ). This poses challenges for qualitative public health researchers, funders, ethics committees and peer reviewers in assessing the purpose, rigour and contribution of such research, and in deciding the appropriateness of the method for answering different research questions.

Using examples from online qualitative surveys that we have been involved in, this article discusses a range of methodological and practical lessons learnt from developing, implementing and analysing data from these types of surveys. While we do not claim to have all the answers, we aim to develop and extend on the methodological and practical guidance from Braun and Clarke (2013) , Terry and Braun (2017) and Braun et al . (2021) about the potential for online qualitative surveys. This includes how they can provide a rigorous ‘wide-angle picture’ [( Toerien and Wilkinson, 2004 ), p. 70] from a diverse range of participants about contemporary public health phenomena.

Figure 1 aims to develop and extend on the key points made by Braun and Clarke (2013) , Terry and Braun (2017) and Braun et al . (2021) , which provide the methodological and empirical foundation for our article.

: Methodological considerations in conducting online qualitative surveys.

Harnessing interpretivist approaches and qualitative values in online qualitative surveys

Online qualitative surveys take many forms. They may be fully qualitative or qualitative dominant—mostly qualitative with some quantitative questions ( Terry and Braun, 2017 ). There are also many different ways of conducting these studies—from using a smaller number of questions that engage specific population groups or knowledge users in understanding detailed experiences  ( Hennessy and O’Donoghue, 2024 ), to a larger number of questions (which may use market research panel providers to recruit participants), that seek broader opinions and attitudes about public health issues ( Marko et al ., 2022a ; McCarthy et al ., 2023 ; Arnot et al ., 2024a ). However, based on our experiences of applying for grant funding and conducting, publishing and presenting these studies, there are still clear misconceptions and uncertainties about these types of  surveys.

One of the concerns raised about online qualitative surveys is how they are situated within broader qualitative values and approaches. This includes whether they can provide empirically innovative, rigorous, rich and theoretically grounded qualitative contributions to knowledge. Our experience is that online qualitative surveys have the most potential when they harness the values of interpretivist ‘Big Q’ approaches to collect information from a diverse range of participants about their experiences, opinions and practices ( Braun et al ., 2021 ). The distinction between positivist (small q) and interpretivist (Big Q) approaches to online qualitative surveys is an important one that requires some initial methodological reflection, particularly in considering the (largely unhelpful) critiques that are made about the rigour and usefulness of these surveys. These critiques often overlook the theoretical underpinnings and qualitative values inherent in such surveys. For example, while there may be a tendency to think of surveys and survey data as atheoretical and descriptive, the use of theory is central in informing online qualitative surveys. For example, Varpio and Ellaway (2021 , p. 343) explain that theory can ‘offer explanations and detailed premises that we can wrestle with, agree with, disagree with, reject and/or accept’. This includes the research design, the approach to data collection and analysis, the interpretation of findings and the conclusions that are drawn. Theory is also important in helping researchers to engage in reflexive practice. The use of theory is essential in progressing online qualitative surveys beyond description and towards in-depth interpretation and explanations—thus facilitating a deeper understanding of the studied phenomenon ( Collins and Stockton, 2018 ; Jamie and Rathbone, 2022 ).

Considering the assumptions that online qualitative surveys can only collect ‘thin’ data

The main assumptions about online qualitative surveys are that they can only collect ‘thin’ textual data, and that they are not flexible enough as a data collection tool for researchers to prompt or ask follow-up questions or to co-create detailed and rich data with participants ( Braun and Clarke, 2013 ; Terry and Clarke, 2017 ; Braun et al ., 2021 ). While we acknowledge that the type of data that is collected in these types of studies is different from those in in-depth interview studies, these surveys may be a more accessible and engaging way to collect rich insights from a diverse range of participants who may otherwise not participate in qualitative research ( Braun and Clarke, 2013 ; Terry and Braun, 2017 ; Braun et al ., 2021 ). Despite this, peer reviewers can question the depth of information that may be collected in these studies. Assumptions about large but ‘thin’ datasets may also mean that researchers, funders and reviewers take (and perhaps expect) a more positivist approach to the design and analytical processes associated with these surveys. For example, the multiple topics and questions, larger sample sizes, and the generally smaller textual responses that online qualitative surveys generate may lead researchers to approach these surveys using more descriptive and atheoretical paradigms. This approach may focus on ‘measuring’ phenomena, using variables, developing thinner analytical description and adding numerical values to the number of responses for different categories or themes.

We have found that assumptions can also impact the review processes associated with these types of studies, receiving critiques from those with both positivist and interpretivist positions. Positivist critiques focus on matters associated with whether the samples are ‘representative’, and the flaws associated with ‘self-selecting convenience’ samples. Critiques from interpretivist colleagues question why such large sample sizes are needed for qualitative studies, seeing surveys as a less rigorous method for gaining rich and meaningful data. For example, we have had reviewers query the scope and depth of the analysis of the data that we present from these studies because they are concerned that the type of data collected lacks depth and does not fully contextualize and explain how participants think about issues. We have also had reviewers request that we should return to the study to collect quantitative data to supplement the qualitative findings of the survey. They also question how ‘representative’ the samples are of population groups. These comments, of course, are not unique to online qualitative surveys but do highlight the difficulty that reviewers may have in placing and situating these types of studies in broader qualitative approaches. With this in mind, we have also found that some reviewers can ask for additional information to justify both the use of online qualitative surveys and why we have chosen these over other qualitative approaches. For example, reviewers have asked us to justify why we have chosen an online qualitative survey and also to explain what we may have missed out on by not conducting in-depth interviews or quantitative or mixed methods surveys instead.

Requests for ‘numbers’ and ‘strategies to minimize bias’

While there is now a general understanding that attributing ‘numbers’ to qualitative data is largely unhelpful and inappropriate ( Chowdhury, 2015 ), there may be expectations that the larger sample sizes associated with online qualitative surveys enable researchers to provide numerical indicators of data. Rather than focusing on the ‘artfully interpretive’ techniques used to analyse and construct themes from the data ( Finlay, 2021 ), we have found that reviewers often ask us to provide numerical information about how many people provided different responses to different questions (or constructed themes), and the number at which ‘saturation’ was determined. Reviewer feedback that we have received about analytical processes has asked for detailed explanations about why attempts to ‘minimize bias’ (including calculations of inter-rater reliability and replicability of data quality) were not used. This demonstrates that peer reviewers may misinterpret the interpretivist values that guide online qualitative surveys, asking for information that is essentially ‘meaningless’ in qualitative paradigms in which researchers’ subjectivity ‘sculpts’ the knowledge that is produced ( Braun and Clarke, 2021a ).

The benefits and limitations of online qualitative surveys for participants, researchers and knowledge users

As well as a ‘wide-angle picture’ [( Toerien and Wilkinson, 2004 ), p. 70] on phenomenon, online qualitative surveys can also: (i) generate both rich and focused data about perceptions and practices, and (ii) have multiple participatory and practical advantages—including helping to overcome barriers to research participation ( Braun and Clarke, 2013 ; Terry and Braun, 2017 ; Braun et al ., 2021 ). For researchers , online qualitative surveys can be a more cost-effective alternative ( Braun and Clarke, 2013 ; Terry and Braun, 2017 )—they are generally more time-efficient and less labour-intensive (particularly if working with market research companies to recruit panels). They are also able to reach a broad range of participants—such as those who are geographically dispersed ( Braun and Clarke, 2013 ; Terry and Braun, 2017 ), and those who may not have internet connectivity that is reliable enough to complete online interviews (a common issue for individuals living in regional or rural settings) ( de Villiers et al ., 2022 ). We are also more able to engage young people in qualitative research through online surveys, perhaps partly due to extensive panel company databases but also because they may be a more accessible and familiar way for young people to participate in research. The ability to quickly investigate new public health threats from the perspective of lived experience can also provide important information for researchers, providing justification for new areas of research focus, including setting agendas and advocating for the need for funding (or policy attention). Collecting data from a diverse range of participants—including from those who hold views that we may see as less ‘politically acceptable’, or inconsistent with our own public health reasoning about health and equity—is important in situating and contextualizing community attitudes towards particular issues.

For participants , benefits include having a degree of autonomy and control over their participation, including completing the survey at a time and place that suits them, and the anonymous nature of participation (that may be helpful for people from highly stigmatized groups). Participants can take time to reflect on their responses or complete the survey, and may feel more able to ‘talk back’ to the researcher about the framing of questions or the purpose of the research ( Braun et al ., 2021 ). We would also add that a benefit of these types of studies is that participants can also drop out of the study easily if the survey does not interest them or meet their expectations—something that we think might be more onerous or uncomfortable for participants in an interview or focus group.

For knowledge users, including advocates, service providers and decision-makers, qualitative research provides an important form of evidence, and the ‘wide-angle picture' [( Toerien and Wilkinson, 2004 ), p. 70] on issues from a diverse range of individuals in a community or population can be a powerful advocacy tool. Online qualitative surveys can also provide rapid insights into how changes to policy and practice may impact population subgroups in different ways.

There are, of course, some limitations associated with online qualitative surveys ( Braun et al ., 2021 ; Marko et al ., 2022b ). For example, there is no ability to engage individuals in a ‘traditional’ conversation or to prompt or probe meaning in the interactive ways that we are familiar with in interview studies. There is less ability to refine the questions that we ask participants in an iterative way throughout a study based on participant responses (particularly when working with market research panel companies). There may also be barriers associated with written literacy, access to digital technologies and stable internet connections ( Braun et al ., 2021 ). They may also not be the most suitable for individuals who have different ways of ‘knowing, being and doing’ qualitative research—including Indigenous populations [( Kennedy et al ., 2022 ), p. 1]. All of these factors should be taken into consideration when deciding whether online qualitative surveys are an appropriate way of collecting data. Finally, while these types of surveys can collect data quickly ( Marko et al ., 2022b ), there can also be additional decision-making processes related to data preparation and inclusion that can be time-consuming.

There are a range of practical considerations that can improve the rigour, trustworthiness and quality of online qualitative survey data. Again, developing and expanding on ( Braun and Clarke, 2013 ; Terry and Braun, 2017 ; Braun et al ., 2021 ), Figure 2 gives an overview of some key practical considerations associated with the design, implementation and analysis of these surveys. We would also note that before starting your survey design, you should be aware that people may use different types of technology to complete the survey, and in different spaces. For example, we cannot assume that people will be sitting in front of a computer or laptop at home or in the office, with people more likely to complete surveys on a mobile phone, perhaps on a train or bus on the way to work or school.

: Top ten practical tips for conducting online qualitative surveys.

Survey design

Creating an appropriate and accessible structure

The first step in designing an online qualitative survey is to plan the structure of your survey. This step is important because the structure influences the way that participants interact with and participate through the survey. The survey structure helps to create an ‘environment’ that helps participants to share their perspectives, prompt their views and develop their ideas ( Braun and Clarke, 2013 ; Terry and Braun, 2017 ). Similar to an interview study, the structure of the survey guides participants from one set of questions (and topics) to the next. It is important to consider the ordering of topics to enable participants to complete a survey that has a logical flow, introduces participants to concepts and allows them to develop their depth of responses.

Before participants start the survey, we provide a clear and simple lay language summary of the survey. Because many individuals will be familiar with completing quantitative surveys, we include a welcoming statement and reiterate the qualitative nature of the survey, stating that their answers can be about their own experiences:

Thank you for agreeing to take part in this survey about [topic] . This survey involves writing responses to questions rather than checking boxes.

We then clearly reiterate the purpose of the survey, providing a short description of the topic that we are investigating. We state that we do not seek to collect any data that is identifiable, that we are interested in participants perspectives, that there are no right or wrong answers, and that participants can withdraw from the survey at any time without giving a reason.

Similar to Braun et al . (2021) , we start our surveys with questions about demographic and related characteristics (which we often call ‘ participant/general characteristics ’). These can be discrete choice questions, but can also utilize open text—for example, in relation to gender identity. We have found that there is always a temptation with surveys to ask many questions about the demographic characteristics of participants. However, we caution that too many questions can be intrusive for participants and can take away valuable time from open-text questions, which are the core focus of the survey. We recommend asking participant characteristic and demographic questions that situate and contextualize the sample ( Elliott et al ., 1999 ).

We generally start the open-text sections of these surveys by asking broad introductory questions about the topic. This might include questions such as: ‘Please describe the main reasons you drink alcohol ’, and ‘W hat do you think are the main impacts of climate change on the world? ’ We have found that these types of questions get participants used to responding to open-text questions relevant to the study’s research questions and aims. For each new topic of investigation (which are based on our theoretical concepts and overall study aims and research questions), we provide a short explanation about what we will ask participants. We also use tools and text to signpost participant progress through the survey. This can be a valuable way to avoid high attrition rates where participants exit the survey because they are getting fatigued and are unclear when the survey will end:

Great! We are just over half-way through the survey.

We ask more detailed questions that are more aligned with our theoretical concepts in the middle of the survey. For example, we may start with broad questions about a harmful industry and their products (such as gambling, vaping or alcohol) and then in the middle of the survey ask more detailed questions about the commercial determinants of health and the specific tactics that these industries use (for example, about product design, political tactics, public relations strategies or how these practices may influence health and equity). In relation to these more complex questions, it is particularly important that we reiterate that there are no wrong answers and try to include encouraging text throughout the survey:

There are no right or wrong answers—we are curious to hear your opinions .

We always try to end the survey on a positive. While these types of questions depend on the study, we try to ask questions which enable participants to reflect on what could be done to address or improve an issue. This might include their attitudes about policy, or what they would say to those in positions of power:

What do you think should be done to protect young people from sports betting advertising on social media? If there was one thing that could be done to prevent young people from being exposed to the risks associated with alcohol, cigarettes, vaping, or gambling, what would it be? If you could say one thing to politicians about climate change, what would it be?

Finally, we ask participants if there is anything we have missed or if they have anything else to add, sometimes referred to as a ‘clean-up’ question ( Braun and Clarke, 2013 ). The following provides a few examples of how we have framed these questions in some of our studies:

Is there anything you would like to say about alcohol, cigarettes, vaping, and gambling products that we have not covered? Is there anything we haven’t asked you about the advertising of alcohol to women that you would like us to know?

Considering the impact of the length of the survey on responses

The length of the survey (both the number of questions and the time it takes an individual to complete the survey) is guided by a range of methodological and practical considerations and will vary between studies ( Braun and Clarke, 2013 ). Many factors will influence completion times. We try to give individuals a guide at the start of the survey about how long we think it will take to complete the survey (for example, between 20 and 30 minutes). We highlight that it may take people a little longer or shorter and that people are able to leave their browser open or save the survey and come back to finish it later. For our first few online qualitative surveys, we found that we asked lots of questions because we felt less in control of being able to prompt or ask follow-up questions from participants. However, we have learned that less is more! Asking too many questions may lead to more survey dropouts, and may significantly reduce the textual quality of the information that you receive from participants ( Braun and Clarke, 2013 ; Terry and Clarke, 2017 ). This includes considering how the survey questions might lead to repetition, which may be annoying for participants, leading to responses such as ‘like I’ve already said’ , ‘I’ve already answered that’ or ‘see above’ .

Providing clear and simple guidance

When designing an online qualitative survey, we try to think of ways to make participation in the survey engaging. We do not want individuals to feel that we are ‘mining’ them for data. Rather we want to demonstrate that we are genuinely interested in their perspectives and views. We use a range of mechanisms to do this. Because there is no opportunity to verbally explain or clarify concepts to participants, there is a particular need to ensure that the language used is clear and accessible ( Braun and Clarke, 2013 ; Terry and Clarke, 2017 ). If language or concepts are complex, you are more likely to receive ‘I don’t know’ responses to your questions. We need to remember that participants have a range of written and comprehension skills, and inclusive and accessible language is important. We also never try to assume a level of knowledge about an issue (unless we have specifically asked for participants who are aware and engaged in an issue—such as women who drink alcohol) ( Pitt et al ., 2023 ). This includes avoiding highly technical or academic language and not making assumptions that the individuals completing the survey will understand concepts in the same way that researchers do ( Braun and Clarke, 2013 ). Clearly explaining concepts or using text or images to prompt memories can help to overcome this:

Some big corporations (such as the tobacco, vaping, alcohol, junk food, or gambling industries) sponsor women's sporting teams or clubs, or other events. You might see sponsor logos on sporting uniforms, or at sporting grounds, or sponsoring a concert or arts event.

At all times, we try to centre the language that we use with the population from which we are seeking responses. Advisory groups can be particularly helpful in framing language for different population subgroups. We often use colloquial language, even if it might not be seen as the ‘correct’ academic language or terminology. Where possible, we also try to define theoretical concepts in a clear and easy to understand way. For example, in our study investigating parent perceptions of the impact of harmful products on young people, we tried to clearly define ‘normalization’:

In this section we ask you about some of the perceived health impacts of the above products on young people. We also ask you about the normalisation of these products for young people. When we talk about normalisation, we are thinking about the range of factors that might make these products more acceptable for young people to use. These factors might include individual factors, such as young people being attracted to risk, the influence of family or peers, the accessibility and availability of these products, or the way the industry advertises and promotes these products.

Using innovative approaches to improve accessibility and prompt responses

Online qualitative surveys can include features beyond traditional question-and-answer formats ( Braun and Clarke, 2013 ; Terry and Braun, 2017 ). For example, we often use a range of photo elicitation techniques (using images or videos) to make surveys more accessible to participate in, address different levels of literacy, and overcome the assumption that we are not able to ‘prompt’ responses. These types of visual methodologies enable a collaborative and creative research experience by asking the participant to reflect on aspects of the visual materials, such as symbolic representations, and discuss these in relation to the research objectives ( Glaw et al ., 2017 ). The combination of visual images and clear descriptions helps to provide a focus for responses about different issues, as well as prompting nuanced information such as participant memories and emotions ( Glaw et al ., 2017 ). We use different types of visuals in our studies, such as photographs (including of the public health issues we’re investigating); screenshots from websites and social media posts (including newspaper headlines) and videos (including short videos from social media sites such as TikTok) ( Arnot et al ., 2024b ). For example, when talking about government responses to the climate crisis, we used a photograph of former Australian Prime Minister Scott Morrison holding a piece of coal in the Australian parliament to prompt participants’ thinking about the government’s relationship with fossil fuels and to provide a focal point for their answer. However, we would caution against using any images that may be confronting for participants or deliberately provocative. The purpose of using visuals must always be in the interests of the participants—to clarify, prompt and reflect on concepts. Ethics committees should carefully review the images used in surveys to ensure that they have a clear purpose and are unlikely to cause any discomfort.

Survey implementation

Thinking carefully about your criteria for recruitment

Determining the sample size of online qualitative studies is not an exact science. The sample sizes for recent studies have ranged from n = 46 in a study about pregnancy loss ( Hennessy and O’Donoghue, 2024 ), to n = 511 in a study with young people about the climate crisis ( Arnot et al ., 2023b ). We follow ‘rules of thumb’ [( Braun and Clarke, 2021b ), p. 211] which try to balance the needs of the research and data richness with key practical considerations (such as funding and time constraints), funder expectations, discipline-specific norms and our knowledge and experience of designing and implementing online qualitative surveys. However, we have found that peer reviewers expect much more justification of sample sizes than they do for other types of qualitative research. Robust justification of sample sizes are often needed to prevent any ‘concerns’ that reviewers may raise. Our response to these reviews often reiterates that our focus (as with all qualitative research) is not to produce a ‘generalisable’ or ‘representative’ sample but to recruit participants who will help to provide ‘rich, complex and textured data’ [( Terry and Braun, 2017 ), p. 15] about an issue. Instead of focusing on data saturation, a contested concept which is incongruent with reflexive thematic analysis in particular ( Braun and Clarke, 2021b ), we find it useful to consider information power to determine the sample size for these surveys ( Malterud et al ., 2016 ). Information power prioritizes the adequacy, quality and variability of the data collected over the number of participants.

Recruitment for online qualitative surveys can be influenced by a range of factors. Monetary and time constraints will impact the size and, if using market research company panels, the specificity of participant quotas. Recruitment strategies must be developed to ensure that the data provides enough information to answer the research questions of the study. For our research purposes, we often try to ensure that participants with a range of socio-demographic characteristics are invited to participate in the sample. We set soft quotas for age, gender and geographic location to ensure some diversity. We have found that some population subgroups may also be recruited more easily than others—although this may depend on the topic of the survey. For example, we have found that quotas for women and those living in metropolitan areas may fill more quickly. In these scenarios, the research team must weigh up the timelines associated with recruitment and data collection (e.g. How long do we want to run data collection for? How much of our budget can be spent on achieving a more equally split sample? Are quotas necessary?) versus the purpose and goals of the research (i.e. to generate ideas rather than data representativeness), and the study-specific aims and research questions.

There are, of course, concerns about not being able to ‘see’ the people that are completing these surveys. There is an increasing focus in the academic literature on ‘false’ respondents, particularly in quantitative online surveys ( Levi et al ., 2021 ; Wang et al ., 2023 ). This will be an important ongoing discussion for qualitative researchers, and we do not claim to have the answers for how to overcome these issues. For example, some individuals may say that they meet the inclusion criteria to access the survey, while others may not understand or misinterpret the inclusion criteria. There is also a level of discomfort about who and how we judge who may be a ‘legitimate’ participant or not. However, we can talk practically about some of the strategies that we use to ensure the rigour of data. For example, we find that screening questions can provide a ‘double-check’ in relation to inclusion criteria and can also help with ensuring that there is consistency between the information an individual provides about how they meet the inclusion criteria and subsequent responses. For example, in a recent survey of parents of young people, a participant stated that they were 18 years old and were a parent to a 16-year-old and 15-year-old. Their overall responses were inconsistent with being a parent of children these ages. Similarly, in our gambling studies, people may tick that they have gambled in the last year but then in subsequent questions say they have not gambled at all. This highlights the importance of checking data across all questions, although it should be noted that time and cost constraints associated with comprehensively scanning the data for such responses are not always feasible and can result in overlooking these participants.

Ensuring that there are strategies to create agency and engage participants in the research

One of the benefits of online qualitative surveys compared to traditional quantitative surveys is the scope for participants to explain their answers and to disagree with the research team’s position. An indication that participants are feeling able to do this is when they are asked for any additional comments at the end of the survey. For example, in a survey about women’s attitudes towards alcohol marketing, the following participant concluded the survey by writing: ‘I think you have covered everything. I think that you need to stop shaming women for having fun’. Other participants demonstrate their engagement and interest in the survey by reaffirming the perspectives they have shared throughout the survey. For example, in a study with young people on climate, participants responded at the end that ‘it’s one of the few things I actually care about’ , while another commented on the quality of the survey questions, stating, ‘I think this survey did a great job with probing questions to prompt all the thoughts I have on it’ .

We also think that online qualitative surveys may lead to less social desirability in participants’ responses. Participants seem less wary about communicating less politically correct opinions than they may do in a face-to-face interview. For example, at times, participants communicate attitudes that may not align with public health values (e.g. supporting personal responsibility, anti-nanny state, and neoliberal ideologies of health and wellbeing), that we rarely see communicated to us in in-depth interview or focus group studies. We would argue that these perspectives are valuable for public health researchers because they capture a different community voice that may not otherwise be represented in research. This may show where there is a lack of support for health interventions and policy reforms and may indicate where further awareness-raising needs to occur. These types of responses also contribute to reflexive practice by challenging our assumptions and positions about how we think people should think or feel about responses to particular public health issues. Examples of such responses from our surveys include:

"Like I have already said, if you try to hide it you will only make it more attractive. This nanny-state attitude of the elite drives me crazy. People must be allowed to decide for themselves."

Ethical issues for participants and researchers

Researchers should also be aware that some of the ethical issues associated with online qualitative surveys may be different from those in in-depth interviews—and it is important that these are explained in any ethical consideration of the study. Providing a clear and simply worded Plain Language Statement (in written or video form) is important in establishing informed consent and willingness to participate. While participants are given information about who to contact if they have further questions about the study, this may be an extra step for participants, and they may not feel as able to ask for clarification about the study. Because of this, we try to provide multiple examples of the types of questions that we will ask, as well as providing downloadable support details (for example, for mental health support lines). A positive aspect of surveys is that participants are able to easily ignore recruitment notices to participate in the study. They are also able to stop the survey at any time by exiting out of the browser if they feel discomfort without having to give a reason in person to a researcher.

While the anonymous nature of the survey may be empowering for some participants ( Braun and Clarke, 2013 ; Terry and Braun, 2017 ; Braun et al. , 2021 ), it can also make it difficult for researchers to ascertain if people need any further support after completing the survey. Participants may also fill in surveys with someone else and may be influenced about how they should respond to questions (with the exception of some studies in which people may require assistance from someone to type their responses). Because of the above, some researchers, ethics committees and funders may be more cautious about using these studies for highly sensitive subjects. However, we would argue that the important point is that the studies follow ethical principles and take the lack of direct contact with participants into the ethical considerations of the study. It is also important to ensure that platforms used to collect survey data are trusted and secure. Here, we would argue that universities have an obligation to investigate and, where possible, approve survey providers to ensure that researchers are using platforms that meet rigorous standards for data and privacy.

It is also important to note that there may be responses from participants that may be challenging ( Terry and Braun, 2017 ; Braun and Clarke, 2021 ). Online spaces are rife with trolling due to their anonymous nature, and online surveys are not immune to this behaviour. Naturally, this leads to some silly responses—‘ Deakin University is responsible for all of this ’, but researchers should also be aware that the anonymity of surveys can (although in our experience not often) lead to responses that may cause discomfort for the researchers. For example, when asked if participants had anything else to add to a climate survey ( Arnot et al ., 2024c ), one responded ‘ nope, but you sure asked a lot of dumbass questions’ . Just as with interview-based studies, there must be processes built into the research for debriefing—particularly for students and early career researchers—as well as clear decisions about whether to include or exclude these types of responses when preparing the dataset for analysis and in writing up the results from the survey.

The importance of piloting the survey

Because of the lack of ability to explain and clarify concepts, piloting is particularly important ( Braun and Clarke, 2013 ; Terry and Braun, 2017 ; Braun et al. , 2021 ) to ensure that: (i) the technical aspects of the survey work as intended; (ii) the survey is eliciting quality responses (with limited ‘nonsensical’ responses such as random characters); (iii) the survey responses indicate comprehension of the survey questions; and (vi) there is not a substantial number of people who ‘drop-out’ of the study. Typically, we pilot our survey with 10% of the intended sample size. After piloting, we often change question wording, particularly to address questions that elicit very small text responses, the length of the survey and sometimes refine definitions or language to ensure increased comprehension. Researchers should remember that changes to the survey questions may need to be reviewed by ethics committees before launching the full survey. It is important to build in time for piloting and the revision of the survey to ensure you get this right as once you launch the full survey, there is no going back!

Survey analysis and write-up

Preparing the dataset

Once launching the full survey, the quality of data and types of responses you receive in these types of surveys can vary. There is very limited transparency around how the dataset was prepared (more familiar to some as ‘data cleaning’) in published papers, including the decisions about which (if any) participants (or indeed responses) were excluded from the dataset and why. Nonsensical responses can be common—and can take a range of forms ( Figure 3 ). These can include random numbers or letters, a chunk of text that has been copied and pasted from elsewhere, predictive text or even repeat emojis. In one study, we had a participant quote the script of The Bee Movie in response to questions.

: Visual examples of nonsensical responses in online qualitative surveys.

Part of our familiarization with the dataset [Phase One in Braun and Clarke’s reflexive approach to thematic analysis ( Braun and Clarke, 2013 ; Braun et al ., 2021 )] includes preparing the dataset for analysis. We use this phase to help make decisions about what to include and exclude from the final dataset. While a row of emojis in the data file can easily be spotted and removed from the dataset, sometimes responses can look robust until you read, become familiar and engage with the data. For example, when asked about what they thought about collective climate action ( Arnot et al ., 2023a , 2024c ), some participants entered random yet related terms such as ‘ plastic ’, or repeated similar phrases across multiple questions:

“ why do we need paper straws ”, “ paper straws are terrible ”, “ papers straws are bad for you ”, “ paper straws are gross .”

Participants can also provide comprehensive answers for the first few questions and then nonsensical responses for the rest, which may also be due to question fatigue [( Braun and Clarke, 2013 ), p. 138]. Therefore, it is important to closely go through each participant’s response to ensure they have attempted to provide bone-fide responses. For example, in one of our young people and climate surveys ( Arnot et al ., 2023a , 2024c ), one participant responded genuinely to the first half of the survey before their quality dropped dramatically:

“I can’t even be bothered to read that question ”, “ why so many questions ”, “ bro too many sections. ”

Some market research panel providers may complete an initial quality screen of data. However, this does not replace the need for the research teams’ own data preparation processes. Researchers should ensure they are checking that responses are coherent—for example, not giving information that contradicts or is not credible. In our more recent studies, we have increasingly seen responses cut and pasted from ChatGPT and other AI tools—providing a new challenge in assessing the quality of responses. If you are seeing these types of responses, it might be an opportunity to think about the style and suitability of the questions being asked. For example, the use of AI tools might suggest that people are finding it difficult to answer questions or may feel that they have to present a ‘correct’ answer. We would also note that because of the volume of data in these surveys, the preparation of data involves multiple members of the team. In many cases, decisions need to be made about participants who may not have provided authentic responses across the survey. The research team should make clear in any paper their decisions about their choices to include or exclude participants from the study. There is a careful balancing act that can require assessing the quality of the participants’ responses across the whole dataset to determine if the overall quality of responses contributes to the research.

Navigating the volume of data and writing up results

Finally, discussions about how to navigate the volume of data that these types of studies produce could be a standalone paper. In general, principles of reflexive practices apply to the analysis of data from these studies. However, as a starting point, here are a few considerations when approaching these datasets.

We would argue that online qualitative surveys lend themselves to some types of analytical approaches over others—for example, reflexive thematic analysis, as compared to grounded theory or interpretive phenomenological analysis (though it can be used with these) ( Braun and Clarke, 2013 ; Terry and Braun, 2017 ).

While initial familiarization, coding and analysis can focus on specific questions and associated responses, it is important to analyse the dataset as a whole (or as clusters associated with particular topics) as participants may provide relevant data to a topic under multiple questions ( Terry and Braun, 2017 ). We initially focus our coding on specific questions or a group of survey questions under a topic of investigation. Once we have developed and constructed preliminary themes from the data associated with these clusters of questions, we then move to looking at responses across the dataset as we review themes further.

Researchers should think carefully about how to manage the data—which may not be available as ‘individual participant transcripts’ but rather as a ‘whole’ dataset in an Excel spreadsheet. Some may prefer qualitative data analysis software (QDAS) to manage and navigate data. However, many of us find that Excel (and particularly the use of labelled Tabs) is useful in grouping data and moving from codes to constructing themes.

As with all rigorous qualitative research, coding and theme development should be guided by the research questions. A clear record of decision-making about analytical choices (and being reflexive about these) should be kept. In any write-up, we would recommend that researchers are clear about which survey questions they used in the analysis [researchers could consider providing a supplementary file of some or all of the survey questions—see, for example Hennessy and O’Donoghue (2024) ].

In writing up the results, researchers should still seek to present a rich description of the data, as demonstrated in the presentation of results in the following papers ( Marko et al ., 2022a , 2022b ; McCarthy et al ., 2023 ; Pitt et al ., 2023 ; Hennessy and O’Donoghue, 2024 ). We have found the use of tables with additional examples of quotes as they relate to themes and subthemes can be a practical way of providing the reader with further examples of the data, particularly when constrained by journal word count limits [see, for example, Table 2 in Arnot et al ., (2024c) ]. However, these tables do not replace a full and complete presentation of the interpretation of the data.

This article offers methodological reflections and practical guidance around online qualitative survey design, implementation and analysis. While online qualitative surveys engage participants in a different type of conversation, they have design features that enable the collection of rich data. We recognize that we have much to learn and that while no survey of ours has been perfect, each new experience with developing and conducting online qualitative surveys has brought new understandings and lessons for future studies. In recognizing that we are learning, we also feel that our experience to date could be valuable for progressing the conversation about the rigour of online qualitative surveys and maximizing this method for public health gains.

H.P. is funded through a VicHealth Postdoctoral Research Fellowship. S.M. is funded through a Deakin University Faculty of Health Deans Postdoctoral Fellowship. G.A. is funded by an Australian Government Research Training Program Scholarship. M.H. is funded through an Irish Research Council Government of Ireland Postdoctoral Fellowship Award [GOIPD/2023/1168].

The pregnancy loss study was funded by the Irish Research Council through its New Foundations Awards and in partnership with the Irish Hospice Foundation as civil society partner [NF/2021/27123063].

S.T. is Editor in Chief of Health Promotion International, H.P. is a member of the Editorial Board of Health Promotion International, S.M. and G.A. are Social Media Coordinators for Health Promotion International, M.H. is an Associate Editor for Health Promotion International. They were not involved in the review process or in any decision-making on the manuscript.

The data used in this study are not available.

Ethical approval for studies conducted by Deakin University include the climate crisis (HEAG-H 55_2020, HEAG-H 162_2021); parents perceptions of harmful industries on young people (HEAG-H 158_2022); women and alcohol marketing (HEAG-H 123_2022) and gambling (HEAG 227_2020).

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