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• 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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Chapter 1. Introduction

“Science is in danger, and for that reason it is becoming dangerous” -Pierre Bourdieu, Science of Science and Reflexivity

Why an Open Access Textbook on Qualitative Research Methods?

I have been teaching qualitative research methods to both undergraduates and graduate students for many years.  Although there are some excellent textbooks out there, they are often costly, and none of them, to my mind, properly introduces qualitative research methods to the beginning student (whether undergraduate or graduate student).  In contrast, this open-access textbook is designed as a (free) true introduction to the subject, with helpful, practical pointers on how to conduct research and how to access more advanced instruction.  

Textbooks are typically arranged in one of two ways: (1) by technique (each chapter covers one method used in qualitative research); or (2) by process (chapters advance from research design through publication).  But both of these approaches are necessary for the beginner student.  This textbook will have sections dedicated to the process as well as the techniques of qualitative research.  This is a true “comprehensive” book for the beginning student.  In addition to covering techniques of data collection and data analysis, it provides a road map of how to get started and how to keep going and where to go for advanced instruction.  It covers aspects of research design and research communication as well as methods employed.  Along the way, it includes examples from many different disciplines in the social sciences.

The primary goal has been to create a useful, accessible, engaging textbook for use across many disciplines.  And, let’s face it.  Textbooks can be boring.  I hope readers find this to be a little different.  I have tried to write in a practical and forthright manner, with many lively examples and references to good and intellectually creative qualitative research.  Woven throughout the text are short textual asides (in colored textboxes) by professional (academic) qualitative researchers in various disciplines.  These short accounts by practitioners should help inspire students.  So, let’s begin!

What is Research?

When we use the word research , what exactly do we mean by that?  This is one of those words that everyone thinks they understand, but it is worth beginning this textbook with a short explanation.  We use the term to refer to “empirical research,” which is actually a historically specific approach to understanding the world around us.  Think about how you know things about the world. [1] You might know your mother loves you because she’s told you she does.  Or because that is what “mothers” do by tradition.  Or you might know because you’ve looked for evidence that she does, like taking care of you when you are sick or reading to you in bed or working two jobs so you can have the things you need to do OK in life.  Maybe it seems churlish to look for evidence; you just take it “on faith” that you are loved.

Only one of the above comes close to what we mean by research.  Empirical research is research (investigation) based on evidence.  Conclusions can then be drawn from observable data.  This observable data can also be “tested” or checked.  If the data cannot be tested, that is a good indication that we are not doing research.  Note that we can never “prove” conclusively, through observable data, that our mothers love us.  We might have some “disconfirming evidence” (that time she didn’t show up to your graduation, for example) that could push you to question an original hypothesis , but no amount of “confirming evidence” will ever allow us to say with 100% certainty, “my mother loves me.”  Faith and tradition and authority work differently.  Our knowledge can be 100% certain using each of those alternative methods of knowledge, but our certainty in those cases will not be based on facts or evidence.

For many periods of history, those in power have been nervous about “science” because it uses evidence and facts as the primary source of understanding the world, and facts can be at odds with what power or authority or tradition want you to believe.  That is why I say that scientific empirical research is a historically specific approach to understand the world.  You are in college or university now partly to learn how to engage in this historically specific approach.

In the sixteenth and seventeenth centuries in Europe, there was a newfound respect for empirical research, some of which was seriously challenging to the established church.  Using observations and testing them, scientists found that the earth was not at the center of the universe, for example, but rather that it was but one planet of many which circled the sun. [2]   For the next two centuries, the science of astronomy, physics, biology, and chemistry emerged and became disciplines taught in universities.  All used the scientific method of observation and testing to advance knowledge.  Knowledge about people , however, and social institutions, however, was still left to faith, tradition, and authority.  Historians and philosophers and poets wrote about the human condition, but none of them used research to do so. [3]

It was not until the nineteenth century that “social science” really emerged, using the scientific method (empirical observation) to understand people and social institutions.  New fields of sociology, economics, political science, and anthropology emerged.  The first sociologists, people like Auguste Comte and Karl Marx, sought specifically to apply the scientific method of research to understand society, Engels famously claiming that Marx had done for the social world what Darwin did for the natural world, tracings its laws of development.  Today we tend to take for granted the naturalness of science here, but it is actually a pretty recent and radical development.

To return to the question, “does your mother love you?”  Well, this is actually not really how a researcher would frame the question, as it is too specific to your case.  It doesn’t tell us much about the world at large, even if it does tell us something about you and your relationship with your mother.  A social science researcher might ask, “do mothers love their children?”  Or maybe they would be more interested in how this loving relationship might change over time (e.g., “do mothers love their children more now than they did in the 18th century when so many children died before reaching adulthood?”) or perhaps they might be interested in measuring quality of love across cultures or time periods, or even establishing “what love looks like” using the mother/child relationship as a site of exploration.  All of these make good research questions because we can use observable data to answer them.

What is Qualitative Research?

“All we know is how to learn. How to study, how to listen, how to talk, how to tell.  If we don’t tell the world, we don’t know the world.  We’re lost in it, we die.” -Ursula LeGuin, The Telling

At its simplest, qualitative research is research about the social world that does not use numbers in its analyses.  All those who fear statistics can breathe a sigh of relief – there are no mathematical formulae or regression models in this book! But this definition is less about what qualitative research can be and more about what it is not.  To be honest, any simple statement will fail to capture the power and depth of qualitative research.  One way of contrasting qualitative research to quantitative research is to note that the focus of qualitative research is less about explaining and predicting relationships between variables and more about understanding the social world.  To use our mother love example, the question about “what love looks like” is a good question for the qualitative researcher while all questions measuring love or comparing incidences of love (both of which require measurement) are good questions for quantitative researchers. Patton writes,

Qualitative data describe.  They take us, as readers, into the time and place of the observation so that we know what it was like to have been there.  They capture and communicate someone else’s experience of the world in his or her own words.  Qualitative data tell a story. ( Patton 2002:47 )

Qualitative researchers are asking different questions about the world than their quantitative colleagues.  Even when researchers are employed in “mixed methods” research ( both quantitative and qualitative), they are using different methods to address different questions of the study.  I do a lot of research about first-generation and working-college college students.  Where a quantitative researcher might ask, how many first-generation college students graduate from college within four years? Or does first-generation college status predict high student debt loads?  A qualitative researcher might ask, how does the college experience differ for first-generation college students?  What is it like to carry a lot of debt, and how does this impact the ability to complete college on time?  Both sets of questions are important, but they can only be answered using specific tools tailored to those questions.  For the former, you need large numbers to make adequate comparisons.  For the latter, you need to talk to people, find out what they are thinking and feeling, and try to inhabit their shoes for a little while so you can make sense of their experiences and beliefs.

Examples of Qualitative Research

You have probably seen examples of qualitative research before, but you might not have paid particular attention to how they were produced or realized that the accounts you were reading were the result of hours, months, even years of research “in the field.”  A good qualitative researcher will present the product of their hours of work in such a way that it seems natural, even obvious, to the reader.  Because we are trying to convey what it is like answers, qualitative research is often presented as stories – stories about how people live their lives, go to work, raise their children, interact with one another.  In some ways, this can seem like reading particularly insightful novels.  But, unlike novels, there are very specific rules and guidelines that qualitative researchers follow to ensure that the “story” they are telling is accurate , a truthful rendition of what life is like for the people being studied.  Most of this textbook will be spent conveying those rules and guidelines.  Let’s take a look, first, however, at three examples of what the end product looks like.  I have chosen these three examples to showcase very different approaches to qualitative research, and I will return to these five examples throughout the book.  They were all published as whole books (not chapters or articles), and they are worth the long read, if you have the time.  I will also provide some information on how these books came to be and the length of time it takes to get them into book version.  It is important you know about this process, and the rest of this textbook will help explain why it takes so long to conduct good qualitative research!

Example 1 : The End Game (ethnography + interviews)

Corey Abramson is a sociologist who teaches at the University of Arizona.   In 2015 he published The End Game: How Inequality Shapes our Final Years ( 2015 ). This book was based on the research he did for his dissertation at the University of California-Berkeley in 2012.  Actually, the dissertation was completed in 2012 but the work that was produced that took several years.  The dissertation was entitled, “This is How We Live, This is How We Die: Social Stratification, Aging, and Health in Urban America” ( 2012 ).  You can see how the book version, which was written for a more general audience, has a more engaging sound to it, but that the dissertation version, which is what academic faculty read and evaluate, has a more descriptive title.  You can read the title and know that this is a study about aging and health and that the focus is going to be inequality and that the context (place) is going to be “urban America.”  It’s a study about “how” people do something – in this case, how they deal with aging and death.  This is the very first sentence of the dissertation, “From our first breath in the hospital to the day we die, we live in a society characterized by unequal opportunities for maintaining health and taking care of ourselves when ill.  These disparities reflect persistent racial, socio-economic, and gender-based inequalities and contribute to their persistence over time” ( 1 ).  What follows is a truthful account of how that is so.

Cory Abramson spent three years conducting his research in four different urban neighborhoods.  We call the type of research he conducted “comparative ethnographic” because he designed his study to compare groups of seniors as they went about their everyday business.  It’s comparative because he is comparing different groups (based on race, class, gender) and ethnographic because he is studying the culture/way of life of a group. [4]   He had an educated guess, rooted in what previous research had shown and what social theory would suggest, that people’s experiences of aging differ by race, class, and gender.  So, he set up a research design that would allow him to observe differences.  He chose two primarily middle-class (one was racially diverse and the other was predominantly White) and two primarily poor neighborhoods (one was racially diverse and the other was predominantly African American).  He hung out in senior centers and other places seniors congregated, watched them as they took the bus to get prescriptions filled, sat in doctor’s offices with them, and listened to their conversations with each other.  He also conducted more formal conversations, what we call in-depth interviews, with sixty seniors from each of the four neighborhoods.  As with a lot of fieldwork , as he got closer to the people involved, he both expanded and deepened his reach –

By the end of the project, I expanded my pool of general observations to include various settings frequented by seniors: apartment building common rooms, doctors’ offices, emergency rooms, pharmacies, senior centers, bars, parks, corner stores, shopping centers, pool halls, hair salons, coffee shops, and discount stores. Over the course of the three years of fieldwork, I observed hundreds of elders, and developed close relationships with a number of them. ( 2012:10 )

When Abramson rewrote the dissertation for a general audience and published his book in 2015, it got a lot of attention.  It is a beautifully written book and it provided insight into a common human experience that we surprisingly know very little about.  It won the Outstanding Publication Award by the American Sociological Association Section on Aging and the Life Course and was featured in the New York Times .  The book was about aging, and specifically how inequality shapes the aging process, but it was also about much more than that.  It helped show how inequality affects people’s everyday lives.  For example, by observing the difficulties the poor had in setting up appointments and getting to them using public transportation and then being made to wait to see a doctor, sometimes in standing-room-only situations, when they are unwell, and then being treated dismissively by hospital staff, Abramson allowed readers to feel the material reality of being poor in the US.  Comparing these examples with seniors with adequate supplemental insurance who have the resources to hire car services or have others assist them in arranging care when they need it, jolts the reader to understand and appreciate the difference money makes in the lives and circumstances of us all, and in a way that is different than simply reading a statistic (“80% of the poor do not keep regular doctor’s appointments”) does.  Qualitative research can reach into spaces and places that often go unexamined and then reports back to the rest of us what it is like in those spaces and places.

Example 2: Racing for Innocence (Interviews + Content Analysis + Fictional Stories)

Jennifer Pierce is a Professor of American Studies at the University of Minnesota.  Trained as a sociologist, she has written a number of books about gender, race, and power.  Her very first book, Gender Trials: Emotional Lives in Contemporary Law Firms, published in 1995, is a brilliant look at gender dynamics within two law firms.  Pierce was a participant observer, working as a paralegal, and she observed how female lawyers and female paralegals struggled to obtain parity with their male colleagues.

Fifteen years later, she reexamined the context of the law firm to include an examination of racial dynamics, particularly how elite white men working in these spaces created and maintained a culture that made it difficult for both female attorneys and attorneys of color to thrive. Her book, Racing for Innocence: Whiteness, Gender, and the Backlash Against Affirmative Action , published in 2012, is an interesting and creative blending of interviews with attorneys, content analyses of popular films during this period, and fictional accounts of racial discrimination and sexual harassment.  The law firm she chose to study had come under an affirmative action order and was in the process of implementing equitable policies and programs.  She wanted to understand how recipients of white privilege (the elite white male attorneys) come to deny the role they play in reproducing inequality.  Through interviews with attorneys who were present both before and during the affirmative action order, she creates a historical record of the “bad behavior” that necessitated new policies and procedures, but also, and more importantly , probed the participants ’ understanding of this behavior.  It should come as no surprise that most (but not all) of the white male attorneys saw little need for change, and that almost everyone else had accounts that were different if not sometimes downright harrowing.

I’ve used Pierce’s book in my qualitative research methods courses as an example of an interesting blend of techniques and presentation styles.  My students often have a very difficult time with the fictional accounts she includes.  But they serve an important communicative purpose here.  They are her attempts at presenting “both sides” to an objective reality – something happens (Pierce writes this something so it is very clear what it is), and the two participants to the thing that happened have very different understandings of what this means.  By including these stories, Pierce presents one of her key findings – people remember things differently and these different memories tend to support their own ideological positions.  I wonder what Pierce would have written had she studied the murder of George Floyd or the storming of the US Capitol on January 6 or any number of other historic events whose observers and participants record very different happenings.

This is not to say that qualitative researchers write fictional accounts.  In fact, the use of fiction in our work remains controversial.  When used, it must be clearly identified as a presentation device, as Pierce did.  I include Racing for Innocence here as an example of the multiple uses of methods and techniques and the way that these work together to produce better understandings by us, the readers, of what Pierce studied.  We readers come away with a better grasp of how and why advantaged people understate their own involvement in situations and structures that advantage them.  This is normal human behavior , in other words.  This case may have been about elite white men in law firms, but the general insights here can be transposed to other settings.  Indeed, Pierce argues that more research needs to be done about the role elites play in the reproduction of inequality in the workplace in general.

Example 3: Amplified Advantage (Mixed Methods: Survey Interviews + Focus Groups + Archives)

The final example comes from my own work with college students, particularly the ways in which class background affects the experience of college and outcomes for graduates.  I include it here as an example of mixed methods, and for the use of supplementary archival research.  I’ve done a lot of research over the years on first-generation, low-income, and working-class college students.  I am curious (and skeptical) about the possibility of social mobility today, particularly with the rising cost of college and growing inequality in general.  As one of the few people in my family to go to college, I didn’t grow up with a lot of examples of what college was like or how to make the most of it.  And when I entered graduate school, I realized with dismay that there were very few people like me there.  I worried about becoming too different from my family and friends back home.  And I wasn’t at all sure that I would ever be able to pay back the huge load of debt I was taking on.  And so I wrote my dissertation and first two books about working-class college students.  These books focused on experiences in college and the difficulties of navigating between family and school ( Hurst 2010a, 2012 ).  But even after all that research, I kept coming back to wondering if working-class students who made it through college had an equal chance at finding good jobs and happy lives,

What happens to students after college?  Do working-class students fare as well as their peers?  I knew from my own experience that barriers continued through graduate school and beyond, and that my debtload was higher than that of my peers, constraining some of the choices I made when I graduated.  To answer these questions, I designed a study of students attending small liberal arts colleges, the type of college that tried to equalize the experience of students by requiring all students to live on campus and offering small classes with lots of interaction with faculty.  These private colleges tend to have more money and resources so they can provide financial aid to low-income students.  They also attract some very wealthy students.  Because they enroll students across the class spectrum, I would be able to draw comparisons.  I ended up spending about four years collecting data, both a survey of more than 2000 students (which formed the basis for quantitative analyses) and qualitative data collection (interviews, focus groups, archival research, and participant observation).  This is what we call a “mixed methods” approach because we use both quantitative and qualitative data.  The survey gave me a large enough number of students that I could make comparisons of the how many kind, and to be able to say with some authority that there were in fact significant differences in experience and outcome by class (e.g., wealthier students earned more money and had little debt; working-class students often found jobs that were not in their chosen careers and were very affected by debt, upper-middle-class students were more likely to go to graduate school).  But the survey analyses could not explain why these differences existed.  For that, I needed to talk to people and ask them about their motivations and aspirations.  I needed to understand their perceptions of the world, and it is very hard to do this through a survey.

By interviewing students and recent graduates, I was able to discern particular patterns and pathways through college and beyond.  Specifically, I identified three versions of gameplay.  Upper-middle-class students, whose parents were themselves professionals (academics, lawyers, managers of non-profits), saw college as the first stage of their education and took classes and declared majors that would prepare them for graduate school.  They also spent a lot of time building their resumes, taking advantage of opportunities to help professors with their research, or study abroad.  This helped them gain admission to highly-ranked graduate schools and interesting jobs in the public sector.  In contrast, upper-class students, whose parents were wealthy and more likely to be engaged in business (as CEOs or other high-level directors), prioritized building social capital.  They did this by joining fraternities and sororities and playing club sports.  This helped them when they graduated as they called on friends and parents of friends to find them well-paying jobs.  Finally, low-income, first-generation, and working-class students were often adrift.  They took the classes that were recommended to them but without the knowledge of how to connect them to life beyond college.  They spent time working and studying rather than partying or building their resumes.  All three sets of students thought they were “doing college” the right way, the way that one was supposed to do college.   But these three versions of gameplay led to distinct outcomes that advantaged some students over others.  I titled my work “Amplified Advantage” to highlight this process.

These three examples, Cory Abramson’s The End Game , Jennifer Peirce’s Racing for Innocence, and my own Amplified Advantage, demonstrate the range of approaches and tools available to the qualitative researcher.  They also help explain why qualitative research is so important.  Numbers can tell us some things about the world, but they cannot get at the hearts and minds, motivations and beliefs of the people who make up the social worlds we inhabit.  For that, we need tools that allow us to listen and make sense of what people tell us and show us.  That is what good qualitative research offers us.

How Is This Book Organized?

This textbook is organized as a comprehensive introduction to the use of qualitative research methods.  The first half covers general topics (e.g., approaches to qualitative research, ethics) and research design (necessary steps for building a successful qualitative research study).  The second half reviews various data collection and data analysis techniques.  Of course, building a successful qualitative research study requires some knowledge of data collection and data analysis so the chapters in the first half and the chapters in the second half should be read in conversation with each other.  That said, each chapter can be read on its own for assistance with a particular narrow topic.  In addition to the chapters, a helpful glossary can be found in the back of the book.  Rummage around in the text as needed.

Chapter Descriptions

Chapter 2 provides an overview of the Research Design Process.  How does one begin a study? What is an appropriate research question?  How is the study to be done – with what methods ?  Involving what people and sites?  Although qualitative research studies can and often do change and develop over the course of data collection, it is important to have a good idea of what the aims and goals of your study are at the outset and a good plan of how to achieve those aims and goals.  Chapter 2 provides a road map of the process.

Chapter 3 describes and explains various ways of knowing the (social) world.  What is it possible for us to know about how other people think or why they behave the way they do?  What does it mean to say something is a “fact” or that it is “well-known” and understood?  Qualitative researchers are particularly interested in these questions because of the types of research questions we are interested in answering (the how questions rather than the how many questions of quantitative research).  Qualitative researchers have adopted various epistemological approaches.  Chapter 3 will explore these approaches, highlighting interpretivist approaches that acknowledge the subjective aspect of reality – in other words, reality and knowledge are not objective but rather influenced by (interpreted through) people.

Chapter 4 focuses on the practical matter of developing a research question and finding the right approach to data collection.  In any given study (think of Cory Abramson’s study of aging, for example), there may be years of collected data, thousands of observations , hundreds of pages of notes to read and review and make sense of.  If all you had was a general interest area (“aging”), it would be very difficult, nearly impossible, to make sense of all of that data.  The research question provides a helpful lens to refine and clarify (and simplify) everything you find and collect.  For that reason, it is important to pull out that lens (articulate the research question) before you get started.  In the case of the aging study, Cory Abramson was interested in how inequalities affected understandings and responses to aging.  It is for this reason he designed a study that would allow him to compare different groups of seniors (some middle-class, some poor).  Inevitably, he saw much more in the three years in the field than what made it into his book (or dissertation), but he was able to narrow down the complexity of the social world to provide us with this rich account linked to the original research question.  Developing a good research question is thus crucial to effective design and a successful outcome.  Chapter 4 will provide pointers on how to do this.  Chapter 4 also provides an overview of general approaches taken to doing qualitative research and various “traditions of inquiry.”

Chapter 5 explores sampling .  After you have developed a research question and have a general idea of how you will collect data (Observations?  Interviews?), how do you go about actually finding people and sites to study?  Although there is no “correct number” of people to interview , the sample should follow the research question and research design.  Unlike quantitative research, qualitative research involves nonprobability sampling.  Chapter 5 explains why this is so and what qualities instead make a good sample for qualitative research.

Chapter 6 addresses the importance of reflexivity in qualitative research.  Related to epistemological issues of how we know anything about the social world, qualitative researchers understand that we the researchers can never be truly neutral or outside the study we are conducting.  As observers, we see things that make sense to us and may entirely miss what is either too obvious to note or too different to comprehend.  As interviewers, as much as we would like to ask questions neutrally and remain in the background, interviews are a form of conversation, and the persons we interview are responding to us .  Therefore, it is important to reflect upon our social positions and the knowledges and expectations we bring to our work and to work through any blind spots that we may have.  Chapter 6 provides some examples of reflexivity in practice and exercises for thinking through one’s own biases.

Chapter 7 is a very important chapter and should not be overlooked.  As a practical matter, it should also be read closely with chapters 6 and 8.  Because qualitative researchers deal with people and the social world, it is imperative they develop and adhere to a strong ethical code for conducting research in a way that does not harm.  There are legal requirements and guidelines for doing so (see chapter 8), but these requirements should not be considered synonymous with the ethical code required of us.   Each researcher must constantly interrogate every aspect of their research, from research question to design to sample through analysis and presentation, to ensure that a minimum of harm (ideally, zero harm) is caused.  Because each research project is unique, the standards of care for each study are unique.  Part of being a professional researcher is carrying this code in one’s heart, being constantly attentive to what is required under particular circumstances.  Chapter 7 provides various research scenarios and asks readers to weigh in on the suitability and appropriateness of the research.  If done in a class setting, it will become obvious fairly quickly that there are often no absolutely correct answers, as different people find different aspects of the scenarios of greatest importance.  Minimizing the harm in one area may require possible harm in another.  Being attentive to all the ethical aspects of one’s research and making the best judgments one can, clearly and consciously, is an integral part of being a good researcher.

Chapter 8 , best to be read in conjunction with chapter 7, explains the role and importance of Institutional Review Boards (IRBs) .  Under federal guidelines, an IRB is an appropriately constituted group that has been formally designated to review and monitor research involving human subjects .  Every institution that receives funding from the federal government has an IRB.  IRBs have the authority to approve, require modifications to (to secure approval), or disapprove research.  This group review serves an important role in the protection of the rights and welfare of human research subjects.  Chapter 8 reviews the history of IRBs and the work they do but also argues that IRBs’ review of qualitative research is often both over-inclusive and under-inclusive.  Some aspects of qualitative research are not well understood by IRBs, given that they were developed to prevent abuses in biomedical research.  Thus, it is important not to rely on IRBs to identify all the potential ethical issues that emerge in our research (see chapter 7).

Chapter 9 provides help for getting started on formulating a research question based on gaps in the pre-existing literature.  Research is conducted as part of a community, even if particular studies are done by single individuals (or small teams).  What any of us finds and reports back becomes part of a much larger body of knowledge.  Thus, it is important that we look at the larger body of knowledge before we actually start our bit to see how we can best contribute.  When I first began interviewing working-class college students, there was only one other similar study I could find, and it hadn’t been published (it was a dissertation of students from poor backgrounds).  But there had been a lot published by professors who had grown up working class and made it through college despite the odds.  These accounts by “working-class academics” became an important inspiration for my study and helped me frame the questions I asked the students I interviewed.  Chapter 9 will provide some pointers on how to search for relevant literature and how to use this to refine your research question.

Chapter 10 serves as a bridge between the two parts of the textbook, by introducing techniques of data collection.  Qualitative research is often characterized by the form of data collection – for example, an ethnographic study is one that employs primarily observational data collection for the purpose of documenting and presenting a particular culture or ethnos.  Techniques can be effectively combined, depending on the research question and the aims and goals of the study.   Chapter 10 provides a general overview of all the various techniques and how they can be combined.

The second part of the textbook moves into the doing part of qualitative research once the research question has been articulated and the study designed.  Chapters 11 through 17 cover various data collection techniques and approaches.  Chapters 18 and 19 provide a very simple overview of basic data analysis.  Chapter 20 covers communication of the data to various audiences, and in various formats.

Chapter 11 begins our overview of data collection techniques with a focus on interviewing , the true heart of qualitative research.  This technique can serve as the primary and exclusive form of data collection, or it can be used to supplement other forms (observation, archival).  An interview is distinct from a survey, where questions are asked in a specific order and often with a range of predetermined responses available.  Interviews can be conversational and unstructured or, more conventionally, semistructured , where a general set of interview questions “guides” the conversation.  Chapter 11 covers the basics of interviews: how to create interview guides, how many people to interview, where to conduct the interview, what to watch out for (how to prepare against things going wrong), and how to get the most out of your interviews.

Chapter 12 covers an important variant of interviewing, the focus group.  Focus groups are semistructured interviews with a group of people moderated by a facilitator (the researcher or researcher’s assistant).  Focus groups explicitly use group interaction to assist in the data collection.  They are best used to collect data on a specific topic that is non-personal and shared among the group.  For example, asking a group of college students about a common experience such as taking classes by remote delivery during the pandemic year of 2020.  Chapter 12 covers the basics of focus groups: when to use them, how to create interview guides for them, and how to run them effectively.

Chapter 13 moves away from interviewing to the second major form of data collection unique to qualitative researchers – observation .  Qualitative research that employs observation can best be understood as falling on a continuum of “fly on the wall” observation (e.g., observing how strangers interact in a doctor’s waiting room) to “participant” observation, where the researcher is also an active participant of the activity being observed.  For example, an activist in the Black Lives Matter movement might want to study the movement, using her inside position to gain access to observe key meetings and interactions.  Chapter  13 covers the basics of participant observation studies: advantages and disadvantages, gaining access, ethical concerns related to insider/outsider status and entanglement, and recording techniques.

Chapter 14 takes a closer look at “deep ethnography” – immersion in the field of a particularly long duration for the purpose of gaining a deeper understanding and appreciation of a particular culture or social world.  Clifford Geertz called this “deep hanging out.”  Whereas participant observation is often combined with semistructured interview techniques, deep ethnography’s commitment to “living the life” or experiencing the situation as it really is demands more conversational and natural interactions with people.  These interactions and conversations may take place over months or even years.  As can be expected, there are some costs to this technique, as well as some very large rewards when done competently.  Chapter 14 provides some examples of deep ethnographies that will inspire some beginning researchers and intimidate others.

Chapter 15 moves in the opposite direction of deep ethnography, a technique that is the least positivist of all those discussed here, to mixed methods , a set of techniques that is arguably the most positivist .  A mixed methods approach combines both qualitative data collection and quantitative data collection, commonly by combining a survey that is analyzed statistically (e.g., cross-tabs or regression analyses of large number probability samples) with semi-structured interviews.  Although it is somewhat unconventional to discuss mixed methods in textbooks on qualitative research, I think it is important to recognize this often-employed approach here.  There are several advantages and some disadvantages to taking this route.  Chapter 16 will describe those advantages and disadvantages and provide some particular guidance on how to design a mixed methods study for maximum effectiveness.

Chapter 16 covers data collection that does not involve live human subjects at all – archival and historical research (chapter 17 will also cover data that does not involve interacting with human subjects).  Sometimes people are unavailable to us, either because they do not wish to be interviewed or observed (as is the case with many “elites”) or because they are too far away, in both place and time.  Fortunately, humans leave many traces and we can often answer questions we have by examining those traces.  Special collections and archives can be goldmines for social science research.  This chapter will explain how to access these places, for what purposes, and how to begin to make sense of what you find.

Chapter 17 covers another data collection area that does not involve face-to-face interaction with humans: content analysis .  Although content analysis may be understood more properly as a data analysis technique, the term is often used for the entire approach, which will be the case here.  Content analysis involves interpreting meaning from a body of text.  This body of text might be something found in historical records (see chapter 16) or something collected by the researcher, as in the case of comment posts on a popular blog post.  I once used the stories told by student loan debtors on the website studentloanjustice.org as the content I analyzed.  Content analysis is particularly useful when attempting to define and understand prevalent stories or communication about a topic of interest.  In other words, when we are less interested in what particular people (our defined sample) are doing or believing and more interested in what general narratives exist about a particular topic or issue.  This chapter will explore different approaches to content analysis and provide helpful tips on how to collect data, how to turn that data into codes for analysis, and how to go about presenting what is found through analysis.

Where chapter 17 has pushed us towards data analysis, chapters 18 and 19 are all about what to do with the data collected, whether that data be in the form of interview transcripts or fieldnotes from observations.  Chapter 18 introduces the basics of coding , the iterative process of assigning meaning to the data in order to both simplify and identify patterns.  What is a code and how does it work?  What are the different ways of coding data, and when should you use them?  What is a codebook, and why do you need one?  What does the process of data analysis look like?

Chapter 19 goes further into detail on codes and how to use them, particularly the later stages of coding in which our codes are refined, simplified, combined, and organized.  These later rounds of coding are essential to getting the most out of the data we’ve collected.  As students are often overwhelmed with the amount of data (a corpus of interview transcripts typically runs into the hundreds of pages; fieldnotes can easily top that), this chapter will also address time management and provide suggestions for dealing with chaos and reminders that feeling overwhelmed at the analysis stage is part of the process.  By the end of the chapter, you should understand how “findings” are actually found.

The book concludes with a chapter dedicated to the effective presentation of data results.  Chapter 20 covers the many ways that researchers communicate their studies to various audiences (academic, personal, political), what elements must be included in these various publications, and the hallmarks of excellent qualitative research that various audiences will be expecting.  Because qualitative researchers are motivated by understanding and conveying meaning , effective communication is not only an essential skill but a fundamental facet of the entire research project.  Ethnographers must be able to convey a certain sense of verisimilitude , the appearance of true reality.  Those employing interviews must faithfully depict the key meanings of the people they interviewed in a way that rings true to those people, even if the end result surprises them.  And all researchers must strive for clarity in their publications so that various audiences can understand what was found and why it is important.

The book concludes with a short chapter ( chapter 21 ) discussing the value of qualitative research. At the very end of this book, you will find a glossary of terms. I recommend you make frequent use of the glossary and add to each entry as you find examples. Although the entries are meant to be simple and clear, you may also want to paraphrase the definition—make it “make sense” to you, in other words. In addition to the standard reference list (all works cited here), you will find various recommendations for further reading at the end of many chapters. Some of these recommendations will be examples of excellent qualitative research, indicated with an asterisk (*) at the end of the entry. As they say, a picture is worth a thousand words. A good example of qualitative research can teach you more about conducting research than any textbook can (this one included). I highly recommend you select one to three examples from these lists and read them along with the textbook.

A final note on the choice of examples – you will note that many of the examples used in the text come from research on college students.  This is for two reasons.  First, as most of my research falls in this area, I am most familiar with this literature and have contacts with those who do research here and can call upon them to share their stories with you.  Second, and more importantly, my hope is that this textbook reaches a wide audience of beginning researchers who study widely and deeply across the range of what can be known about the social world (from marine resources management to public policy to nursing to political science to sexuality studies and beyond).  It is sometimes difficult to find examples that speak to all those research interests, however. A focus on college students is something that all readers can understand and, hopefully, appreciate, as we are all now or have been at some point a college student.

Recommended Reading: Other Qualitative Research Textbooks

I’ve included a brief list of some of my favorite qualitative research textbooks and guidebooks if you need more than what you will find in this introductory text.  For each, I’ve also indicated if these are for “beginning” or “advanced” (graduate-level) readers.  Many of these books have several editions that do not significantly vary; the edition recommended is merely the edition I have used in teaching and to whose page numbers any specific references made in the text agree.

Barbour, Rosaline. 2014. Introducing Qualitative Research: A Student’s Guide. Thousand Oaks, CA: SAGE.  A good introduction to qualitative research, with abundant examples (often from the discipline of health care) and clear definitions.  Includes quick summaries at the ends of each chapter.  However, some US students might find the British context distracting and can be a bit advanced in some places.  Beginning .

Bloomberg, Linda Dale, and Marie F. Volpe. 2012. Completing Your Qualitative Dissertation . 2nd ed. Thousand Oaks, CA: SAGE.  Specifically designed to guide graduate students through the research process. Advanced .

Creswell, John W., and Cheryl Poth. 2018 Qualitative Inquiry and Research Design: Choosing among Five Traditions .  4th ed. Thousand Oaks, CA: SAGE.  This is a classic and one of the go-to books I used myself as a graduate student.  One of the best things about this text is its clear presentation of five distinct traditions in qualitative research.  Despite the title, this reasonably sized book is about more than research design, including both data analysis and how to write about qualitative research.  Advanced .

Lareau, Annette. 2021. Listening to People: A Practical Guide to Interviewing, Participant Observation, Data Analysis, and Writing It All Up .  Chicago: University of Chicago Press. A readable and personal account of conducting qualitative research by an eminent sociologist, with a heavy emphasis on the kinds of participant-observation research conducted by the author.  Despite its reader-friendliness, this is really a book targeted to graduate students learning the craft.  Advanced .

Lune, Howard, and Bruce L. Berg. 2018. 9th edition.  Qualitative Research Methods for the Social Sciences.  Pearson . Although a good introduction to qualitative methods, the authors favor symbolic interactionist and dramaturgical approaches, which limits the appeal primarily to sociologists.  Beginning .

Marshall, Catherine, and Gretchen B. Rossman. 2016. 6th edition. Designing Qualitative Research. Thousand Oaks, CA: SAGE.  Very readable and accessible guide to research design by two educational scholars.  Although the presentation is sometimes fairly dry, personal vignettes and illustrations enliven the text.  Beginning .

Maxwell, Joseph A. 2013. Qualitative Research Design: An Interactive Approach .  3rd ed. Thousand Oaks, CA: SAGE. A short and accessible introduction to qualitative research design, particularly helpful for graduate students contemplating theses and dissertations. This has been a standard textbook in my graduate-level courses for years.  Advanced .

Patton, Michael Quinn. 2002. Qualitative Research and Evaluation Methods . Thousand Oaks, CA: SAGE.  This is a comprehensive text that served as my “go-to” reference when I was a graduate student.  It is particularly helpful for those involved in program evaluation and other forms of evaluation studies and uses examples from a wide range of disciplines.  Advanced .

Rubin, Ashley T. 2021. Rocking Qualitative Social Science: An Irreverent Guide to Rigorous Research. Stanford : Stanford University Press.  A delightful and personal read.  Rubin uses rock climbing as an extended metaphor for learning how to conduct qualitative research.  A bit slanted toward ethnographic and archival methods of data collection, with frequent examples from her own studies in criminology. Beginning .

Weis, Lois, and Michelle Fine. 2000. Speed Bumps: A Student-Friendly Guide to Qualitative Research . New York: Teachers College Press.  Readable and accessibly written in a quasi-conversational style.  Particularly strong in its discussion of ethical issues throughout the qualitative research process.  Not comprehensive, however, and very much tied to ethnographic research.  Although designed for graduate students, this is a recommended read for students of all levels.  Beginning .

Patton’s Ten Suggestions for Doing Qualitative Research

The following ten suggestions were made by Michael Quinn Patton in his massive textbooks Qualitative Research and Evaluations Methods . This book is highly recommended for those of you who want more than an introduction to qualitative methods. It is the book I relied on heavily when I was a graduate student, although it is much easier to “dip into” when necessary than to read through as a whole. Patton is asked for “just one bit of advice” for a graduate student considering using qualitative research methods for their dissertation.  Here are his top ten responses, in short form, heavily paraphrased, and with additional comments and emphases from me:

• Make sure that a qualitative approach fits the research question. The following are the kinds of questions that call out for qualitative methods or where qualitative methods are particularly appropriate: questions about people’s experiences or how they make sense of those experiences; studying a person in their natural environment; researching a phenomenon so unknown that it would be impossible to study it with standardized instruments or other forms of quantitative data collection.
• Study qualitative research by going to the original sources for the design and analysis appropriate to the particular approach you want to take (e.g., read Glaser and Straus if you are using grounded theory )
• Find a dissertation adviser who understands or at least who will support your use of qualitative research methods. You are asking for trouble if your entire committee is populated by quantitative researchers, even if they are all very knowledgeable about the subject or focus of your study (maybe even more so if they are!)
• Really work on design. Doing qualitative research effectively takes a lot of planning.  Even if things are more flexible than in quantitative research, a good design is absolutely essential when starting out.
• Practice data collection techniques, particularly interviewing and observing. There is definitely a set of learned skills here!  Do not expect your first interview to be perfect.  You will continue to grow as a researcher the more interviews you conduct, and you will probably come to understand yourself a bit more in the process, too.  This is not easy, despite what others who don’t work with qualitative methods may assume (and tell you!)
• Have a plan for analysis before you begin data collection. This is often a requirement in IRB protocols , although you can get away with writing something fairly simple.  And even if you are taking an approach, such as grounded theory, that pushes you to remain fairly open-minded during the data collection process, you still want to know what you will be doing with all the data collected – creating a codebook? Writing analytical memos? Comparing cases?  Having a plan in hand will also help prevent you from collecting too much extraneous data.
• Be prepared to confront controversies both within the qualitative research community and between qualitative research and quantitative research. Don’t be naïve about this – qualitative research, particularly some approaches, will be derided by many more “positivist” researchers and audiences.  For example, is an “n” of 1 really sufficient?  Yes!  But not everyone will agree.
• Do not make the mistake of using qualitative research methods because someone told you it was easier, or because you are intimidated by the math required of statistical analyses. Qualitative research is difficult in its own way (and many would claim much more time-consuming than quantitative research).  Do it because you are convinced it is right for your goals, aims, and research questions.
• Find a good support network. This could be a research mentor, or it could be a group of friends or colleagues who are also using qualitative research, or it could be just someone who will listen to you work through all of the issues you will confront out in the field and during the writing process.  Even though qualitative research often involves human subjects, it can be pretty lonely.  A lot of times you will feel like you are working without a net.  You have to create one for yourself.  Take care of yourself.
• And, finally, in the words of Patton, “Prepare to be changed. Looking deeply at other people’s lives will force you to look deeply at yourself.”
• We will actually spend an entire chapter ( chapter 3 ) looking at this question in much more detail! ↵
• Note that this might have been news to Europeans at the time, but many other societies around the world had also come to this conclusion through observation.  There is often a tendency to equate “the scientific revolution” with the European world in which it took place, but this is somewhat misleading. ↵
• Historians are a special case here.  Historians have scrupulously and rigorously investigated the social world, but not for the purpose of understanding general laws about how things work, which is the point of scientific empirical research.  History is often referred to as an idiographic field of study, meaning that it studies things that happened or are happening in themselves and not for general observations or conclusions. ↵
• Don’t worry, we’ll spend more time later in this book unpacking the meaning of ethnography and other terms that are important here.  Note the available glossary ↵

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

In contrast to methodology, methods are more simply the practices and tools used to collect and analyze data.  Examples of common methods in qualitative research are interviews , observations , and documentary analysis .  One’s methodology should connect to one’s choice of methods, of course, but they are distinguishable terms.  See also methodology .

A proposed explanation for an observation, phenomenon, or scientific problem that can be tested by further investigation.  The positing of a hypothesis is often the first step in quantitative research but not in qualitative research.  Even when qualitative researchers offer possible explanations in advance of conducting research, they will tend to not use the word “hypothesis” as it conjures up the kind of positivist research they are not conducting.

The foundational question to be addressed by the research study.  This will form the anchor of the research design, collection, and analysis.  Note that in qualitative research, the research question may, and probably will, alter or develop during the course of the research.

An approach to research that collects and analyzes numerical data for the purpose of finding patterns and averages, making predictions, testing causal relationships, and generalizing results to wider populations.  Contrast with qualitative research .

Data collection that takes place in real-world settings, referred to as “the field;” a key component of much Grounded Theory and ethnographic research.  Patton ( 2002 ) calls fieldwork “the central activity of qualitative inquiry” where “‘going into the field’ means having direct and personal contact with people under study in their own environments – getting close to people and situations being studied to personally understand the realities of minutiae of daily life” (48).

The people who are the subjects of a qualitative study.  In interview-based studies, they may be the respondents to the interviewer; for purposes of IRBs, they are often referred to as the human subjects of the research.

The branch of philosophy concerned with knowledge.  For researchers, it is important to recognize and adopt one of the many distinguishing epistemological perspectives as part of our understanding of what questions research can address or fully answer.  See, e.g., constructivism , subjectivism, and  objectivism .

An approach that refutes the possibility of neutrality in social science research.  All research is “guided by a set of beliefs and feelings about the world and how it should be understood and studied” (Denzin and Lincoln 2005: 13).  In contrast to positivism , interpretivism recognizes the social constructedness of reality, and researchers adopting this approach focus on capturing interpretations and understandings people have about the world rather than “the world” as it is (which is a chimera).

The cluster of data-collection tools and techniques that involve observing interactions between people, the behaviors, and practices of individuals (sometimes in contrast to what they say about how they act and behave), and cultures in context.  Observational methods are the key tools employed by ethnographers and Grounded Theory .

Research based on data collected and analyzed by the research (in contrast to secondary “library” research).

The process of selecting people or other units of analysis to represent a larger population. In quantitative research, this representation is taken quite literally, as statistically representative.  In qualitative research, in contrast, sample selection is often made based on potential to generate insight about a particular topic or phenomenon.

A method of data collection in which the researcher asks the participant questions; the answers to these questions are often recorded and transcribed verbatim. There are many different kinds of interviews - see also semistructured interview , structured interview , and unstructured interview .

The specific group of individuals that you will collect data from.  Contrast population.

The practice of being conscious of and reflective upon one’s own social location and presence when conducting research.  Because qualitative research often requires interaction with live humans, failing to take into account how one’s presence and prior expectations and social location affect the data collected and how analyzed may limit the reliability of the findings.  This remains true even when dealing with historical archives and other content.  Who we are matters when asking questions about how people experience the world because we, too, are a part of that world.

The science and practice of right conduct; in research, it is also the delineation of moral obligations towards research participants, communities to which we belong, and communities in which we conduct our research.

An administrative body established to protect the rights and welfare of human research subjects recruited to participate in research activities conducted under the auspices of the institution with which it is affiliated. The IRB is charged with the responsibility of reviewing all research involving human participants. The IRB is concerned with protecting the welfare, rights, and privacy of human subjects. The IRB has the authority to approve, disapprove, monitor, and require modifications in all research activities that fall within its jurisdiction as specified by both the federal regulations and institutional policy.

Research, according to US federal guidelines, that involves “a living individual about whom an investigator (whether professional or student) conducting research:  (1) Obtains information or biospecimens through intervention or interaction with the individual, and uses, studies, or analyzes the information or biospecimens; or  (2) Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens.”

One of the primary methodological traditions of inquiry in qualitative research, ethnography is the study of a group or group culture, largely through observational fieldwork supplemented by interviews. It is a form of fieldwork that may include participant-observation data collection. See chapter 14 for a discussion of deep ethnography. 

A form of interview that follows a standard guide of questions asked, although the order of the questions may change to match the particular needs of each individual interview subject, and probing “follow-up” questions are often added during the course of the interview.  The semi-structured interview is the primary form of interviewing used by qualitative researchers in the social sciences.  It is sometimes referred to as an “in-depth” interview.  See also interview and  interview guide .

A method of observational data collection taking place in a natural setting; a form of fieldwork .  The term encompasses a continuum of relative participation by the researcher (from full participant to “fly-on-the-wall” observer).  This is also sometimes referred to as ethnography , although the latter is characterized by a greater focus on the culture under observation.

A research design that employs both quantitative and qualitative methods, as in the case of a survey supplemented by interviews.

An epistemological perspective that posits the existence of reality through sensory experience similar to empiricism but goes further in denying any non-sensory basis of thought or consciousness.  In the social sciences, the term has roots in the proto-sociologist August Comte, who believed he could discern “laws” of society similar to the laws of natural science (e.g., gravity).  The term has come to mean the kinds of measurable and verifiable science conducted by quantitative researchers and is thus used pejoratively by some qualitative researchers interested in interpretation, consciousness, and human understanding.  Calling someone a “positivist” is often intended as an insult.  See also empiricism and objectivism.

A place or collection containing records, documents, or other materials of historical interest; most universities have an archive of material related to the university’s history, as well as other “special collections” that may be of interest to members of the community.

A method of both data collection and data analysis in which a given content (textual, visual, graphic) is examined systematically and rigorously to identify meanings, themes, patterns and assumptions.  Qualitative content analysis (QCA) is concerned with gathering and interpreting an existing body of material.    

A word or short phrase that symbolically assigns a summative, salient, essence-capturing, and/or evocative attribute for a portion of language-based or visual data (Saldaña 2021:5).

Usually a verbatim written record of an interview or focus group discussion.

The primary form of data for fieldwork , participant observation , and ethnography .  These notes, taken by the researcher either during the course of fieldwork or at day’s end, should include as many details as possible on what was observed and what was said.  They should include clear identifiers of date, time, setting, and names (or identifying characteristics) of participants.

The process of labeling and organizing qualitative data to identify different themes and the relationships between them; a way of simplifying data to allow better management and retrieval of key themes and illustrative passages.  See coding frame and  codebook.

A methodological tradition of inquiry and approach to analyzing qualitative data in which theories emerge from a rigorous and systematic process of induction.  This approach was pioneered by the sociologists Glaser and Strauss (1967).  The elements of theory generated from comparative analysis of data are, first, conceptual categories and their properties and, second, hypotheses or generalized relations among the categories and their properties – “The constant comparing of many groups draws the [researcher’s] attention to their many similarities and differences.  Considering these leads [the researcher] to generate abstract categories and their properties, which, since they emerge from the data, will clearly be important to a theory explaining the kind of behavior under observation.” (36).

A detailed description of any proposed research that involves human subjects for review by IRB.  The protocol serves as the recipe for the conduct of the research activity.  It includes the scientific rationale to justify the conduct of the study, the information necessary to conduct the study, the plan for managing and analyzing the data, and a discussion of the research ethical issues relevant to the research.  Protocols for qualitative research often include interview guides, all documents related to recruitment, informed consent forms, very clear guidelines on the safekeeping of materials collected, and plans for de-identifying transcripts or other data that include personal identifying information.

Introduction to Qualitative Research Methods Copyright © 2023 by Allison Hurst is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

Venturing into Qualitative Research: A Practical Guide to Getting Started

Scholarship and Practice of Undergraduate Research Journal

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In this commentary, we offer an introduction to qualitative research. Our goal is to provide guidance so that others can avoid common missteps and benefit from our lessons learned. We explain what qualitative data and research are, the value of qualitative research, and features that make qualitative research excellent, as well as how qualitative data can be collected and used to study undergraduate research. Our advice and recommendations are targeted at researchers who, like us, were first trained in fields with tendencies to overlook or underestimate qualitative research and its contributions. We share examples from our own and others’ research related to undergraduate research settings. We provide a table of resources researchers may find useful as they continue to learn about and conduct qualitative studies.

Introduction

We both started our scholarly journeys as biologists. As we trained, we both grew interested in researching undergraduate education and we transitioned to doing education research. We quickly came to realize that our training in experimental approaches and quantitative methods was woefully insufficient to study the diversity of ways students think, believe, value, feel, behave, and change in a variety of learning environments and educational systems.

For instance, there are established ways to quantify some educational variables, but not others. In addition, there may be phenomena at play that we haven’t thought of or that might be counterintuitive, which could lead us to quantify things that end up being irrelevant or meaningless. Herein lies the power of qualitative research. Qualitative research generates new knowledge by enabling rich, multifaceted descriptions of phenomena of interest, known as constructs (i.e., latent, unobservable variables), and producing possible explanations of how phenomena are occurring (i.e., mechanisms or relationships between constructs in different contexts and situations with different individuals and groups).

In this essay, we aim to offer an approachable explanation of qualitative research, including the types of questions that qualitative research is suited to address, the characteristics of robust qualitative research, and guidance on how to get started. We use examples from our own and others’ research to illustrate our explanations, and we cite references where readers can learn more. We expect Scholarship and Practice of Undergraduate Research (SPUR) readers from disciplines with a tradition of qualitative research might question why we would write this piece and what makes us qualified to do so. There are many scholars with much more qualitative research expertise than we have. Yet, we think we can offer a unique perspective to SPUR readers who are new to qualitative research or coming from disciplines where qualitative research is unfamiliar or undervalued. We have both designed, conducted, and published qualitative research in the context of undergraduate education and research experiences. We draw upon this experience in the recommendations we offer here.

Doing qualitative research involves acknowledging your “positionality,” or how your own background, lived experiences, and philosophical understandings of research influence how you approach and interpret the work (e.g., Hampton, Reeping, and Ozkan 2021; Holmes and Darwin 2020). Our positionalities have influenced our approach to this article and qualitative research generally. I (MAP) first learned about qualitative research from my undergraduate academic adviser. She invited me to help her implement and evaluate a capstone course in which groups of microbiology undergraduates engaged in a semester-long research project to address problems faced by community organizations (Watson, Willford, and Pfeifer 2018). At the time, I wasn’t aware of the long-standing history of qualitative research or its different forms and approaches. I just knew that reading quote data helped me understand human experiences in a way that survey numbers did not. Since my introduction to qualitative research, I’ve been fortunate to receive formal training. I consider my most valuable lessons about qualitative research to be through the practical experience of doing qualitative research and being mentored by qualitative researchers.

When I (ELD) first learned about qualitative research, I thought it meant words – perhaps collected through surveys, focus groups, interviews, or class recordings. I thought qualitative research would be easy – it was just words after all, and I had been using words almost my whole life. I assumed if I collected some words and summarized what I thought they meant (think word cloud), I would be doing qualitative research. As we will elaborate here, this is a limited view of what qualitative research is and what qualitative research can accomplish. When I began presenting qualitative research, I found it helpful to draw analogies to qualitative studies in natural science and medical disciplines. For instance, in the field of biology, the invention of technologies (e.g., lenses, microscopes) allowed for detailed observation and rich descriptions of cells (i.e., qualitative research) that led to the development of cell theory, the establishment of the field of cell biology, and quantitative research on cell structure, function, and dysfunction. In my own field of neuroscience, Henry Moliason, known as HM, was the focus of qualitative case study because he lost the ability to form new long-term memories due to a surgical treatment for severe epilepsy. Rich (i.e., comprehensive and detailed) description of Mr. Moliason’s memory impairment was the basis for hippocampal function being proposed as the main mechanism through which memories are formed. These examples of “non-numbery” research that produce influential descriptions and testable mechanisms helped me recognize the potential value and impact of qualitative research.

Types of Qualitative Research Questions

Qualitative research is useful for addressing two main types of questions: descriptive and mechanistic. Descriptive questions ask what is happening, for whom, and in what circumstances. Mechanistic questions ask how a phenomenon of interest happening. Here we explain each type of question and highlight some example studies conducted in the context of undergraduate research.

Descriptive Questions

Descriptive research seeks to elucidate details that enhance our overall understanding of a particular phenomenon—it answers questions about what a phenomenon is, including its defining features (i.e., dimensions) and what makes it distinct from other phenomena (Loeb et al. 2017). Descriptive research can also reveal who experiences the phenomenon, as well as when and where a phenomenon occurs (Loeb et al. 2017). Details like these serve as a starting point for future research, policy development, and enhanced practice. For instance, Hunter, Laursen, and Seymour (2007) carried out a qualitative study that identified and described the benefits of undergraduate research from the perspectives of both students and faculty. This work prompted calls for expansion of undergraduate research nationally and led to numerous quantitative studies (Gentile, Brenner, and Stephens 2017). Among these were quantitative studies from our group on the influences of research mentors on undergraduate researchers (Aikens et al. 2016, 2017; Joshi, Aikens, and Dolan 2019). Although these studies were framed to identify beneficial outcomes, we observed that undergraduates who had less favorable experiences with mentors were opting not to participate in our studies. Given this observation and the dearth of research on negative experiences in undergraduate research, we carried out a descriptive qualitative study of the dimensions (i.e., the what) of negative mentoring—that is, problematic or ineffective mentoring—in undergraduate life science research (Limeri et al. 2019). This study revealed that negative mentoring in undergraduate research included the absence of support from mentors and actively harmful mentor behaviors. These results served as the basis for practical guidance on how to curtail negative mentoring and its effects and for ongoing quantitative research. We use this study as the basis for the extended examples highlighted in Table 1.

Descriptive research is also suited to investigating the experiences of groups that are marginalized or minoritized in higher education. These studies offer insights into student experiences that may be otherwise overlooked or masked in larger quantitative studies (Vaccaro et al. 2015). For example, descriptive qualitative research shed light on how Black women in undergraduate and graduate STEM programs recognized and responded to structural racism, sexism, and race-gender bias. This research identified how high-achieving Black STEM students experienced racial battle fatigue and offered program-level suggestions for how to better support Black students (McGee and Bentley 2017). Descriptive qualitative research of deaf students involved in undergraduate research revealed that lack of awareness of Deaf culture of research mentors as well as lack of communication hindered students’ research experiences (Majocha et al. 2018). This research led to recommendations for research programs, research mentors, and students themselves. Another descriptive qualitative study showed how Latine students’ science identity changed over time when involved in an undergraduate research program (Vasquez-Salgado et al. 2023). Specifically, Vasguez-Salgado and colleagues identified patterns in students’ science identity through three waves of data collection spanning 18 months. Students’ identities showed consistent or fast achievement of feeling like a scientist, gradual achievement of feeling like a scientist, achievement adjustment of feeling like a scientist at one point and less so later in the program, or never feeling like a scientist. Together, these and other studies have generated knowledge that raises questions for future research and informs our collective efforts to make undergraduate research more accessible and inclusive.

Mechanistic Questions

Mechanistic qualitative research aims to address questions of how or why a phenomenon occurs. In the context of undergraduate research, an investigator may seek to understand how or why a particular practice or program design affects students. Recently, we conducted a mechanistic qualitative study that aimed, in part, to understand how early career researchers (undergraduate, postbaccalaureate, and graduate students) conceptualized their science identity (Pfeifer et al. 2023). Previous research theorized that someone is more likely to identify as a scientist if they are interested in science, believe they are competent in and can perform science, and feel recognized by others for their scientific aptitude or accomplishments (Carlone and Johnson 2007; Hazari et al. 2010; Potvin and Hazari 2013). However, this theory is somewhat limited in that it does not fully explain how context affects science identity or how science identity evolves, especially as researchers advance in their scientific training (Hazari et al. 2020; Kim and Sinatra 2018). To address this, we integrated science identity theory with research on professional identity development to design our study (Pratt, Rockmann, and Kaufmann 2006). We analyzed data from two national samples, including open-ended survey responses from 548 undergraduates engaged in research training and interview data from 30 early career researchers in the natural sciences. We found that they conceptualized science identity as a continuum that encompassed being a science student, being a science researcher, and being a career researcher. How students saw their science identity depended on how they viewed the purpose of their daily research, the level of intellectual responsibility they have for their research, and the extent of their autonomy in their research. We consider these findings to be hypotheses that can be tested quantitatively to better understand science identity dynamics in research training contexts. By asking this mechanistic question about science identity, we sought to add to and refine existing theory.

Key Attributes of Qualitative Research

For any type of research to be meaningful, it must possess some degree of rigor—what qualitative researchers call trustworthiness (Morse et al. 2002; Yilmaz 2013). Qualitative research is more trustworthy if it is characterized by credibility, transferability, dependability, and confirmability (Creswell and Poth 2016; Lincoln and Guba 1985). For instance, like accuracy and precision in quantitative research, do qualitative findings reflect what is being studied and are the interpretations true to the data (credibility)? Similar to reproducibility in quantitative research, how can qualitative research findings be applied to similar contexts (transferability)? Like validity in quantitative research, to what degree are the framing, methods, and findings of qualitative research appropriate given the aims (dependability)? Similar to the idea of replicability in quantitative research, if the same analytic tools were applied to the same data set could similar findings be reached by someone outside the original research team (confirmability)? The exact dimensions of trustworthiness, how trustworthiness manifests in the research process, the best ways to achieve trustworthiness, and how to talk about trustworthiness in research products are the subject of ongoing and often-spirited debate (e.g., Gioia et al. 2022; Mays and Pope 2020; Morse et al. 2002; Ritchie et al. 2013; Tracy 2010; Welch 2018; Yadav 2022). Central to these dialogues is the fact that qualitative research is composed of different philosophical approaches that emerged and evolved from diverse social science fields (Creswell and Poth 2016; Ritchie et al. 2013). Identifying universally agreed-upon criteria and the means to achieve these criteria is complex.

In our own work, we have found Tracy’s (2010) eight criteria for excellent qualitative research particularly useful. These criteria have helped us design studies, make decisions during the course of research, and articulate in our papers how our research seeks to achieve trustworthiness (e.g., Pfeifer, Cordero, and Stanton 2023). The full list of criteria is: worthy topic, rich rigor, sincerity, credibility, resonance, significant contribution, ethical conduct, and meaningful coherence (Tracy 2010). These criteria borrow from and build on the presented concepts of credibility, transferability, dependability, and confirmability. In our view, these criteria are presented and described in a way that makes sense to us and fits our approach to research. Here we highlight two criteria that may be particularly relevant if you are new to qualitative research.

Worthy Topics

As scholars familiar with undergraduate research and scholarly inquiry, SPUR readers are well-positioned to design studies that address research questions that are significant and timely in the context of undergraduate research. The first step in doing qualitative research (or any research) is to figure out what you want to study. You’ll want to select a topic that you find interesting, relevant, or otherwise compelling so you are motivated to spend time and effort investigating it. One way to find a topic is to notice what is happening in your environment and your work. What are you observing about undergraduate research? Something about students who participate (or not)? Something about colleagues who work with undergraduate researchers (or not)? Something about the design, implementation, or outcomes of the research experience? Something about the programmatic or institutional context? For a topic to be worthy of research, it should be interesting to you and to others. Consider sharing your observations with a few critical friends (i.e., trusted colleagues who will give you honest feedback) about whether they find your observations interesting or worth your time and energy to explore.

Like other human research, qualitative studies must adhere to basic ethical principles of respect for persons, beneficence, and justice (National Commission for the Protection of Human Subjects 1978). Respect for persons means treating all people as autonomous and protecting individuals with diminished autonomy (e.g., students whom we teach and assess). Beneficence involves treating people in an ethical manner, including respecting their decisions, protecting them from harm, and securing their well-being. Justice refers to the balance between benefiting from research and bearing its burdens; in other words, people should be able to benefit from research and should not be expected to bear the burden of research if they cannot benefit. Although it is beyond the scope of this essay to provide guidance on how to adhere to these principles, it is important to recognize that qualitative methods like interviewing can be highly personal and sometimes powerful experiences for both participants (and researchers). Investigators should carefully consider how their participants may be affected by data collection. For example, you may interview or survey participants about a personally difficult or painful experience. Do you then bear responsibility for helping them find support to navigate these difficulties? What if a participant reveals to you a serious mental health issue or physical safety concern? These situations occurred during our negative mentoring studies. We provided information to participants about where they could seek counseling or support for specific issues that can occur with mentors, such as harassment and discrimination.

Certainly not all qualitative data collection brings up these issues, but it can and does happen more frequently than you might expect. Your institutional review board (IRB), collaborators, and critical friends can be helpful resources when planning for and navigating tough scenarios like this. If working with an IRB is new to you, we recommend finding colleagues at your institution who have conducted IRB-reviewed research and asking them for guidance and examples. Some IRBs offer training for individuals new to developing human research protocols, and there are likely to be templates for everything from recruitment letters to consent forms to study information. We have found the process of developing IRB protocols helps refine research questions and study plans. Furthermore, IRB review is needed before you collect data that will be used for your study; IRBs rarely if ever allow for retrospective review and approval. In our experience, these studies are likely to be determined as exempt from IRB review because they involve minimal risk and use standard educational research procedures. However, the IRB is still responsible for making this determination and is a valuable partner for helping investigators navigate sensitive or complex situations that occur in human research.

Getting Started with Qualitative Research

Now that you have a sense of the purposes of qualitative research and what features help to ensure its quality, you are probably wondering how to do it. We want to emphasize that there are entire programs of study, whole courses, and lengthy texts that aim to teach qualitative research. We cannot come close to describing what can be learned from these more substantial resources. With this is mind, we share our own process of carrying out qualitative research as an example that others might find helpful to follow. We outline this “how to” as a series of steps, but qualitative research (like all research) is iterative and dynamic (University of California Museum of Paleontology 2022). Feel free to read through the steps in a linear fashion but then move in non-linear ways through the various steps. Extended discussion of each of these steps with examples from our research on negative mentoring is provided in Table 1 along with an abridged list of our go-to references.

Observe, Search, and Read

For a topic to be worthy of qualitative research (or any research), it should also have the potential to address a knowledge gap. After we identify a “worthy topic,” we try to find as much information about that topic as possible (Dolan 2013). We read, then we keep reading, and then we read some more. This may seem obvious, but we find that investing time reading literature can save us a lot of time designing, conducting, and writing up a study on a phenomenon that is already well known or understood by others and just not (yet) by us. To help us in our searching, we will sometimes reach out to colleagues in related fields to describe the phenomenon we are interested in studying and see if they have terms that they use to describe the phenomenon or theories they think are related. Theory informs our research questions, study designs, analytic approaches, and interpretation and reporting of findings, and enables alignment among all of these elements of research (e.g., Grant and Osanloo 2014; Luft et al. 2022; Spangler and Williams 2019). Theory also serves as a touchstone for connecting our findings to larger bodies of knowledge and communicating these connections in a way that promotes collective understanding of whatever we are investigating.

Formulate a Question

Once you have selected a topic and identified a knowledge gap, consider research questions that, if answered, would address the knowledge gap. Recall that qualitative research is suited to questions that require a descriptive (what) or mechanistic (how) answer.

Decide on a Study Design

Just like quantitative research, qualitative research has characteristic approaches, designs, and methodologies, each of which has affordances and constraints (Creswell and Poth 2016; Merriam 2014; Miles, Huberman, and Saldana 2014). Creswell and Poth provide a valuable resource for learning more about different types of qualitative research study designs, including which designs are suited to address which kinds of research questions. Given the labor intensiveness of qualitative data collection and analysis, it is critical to think carefully about how to recruit and select study participants. What this looks like and who might be appropriate study participants will depend on many factors, including the knowledge gap, research question, study design, and methods. Questions that can be helpful to ask are: Who do I need to study to answer my research question? What should the study participants have in common? In what ways should study participants vary to provide rich, complex, and varied insight into what I am studying? To whom do I want to generalize my findings, keeping in mind the qualitative nature of the work?

Based on the answers to these questions, you may opt for purposeful sampling in which you collect data only from participants who meet the characteristics you decide upon given the aims of your study. In this case, you will likely send a screening survey to potential participants to determine what their characteristics of interest are, which will help you decide if you will invite them for further data collection or not. A purposeful sample contrasts with a convenience sample where essentially any person who agrees to participate in the study will be selected for further data collection.

Collect and Analyze Data Systematically

Qualitative data can be collected in a variety of ways, including surveys, interviews, and focus groups, as well as audio and video recordings of learning experiences such as class sessions. To decide which method(s) to use for data collection, it is helpful to consider what you aim to learn from study participants. Surveys tend to be easier to distribute to a larger sample, but may elicit shorter or shallower responses, which are challenging to interpret because there is less information (i.e., words) and no opportunity to clarify with participants. Focus groups can be effective for quickly gathering input from a group of participants. However, social dynamics may result in one or a few people dominating the discussion, or “group think,” when people agree with one another rather than providing their own unique perspectives. Interviews with individuals can be a rich and varied data source because each participant has time and space to offer their own distinct perspective. Interviews also allow for follow-up questions that are difficult through survey methods. Yet, conducting interviews skillfully—avoiding leading questions and ensuring that the line of questioning yields the desired data—takes a lot of thought and practice. Kvale (1996) offers detailed guidance on how to design and carry out research interviews. Observing an expert interviewer and having them observe and give feedback as you interview can help improve your skills. Audio and video recordings of learning experiences like class sessions or group work can provide a plethora of information (e.g., verbal and nonverbal exchanges among students or between students and instructors) in a more natural setting than surveys or interviews. Yet deciding what information will serve as data to answer your research question, or how that large body of data will be systematically analyzed, can be cumbersome.

Regardless of the data collection method, you’ll need to decide how much data to collect. There is no one right sample size. A good rule of thumb is collecting data until you reach “saturation,” which is the notion that the same ideas are coming up repeatedly and that no new ideas are emerging during data collection. This means that your data collection and analysis are likely to overlap in time, with some data collection then some analysis and then more data collection.

Analytic methods in qualitative research vary widely in their interpretive complexity. As natural scientists, we favor sticking close to the data and analyzing using a method called qualitative content analysis. Content analysis involves taking quotes or segments of text and capturing their meaning with short words or phrases called codes. The process of developing codes and systematically applying them to a dataset is called coding. Coding is highly iterative and time-consuming because it typically requires multiple, careful passes through the dataset to ensure all codes have been evenly applied to all data. In a recent study, we spent 10 to 15 person-hours to code a single interview, and about 400 person-hours to complete coding for a 30-participant study. The time involved in coding depends on what is being studied, the type of coding, and who is coding the data. Saldaña (2016) provides excellent guidance on the coding process, including various ways of making sense of codes by grouping them into themes. Content analysis is just one approach to qualitative data analysis. We encourage you to learn more about different forms of qualitative approaches and choose what works best for you, including your skill level, research goals, and data (e.g., Creswell and Poth 2016; Starks and Brown Trinidad 2007).

Interpret and Write Results

There are many ways to effectively write up results, often called findings, from qualitative research. Because qualitative research involves extensive interpretation, it can sometimes be easier to integrate the results and discussion of a qualitative paper. Integration allows the interpretation (discussion) to be directly supported by the evidence in the form of quotations (results). The conclusions of the paper should avoid repeating the results and instead comment on the implications and applications of the findings: why they matter and what to do as a result. Because qualitative data are quotations rather than numbers, qualitative papers tend to be longer than papers presenting quantitative studies. That said, qualitative papers should still aim to be succinct. For instance, depending on the approach and methods, quotations can be lightly edited to remove extra words or filler language (e.g., um, uh) that is a natural part of language but otherwise irrelevant to the findings. Presenting only the most pertinent part of a quotation not only facilitates succinctness, but helps readers attend to the specific evidence that supports the claims being made. Another strategy to shorten qualitative papers is to present some findings in supplemental materials.

Final Recommendations

In closing our article, we offer some advice that we wish we knew when we began conducting qualitative research. We hope that these recommendations will help you think through issues that are likely emerge as you delve deeper into qualitative analysis, both as a producer and a consumer of qualitative research.

Consensus Coding in Qualitative Analysis

In qualitative analysis, we work to ensure that the analysis yields trustworthy findings by coding to consensus, meaning that the analytic team reaches 100 percent agreement on the application of each code to the data. Any disagreement between coders is discussed until a resolution is resolved. In some cases, these discussions may result in a code description being redefined. Redefinition of a code requires that all data previously coded using the original code be reanalyzed to ensure fit with the revised definition. As you might imagine, coding to consensus can be time-consuming. Yet, in our experience, the time invested in coding to consensus is well spent because the analysis yields deeper insights about the data and phenomenon being investigated. We also see coding to consensus as a great way to take advantage of the diverse viewpoints that team members bring to our research. By coding to consensus, we consider multiple interpretations of the data throughout the analysis process. We are well-positioned to develop theory (as appropriate for our study design) as a team because we all have engaged in meaningful conversations about our findings throughout analysis.

Some qualitative research relies on a calculated measure of intercoder reliability (ICR) instead of coding to consensus. ICR values indicate how often a set of coders agree on the application of a code in the dataset. This quantification of coding is tempting because we love numbers, yet it can also be problematic (O’Connor and Joffe 2020). For instance, aiming for high ICR can create situations when coders are pressured to agree with each other rather than bringing their own unique perspective to the coding process (e.g., Belur et al. 2018; Morse 1997). Quantifying qualitative work also can imply a false precision in the analysis. In some research, ICR is calculated partway through the analysis to determine whether an “acceptable” level of agreement has been reached, at which point the remainder of the data are coded by just one researcher. This approach of using ICR as a cut-off runs counter to what many argue is the value of qualitative research: generating new theoretical understandings informed by multiple perspectives.

Using Numbers in Qualitative Analysis

Although numbers certainly have a place in qualitative analysis (Sandelowski 2001), we encourage researchers to move beyond word clouds or frequency counts of codes and themes in their results for two reasons. First, a code or theme that is infrequently observed in the data set can still be important to the phenomenon being studied. As an analogy, consider making qualitative observations of living cells under a typical light microscope. We would most frequently see a relatively stationary cell that is punctuated by a relatively rare cell division or mitosis. If we only reported stationary observations in findings, we would overlook describing mitosis, one of the most dynamic and fundamental processes that cells display. Second, given limited sample sizes, it may be that a unique and important code or theme is reported by only one participant in the data set. In fact, rare observations can serve as “a-ha moments” that lead to a more comprehensive understanding of the phenomenon under investigation. These rare observations also may inspire new studies about topics that were not initially anticipated; this speaks to the value of qualitative research.

Closing Thoughts

We encourage readers to continue to learn about qualitative research as there is much that could not be addressed in a single article. For instance, we did not introduce how philosophical stances, like how someone views the nature of truth or what counts as evidence, influence the research process. (Creswell and Poth 2016). For now, we will close with one final piece of advice. We both became better qualitative researchers by working with mentors and collaborators who have this expertise. We encourage you to find colleagues in your networks or at your institutions who may be interested in being a collaborator, mentor, or critical friend. The complexity of students and their experiences lend themselves to qualitative approaches. We hope this article might serve as an impetus for you to learn more about qualitative research and even start your own investigations.

Data Availability Statement

The data included in this commentary have been published in an open-access journal under a Creative Commons license. Citations are included in the text.

Institutional Review Board Statement

Not applicable.

Conflict of Interest Statement

The authors have no conflicts of interest to report.

Acknowledgments

This material is based upon work supported by the National Science Foundation under award number OCE-2019589. This is the National Science Foundation’s Center for Chemical Currencies of a Microbial Planet (C-Comp) publication #026. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. We thank Patricia Mabrouk for inviting us to contribute this commentary. We thank members of the Biology Education Research Group at the University of Georgia and Daniel Dries, Joseph Provost, and Verónica Segarra for their thoughtful feedback on manuscript drafts.

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Mariel A. Pfeifer

University of Georgia, [email protected]

Mariel A. Pfeifer is a postdoctoral researcher at the University of Georgia’s SPREE (Social Psychology of Research Experiences and Education) Lab. Her passion for biology education research was sparked by her experiences as an undergraduate teaching assistant, a pre-service science teacher, and a disability services coordinator. Soon Pfeifer will begin her new role as an assistant professor of biology at the University of Mississippi.

Erin L. Dolan is a professor of biochemistry and molecular biology and Georgia Athletic Association Professor of Innovative Science Education at the University of Georgia As a graduate student, Dolan volunteered in K–12 schools, which inspired her pursuit of a biology education career. She teaches introductory biology and her research group, the SPREE Lab, works to delineate features of undergraduate and graduate research that influence students’ career decisions.

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SPUR advances knowledge and understanding of novel and effective approaches to mentored undergraduate research, scholarship, and creative inquiry by publishing high-quality, rigorously peer reviewed studies written by scholars and practitioners of undergraduate research, scholarship, and creative inquiry. The SPUR Journal is a leading CUR member benefit. Gain access to all electronic articles by joining CUR.

• Open access
• Published: 27 May 2020

How to use and assess qualitative research methods

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

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

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

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

What is qualitative research?

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

Why conduct qualitative research?

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

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

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

How to conduct qualitative research?

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

Iterative research process

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

Data collection

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

Document study

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

Observations

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

Semi-structured interviews

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

Focus groups

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

Choosing the “right” method

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

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

Possible combination of data collection methods

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

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

Data analysis

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

From data collection to data analysis

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

How to report qualitative research?

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

How to combine qualitative with quantitative research?

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

Three common mixed methods designs

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

How to assess qualitative research?

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

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

Reflexivity

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

Sampling and saturation

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

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

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

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

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

Member checking

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

Stakeholder involvement

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

How not to assess qualitative research

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

Protocol adherence

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

Sample size

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

Randomisation

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

Interrater reliability, variability and other “objectivity checks”

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

Not being quantitative research

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

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

Availability of data and materials

Not applicable.

Abbreviations

Endovascular treatment

Randomised Controlled Trial

Standard Operating Procedure

Standards for Reporting Qualitative Research

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

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Home » Qualitative Research – Methods, Analysis Types and Guide

Qualitative Research – Methods, Analysis Types and Guide

Table of Contents

Qualitative Research

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

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

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

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

Focus Groups

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

Ethnographic Studies

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

Text Analysis

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

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

Process of Observation

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

Record Keeping

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

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

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

Qualitative Research Analysis Methods

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

Thematic Analysis

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

Content Analysis

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

Discourse Analysis

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

Grounded Theory Analysis

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

Narrative Analysis

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

Phenomenological Analysis

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

Comparative Analysis

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

Applications of Qualitative Research

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

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

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

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

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

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

Purpose of Qualitative Research

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

Qualitative research can serve multiple purposes, including:

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

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

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

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

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

Advantages of Qualitative Research

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

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

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

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

Also see Research Methods

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Muhammad Hassan

Researcher, Academic Writer, Web developer

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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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Qualitative Research 101: Everything you need to know

How to choose the right software for qualitative research

What does psychology say about qualitative research via webcam?

Which is better - online or face-to-face qual (according to psychology)?

If you are keen on learning more about qualitative research, it can be hard to find an overview of all the key things you need to know, and how to apply everything that is available in the qualitative research sphere to your particular needs. This article has been designed to be that overview - a "pillar page" that will provide everything you need to know before spreading your search further into specific areas that interest you or that directly relate to what you are trying to achieve using the latest qualitative research tools and methods.

In this article you will discover:

The difference between qualitative and quantitative research The difference between online and offline qualitative research Common qualitative research methodologies The powerful market research trend towards video that is changing the qualitative research landscape Modern approaches to qualitative data analysis How to choose qualitative research software

When talking about research methods, there are generally two distinct styles of research that need to be considered - qualitative and quantitative. Any discussion about qualitative research, what it is, and how it can be used inevitably must also consider how it is different from quantitative research - so that is where we will begin!

Qualitative vs quantitative research

Quantitative research: all about the numbers.

Quantitative research is most often associated with the social sciences, natural sciences, and business administration. It often involves measuring the impact of certain events on a population. Specifically, it is research that measures something with numbers.

For example, in medicine, a researcher might investigate the efficacy of a new vaccine on patients by conducting a quantitative research study. A simpler example might be finding out how many people have heard of a particular brand, and how many like the brand.

Data collection for quantitative studies is often through running Web surveys, and there are a large number of platforms available to create such surveys, ranging from the relatively cheap Survey Monkey through to Confirmit and Qualtrics at the high end.

Due to the nature of quantitative research - the collection and analysis of numbers - research is heavily biased towards online methods, and data analysis takes advantage of all the intrinsic benefits of computers ("crunching" large amounts of data, performing analytics to uncover trends and producing digestible summaries of big data sets).

Qualitative research: Analysis of non-numerical data

Qualitative research is literally everything quantitative research is not. It involves the collection and analysis of non-numerical data (e.g., text, video, audio). Rather than resulting in "statistics", it results in "insights" (i.e. it helps to understand concepts, opinions, or experiences). The goal is often to delve into what problems exist or to generate new ideas for research.

The purpose of qualitative research is to "explain rather than describe". Qualitative research projects are often exploratory rather than explanatory, aiming to explore phenomenon rather than test a hypothesis. As such, the research may be used to generate or contribute evidence towards new hypotheses.

One of the biggest concerns when conducting qualitative research is sampling. Because most studies aim to understand a larger group through intensive observation (e.g. ethnography), samples are typically smaller than in quantitative research where random sampling is more common. Sampling may also be more purposive rather than random. Participants may be selected by convenience, snowball, or judgemental methods, which raises concerns that findings cannot be generalised beyond the sample.

An effort is usually made to avoid this problem by collecting data from multiple, diverse sources and triangulating findings so that different perspectives are considered at the same time. Rather than looking for statistical significance in the results, "thematic findings" are what is important in qualitative research.

Factors to determine your sample size for qualitative research

Qualitative research is often overshadowed by quantitative research due to the sheer size of the quantitative research industry, and the ease with which the benefits of quantitative methods can be understood and applied. The broadness of qualitative research is both a strength and a weakness. While it provides insights that are impossible to get through numbers, the broadness of approaches and the ever-improving suite of tools and technologies available can make it harder to understand (and keep up with).

Gaining an understanding of qualitative research methods and approaches and applying them to your clients can distinguish you from your competitors, so it is certainly worth the effort to understand what is possible. Providing something different, and better, that results in deeper insights is always going to be of greater value than a "quant only" offering.

The best way to expand your quant-based research firm is to move into qual and provide a hybrid approach that gives clients the best of both worlds. Because of the more open-ended and emergent nature of the qualitative inquiry, the field is more amenable to using mixed-methods approaches. For instance, researchers can use a qualitative methodology such as ethnography to guide the focus of a larger, quantitative survey.

How to conduct qualitative market research successfully

Online vs. offline qualitative research

The qualitative research methods being used most commonly today fall into two distinct "camps" - online and offline. Online qualitative research is defined as research where the qualitative data is collected "digitally" - usually over the Internet. Offline research is where more traditional data collection methods are used involving physical contact between moderators and participants.

Online research methods are on the rise

Online research is on the rise because it enables fast and wide-scale access to participants (e.g. through social media recruitment) without needing any specific fieldwork abilities (e.g. recruiting on the street). Furthermore, it enables researchers to be more flexible with whom they can communicate with (e.g. online focus groups that involve geographically remote participants).

Advantages of online research: Why you should move your project online

Due to these advantages, more and more researchers are embracing digital technologies for at least some of their qualitative research data collection. Lastly, it can be argued that digital research not only enhances but also move beyond traditional qualitative methods such as interviews and observations.

As with any form of research, it is important to take all of the key advantages and disadvantages of going online into account before making a final decision about which way to take a particular project.

The top 7 advantages of online research

Data can be collected from anywhere in the world (e.g., recruitment through social media) Approach participants quickly and with minimal costs (e.g., data is crowd-sourced) Data can be analyzed automatically (e.g., using an online platform that analyses textual data such as words and phrases used or frequency of self-reported emotions). Enables researchers to be more flexible with whom they can communicate with (e.g., online focus groups) Allows researchers to easily create their own coding schemes when using specific platforms for data collection. Data provides insight into unmeasured or under-researched phenomena that are not typically covered by traditional qualitative methods (e.g., consumer loyalty) The ability to protect anonymity and confidentiality of respondents due to its largely distance-based nature

Offline qualitative research methods are still important

Online research is never going to completely replace offline methods. Regardless of any other reasons, online methods are simply not right for every circumstance.

Critics of online research believe that the main disadvantages in collecting qualitative data digitally are related to the quality and reliability of the data being collected. Some of their specific concerns are:

That without in-depth knowledge about how these platforms work, researchers might not be able to prevent participants from breaking their anonymity rules for example. In some cases it is difficult if not impossible for researchers to identify who exactly is behind a certain set of data. Data which is collected online will most likely only give one interpretation, since there is no way to verify what respondents mean/intend by their responses . Because of the lack of control over study participants (e.g. drop out rates), drawing definitive conclusions about phenomena becomes harder.

What is interesting about all of these concerns is they all appear to be the result of poor platform choice, platform training, or project management. For researchers who what to take the lead into online research, a key point from all of these concerns is going online requires both careful research and personal commitment to make these online research methods work.

How to choose qualitative research software

The reason offline qualitative research will continue to be important has nothing really to do with pitfalls of going online that can be avoided with the right platform and training. It has much more to do with the simple fact that offline will always be better in certain circumstances . An example would be a taste test or a group trial of a physical product where initial reactions are key.

Common qualitative research methodologies

Qualitative research methods are designed to discover what people "think" about a particular topic. It can involve looking at how they behave, and what their perceptions are. While there are many different types of research that can be classed as "qualitative research" - including things like document analysis - here we will focus on the main types of research requested from market research professionals by their clients.

In-depth interviews

These are known by various names - including one-on-one interviews and "IDIs". This method involves directly asking research participants questions in order to gain their opinions on specific subjects.

Focus groups

Focus groups are one of the more commonly used qualitative research methods, and they play an important role in many qualitative research projects. A focus group usually includes a relatively small group of respondents (usually between 6-10) who will meet together either (i.e. in a "group") in person or virtually on a zoom call or through an online platform.

The use of a focus group has some benefits and some disadvantages when compared to one-on-one interviews as discussed below.

Advantages over in-depth interviews

Focus groups allow for more people to be covered in a shorter period of time so you can reach more people outside your group faster than you could with just one-on-one interviews Because multiple people are involved it's easier to see how certain people may affect others' thoughts and opinions It allows for a much faster response time because all of your information is being collected from multiple sources at once.

Disadvantages to in-depth interviews

Much can be lost in translation when trying to interpret everyone's answers Much depends on the quality and experience of the moderator It may be difficult for people who are interacting with other people to remain completely unbiased.

Taking focus groups online is one of the key "battlegrounds" between online and offline research methods. There is a lot to consider when deciding if taking your next project online is a good option.

Online consumer research panels: Are they the right method for your next project?

Ethnography

Another common method of qualitative research is known as "Ethnography". This type of research involves immersing yourself within a group or culture for an extended period of time.

For example, you might want to learn about the daily life of teenagers living on their own or what it's like to be a stay-at-home mom.

Online-specific research methodologies

The research methodologies that we have discussed above all have a common trait - they existed before online research was even an option. There is a long history of these research methods being used, and the move to online for all of these methodologies does not change their fundamental structure and purpose.

For example, video groups on Zoom and other video-based platforms can replicate focus groups and one-on-one interviews. These are still essentially the same "methodologies" - they are just conducted online rather than offline.

New online methodologies

The rise of online research has led to the creation of a whole series of new online tools that have created opportunities for completely new methodologies that have no equivalent in the offline research world. Since they have been designed specifically for online, they provide an optimised digital experience for participants.

Online discussions

Online discussions can have many different names, including bulletin boards, forums and short-term communities. Regardless of what they are called, they all have the same traits:

They generally have between 10-60 participants (though they can have more)

The discussion is run over a few days of weeks

Generally there will be a couple of activities each day to complete

A moderator will probe participants for further information or engage with them in other ways to help get deeper insights

Participants may be able to engage with each other to give more of a "community feel" to a particular activity.

Advanced activities - like ideations - may provide specific functionality for certain types of research that can be conducted within a wider discussion project.

Online discussions can be accessed on any modern device - including mobile phones, tablets and laptops - making access easy regardless of where a participant is at any particular time. This makes them perfect for longer term research that will need participants to be involved for multiple days or weeks. Such involvement would be impossible in the "real world" because the amount of time that would have to be allocated to performing activities in person would be impossibly high.

The technologies available to you to complete online discussions is extensive, with a number of platforms offering suites of 15 or more activity types for all types of data collection. These collection methods can be mixed and matched to create a more engaging experience for the people taking part - perhaps a video and a quick poll today, followed by a pin task and some picture taking tomorrow.

Long-term communities

For many years, long-term communities were simply "panels". They existed mainly as a pool of people that could be used as respondents to Web surveys. Qualitative research wasn't part of the research process, and these panels were just a means to get the people required to collect quantitative data.

Over the years, as qualitative research grew online, qualitative researchers started see whether they could run a qualitative study as a semi structured project directly from within these panels. What they found was using a new research method with people who were used to Web surveys meant they didn't always get the quality of results they expected.

This has led to the growth of something designed to be used in qualitative research from the very start - smaller panels of people (as small as a few hundred up to a thousand people in total) specifically recruited to provide valuable qualitative insights for a long period of time.

Long-term communities differ from short-term communities (i.e. discussions) in a number of ways:

Discussions tend to be very structured - e.g. three days of activities, with four activities on each day. Long-term communities are much less structured - "add a task whenever needed" is a common approach. Clients often use a long-term community as an easily accessible pool of people to ask opinions of at a moment's notice. Discussions are very "ad-hoc" - it's all over in a matter of days or weeks. Long-term communities are much more of a commitment for participants. They feel more like their own Web site, and things like logins, ongoing rewards and additional content like blogs are much more common. Discussions are quicker to set up and recruit for, but once they are done, the recruits are gone. Each discussion usually needs to be recruited for all over again. Long-term communities require more set up including theming and various content pages, but once set up and recruited for you don't necessarily have to recruit again - you keep going back to the same pool of people.

From a qualitative research perspective, the thing that is the same regardless of whether you are doing a short-term or long-term community is the suite of activities available to you.

The powerful market research trend towards video

We live in a world right now, however, where the speed of change is being forced upon a market research professional is much faster than normal. Remote working has become much more common, and all manner of research (for example - tracking a customer journey) has had to be adjusted to consider new restrictions on practical aspects of conducting market research - particularly in terms of how data collection will need to be done.

Online research has primarily grown through the use of technology to add to the existing research methods in ways that can not be replicated in the "real world". Huge scale, the ability to leverage social media, and the ability to crunch a lot of data are just some of the things that have made certain online research methods so important for literally decades.

As an increasing slice of new projects moves online, the replacement for "in-person" will primarily be "on video". It will be easier to get participants (because being in the vicinity of a central location is no longer necessary, and attending virtually is less of a "hassle"), and moderator location is also unimportant. Incentives can be less, and some costs - like the cost of a group room - will disappear completely.

Understanding the bigger picture by including video as part of any research project is considered to be extremely important by clients who want to make informed decisions, understand the biggest trends and get a better understanding of what various different types of people think - regardless of whether they are looking at consumers online through, people using social media, employees of many companies or anyone else. Video is almost always a powerful tool to go beyond text-based responses.

As the amount of video being collected grows, and the level of analysis and quality of expected outputs also becomes higher - this all begs the question... how is this even achievable? Watching hours and hours of video and trying to make sense of it all is extremely time-consuming, so manually solving this problem is expensive at best, and near-impossible at worst.

Fortunately, analysis of the ever-growing amount of video being collected is made feasibly through the use of automated "video analytics". Harnessing these new technologies has been made possible by taking the capabilities of Google, Microsoft, Amazon and others, and using them as building blocks to create a solution that is specific to market research.

The 3 Market Research Trends taking the industry by storm

Modern approaches to qualitative data analysis

The process of analyzing data and your research findings is critical when it comes to making decisions; this is why it's vital you make the process of analysing qualitative data as easy and as simple as possible.

Traditional analysis is undertaken by researchers while in the room with focus groups or conducting the interviews - benefiting from the social context of being able to read and individuals emotions and keep participants from straying off course. The quality of the analysis is directly related to the skill and experience of the researchers themselves, which can be a limiting factor.

Online approaches to qualitative study help foster creativity and ingenuity - with researchers always looking for new ways of engaging with participants. The great thing about modern online data analysis is that sky is indeed the limit in terms of developing new ideas and methodologies when collecting data and how to analyse it.

Qualitative analysis does not need to take up your time - modern approaches enable you to receive responses in real-time so that you can start to analyze data right from the get-go. As part of any campaign, you should be given access to a dashboard that provides you with the tools to start your data analysis.

Your dashboard is the start of your qualitative data analysis and shows you how your sample is responding or engaging to your research questions; it'll display all data collected and the level of engagement from your sample.

The modern approach of using a dedicated platform empowers the researcher to track respondent behaviour and the wider community.

How to make qualitative data analysis easy and simple

Any venture into the world of online qualitative research necessitates to use of a platform to create and run your projects. Finding the right platform can be a daunting task, but there are a few basic things to consider when taking this journey of discovery.

Avoid lock-in to untried solutions

Unfortunately, we live in a world where "subscriptions are king" and locking you into a particular platform - preferably for a few years - is the end goal of many platform providers. Big promises linked to a long-term commitment or large upfront costs are quite common.

There is no need to lock into anything, ever, if you don't want to . A number of providers will offer very reasonable per-project pricing that will not only suit your existing project but will also let you try the platform, set up your project design, and show your client a preview of what they will be getting before making you pay for anything. Providers who are happy to back their platform and show you everything you need to make an informed decision without trying to first lock you in are the ones to look for.

Ensure you will get the support you need

Even the best qualitative research platforms can fall down due to poor support - particularly when you are new to the platform. Confirm what support is provided - and if it costs extra factor this into your costs. Online research often requires quick support response times - particularly when you are dealing with real-time research like a live group.

There are various levels of support available, but some of the things to look out for:

You may be able to get free setup included for your first project - some suppliers offer this to help make this first experience as smooth as possible, and to help you get the most out of the platform from day one.

Some platforms give you instant access to the support team through an online chat. Often this is also a great way to get quick access to their knowledgebase.

When looking at testimonials for a platform, pay particular attention to what is said about support - the quality and level of support is hard to gauge prior to getting involved in a project (it's easy to promise good support - harder to confirm the promises).

Try to discover the true capabilities of a platform

At first glance, all platforms can seem very similar. Same promise about how great they are. Similar list of qualitative research methods is available to you. Similar indications that they would be perfect for "you". The trick is to look around the edges of all these claims to determine whether what you need is truly available. Examples of things to consider are:

Does the platform use an app on phones and tablets? A few years ago apps were necessary to support some of the more advanced activities, however advances in browsers make them redundant nowadays, so all you are left with is their limitations. If they don't install as expected or crash when running, fixing the specific issue with a specific device is near impossible. Completely browser-based solutions can be used by participants on any device from a single link. Access is instant, and if a device is playing up, simply move to another one. Does the platform do what you want with videos? This point leads on from what we discussed earlier in this article - the rise of video in qualitative research. If you don't need video, or you just want to collect the video and deal with it yourself this is not a big issue - all platforms will do that. If, however, the idea of video analytics excites you (and more importantly your clients) make sure you pick a platform with powerful analytics features. All platforms will offer some sort of text transcription - the question is whether they go beyond that to identify sentiment and themes, and whether they help you build showreels (often also known as highlight reels). Does the platform cost rise steeply as the number of participants or days rise? Platforms can often appear to be around the same price, but always make sure you get a final price based on your exact needs. So of the pricing offered by platforms is for as few as 10 participants, while other platforms provide the same price all the way to 200 participants. If you have a discussion with 50 participants, the final cost between these platforms is likely to be substantial.

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How to write qualitative research questions.

11 min read Here’s how to write effective qualitative research questions for your projects, and why getting it right matters so much.

What is qualitative research?

Qualitative research is a blanket term covering a wide range of research methods and theoretical framing approaches. The unifying factor in all these types of qualitative study is that they deal with data that cannot be counted. Typically this means things like people’s stories, feelings, opinions and emotions , and the meanings they ascribe to their experiences.

Qualitative study is one of two main categories of research, the other being quantitative research. Quantitative research deals with numerical data – that which can be counted and quantified, and which is mostly concerned with trends and patterns in large-scale datasets.

What are research questions?

Research questions are questions you are trying to answer with your research. To put it another way, your research question is the reason for your study, and the beginning point for your research design. There is normally only one research question per study, although if your project is very complex, you may have multiple research questions that are closely linked to one central question.

A good qualitative research question sums up your research objective. It’s a way of expressing the central question of your research, identifying your particular topic and the central issue you are examining.

Research questions are quite different from survey questions, questions used in focus groups or interview questions. A long list of questions is used in these types of study, as opposed to one central question. Additionally, interview or survey questions are asked of participants, whereas research questions are only for the researcher to maintain a clear understanding of the research design.

Research questions are used in both qualitative and quantitative research , although what makes a good research question might vary between the two.

In fact, the type of research questions you are asking can help you decide whether you need to take a quantitative or qualitative approach to your research project.

Discover the fundamentals of qualitative research

Quantitative vs. qualitative research questions

Writing research questions is very important in both qualitative and quantitative research, but the research questions that perform best in the two types of studies are quite different.

Quantitative research questions

Quantitative research questions usually relate to quantities, similarities and differences.

It might reflect the researchers’ interest in determining whether relationships between variables exist, and if so whether they are statistically significant. Or it may focus on establishing differences between things through comparison, and using statistical analysis to determine whether those differences are meaningful or due to chance.

• How much? This kind of research question is one of the simplest. It focuses on quantifying something. For example:

How many Yoruba speakers are there in the state of Maine?

• What is the connection?

This type of quantitative research question examines how one variable affects another.

For example:

How does a low level of sunlight affect the mood scores (1-10) of Antarctic explorers during winter?

• What is the difference? Quantitative research questions in this category identify two categories and measure the difference between them using numerical data.

Do white cats stay cooler than tabby cats in hot weather?

If your research question fits into one of the above categories, you’re probably going to be doing a quantitative study.

Qualitative research questions

Qualitative research questions focus on exploring phenomena, meanings and experiences.

Unlike quantitative research, qualitative research isn’t about finding causal relationships between variables. So although qualitative research questions might touch on topics that involve one variable influencing another, or looking at the difference between things, finding and quantifying those relationships isn’t the primary objective.

In fact, you as a qualitative researcher might end up studying a very similar topic to your colleague who is doing a quantitative study, but your areas of focus will be quite different. Your research methods will also be different – they might include focus groups, ethnography studies, and other kinds of qualitative study.

A few example qualitative research questions:

• What is it like being an Antarctic explorer during winter?
• What are the experiences of Yoruba speakers in the USA?
• How do white cat owners describe their pets?

Qualitative research question types

Marshall and Rossman (1989) identified 4 qualitative research question types, each with its own typical research strategy and methods.

• Exploratory questions

Exploratory questions are used when relatively little is known about the research topic. The process researchers follow when pursuing exploratory questions might involve interviewing participants, holding focus groups, or diving deep with a case study.

• Explanatory questions

With explanatory questions, the research topic is approached with a view to understanding the causes that lie behind phenomena. However, unlike a quantitative project, the focus of explanatory questions is on qualitative analysis of multiple interconnected factors that have influenced a particular group or area, rather than a provable causal link between dependent and independent variables.

• Descriptive questions

As the name suggests, descriptive questions aim to document and record what is happening. In answering descriptive questions , researchers might interact directly with participants with surveys or interviews, as well as using observational studies and ethnography studies that collect data on how participants interact with their wider environment.

• Predictive questions

Predictive questions start from the phenomena of interest and investigate what ramifications it might have in the future. Answering predictive questions may involve looking back as well as forward, with content analysis, questionnaires and studies of non-verbal communication (kinesics).

Why are good qualitative research questions important?

We know research questions are very important. But what makes them so essential? (And is that question a qualitative or quantitative one?)

Getting your qualitative research questions right has a number of benefits.

• It defines your qualitative research project Qualitative research questions definitively nail down the research population, the thing you’re examining, and what the nature of your answer will be.This means you can explain your research project to other people both inside and outside your business or organization. That could be critical when it comes to securing funding for your project, recruiting participants and members of your research team, and ultimately for publishing your results. It can also help you assess right the ethical considerations for your population of study.
• It maintains focus Good qualitative research questions help researchers to stick to the area of focus as they carry out their research. Keeping the research question in mind will help them steer away from tangents during their research or while they are carrying out qualitative research interviews. This holds true whatever the qualitative methods are, whether it’s a focus group, survey, thematic analysis or other type of inquiry.That doesn’t mean the research project can’t morph and change during its execution – sometimes this is acceptable and even welcome – but having a research question helps demarcate the starting point for the research. It can be referred back to if the scope and focus of the project does change.
• It helps make sure your outcomes are achievable

Because qualitative research questions help determine the kind of results you’re going to get, it helps make sure those results are achievable. By formulating good qualitative research questions in advance, you can make sure the things you want to know and the way you’re going to investigate them are grounded in practical reality. Otherwise, you may be at risk of taking on a research project that can’t be satisfactorily completed.

Developing good qualitative research questions

All researchers use research questions to define their parameters, keep their study on track and maintain focus on the research topic. This is especially important with qualitative questions, where there may be exploratory or inductive methods in use that introduce researchers to new and interesting areas of inquiry. Here are some tips for writing good qualitative research questions.

1. Keep it specific

Broader research questions are difficult to act on. They may also be open to interpretation, or leave some parameters undefined.

Strong example: How do Baby Boomers in the USA feel about their gender identity?

Weak example: Do people feel different about gender now?

2. Be original

Look for research questions that haven’t been widely addressed by others already.

Strong example: What are the effects of video calling on women’s experiences of work?

Weak example: Are women given less respect than men at work?

3. Make it research-worthy

Don’t ask a question that can be answered with a ‘yes’ or ‘no’, or with a quick Google search.

Strong example: What do people like and dislike about living in a highly multi-lingual country?

Weak example: What languages are spoken in India?

4. Focus your question

Don’t roll multiple topics or questions into one. Qualitative data may involve multiple topics, but your qualitative questions should be focused.

Strong example: What is the experience of disabled children and their families when using social services?

Weak example: How can we improve social services for children affected by poverty and disability?

4. Focus on your own discipline, not someone else’s

Avoid asking questions that are for the politicians, police or others to address.

Strong example: What does it feel like to be the victim of a hate crime?

Weak example: How can hate crimes be prevented?

5. Ask something researchable

Big questions, questions about hypothetical events or questions that would require vastly more resources than you have access to are not useful starting points for qualitative studies. Qualitative words or subjective ideas that lack definition are also not helpful.

Strong example: How do perceptions of physical beauty vary between today’s youth and their parents’ generation?

Weak example: Which country has the most beautiful people in it?

Related resources

Qualitative research design 12 min read, primary vs secondary research 14 min read, business research methods 12 min read, qualitative research interviews 11 min read, market intelligence 10 min read, marketing insights 11 min read, ethnographic research 11 min read, request demo.

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How to Do Qualitative Research

Last Updated: October 26, 2022 Fact Checked

This article was co-authored by Jeremiah Kaplan . Jeremiah Kaplan is a Research and Training Specialist at the Center for Applied Behavioral Health Policy at Arizona State University. He has extensive knowledge and experience in motivational interviewing. In addition, Jeremiah has worked in the mental health, youth engagement, and trauma-informed care fields. Using his expertise, Jeremiah supervises Arizona State University’s Motivational Interviewing Coding Lab. Jeremiah has also been internationally selected to participate in the Motivational Interviewing International Network of Trainers sponsored Train the Trainer event. Jeremiah holds a BS in Human Services with a concentration in Family and Children from The University of Phoenix. There are 10 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 749,566 times.

Qualitative research is a broad field of inquiry that uses unstructured data collections methods, such as observations, interviews, surveys and documents, to find themes and meanings to inform our understanding of the world. [1] X Trustworthy Source PubMed Central Journal archive from the U.S. National Institutes of Health Go to source Qualitative research tends to try to cover the reasons for behaviors, attitudes and motivations, instead of just the details of what, where and when. Qualitative research can be done across many disciplines, such as social sciences, healthcare and businesses, and it is a common feature of nearly every single workplace and educational environment.

Preparing Your Research

• The research questions is one of the most important pieces of your research design. It determines what you want to learn or understand and also helps to focus the study, since you can't investigate everything at once. Your research question will also shape how you conduct your study since different questions require different methods of inquiry.
• You should start with a burning question and then narrow it down more to make it manageable enough to be researched effectively. For example, "what is the meaning of teachers' work to teachers" is too broad for a single research endeavor, but if that's what you're interested you could narrow it by limiting the type of teacher or focusing on one level of education. For example, "what is the meaning of teachers' work to second career teachers?" or "what is the meaning of teachers' work to junior high teachers?"

Tip: Find the balance between a burning question and a researchable question. The former is something you really want to know about and is often quite broad. The latter is one that can be directly investigated using available research methods and tools.

• For example, if your research question focuses on how second career teachers attribute meaning to their work, you would want to examine the literature on second career teaching - what motivates people to turn to teaching as a second career? How many teachers are in their second career? Where do most second career teachers work? Doing this reading and review of existing literature and research will help you refine your question and give you the base you need for your own research. It will also give you a sense of the variables that might impact your research (e.g., age, gender, class, etc.) and that you will need to take into consideration in your own study.
• A literature review will also help you to determine whether you are really interested and committed to the topic and research question and that there is a gap in the existing research that you want to fill by conducting your own investigation.

For example, if your research question is "what is the meaning of teachers' work to second career teachers?" , that is not a question that can be answered with a 'yes' or 'no'. Nor is there likely to be a single overarching answer. This means that qualitative research is the best route.

• Consider the possible outcomes. Because qualitative methodologies are generally quite broad, there is almost always the possibility that some useful data will come out of the research. This is different than in a quantitative experiment, where an unproven hypothesis can mean that a lot of time has been wasted.
• Your research budget and available financial resources should also be considered. Qualitative research is often cheaper and easier to plan and execute. For example, it is usually easier and cost-saving to gather a small number of people for interviews than it is to purchase a computer program that can do statistical analysis and hire the appropriate statisticians.

• Action Research – Action research focuses on solving an immediate problem or working with others to solve problem and address particular issues. [7] X Research source
• Ethnography – Ethnography is the study of human interaction in communities through direct participation and observation within the community you wish to study. Ethnographic research comes from the discipline of social and cultural anthropology but is now becoming more widely used. [8] X Research source
• Phenomenology – Phenomenology is the study of the subjective experiences of others. It researches the world through the eyes of another person by discovering how they interpret their experiences. [9] X Research source
• Grounded Theory – The purpose of grounded theory is to develop theory based on the data systematically collected and analyzed. It looks at specific information and derives theories and reasons for the phenomena.
• Case Study Research – This method of qualitative study is an in-depth study of a specific individual or phenomena in its existing context. [10] X Research source

Collecting and Analyzing Your Data

• Direct observation – Direct observation of a situation or your research subjects can occur through video tape playback or through live observation. In direct observation, you are making specific observations of a situation without influencing or participating in any way. [12] X Research source For example, perhaps you want to see how second career teachers go about their routines in and outside the classrooms and so you decide to observe them for a few days, being sure to get the requisite permission from the school, students and the teacher and taking careful notes along the way.
• Participant observation – Participant observation is the immersion of the researcher in the community or situation being studied. This form of data collection tends to be more time consuming, as you need to participate fully in the community in order to know whether your observations are valid. [13] X Research source
• Interviews – Qualitative interviewing is basically the process of gathering data by asking people questions. Interviewing can be very flexible - they can be on-on-one, but can also take place over the phone or Internet or in small groups called "focus groups". There are also different types of interviews. Structured interviews use pre-set questions, whereas unstructured interviews are more free-flowing conversations where the interviewer can probe and explore topics as they come up. Interviews are particularly useful if you want to know how people feel or react to something. For example, it would be very useful to sit down with second career teachers in either a structured or unstructured interview to gain information about how they represent and discuss their teaching careers.
• Surveys – Written questionnaires and open ended surveys about ideas, perceptions, and thoughts are other ways by which you can collect data for your qualitative research. For example, in your study of second career schoolteachers, perhaps you decide to do an anonymous survey of 100 teachers in the area because you're concerned that they may be less forthright in an interview situation than in a survey where their identity was anonymous.
• "Document analysis" – This involves examining written, visual, and audio documents that exist without any involvement of or instigation by the researcher. There are lots of different kinds of documents, including "official" documents produced by institutions and personal documents, like letters, memoirs, diaries and, in the 21st century, social media accounts and online blogs. For example, if studying education, institutions like public schools produce many different kinds of documents, including reports, flyers, handbooks, websites, curricula, etc. Maybe you can also see if any second career teachers have an online meet group or blog. Document analysis can often be useful to use in conjunction with another method, like interviewing.

• Coding – In coding, you assign a word, phrase, or number to each category. Start out with a pre-set list of codes that you derived from your prior knowledge of the subject. For example, "financial issues" or "community involvement" might be two codes you think of after having done your literature review of second career teachers. You then go through all of your data in a systematic way and "code" ideas, concepts and themes as they fit categories. You will also develop another set of codes that emerge from reading and analyzing the data. For example, you may see while coding your interviews, that "divorce" comes up frequently. You can add a code for this. Coding helps you organize your data and identify patterns and commonalities. [15] X Research source tobaccoeval.ucdavis.edu/analysis-reporting/.../CodingQualitativeData.pdf
• Descriptive Statistics – You can analyze your data using statistics. Descriptive statistics help describe, show or summarize the data to highlight patterns. For example, if you had 100 principal evaluations of teachers, you might be interested in the overall performance of those students. Descriptive statistics allow you to do that. Keep in mind, however, that descriptive statistics cannot be used to make conclusions and confirm/disprove hypotheses. [16] X Research source
• Narrative analysis – Narrative analysis focuses on speech and content, such as grammar, word usage, metaphors, story themes, meanings of situations, the social, cultural and political context of the narrative. [17] X Research source
• Hermeneutic Analysis – Hermeneutic analysis focuses on the meaning of a written or oral text. Essentially, you are trying to make sense of the object of study and bring to light some sort of underlying coherence. [18] X Research source
• Content analysis / Semiotic analysis – Content or semiotic analysis looks at texts or series of texts and looks for themes and meanings by looking at frequencies of words. Put differently, you try to identify structures and patterned regularities in the verbal or written text and then make inferences on the basis of these regularities. [19] X Research source For example, maybe you find the same words or phrases, like "second chance" or "make a difference," coming up in different interviews with second career teachers and decide to explore what this frequency might signify.

Community Q&A

• Qualitative research is often regarded as a precursor to quantitative research, which is a more logical and data-led approach which statistical, mathematical and/or computational techniques. Qualitative research is often used to generate possible leads and formulate a workable hypothesis that is then tested with quantitative methods. [20] X Research source Thanks Helpful 0 Not Helpful 0
• Try to remember the difference between qualitative and quantitative as each will give different data. Thanks Helpful 4 Not Helpful 0

You Might Also Like

• ↑ https://www.ncbi.nlm.nih.gov/books/NBK470395/
• ↑ https://owl.purdue.edu/owl/research_and_citation/conducting_research/writing_a_literature_review.html
• ↑ https://academic.oup.com/humrep/article/31/3/498/2384737?login=false
• ↑ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4275140/
• ↑ http://www.qual.auckland.ac.nz/
• ↑ http://www.socialresearchmethods.net/kb/qualapp.php
• ↑ http://www.socialresearchmethods.net/kb/qualdata.php
• ↑ tobaccoeval.ucdavis.edu/analysis-reporting/.../CodingQualitativeData.pdf
• ↑ https://statistics.laerd.com/statistical-guides/descriptive-inferential-statistics.php
• ↑ https://explorable.com/qualitative-research-design

About This Article

To do qualitative research, start by deciding on a clear, specific question that you want to answer. Then, do a literature review to see what other experts are saying about the topic, and evaluate how you will best be able to answer your question. Choose an appropriate qualitative research method, such as action research, ethnology, phenomenology, grounded theory, or case study research. Collect and analyze data according to your chosen method, determine the answer to your question. For tips on performing a literature review and picking a method for collecting data, read on! Did this summary help you? Yes No

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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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How to do qualitative research?

Elaine denny.

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

Annalise Weckesser

Associated data.

Not applicable

Learning points

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

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

There are three main methods used in qualitative research.

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

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

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

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

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

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

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

CONFLICT OF INTEREST

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

AUTHOR CONTRIBUTION

Elaine Denny and Annalise Weckesser contributed equally to the paper.

USEFUL RESOURCES

Britten N. Qualitative research: qualitative interviews in medical research. BMJ 1995;311:251–3.

Kitzinger J. Qualitative research: introducing focus groups. BMJ 1995;311:229.

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Supporting information

Appendix S1

Appendix S2

Denny E, Weckesser A. How to do qualitative research? . BJOG . 2022; 129 :1166–1167. 10.1111/1471-0528.17150 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

DATA AVAILABILITY STATEMENT

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