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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.

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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.

Qualitative Research: Characteristics, Design, Methods & Examples

Lauren McCall

MSc Health Psychology Graduate

MSc, Health Psychology, University of Nottingham

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

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Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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

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

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

On This Page:

Qualitative research is a type of research methodology that focuses on gathering and analyzing non-numerical data to gain a deeper understanding of human behavior, experiences, and perspectives.

It aims to explore the “why” and “how” of a phenomenon rather than the “what,” “where,” and “when” typically addressed by quantitative research.

Unlike quantitative research, which focuses on gathering and analyzing numerical data for statistical analysis, qualitative research involves researchers interpreting data to identify themes, patterns, and meanings.

Qualitative research can be used to:

• Gain deep contextual understandings of the subjective social reality of individuals
• To answer questions about experience and meaning from the participant’s perspective
• To design hypotheses, theory must be researched using qualitative methods to determine what is important before research can begin. 

Examples of qualitative research questions include: 

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

Characteristics 

Naturalistic setting.

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

Naturalistic settings provide valuable contextual information to help researchers better understand and interpret the data they collect.

The environment, social interactions, and cultural factors can all influence behavior and experiences, and these elements are more easily observed in real-world settings.

Reality is socially constructed

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

The primacy of subject matter 

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

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

Variables are complex, interwoven, and difficult to measure

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

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

Emic (insider’s point of view)

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

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

Interpretive analysis

In qualitative research, interpretive analysis is crucial in making sense of the collected data.

This process involves examining the raw data, such as interview transcripts, field notes, or documents, and identifying the underlying themes, patterns, and meanings that emerge from the participants’ experiences and perspectives.

Collecting Qualitative Data

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

Observations

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

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

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

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

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

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

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

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

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

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

Focus groups 

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

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

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

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

Ethnography

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

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

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

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

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

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

Qualitative Data Analysis Methods

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

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

Grounded theory

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

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

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

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

Content analysis

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

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

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

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

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

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

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

Discourse analysis

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

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

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

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

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

Thematic analysis

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

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

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

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

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

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

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

Phases of Thematic Analysis

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

Template analysis

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

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

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

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

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

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

Frame analysis

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

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

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

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

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

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

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

Preventing Bias in Qualitative Research

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

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

Co-coding 

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

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

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

Member checking

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

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

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

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

Reflexivity in qualitative research

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

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

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

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

Reflexivity Example

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

Establishing Trustworthiness in Qualitative Research

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

1. Credibility in Qualitative Research

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

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

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

2. Transferability in Qualitative Research

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

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

3. Dependability in Qualitative Research

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

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

4. Confirmability in Qualitative Research

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

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

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

Audit Trails in Qualitative Research

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

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

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

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

Discovery of unexpected data

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

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

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

Flexibility

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

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

Naturalistic settings

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

Limitations

Time-consuming .

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

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

Subjectivity 

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

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

Limited generalizability

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

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

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

While individual qualitative studies are often limited in their generalizability due to factors such as sample size and context, metasynthesis enables researchers to synthesize findings from multiple studies, potentially leading to more generalizable conclusions.

By integrating findings from studies conducted in diverse settings and with different populations, metasynthesis can provide broader insights into the phenomenon of interest.

Extraneous variables

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

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

What sample size should qualitative research be?

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

Are surveys qualitative or quantitative?

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

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

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

What are the ethical considerations of qualitative research?

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

What is triangulation in qualitative research?

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

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

Why is qualitative research important?

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

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

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

What is coding data in qualitative research?

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

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

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

What is the difference between qualitative and quantitative research?

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

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

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

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

What is trustworthiness in qualitative research?

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

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

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

What is data saturation in qualitative research?

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

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

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

Why is sampling in qualitative research important?

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

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

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

What is narrative analysis?

Narrative analysis is a qualitative research method used to understand how individuals create stories from their personal experiences.

There is an emphasis on understanding the context in which a narrative is constructed, recognizing the influence of historical, cultural, and social factors on storytelling.

Researchers can use different methods together to explore a research question.

Some narrative researchers focus on the content of what is said, using thematic narrative analysis, while others focus on the structure, such as holistic-form or categorical-form structural narrative analysis. Others focus on how the narrative is produced and performed.

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A Guide to Field Notes for Qualitative Research: Context and Conversation

Affiliation.

• 1 1 Vanderbilt University School of Nursing, Nashville, Tennessee, USA.
• PMID: 29298584
• DOI: 10.1177/1049732317697102

Field notes are widely recommended in qualitative research as a means of documenting needed contextual information. With growing use of data sharing, secondary analysis, and metasynthesis, field notes ensure rich context persists beyond the original research team. However, while widely regarded as essential, there is not a guide to field note collection within the literature to guide researchers. Using the qualitative literature and previous research experience, we provide a concise guide to collection, incorporation, and dissemination of field notes. We provide a description of field note content for contextualization of an entire study as well as individual interviews and focus groups. In addition, we provide two "sketch note" guides, one for study context and one for individual interviews or focus groups for use in the field. Our guides are congruent with many qualitative and mixed methodologies and ensure contextual information is collected, stored, and disseminated as an essential component of ethical, rigorous qualitative research.

Keywords: field notes; qualitative research; research methods.

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Research Design Review

A discussion of qualitative & quantitative research design, contextual analysis: a fundamental attribute of qualitative research.

One of the 10 unique or distinctive attributes of qualitative research is contextual, multilayered analysis. This is a fundamental aspect of qualitative research and, in fact, plays a central role in the unique attributes associated with data generation, i.e., the importance of context, the importance of meaning, the participant-researcher relationship , and researcher as instrument —

“…the interconnections, inconsistencies, and sometimes seemingly illogical input reaped in qualitative research demand that researchers embrace the tangles of their data from many sources. There is no single source of analysis in qualitative research because any one research event consists of multiple variables that need consideration in the analysis phase. The analyzable data from an in-depth interview, for example, are more than just what was said in the interview; they also include a variety of other considerations, such as the context in which certain information was revealed and the interviewee–interviewer relationship.” (Roller & Lavrakas, pp. 7-8)

The ability — the opportunity — to contextually analyze qualitative data is also associated with basic components of research design, such as sample size and the risk of relying on saturation which “misguides the researcher towards prioritizing manifest content over the pursuit of contextual understanding derived from latent, less obvious data.” And the defining differentiator between a qualitative and quantitative approach, such as qualitative content analysis in which it is “the inductive strategy in search of latent content, the use of context, the back-and-forth flexibility throughout the analytical process, and the continual questioning of preliminary interpretations that set qualitative content analysis apart from the quantitative method.”

There are many ways that context is integrated into the qualitative data analysis process to ensure quality analytical outcomes and interpretations . Various articles in Research Design Review have discussed contextually grounded aspects of the process, such as the following (each header links to the corresponding RDR article).

Unit of Analysis

“Although there is no perfect prescription for every study, it is generally understood that researchers should strive for a unit of analysis that retains the context necessary to derive meaning from the data. For this reason, and if all other things are equal, the qualitative researcher should probably err on the side of using a broader, more contextually based unit of analysis rather than a narrowly focused level of analysis (e.g., sentences).”

Meaning of Words

“How we use our words provides the context that shapes what the receiver hears and the perceptions others associate with our words. Context pertains to apparent as well as unapparent influences that take the meaning of our words beyond their proximity to other words [or] their use in recognized terms or phrases…”

Categorical Buckets

“No one said that qualitative data analysis is simple or straightforward. A reason for this lies in the fact that an important ingredient to the process is maintaining participants’ context and potential multiple meanings of the data. By identifying and analyzing categorical buckets, the researcher respects this multi-faceted reality and ultimately reaps the reward of useful interpretations of the data.”

Use of Transcripts

“Although serving a utilitarian purpose, transcripts effectively convert the all-too-human research experience that defines qualitative inquiry to the relatively emotionless drab confines of black-on-white text. Gone is the profound mood swing that descended over the participant when the interviewer asked about his elderly mother. Yes, there is text in the transcript that conveys some aspect of this mood but only to the extent that the participant is able to articulate it.”

Use of Recordings

“Unlike the transcript, the recording reminds the researcher of how and when the atmosphere in the [focus] group environment shifted from being open and friendly to quiet and inhibited; and how the particular seating arrangement, coupled with incompatible personality types, inflamed the atmosphere and seriously colored participants’ words, engagement, and way of thinking.”

Roller, M. R., & Lavrakas, P. J. (2015). Applied qualitative research design: A total quality framework approach . New York: Guilford Press.

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

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

Characteristics of Qualitative Research

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

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

The Collection of Data

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

The Analysis

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

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

Basic Research Design for Qualitative Studies

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

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

Strengths of Using Qualitative Methods

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

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

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

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

Limitations of Using Qualitative Methods

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

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

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

Research Tip

Human Subject Research and Institutional Review Board Approval

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

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

Another Research Tip

Finding Examples of How to Apply Different Types of Research Methods

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

SAGE Research Methods Online and Cases

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

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

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What is Qualitative Research? Methods and Examples

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Qualitative research seeks to gain insights and understand people’s experiences and perspectives by studying social organizations and human behavior. Data in qualitative studies focuses on people’s beliefs and emotional responses. Qualitative data is especially helpful when a company wants to know how customers feel about a product or service, such as in user experience (UX) design or marketing . 

In this guide, we’ll go over:

Qualitative Research Definition

Qualitative research methods and examples, advantages and disadvantages of qualitative approaches, qualitative vs. quantitative research, showing qualitative research skills on resumes.

Researchers use qualitative approaches to “determine answers to research questions on human behavior and the cultural values that drive our thinking and behavior,” says Margaret J. King, director at The Center for Cultural Studies & Analysis in Philadelphia.

Data in qualitative research typically can’t be assessed mathematically — the data is not sets of numbers or quantifiable information. Rather, it’s collections of images, words, notes on behaviors, descriptions of emotions, and historical context. Data is collected through observations, interviews, surveys, focus groups, and secondary research. 

However, a qualitative study needs a “clear research question at its base,” notes King, and the research needs to be “observed, categorized, compared, and evaluated (along a scale or by a typology chart) by reference to a baseline in order to determine an outcome with value as new and reliable information.”

Who Uses Qualitative Research?

Researchers in social sciences and humanities often use qualitative research methods, especially in specific areas of study like anthropology, history, education, and sociology. 

Qualitative methods are also applicable in business, technology , and marketing spaces. For example, product managers use qualitative research to understand how target audiences respond to their products. They may use focus groups to gain insights from potential customers on product prototypes and improvements or surveys from existing customers to understand what changes users want to see. 

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Grounded Theory

Grounded theory is an inductive approach to theory development. In many forms of research, you begin with a hypothesis and then test it to see if you’re correct. In grounded theory, though, you go in without any assumptions and rely on the data you collect to form theories. You start with an open question about a phenomenon you are studying and collect and analyze data until you can form a fully-fledged theory from the information. 

Example: A company wants to improve its brand and marketing strategies. The company performs a grounded theory approach to solving this problem by conducting interviews and surveys with past, current, and prospective customers. The information gathered from these methods helps the company understand what type of branding and marketing their customer-base likes and dislikes, allowing the team to inductively craft a new brand and marketing strategy from the data. 

Action Research

Action research is one part study and one part problem-solving. Through action research, analysts investigate a problem or weakness and develop practical solutions. The process of action research is cyclical —- researchers assess solutions for efficiency and effectiveness and create further solutions to correct any issues found. 

Example: A manager notices her employees struggle to cooperate on group projects. She carefully reviews how team members interact with each other and asks them all to respond to a survey about communication. Through the survey and study, she finds that guidelines for group projects are unclear. After changing the guidelines, she reviews her team again to see if there are any changes to their behavior.  

>>MORE: Explore how action research helps consultants serve clients with Accenture’s Client Research and Problem Identification job simulation .

Phenomenological Research

Phenomenological research investigates a phenomenon in depth, looking at people’s experiences and understanding of the situation. This sort of study is primarily descriptive and seeks to broaden understanding around a specific incident and the people involved. Researchers in phenomenological studies must be careful to set aside any biases or assumptions because the information used should be entirely from the subjects themselves. 

Example : A researcher wants to better understand the lived experience of college students with jobs. The purpose of this research is to gain insights into the pressures of college students who balance studying and working at the same time. The researcher conducts a series of interviews with several college students, learning about their past and current situations. Through the first few interviews, the researcher builds a relationship with the students. Later discussions are more targeted, with questions prompting the students to discuss their emotions surrounding both work and school and the difficulties and benefits arising from their situation. The researcher then analyzes these interviews, and identifies shared themes to contextualize the experiences of the students. 

Ethnography

Ethnography is an immersive study of a particular culture or community. Through ethnographic research, analysts aim to learn about a group’s conventions, social dynamics, and cultural norms. Some researchers use active observation methods, finding ways to integrate themselves into the culture as much as possible. Others use passive observation, watching closely from the outside but not fully immersing themselves. 

Example: A company hires an external researcher to learn what their company’s culture is actually like. The researcher studies the social dynamics of the employees and may even look at how these employees interact with clients and with each other outside of the office. The goal is to deliver a comprehensive report of the company’s culture and the social dynamics of its employees. 

Case Studies

A case study is a type of in-depth analysis of a situation. Case studies can focus on an organization, belief system, event, person, or action. The goal of a case study is to understand the phenomenon and put it in a real-world context. Case studies are also commonly used in marketing and sales to highlight the benefits of a company’s products or services. 

Example: A business performs a case study of its competitors’ strategies. This case study aims to show why the company should adopt a specific business strategy. The study looks at each competitor’s business structure, marketing campaigns, product offerings, and historical growth trends. Then, using this data on other businesses, the researcher can theorize how that strategy would benefit their company. 

>>MORE: Learn how companies use case study interviews to assess candidates’ research and problem-solving skills. 

Qualitative research methods are great for generating new ideas. The exploratory nature of qualitative research means uncovering unexpected information, which often leads to new theories and further research topics. Additionally, qualitative findings feel meaningful. These studies focus on people, emotions, and societies and may feel closer to their communities than quantitative research that relies on more mathematical and logical data. 

However, qualitative research can be unreliable at times. It’s difficult to replicate qualitative studies since people’s opinions and emotions can change quickly. For example, a focus group has a lot of variables that can affect the outcome, and that same group, asked the same questions a year later, may have entirely different responses. The data collection can also be difficult and time-consuming with qualitative research. Ultimately, interviewing people, reviewing surveys, and understanding and explaining human emotions can be incredibly complex. 

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While qualitative research deals with data that isn’t easily manipulated by mathematics, quantitative research almost exclusively involves numbers and numerical data. Quantitative studies aim to find concrete details, like units of time, percentages, or statistics. 

Besides the types of data used, a core difference between quantitative and qualitative research is the idea of control and replication. 

“Qualitative is less subject to control (as in lab studies) and, therefore, less statistically measurable than quantitative approaches,” says King.

One person’s interview about a specific topic can have completely different responses than every other person’s interview since there are so many variables in qualitative research. On the other hand, quantitative studies can often be replicated. For instance, when testing the effects of a new medication, quantifiable data, like blood test results, can be repeated. Qualitative data, though, like how people feel about the medication, may differ from person to person and from moment to moment. 

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You can show your experience with qualitative research on your resume in your skills or work experience sections and your cover letter . 

In your skills section, you can list types of qualitative research you are skilled at, like conducting interviews, performing grounded theory research, or crafting case studies. 

You can highlight specific examples in the description of your past work or internship experiences. For example, you can talk about a time you used action research to solve a complex issue at your last job. 

Your cover letter is an excellent place to discuss in-depth qualitative research projects you’ve completed. For instance, say you spent a summer conducting ethnographic research or a whole semester running focus groups to get feedback on a product. You can talk about these experiences in your cover letter and note how these skills make you a great fit for the job. 

Grow your skills and explore your career options with Forage’s free job simulations . 

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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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• ROBVALU: a tool for...

ROBVALU: a tool for assessing risk of bias in studies about people’s values, utilities, or importance of health outcomes

• Related content
• Peer review
• Samer G Karam , doctoral student 1 2 ,
• Yuan Zhang , assistant clinical professor 1 2 ,
• Hector Pardo-Hernandez , researcher 3 4 ,
• Uwe Siebert , professor 5 6 7 ,
• Laura Koopman , senior adviser 8 ,
• Jane Noyes , professor 9 ,
• Jean-Eric Tarride , professor 1 10 11 ,
• Adrienne L Stevens , manager 12 ,
• Vivian Welch , senior investigator 13 ,
• Zuleika Saz-Parkinson , project adviser 14 ,
• Brendalynn Ens , director (retired) 15 ,
• Tahira Devji , medical student 16 ,
• Feng Xie , professor 1 10 ,
• Glen Hazlewood , associate professor 17 18 ,
• Lawrence Mbuagbaw , associate professor 1 19 20 21 22 23 ,
• Pablo Alonso-Coello , senior researcher 3 4 24 ,
• Jan L Brozek , associate professor 1 2 ,
• 1 Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada
• 2 Michael G DeGroote Cochrane Canada and McMaster GRADE Centres, McMaster University, Hamilton, ON, Canada
• 3 Iberoamerican Cochrane Centre, Sant Antoni Maria Claret, Barcelona, Spain
• 4 Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
• 5 Department of Public Health, Health Services Research and Health Technology Assessment, Institute of Public Health, Medical Decision Making and Health Technology Assessment, UMIT TIROL-University for Health Sciences and Technology, Hall in Tirol, Austria
• 6 Center for Health Decision Science and Departments of Epidemiology and Health Policy and Management, Harvard T H Chan School of Public Health, Boston, MA, USA
• 7 Institute for Technology Assessment and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
• 8 Department of Specialist Medical Care, National Health Care Institute, Diemen, Netherlands
• 9 School of Medical and Health Sciences, Bangor University, Wales, UK
• 10 Centre for Health Economics and Policy Analysis, McMaster University Faculty of Health Sciences, Hamilton, ON, Canada
• 11 Programs for Assessment of Technologies in Health, St Joseph’s Healthcare Hamilton, Hamilton, ON, Canada
• 12 Centre for Immunisation Programmes, Public Health Agency of Canada, ON, Canada
• 13 Bruyère Research Institute and, School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
• 14 European Commission, Joint Research Centre, Ispra, Italy
• 15 Implementation Support and Knowledge Mobilisation, Canadian Agency for Drugs and Technologies in Health, Ottawa, ON, Canada
• 16 Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
• 17 Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
• 18 Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
• 19 Department of Anaesthesia, McMaster University, Hamilton, ON, Canada
• 20 Department of Paediatrics, McMaster University, Hamilton, ON, Canada
• 21 Biostatistics Unit, Father Sean O’Sullivan Research Centre, St Joseph’s Healthcare, Hamilton, ON, Canada
• 22 Centre for Development of Best Practices in Health, Yaoundé Central Hospital, Yaoundé, Cameroon
• 23 Division of Epidemiology and Biostatistics, Department of Global Health, Stellenbosch University, Cape Town, South Africa
• 24 Institut de Recerca Sant Pau (IR SANT PAU), Sant Quintí, Barcelona, Spain
• 25 Clinical Epidemiology and Research Centre (CERC), Humanitas University and Humanitas Research Hospital, Via Rita Levi Montalcini 4, 20090 Pieve Emanuele, Milan, Italy
• Correspondence to: H J Schünemann schuneh{at}mcmaster.ca
• Accepted 9 April 2024

People’s values are an important driver in healthcare decision making. The certainty of an intervention’s effect on benefits and harms relies on two factors: the certainty in the measured effect on an outcome in terms of risk difference and the certainty in its value, also known as utility or importance. The GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) working group has proposed a set of questions to assess the risk of bias in a body of evidence from studies investigating how people value outcomes. However, these questions do not address risk of bias in individual studies that, similar to risk-of-bias tools for other research studies, is required to evaluate such evidence. Thus, the Risk of Bias in studies of Values and Utilities (ROBVALU) tool was developed. ROBVALU has good psychometric properties and will be useful when assessing individual studies in measuring values, utilities, or the importance of outcomes. As such, ROBVALU can be used to assess risk of bias in studies included in systematic reviews and health guidelines. It also can support health research assessments, where the risk of bias of input variables determines the certainty in model outputs. These assessments include, for example, decision analysis and cost utility or cost effectiveness analysis for health technology assessment, health policy, and reimbursement decision making.

Healthcare decision making relies on evidence on the relative effectiveness, safety, and cost effectiveness of an intervention evaluated in appropriate studies. 1 2 Choosing between different interventions (such as preventive, diagnostic, or treatment strategies) depends on the importance or value that people place on specific health states or health outcomes. 2 Values have a major role at different levels of decision making, from the individual level to the healthcare system level. In this context, people’s values reflect the importance they place on outcomes of interest that result from decisions about using an intervention—for example, taking a certain test or starting a new treatment regimen. 2 We use the term “people” when talking about value because the term is inclusive to patients, healthcare providers, policy makers, and the general public.

Utility instruments are widely used to elicit the absolute value of a health outcome, and provide an index measure anchored on a scale with 1 reflecting perfect health and 0 reflecting being dead. 3 4 Various methods are used to establish values, including direct measures of utility, indirect measurements of utility, or qualitative research. 2 5 The visual analogue scale (VAS) is one of the simplest measures to elicit these values. People are asked to rate a health state on a VAS that is then converted to a utility value. 6 7 While the scale directly measures the importance of an outcome, concerns exist about how accurate and valid it might be. 2 Other direct measures such as the standard gamble and time trade-off require people to choose between their current health state and a treatment option that could result in perfect health or in immediate death. 4 8 Discrete choice experiments ask people to choose between two or more treatment options where the choices differ in terms of their attributes, that are defined by the investigators. 9 The relative importance of each attribute is then inferred by analysing the responses, assuming that patients choose the option with the highest value. 9 Indirect methods of measuring utility values include validated, health related, quality-of-life instruments, such as the EQ-5D and the Health Utilities Index. 10 The EQ-5D requires respondents to answer questions across five domains that are converted to a utility value using validated scoring systems. 11 12

Summary points

Assessing the risk of bias in individual studies is an essential step to determine overall certainty of evidence in a systematic review or health technology assessment and for guideline development

The Risk of Bias in Values and Utilities (ROBVALU) tool assesses risk of bias in quantitative studies of people’s values, utilities, or importance of outcomes

A sequential mixed methods approach was used to develop ROBVALU, initially based on signalling questions and subdomains developed by the GRADE working group to assess risk of bias; a modified Delphi approach was used for final refinement of the tool

ROBVALU covers four separate subdomains through which bias might be introduced; individual subdomain judgments inform the overall risk of bias of studies

ROBVALU has demonstrated high validity and reliability

General application of utility values in research

These utility values allow researchers to weigh the benefits and harms of an option and, thus, they also are important in health economics and health technology assessments. 3 13 For instance, in decision analysis, they are required to calculate quality adjusted life years. Confidence in studies that report on values needs to be ascertained for decision making in guideline recommendations, health technology assessments, or coverage decision. 14 For example, in a systematic review on people with chronic obstructive pulmonary disease, we found moderate certainty that patients value adverse events as important, but on average valued them as less important than symptom relief. 15 We also found moderate certainty that exacerbation and hospital admission owing to exacerbation are the outcomes that patients with chronic obstructive pulmonary disease rate as most important. In another example, a systematic review on patients’ values on venous thromboembolism, we found that people with cancer placed more importance on a reduction in new or recurrent venous thromboembolism than on a decrease in major or minor bleeding events. 16

The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) Evidence to Decision frameworks is a widely used approach in guidelines, health technology assessment, and other decisions. The frameworks require judgments about the certainty in how much people value the main outcomes: “Is there important uncertainty about . . . how much people value the main outcomes?” 17 18 A key determinant of certainty is internal validity—that is, how well individual studies were designed and conducted (ie, internal validity, which GRADE and Cochrane label as the risk-of-bias (ROB) domain).

Risk of bias

Similar to other study designs, threats to internal validity arising from the study design, conduct, analysis, and reporting of the study introduce ROB in research on utility values. 2 Poor study quality could result in indirectness which encompasses applicability and external validity, often as a result of PICO (patient/population, intervention, comparison, and outcomes) elements. Another quality issue is low sample size or no sample size calculation, which could result in imprecision. ROB assessment tools are developed to assess biases that result in threats of internal validity and would not measure indirectness and precision. Quality assessment tools and reporting checklists often include all factors of a study’s qualities and safeguards, but these tools differ from a ROB assessment tool that aims to present a ROB judgment for a study. A key factor that might introduce bias in values studies is the instrument used to measure utilities of the people in the study. Bias means that a value people place on an outcome in a research study (eg, a value of 0.5 for stroke) would be systematically different from the true value that people would place on that outcome. For example, the true unbiased value might be 0.3 and, thus, use of biased estimates would provide inaccurate answers in the modelling and health decision making context.

ROB assessment tools exist for many study designs, including the Cochrane Risk of Bias 2 (RoB 2) for randomised trials, 19 ROBINS-I for non-randomised studies of the effects of interventions, 20 and ROBINS-E for studies about exposures. 21 22 Critical appraisal tools to assess the quality of a study are also study design specific, such as the Newcastle-Ottawa scale and the Joanna Briggs Institute’s critical appraisal tool for cross sectional studies. 23 24 These tools are regularly used by researchers to assess the quality of individual studies or to assess ROB, but they were not developed for studies on utility values. These checklists invariably include questions specific to the study design, which would not always be appropriate to answer in studies about people’s values (eg, “Were there deviations from the intended intervention that arose because of the trial context?” or “Was the exposure measured in a valid and reliable way?”). 19 21 22 For studies on utility values, a major concern that is not adequately addressed by any commonly used ROB tool is the method used to elicit people’s values. The measurement instrument needs to be valid and reliable, be used appropriately, use valid health outcomes, and explore proper understanding of the instrument. No validated tool is available for the nuanced assessment of ROB in individual studies measuring utility values. 9 20 25 26

To properly implement evidence based decision making and formulate evidence based recommendations in clinical or public health guidelines, evaluation of ROB is crucial in studies of values, utilities, or importance of outcomes. However, owing to the absence of specialised and validated tools to assess ROB, this evaluation is rarely done. Thus, our goal was to develop, validate, and describe a pragmatic tool for studies measuring the value people place on health outcomes with appropriate guidance to apply it correctly.

Development of the ROBVALU tool and guidance

We used a sequential, mixed methods approach to develop ROBVALU and related guidance document (supplement S1), 27 starting with a qualitative approach and followed by a quantitative phase to assess the psychometric properties of the tool ( fig 1 ). In the qualitative phase, we first considered the ROB signalling questions (appendix table A1) and subdomains that we had developed for GRADE guidance to assess ROB about values across studies in a body of evidence. 2 For that GRADE guidance, we iteratively developed the subdomains and signalling questions starting with a list of 23 items identified as part of a systematic survey project. 26 The core research group reviewed the 23 items to identify any missing item that might be relevant for the single study ROBVALU tool. After thorough group discussions, a decision was made not to add any new items or subdomains to avoid complexity, thereby improving applicability, feasibility, and adoption of the tool.

Tool development process for the Risk of Bias in Values and Utilities (ROBVALU) tool. GRADE=Grading of Recommendations, Assessment, Development, and Evaluation

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We first structured a preliminary version of the tool and added simple considerations to help answer the signalling questions. These signalling questions were categorised into four subdomains: selection of participants into the study, completeness of data, measurement instrument, and data analysis. We used a 4 point, Likert-type scale (ie, yes, probably yes, probably no, no) to judge the individual items, to avoid a neutral option of a 5 point Likert scale when studies lack sufficient information to make a proper judgment. In each subdomain, the tool asked how important and how serious the ROB issue is. The core research group iteratively revised the tool and accompanying guidance document. An advisory group of experts provided feedback and suggested appropriate changes to establish face and content validity (supplement S2).

Participant testing

We used purposeful sampling to recruit 15 participants with experience in critical appraisal, systematic reviews, or guidelines for user testing and semi-structured interviews (supplement S3). The participants had a broad level of expertise, from masters level students to senior researchers with experience in health research ranging from six months to 30 years (appendix table A2). All users received the ROBVALU tool and the accompanying guidance document (supplement S1). We instructed the participants to complete three to four assessments and every sample study was assessed by four users independently, 11 studies in total were assessed (appendix table A3). Based on feedback received in the semi-structured interview after user testing, we iteratively revised and improved the guidance document throughout the project with a focus on the wordings, spelling, and grammatical structure of the guidance document. The ROBVALU tool demonstrated good psychometric properties with an overall intraclass correlation coefficient of 0.87 and the four subdomains showed good to excellent reliability ranging from 0.80 to 0.91 ( table 1 and supplement S4). We also calculated the inter-rater reliability of the global ROB judgment using the ROBVALU tool with Kendall’s W, which showed substantial agreement of 0.62 (supplement S4). We invited four expert participants in the field to provide a global judgment for ROB without using the ROBVALU, with each expert rating three to four studies. When we added expert participant responses of the global ROB judgment, the Kendall’s W dropped to 0.45, showing moderate agreement (supplement S4). However, only four global judgment responses were more than one level of seriousness higher or lower than the expert participant judgment (appendix table A4).

Reliability of the Risk of Bias in Values and Utilities (ROBVALU) tool. CI=confidence interval

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Modified Delphi process

Finally, following our protocol, we used purposeful sampling to invite 20 experts in values, utilities, health technology assessment, and health decision science to participate in a modified Delphi process for final refinement of the tool (supplement S5, fig S8). 28 29 30 We used our extensive network of global colleagues working in the field of study to identify and invite the expert panel. Ten voting members accepted the invite to participate in the Delphi panel, and four members of the working group participated as non-voting members. We shared the ROBVALU tool draft, guidance document, and results of our participant testing with the panel members.

The first round of the Delphi process involved an anonymous survey to determine the signalling questions to be included. The second round took place via recorded video conferences with the aim of identifying common themes and reaching consensus on simplifying and harmonising language across the tool. The third and final round of the Delphi process included an anonymous survey for final consensus on the wording of the signalling questions and the proposed methods for providing a global ROB judgment. We used Google forms to prepare the surveys; the first survey used a 7 point Likert scale (ie, strongly agree, agree, somewhat agree, neutral, somewhat agree, disagree, and strongly disagree) to rate each item, with 70% agreement set as the cut-off threshold to retain or remove a signalling question. The final survey used a 3 point scale (ie, agree, neutral, and disagree) with a 70% agreement set as the cut-off threshold to retain the signalling question.

We had a 100% response rate in the first round of the Delphi process, with 80-100% consensus to retain all signalling questions. We also collected feedback from open ended questions for suggested edits for the signalling questions (supplement S6). In the second round of the Delphi process, we presented the ROBVALU tool, psychometric properties, exploratory factor analysis, and results of the first round of the Delphi to the panel members. After deliberating on the tool’s properties, agreement was reached to edit some signalling questions to simplify the language or to harmonise the language across the tool, which resulted in minor changes only. We also discussed how to make a final judgment for ROB for a study.

We had a 100% response rate in the third and final Delphi round, with 80-100% consensus on the tool’s signalling questions, including those with minor adjustments to the wording. We also established a consensus of >70% that the overall ROB judgment should match the most severe ROB judgment on an item, unless appraisers can provide justifications to rate the overall ROB lower (eg, many concerns on many items) or higher (eg, concern seems not to have an important influence on overall ROB). For example, if multiple subdomains were rated as very serious, the final judgment could be rated as extremely serious (supplement S7).

Risk-of-bias subdomains

ROBVALU includes seven key signalling questions across four subdomains: selection of participants into the study, completeness of data, measurement instrument, and data analysis ( table 2 ).

Subdomains and considerations in the Risk of Bias in Values and Utilities (ROBVALU) tool

Selection of participants into the study

Precise research questions include a clear definition of the target population. The study population of any empirical study must be representative for this target population, and is therefore, a critical component because bias in the selection will lead to biased estimates of the values people place on outcomes in the target population. 2 When assessing selection bias, users should consider the study’s sampling strategy, in particular if the achieved sample population deviates from the intended sample population, 2 because this might lead to biased estimates for the study’s population of interest owing to threats to internal validity. If the achieved sample population does not deviate from the intended sample population but differs from the population researchers intend to extrapolate the results to, this difference will result in a lack of generalisability. We refer to this lack of generalisability as indirectness, which encompasses applicability and external validity. The ROBVALU tool is not intended to deal with indirectness, a different domain in assessing the certainty of a body of evidence according to GRADE, but we are developing a tool that is specific to indirectness separately.

Completeness of data

When judging completeness of data, reviewers need to consider the response rate of the study population, the attrition rate if follow-up was involved, and the differential responders compared with non-responders. 2 High response rates and low proportion of loss to follow-up are clearly preferable, and a high proportion of non-response or dropout rates could be problematic. 2 Participants providing responses could plausibly differ from those who do not, and researchers should consider that results coming only from those participants who responded or completed follow-up might be misleading. 2

Measurement instrument

Reliable and valid instruments should be used to measure the relative importance of outcomes in values, preferences, and utility studies. 2 Using unreliable or poorly validated instruments can result in biased measurements of the outcome. Similarly, utility values for specific health states based on instruments not sufficiently validated that are used as input parameters for decision analytical models can result in biased estimates, such as quality adjusted life years derived from state transition models. 31 32 Researchers conducting primary empirical studies should provide information regarding the measurement properties of their chosen instrument. 2

Researchers should also demonstrate that the instrument has been used correctly and in a consistent manner across all participants in a study. For example, if the standard gamble is to be administered by an interviewer, but a subset of participants used self-administration, this could result in biased utility estimates that could be due to systematic differences between the two groups. In addition, an optimal representation of the outcome or health state should be presented or described in a way that accurately reflects the attribute the researchers intended to measure. This information could include a detailed explanation of how the outcome defines the experience, the probability of the outcome, durations, and possible consequences. Finally, researchers should evaluate whether participants had a proper understanding of the instrument to complete the tasks.

Data analysis

Studies should explore heterogeneity in values when appropriate and present results for the different subgroups. The data analysis plan and exploration of heterogeneity should be outlined a priori before collection of data. A causal framework that helps delineate health state and outcome interactions with possible confounding factors will help make assumptions explicit. If heterogeneity is found, the evaluator needs to consider whether the adjustment, stratification, or model selection used in the study reporting on values was appropriate. 2 Adjusting for important confounding factors (such as age if it is associated with the intervention and influences the estimated values) or reporting values in a stratified manner reduces biased estimates of the value placed on an outcome. In addition, self-inflicted biases, including selection bias or immortal time bias should be controlled for appropriately using modern causal inference methods (eg, target trial emulation or g methods for time varying confounding). 33

ROBVALU tool application

The assessment of ROB in studies evaluating the value people place on outcomes follows seven steps:

Specify the research or review question.

Specify the outcome being assessed.

Identify the sampling frame, the response rate and/or attrition rate, the measurement instrument used, and the data analysis plan.

Answer the signalling questions of the four subdomains.

Make a judgment if the four subdomains have important ROB concerns.

Formulate a ROB judgment for the four subdomains.

Formulate an overall ROB judgment for the study outcome being assessed.

The ROBVALU tool (supplement S8) provides users with space to record vital information of the study being assessed, and signalling questions to all four subdomains that must be answered. We validated a 4 point Likert-type scale (yes, probably yes, probably no, no) to respond to the individual signalling questions (items). When rating individual signalling questions, we suggest following the flowchart in figure 2 for consistent answers between raters. In each subdomain, the tool asks to specify how important the ROB issue is on a 4 point Likert-type scale (yes, probably yes, probably no, no), and how serious the overall ROB issue is on a 4 point Likert-type scale (not serious, serious, very serious, extremely serious). Responses to the signalling questions should provide the basis for the subdomain level judgment, of how important and how serious the ROB issues are in the study. Raters should provide a rationale for the response as free text, to justify their judgments. We suggest that the final judgment for each subdomain inversely correlates with the signalling question judgment. For example, in the measurement instrument subdomain, if the answer to “Was the instrument administered in the intended way?” was “No,” then the answer to “Are there important risk of bias issues concerning the measurement instruments?” should be “Yes.” If raters believe that the lowest signalling question judgment does not reflect the overall subdomain judgment, they might choose not to deem the results of the study at ROB for that subdomain, but they are asked to provide explanations for why they would not do this.

Rating individual signalling questions in the Risk of Bias in Values and Utilities (ROBVALU) tool

The global ROB judgment for a study corresponds to the lowest subdomain judgment ( table 3 ), because any domain level bias will lower our confidence in the study results. If users do not believe that the lowest subdomain judgment reflects the global ROB judgment, they should provide a justification. For example, if a study has a low response rate resulting in very serious ROB domain judgment and the study results are comparable to better quality studies, a reviewer might consider that the subdomain judgment does not reflect the global ROB judgment. Box 1 presents an illustrative example of a completed assessment (supplement S9).

Response options for judgments on risk of bias at an overall study level, according to the Risk of Bias in Values and Utilities (ROBVALU) tool

Example application of the Risk of Bias in Values and Utilities (ROBVALU) tool to assess risk of bias in values assigned to exacerbation of chronic obstructive pulmonary disease 34

In a study of 65 men and women with chronic obstructive pulmonary disease, researchers assessed the utility value that participants placed on an exacerbation, at seven study sites in the US when they visited an outpatient clinic within 48 hours of symptom onset. 34 Eligible participants were at least 40 years old and were current or former smokers with a history of at least 10 pack years. Of 65 participants, 59 completed the study, three were lost to follow-up, and three were ineligible. Utility values were measured using the EQ-5D.

An assessment using the ROBVALU tool revealed the following (supplement 9):

Selection of participants into the study would likely lead to risk of bias.

Exacerbations that required hospital admission were considered severe and were excluded from this study and might importantly bias the estimates. Thus, the population was deemed to be probably not representative of the intended population.

Completeness of data was present:

Only three patients were lost to follow-up, which did not cause risk of bias.

Measurement instrument caused some concern about risk of bias:

It was not clear whether the instrument was used in a valid and reliable manner, but it was applied in the intended way using a valid representation of the outcome. Patients also appeared to show an understanding of the instrument that was used and did not encounter difficulties, but this was not reported.

Data analysis did not cause concern for risk of bias:

Adjustment, stratification, and model selection was appropriate based on a plan created a priori.

ROBVALU assessment

Overall risk of bias was deemed serious because of issues related to the selection of participants into the study and the way the measurement instrument was used.

We have developed and validated the ROBVALU tool, a new instrument to assess ROB in studies measuring the value, utility, or relative importance that people place on health outcome. We followed a sequential mixed methods approach, by first adapting the signalling questions from the GRADE guidance for judging ROB across studies. ROBVALU differs from existing GRADE guidance by specifically assessing ROB in individual studies as opposed to across studies. 2 We iteratively revised the tool with our core group and an advisory group. The final draft tool contains 15 items in four subdomains: selection of participants, completeness of data, measurement instrument, and data analysis. We conducted a validation exercise with 15 participants that showed good reliability. Additional refinement using a modified Delphi process established construct validity on the final content of the tool.

Strengths and limitations

Assessing ROB is an essential step to assess the overall certainty of the evidence in a systematic review or health technology assessment and to develop a guideline. This assessment has often relied on adapting ROB tools not specifically designed for this type of research. 26 However, the lack of validation could lead to unreliable certainty of the evidence assessments, both for single studies and for a body of evidence. By using ROBVALU, evaluators can incorporate the ROB assessment into their meta-analysis, such as performing a sensitivity analysis to evaluate how studies with higher ROB might affect the study’s conclusion or primary outcomes. An advantage of the ROBVALU tool is the use of standardised GRADE terminology and judgments to facilitate assessment when establishing the certainty of the evidence. The ROBVALU tool can also be used to assess ROB in all elicitation studies of values, utilities, and importance of outcomes that use discrete choice, ranking, indifference, and rating methods. 35 Finally, the tool can be used in individual studies that use indirect methods to elicit people’s preferences, such as quality of life and EQ-5D scores.

This study and the derived tool also has several limitations. The new tool focuses on assessing values quantitively. For any given intervention, there is usually qualitative literature exploring what patients want to achieve and what they value (or not) from interventions; this information could be important for decision making. While some of the signalling questions might be used for qualitative studies, other signalling questions will not apply. Further exploration with qualitative studies should be performed to assess how ROBVALU can be adapted for that particular use, or whether a different tool is required. Furthermore, an exploratory factor analysis showed that one item in the tool had relatively poor fit (Was a valid representation of the outcome (health state) used?), but this poor fit could be due to the relatively small sample size. However, we retained this item because of feedback from the Delphi panel, who deemed it important. External validation of ROBVALU’s reliability by different users and on different studies will help refine the guidance and the tool.

Future implications

ROBVALU allows researchers to appraise individual studies reporting utilities, values, or the importance of outcomes for risk of bias. For example, in health technology assessments, the certainty of input variables from an individual study determines the certainty of outputs from decision analytical models (eg, cost utility and cost effectiveness analyses). 32 36 ROBVALU should also help with evaluating ROB as part of a systematic review, health technology assessment, or formal health guideline, to develop recommendations and make judgments across the overall body of this type of evidence (eg, assessing overall certainty of the evidence when following the GRADE approach).

Ethics statements

Ethical approval.

This international study was designed and coordinated at McMaster University after approval by the Hamilton Integrated Research Ethics Board (project ID 5634), and interviews and meetings were conducted in person or over video conference. All participants provided informed consent.

Contributors: The authors are epidemiologists, statisticians, systematic reviewers, and health services researchers, many of whom are involved with methods research and GRADE. Development of ROBVALU was informed by GRADE guideline 19, previously published tools for assessing risk of bias in intervention studies, systematic reviews of available tools to assess risk of bias in values and preferences, and the authors’ experience of developing similar tools to assess risk of bias. All authors contributed to development of the ROBVALU tool and to writing associated guidance. SGK, YZ, JLB, and HJS designed the study and formed the core group. YZ, JLB, and HJS conceived of the project. HJS oversaw the project and is guarantor. SGK, YZ, TD, JLB, and HJS drafted the ROBVALU tool. JN, PAC, FX, and US formed the advisory group. SGK led working groups and conducted the semi-structured interviews. SGK and LM analysed the data. HP-H, GH, YZ, and PAC assessed studies. PAC, FX, BE, ZSP, VW, ALS, J-ET, JN, LK, and US participated in the Delphi process as voting members, and HJS, YZ, SGK, and JLB were non-voting members. SGK and HJS drafted the manuscript. YZ, JLB, and HJS obtained funding for the study. All authors reviewed and commented on drafts of the manuscript. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

Funding: The study was funded by the Canadian Institutes of Health Research (grant 401310 to HJS and JLB). The funders had no role in considering the study design or in the collection, analysis, interpretation of data, writing of the report, or decision to submit the article for publication.

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: support from the Canadian Institutes of Health Research for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.

Provenance and peer review: Not commissioned; externally peer reviewed.

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ .

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Week 3 Assignment - Critiquing Quantitative or Qualitative Research

Qualitative Survey Questions with Some Examples

Understanding your customers’ experiences and perceptions is crucial for enhancing your products and services. While quantitative research provides numerical insights, qualitative survey questions dive deeper, exploring the “why” behind customer behaviors.

This article answers what qualitative research questions focus on, their applications, types, and the advantages and disadvantages of using them.

Qualitative vs. Quantitative Questions

Surveys can include both qualitative and quantitative questions. Quantitative questions yield numerical data, easily measured and statistically analyzed, like “How many times have you used our app this week?” or “On a scale of 1-10, how satisfied are you with our service?” This data is invaluable for spotting trends, measuring performance, and making data-driven decisions.

Qualitative research questions, however, seek to understand the underlying reasons, opinions, and motivations behind customer actions. They often start with “why,” “how,” or “what.” For instance, “What features do you find most useful in our app?” or “Can you describe a challenge you faced while using our service?”

Our Tip: A Balanced Approach

These qualitative survey questions examples provide richer, more detailed data, invaluable for customer experience (CX) professionals aiming to boost user satisfaction and loyalty. They uncover insights that quantitative data alone can’t, such as emotional responses and personal stories, revealing deeper customer needs and preferences.

A balanced approach, blending qualitative and quantitative research, typically yields the best results. Quantitative data highlights areas needing attention, while qualitative data explains why these issues exist and suggests potential solutions. This combination offers a comprehensive understanding of customer experiences, guiding more effective improvements and innovations.

When Should We Use Qualitative Research Questions?

Qualitative research questions are especially useful in various scenarios. By asking these “why” questions, you uncover insights that shape strategies, conduct market research, and enhance customer experiences.

Exploring Experiences:

Understand how customers interact with your product or service. For instance, “Can you describe your overall experience with our customer support ?” This type of question helps you focus on uncovering the nuances of customer interactions, highlighting what works well and what needs improvement.

Investigating Processes:

Gain insights into how customers use your product. For example, “Can you walk us through how you typically use our app?” This helps identify pain points in the user journey and opportunities to streamline processes.

Addressing Sensitive Topics:

Delve into issues that might be uncomfortable or nuanced, such as “How do you feel about the privacy features of our app?” A careful approach ensures respondents feel safe and respected while sharing their thoughts.

Understanding Change:

Comprehend shifts in customer behavior or preferences, like “Why did you decide to upgrade to our premium plan?” Understanding these reasons guides strategic decisions and product development.

Uncovering Motivations:

Discover what drives customer decisions. For instance, “What motivated you to choose our product over competitors?” This helps understand the unique value propositions that attract customers to your brand.

Identifying Expectations:

Determine what customers expect from your service or product. For example, “What features would you like to see in future updates?” Knowing these expectations helps prioritize developments to enhance satisfaction and loyalty.

Evaluating Impact:

Assess the impact of changes or new features. For instance, “How has the new dashboard improved your workflow?” This provides direct feedback on recent updates, helping measure their effectiveness.

Try Ready-To-Use CX Surveys

Patient Satisfaction Survey

Net Promoter® Score (NPS) Survey

Hotel Survey

Service quality survey

Customer Needs Survey

Product Feedback Survey (NPS)

Types of Qualitative Research Questions – Examples

There are various types of qualitative research questions, each serving a distinct purpose. Here are some examples focused on customer experience and marketing:

Descriptive

Descriptive questions gather detailed information about specific aspects of your product or service, helping understand what customers notice and appreciate.

• “What specific design elements stand out in our app?”
• “What features do you find most helpful on our website?”
• “Which elements of our service do you value most, and why?”

These effective qualitative research questions uncover details often missed in broader surveys. Customers might highlight a feature’s simplicity or the aesthetic appeal of your app’s interface, offering actionable insights for your design team.

Predictive questions explore potential future behaviors or outcomes, helping anticipate customer needs and preferences for proactive improvements.

• “If we had a project management tool integration for our app, how often would you use it?”
• “How likely are you to recommend our service to a friend after using our new feature?”
• “What impact do you think adding live chat support would have on your overall satisfaction?”

Predictive questions gauge the potential success of new features or changes before implementation, allowing adjustments based on customer feedback and reducing the risk of investing in unwanted developments.

Experiential

Experiential questions focus on understanding customers’ personal experiences and emotions, providing insights into their journey and emotional responses at various touchpoints.

• “How would you describe your first impressions of our application?”
• “Can you share a time when our customer service exceeded your expectations?”
• “What emotions do you associate with using our product, and why?”

These questions help qualitative research methods identify emotional factors influencing customer satisfaction and loyalty, amplifying positive experiences and addressing negative ones to enhance overall perception.

Compar a tive

Comparative questions draw comparisons between different products, services, or experiences, helping understand your competitive position and identify areas for improvement.

• “Was the pricing clear and easy to understand compared to our competitors?”
• “How does our product compare to others you’ve used in terms of ease of use?”
• “In what ways do you think our service stands out from competitors?”

Comparative questions reveal strengths and weaknesses relative to competitors, guiding strategies to enhance unique selling points and address gaps in your offerings.

Process-oriented

Process-oriented questions explore the steps customers take when interacting with your product or service, identifying barriers and opportunities to optimize the customer journey.

• “What are your next steps when you encounter an issue with our product?”
• “How do you typically find information on our website?”
• “What process do you follow to decide to make a purchase on our platform?”

Each qualitative research question, together with its statistical analysis, provide insights into practical aspects of customer interactions, highlighting areas to streamline and make the UX more intuitive.

Advantages and Disadvantages of Using Qualitative Questions in Surveys

Qualitative methods in conducting online research have their strengths and weaknesses. Let’s take a brief look at them.

In-Depth Data Gathering:

Qualitative questions provide detailed insights into customer thoughts and feelings, helping understand the “why” behind their actions. This depth leads to more targeted and effective improvements.

Encouraging Customers to Speak Their Minds:

These questions invite open-ended responses, letting customers express their opinions and experiences in their own words. This uncovers insights that structured questions might miss, capturing the full range of customer sentiments.

Participant Engagement:

Qualitative questions make surveys more engaging, encouraging participants to spend more time providing thoughtful answers. Engaged participants offer richer data, leading to more valuable insights.

Flexibility in Responses:

Unlike quantitative questions, which limit answers to predefined options, qualitative questions let respondents answer in their own words. This flexibility reveals unexpected insights and nuances.

Contextual Understanding:

Qualitative responses include context that quantitative data lacks, providing a fuller picture of customer experiences and perceptions. This context is crucial for accurately interpreting feedback and making informed decisions.

Disadvantages

Sample Bias:

The open-ended nature of qualitative questions may attract responses from customers with strong opinions, potentially skewing the data. Ensure a diverse range of participants to mitigate this bias.

Privacy Issues:

Collecting detailed personal information can raise privacy concerns, requiring careful data handling to ensure confidentiality. Robust data protection measures are essential to maintain customer trust.

Time-Consuming Analysis:

Analyzing qualitative data is time-consuming, requiring a nuanced approach compared to quantitative data. This often involves coding responses, identifying themes, and interpreting meanings, which can be labor-intensive.

Subjectivity in Interpretation:

Qualitative data is inherently subjective, both in how respondents articulate their answers and in how researchers interpret them. Ensuring consistent, unbiased interpretation requires careful methodological rigor.

Limited Generalizability:

Qualitative data is detailed and specific, making it harder to generalize findings across a larger population. While valuable, these insights often need to be complemented with quantitative research to provide a broader perspective.

Good Qualitative Research Questions – Sum Up

Incorporating qualitative surveys into your research can unlock valuable insights that quantitative data alone can’t. By crafting and strategically using these questions, CX specialists can gain a deeper understanding of customer experiences, motivations, and preferences. Though challenges exist with qualitative data, its rich, detailed feedback is instrumental in shaping product and service strategies, enhancing customer satisfaction and loyalty.

Conducting qualitative research explore the nuanced aspects of CX in focus groups, laying the foundation for meaningful improvements. Whether you’re understanding customer behavior, addressing sensitive issues, or evaluating changes’ impact, qualitative questions offer the depth needed for informed decision-making. By balancing these with quantitative measures, you get a comprehensive view of your customers, enabling you to create more personalized, responsive, and effective CX strategies.

Tool For Quantitative and Qualitative Questions

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Author: Dariusz Jaroń

Updated: 20 June 2024

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Responding to health literacy of refugees in Australian primary health care settings: a qualitative study of barriers and potential solutions

• Prince Peprah 1 , 2 ,
• Jane Lloyd 2 , 3 &
• Mark Harris 2  

BMC Health Services Research volume  24 , Article number:  757 ( 2024 ) Cite this article

Metrics details

Organisational health literacy is a promising area of research that enables a focus on how systems and services can be designed in ways that are responsive to populations with varying states and levels of health literacy, knowledge, and practices, including African refugees. The challenge is how organisations and professionals do this in practice, and research in this area is in its early stages. This qualitative study examined barriers to implementing health literacy responsive care practices in primary health care settings in Australia. It also offered suggestions to potentially address the barriers to improving organisational health literacy.

Refugees ( n  = 19), primary health care professionals ( n  = 14), and other key stakeholders ( n  = 19) were recruited through convenience and snowball strategies from three states in Australia: New South Wales, Victoria, and Queensland. All but one participant was interviewed face-to-face via Zoom. Semi-structured interview guides were used to guide the conversations. Transcriptions from audio recordings were analysed using directed content analysis.

Thirteen themes were extracted from the data. Themes were organised into the following categories: structural and systemic, organisational context, individual professional level, individual patient level, and socio-community level. Major structural and system-level factors affecting organisational health literacy included rigid systems and structures and limited time. Key organisation-level factors included inflexible organisational processes and policies, institutionalised othering, discrimination and racism, and lack of interpreters. Individual professional factors were poor communication with patients and cultural knowledge gaps. Linguistic issues and service mistrust were key individual patient-level factors. Socio-community factors included limited community engagement. Participants identified potential solutions to help services navigate out of the barriers and improve their response to health literacy.

The findings suggest that mainstream services and organisations could improve timely and appropriate health care access and utilisation for refugees through strategies such as designing services and health literacy programs with refugee communities, promoting health literacy champions in the workforce, integrating health literacy and culturally responsive care plans and strategies into organisational priorities.

Peer Review reports

Understanding the barriers to organisational response to patients’ health literacy is crucial for planning and designing services that are easy to use and appropriate to needs and preferences [ 1 ]. Actions to support organisational health literacy are defined as the extent to which health organisations design, establish, and implement policies, practices, and systems that accommodate needs and make it easy for all people, including refugees with different health literacy and knowledge states and levels, to easily access, navigate, comprehend, and utilise health services and information to improve their health and well-being [ 2 , 3 ].

Accessing high quality primary health care, especially for marginalised populations such as refugees, is exceptionally challenging. Several structural and social factors impede this goal, including cultural differences, language barriers, structural racism, othering and discrimination, and health-system complexity [ 4 , 5 , 6 , 7 , 8 ]. Difficulty accessing health care is continuously exacerbated by systems and service demands [ 9 ]. When a health system consistently demands navigation, literacy, and other skills, knowledge, and abilities that marginalised persons, such as refugees in Australia, do not possess [ 3 , 10 ], it systematically disadvantages them in terms of health care access [ 11 , 12 ]. Thus, focusing on individual patients’ health literacy alone can prove burdensome because, it, ultimately places the responsibility on them to navigate and access health care services and information [ 13 , 14 ].

Efforts are being made to improve the health literacy of organisations in Australia due to its importance to promoting patients’ access to health care [ 15 , 16 , 17 ]. For instance, Federal and State governments and entities, such as the Australian Commission on Safety and Quality in Health Care, have consistently called for a prioritisation of health literacy practices and research that focuses on eliminating barriers to navigating, accessing, understanding, and using health services [ 15 ]. The NSW Health Literacy Framework 2019–2024 also acknowledged the need to promote systems and workforces to provide services that meet refugee patients’ health literacy and cultural and linguistic backgrounds [ 18 ]. Moreover, scholars such as Trezona and colleagues have developed and validated a tool called the Organisational Health literacy Responsiveness (Org-HLR) for organisations to assess, action on and improve their health literacy [ 3 , 19 ]. These health literacy frameworks and tools identify enabling factors for organisational health literacy. These include community engagement and partnership, community/peer navigators, interpreter use, family involvement in care, effective communication, cultural competence, easy and accessible health care environments, and leadership buy-in and support [ 3 , 18 ]. Thus, these frameworks and tools aim to improve the fit between the health system and services and the needs of marginalised groups, such as refugees.

Overall, achieving organisational health literacy is an important idea that has not been systematically implemented across the health care system [ 20 , 21 ]. Health literacy frameworks may be developed, but they are not routinely applied or adequate in scope to responding to the health literacy issues of marginalised populations such as refugees. Some reviews have shown that the barriers to system and organisational health literacy are universal [ 22 , 23 , 24 ]. They include poor communication skills of health professionals, lack of training regarding health literacy responsiveness, limited human resource capacity, lack of organisational leadership support, and low priority and commitment towards health literacy. Other organisational level factors include design and implementation issues, such as the absence of change champions, lack of a culture of change, the complexity of health literacy tools and guides, and lack of physical resources [ 22 , 23 , 24 , 25 ]. Some recent studies also reported facilitators such as established partnerships with external organisations, experienced and skilled staff, and active initiatives in clinical settings [ 1 , 17 , 25 ].

The development and testing of organisational health literacy frameworks, self-assessment tools and guides lead to insight about organisational performance, however implementation is often complex and difficult in practice [ 17 , 20 , 24 , 25 ]. At the same time, there is limited evidence on the factors that either promote or hinder the application and implementation of these frameworks and tools in practice, especially in primary health care settings in Australia. Currently, one qualitative study in Australia explored the issues faced by General Practitioners (GPs) when supporting patients with limited health literacy and the strategies they used to support patients [ 26 ]. One pilot study using sequential mixed method approach also examined the efficacy of the Org-HLR tool and associated assessment process in a remote primary health care setting [ 25 ]. Another evaluation study based on a literature review established a case for the importance of appraising the health literacy of health care services in Australia [ 17 ]. However, these studies only involved clinicians and administrative staff and as a result, service users’ perspective on organisational response to health literacy remains largely unknown. Also, less emphasis has been placed on organisational response to health literacy of marginalised groups, especially African refugees who may come from different health systems with varying health literacy issues, knowledge, beliefs, and practices that affect their access to services [ 10 , 27 ].

Here, these study addressed a significant knowledge gap by investigating barriers to organisational health literacy of refugees within primary health care settings in Australia. The study also investigated what can be done by health services to better meet the health literacy, knowledge, and practices of refugee patients. A qualitative study conducted from multiple perspectives at the primary health care level on barriers to organisational health literacy in Australia is needed to offer evidence to guide health organisations and decision makers in designing and implementing health literacy responsive care strategies and programs.

Study approach and population

This exploratory qualitative paper presents data on barriers to responding to health literacy of refugees among primary health care organisations and professionals. This study also offers evidence on how barriers can be addressed to improve organisational response to health literacy. The participants in this study included 14 primary health care providers (with diverse professional and disciplinary backgrounds such as GPs ( n  = 4), registered nurses ( n  = 5), nurse practitioners ( n  = 2), pharmacist ( n  = 1), paediatrician ( n  = 1), and psychologist ( n  = 1)) and 19 stakeholders (from different backgrounds such as health service directors ( n  = 4) practice managers ( n  = 3), multicultural health workers ( n  = 3), resettlement workers ( n  = 3), liaison officers ( n  = 4), and community elders ( n = 2) from several local health districts and primary health networks across three Australian states: New South Wales, Victoria, and Queensland. Also, 19 refugees including both males and females from nine African countries also participated in this study. Details on the study design/approach, sample, and selection process, including inclusion and exclusion criteria have been reported in an earlier study [ 28 ].

Recruitment

The South-Western Sydney Local Health District Human Research Ethics Committee approved the research (Ethics Approval Number: 2021/ETH11161). Informed consent was obtained from all subjects who participated in this study. Detailed report on the recruitment procedure(s) have been reported in a previous study [ 28 ]. Briefly, participants were invited to participate in face-to-face semi-structured interviews to offer their perspectives on factors that obstruct health literacy responsive care practices and strategies through different sampling techniques, including convenience and snowball strategies. Invitation letters containing flyers and information sheets were sent to primary health care professionals and stakeholders through professional bodies and organisations working with refugees. The flyers were also given to government and non-governmental agencies that either directly or indirectly provided services and support to refugees. Emails, text messages, or phone calls were used for follow-up. All participants who showed an interest in the study were screened to ensure that they were eligible to participate. The initial interview participants were asked to invite others within their networks to participate in the study.

Semi-structured interview design

Three semi-structured interview guides were developed for providers, refugees, and other key stakeholders, respectively (see supplementary files 1–3). The guides were informed by and refined through literature review [ 19 , 26 ], reflective supervision, and feedback from pilot interviews. A semi-structured approach was adopted because an understanding of organisational response to health literacy, especially within the primary health care context in Australia, is a relatively new area of research [ 29 ]. Data for this study were mainly gathered from two main open-ended questions that were asked to provider and stakeholder participants followed by a range of prompts that encouraged participants to reflect and share their experiences on 1) barriers to health literacy responsive care strategies, programs, and policies,and 2) perspectives on what can be done to address the perceived barriers to health literacy responsive care strategies, programs, and policies. Refugees’ perspectives on barriers and solutions to implementing health literacy responsive care strategies, programs, and policies were drawn from their experiences of primary health care access.

The first author conducted the interviews in English using an institutional Zoom platform, except for one stakeholder interview. The first author is an international student from Africa who has previously conducted extensive qualitative interviews with marginalised populations. However, he had no relationship with any of the participants before the interview. The interviewer understands how it is to live in an African country like Ghana and a Western nation like Australia. This knowledge enhanced his ability to conduct the interviews. More importantly, the research team composed of qualitative researchers with diverse knowledge and experience in conducting health services research, especially among service providers and marginalised health care consumers such as refugees in Australia. The interviews were conducted between March 2022 and December 2022. Data collection was stopped after the realisation that thematic saturation has been met [ 30 ]. Each interview lasted between 30 and 60 min and was audio recorded. Before the interviews, information sheets and consent forms were provided to the participants to enable them to understand the study and their participation before consenting. Refugees were given a $30 gift voucher for their time.

The first author and an external professional transcription company transcribed the interviews. The first author verified all transcripts for accuracy once received from the transcription company by listening to the recordings and comparing them to the written transcripts. The analysis involved a recursive process of several stages for key concepts in NVivo 12. Coding was conducted by the first author but was discussed with the supervision team. Revisions were made by considering emergent themes and interpretations. The directed content analytical approach guided the analysis of patterns and themes within the data [ 31 ]. Directed content analysis is a flexible content analysis approach commonly used in health care and service research to interpret meaning from the content of text data when the structure of the analysis is operationalised based on an existing theory/model or prior knowledge on the topic under investigation [ 30 , 31 , 32 , 33 ]. The main goal of the approach is to test, correct, and/or possibly extend and enrich an existing knowledge or a model unlike the conventional content analysis approach which seeks to derive new theories [ 30 , 33 , 34 ]. Thus, the directed content analysis was selected over the conventional approach because of its flexibility and ability to extend existing knowledge and model. In this study, the approach was used to guide, examine, and extend knowledge and models regarding organisational health literacy in the context of refugee population to enrich existing evidence and understanding.

The analysis identified two key themes: 1) the barriers to health literacy responsive service strategies, programs, and policies; and 2) solutions to the barriers. Data were categorised as a barrier if, according to the participants, the factor(s) made it difficult or impossible for organisations and professionals to respond to the health literacy needs of refugee patients and communities. Next, we went to the dataset for a more intensive analysis and identified codes and placed them under their respective categories along with key quotes. Through this iterative process, involving going back and forth to the dataset to obtain further evidence, further codes were developed and eventually collated into themes. When there were differences in opinions among the research team about the codes and themes, consensus was reached through further discussions.

Thematic categories were created based on the observed patterns of meaning in the dataset, along with solutions to navigate out of the barriers. Finally, since the development of the initial interview questions was guided by the literature [ 3 , 19 ] the directed content analysis results/categories were organised based on five levels derived from the literature applying systems theory to health care systems. These levels included structural and system levels (the broader external Australian health system), organisational context, individual professional level, individual patient level, and social community context.

Barriers to health literacy responsive strategies, policies and programs

The following section describes the themes which are organised into 5 topics. The section includes a diagram summarising the themes and how they interact with each other (see Fig.  1 ).

Summary of the thematic categories interacting with each other

Structures and systems (the broader external Australian health system)

Structural and system-level factors were grouped into three categories: the structural arrangement of the broader Australian health system, structural issues of time and remuneration, and lack of funding. Providers and stakeholders perceived the traditional/hierarchical structure of the Australian health care system that delineates roles, responsibilities, and relationships among health care organisations as rigid. Provider and stakeholder participants mentioned that the structure of the health system significantly influences the care coordination, delivery of quality services, and patient health outcomes such as access and health literacy. The provider and stakeholder participants stated that the Australian health system’s hierarchical structure impedes changes and innovation, mainly due to the changing health care environment.

… the health system is rigid, the structures are rigid, and the organisations are rigid. So, it becomes difficult if you want to do something new because it is not easy to change the structures. I think it goes down to the rigid structures and systems that do not allow this improvement and change. [Nurse]

One service director also lamented the hierarchical structure of the Australian health system by focusing on its rigidity and complexity that do not promote flexibility and patient-centred care.

The system has it[s] several hierarchies and… culture which is very complicated and rigid to my view… everyone working there including doctors and services… are rigid [;] they are not flexible. [Service director]

Some providers mentioned that, in most cases, organisations and professionals are motivated and willing to improve and adapt their practices to respond to the health literacy needs of marginalised groups such as refugees. However, the structural issues do not support them.

… I don’t think we do a very good job in educating our clients unless we’re asked to [do so], and I really think it goes down to the structures and systems in place that are rigid to allow this education… we basically cannot do more enough to [help] those people… who do not have the capacity. [Nurse]

One provider participant reflected in support of the above:

… it is not easy to do sort of things because you are working with the broader bigger health system that is… too immovable so hospitals… clinics and people [working] there may want to do things differently… to help [but may not be able to do so] . [Nurse practitioner]

The rigidity of the health care system left some providers feeling frustrated about the difficulties in generating change within the system.

[I see a lot of committed people] … but time is not there because this takes a lot of time, this takes a lot of energy, it takes resources, [but] there’s no time… people who completely understand what is happening [within the system] , just get frustrated… [because] they’re not getting what they’re asking for to change things, and then they just get frustrated… [and] burn out. [Multicultural health worker]

Time was portrayed as a critical structural hurdle in most interviews among providers. For instance, providers mentioned that using interpreters and models, such as teach-back, requires time, and formal consultation or appointment cannot be sufficient.

…the structures are so rigid that they dictate the duration of the consultation. So, you see a refugee patient for 10-15 minutes, which is never enough to support them in building their knowledge levels. Sometimes, you wish to help, but the time is not there. [GP]

Some providers also focused on systems that did not allow for interpreter use because of the structural issue of time.

Getting them to use interpreters is one of the biggest problems, and… getting them [to] take their time to let people understand things better is another thing… I think it is because of time because within 5 minutes you should leave the office for someone to come in and I think it is because of the system and structures we have… [Nurse]

Some providers also re-emphasised the structural issue of time, focusing on the effect of time on culturally responsive service delivery in mainstream services.

The main challenge [is] that [it] obviously takes longer, it’s more resource intensive, and that’s the very reason why you’ll find so many like GPs or health services like hospitals … [not doing that] . It takes too long, and they have too many people to see… [Nurse]

It was mentioned that delivering culturally responsive care for patients from refugee backgrounds requires time to build rapport and trustful relationships.

I guess time is [an] important element because doing things in a delicate way [is important] so that you do not rule out… [people’s] norms… practices [and] beliefs… [It] takes time… building rapport and knowing them and… it is one reason mainstream services cannot respond to these people well because they do not have time. [Nurse]

Providers explained that seeing a patient from a refugee background is a double appointment since they require longer consultations and extra-consultation activities that cannot be paid or remunerated under the current Medicare billing system.

I think the workload as well… In fact, not just the time but… [also] the pain [because] you get no extra pay. Sometimes you wish to help but end up sticking with your regular appointment. Using phone interpreters… sometimes… takes a good three [to] five minutes to get the phone interpreter working in the consultation… So, every refugee patient I see… is a double appointment, and you don’t get paid for that and [that is] … hard… [GP]

External funding is needed by organisations to effectively respond to the health literacy and cultural needs of their service users and broader communities. Providers and stakeholders mentioned that funding for community activities, consultations, programs, and education could help address health literacy issues among culturally and linguistically diverse communities such as refugees. Nevertheless, stakeholders and providers predominantly mentioned funding. They explained that they have limited financial resources and capacity to undertake community-based programs, education and activities that foster and sustain health literacy among marginalised communities.

How we can get the finances… that’s the big[gest] issue… I’m getting the government to recognise it… I think we do [a] great work, but we do not have the funding capacity, and no one is helping us. [Multicultural health/resettlement worker ]

For instance, some stakeholders shared that some health literacy promotion activities and programs within communities by their organisations could not be continued due to a lack of funding.

… the fact is that we do not have the needed funding for our work most of the time… there was a great piece of work done around the Afghan community… we need to do that for a whole lot of backgrounds, but we just don’t have the capacity… funding capacity. [Service director/manager]

The above description suggests that structural barriers to providing refugees with health-literate and culturally responsive care may not be new. However, more interesting is the acceptance of the system’s limitations by providers and other stakeholders. In addition, the system’s inadequacies must be overcome by the goodwill and discretion of the individual providers. For instance, providers had to see a patient for a double appointment, even though they were only charged for one consultation.

Organisational context

In this context, five categories were identified from the data: 1) inflexible organisational policies and processes; 2) institutionalised othering, racism, and discrimination; 3) limited organisational leadership, priority and commitment; 4) lack of interpreters; and 5) lack of training. Provider and stakeholder participants felt that policies and processes, within many primary health care organisations do not support health literacy development because they are inflexible.

… for [all] this while, I understand primary care need to be very flexible, but I doubt if that is what we see… in Australia, because most [of the] things like policies… processes and systems in the organisations are not flexible... It cannot be change [d] or modify so easily to make change occur and I guess because the general practice itself is rigid [and] the health system is rigid. [Nurse ]

Some provider and stakeholder participants lamented the inflexibility of actions particularly within hospital services such as communicating health information to patients, utilising medical and non-medical approaches to perform wide range of patient care education activities, and contacting patients for care. For instance, one stakeholder participant was concerned about how hospitals contact or share information with patients:

… when they… send out appointments, they’ll send it out in English to the person [and when the] … person doesn’t respond, they take them off the waiting list. So that’s an example of a… culturally unfriendly and unresponsive service because people get stuff in the mail in English all the time. And if they don’t speak English, you can’t tell that, it’s ridiculous. [Service manager]

Due to the perceived inflexibilities within services, this participant maintained that it was difficult for organisations to adopt a right-based approach to service delivery by adopting an individualised approach to care.

… it’s really hard to… take a rights-based approach, which I think should be taken. People have got a right to… equal service... and if you’re looking at hard to reach communities and you have to reach out, it’s not okay to just use the same system or follow up… when services are asked to do things differently it becomes a problem. [Service director]

Some providers stated that the inflexible processes have created a one-size-fits-all approach or model for service delivery to every patient, including refugees.

…we provide a generalist service without special consideration to people from different backgrounds with unique challenges and needs. [Nurse]

All participant groups stressed various forms of discrimination and racism within health institutions as barriers to responding to health literacy of refugees. Refugee patients face racist and discriminatory attitudes and behaviours in mainstream health services. A notable description of these accounts is the concepts of blackness and othering, especially in mainstream primary health care. One stakeholder reflected on the blackness below:

I think the biggest barrier is ourselves, and ourselves I mean the structures, the providers who are whites, the structures that are for the whites… we assume that everyone gets the same level of… education… [as] what we do. How we see people who are not natives as ‘others’, especially those who are black. So, more often, we use the words like ‘others’ and ‘blacks’… it is rooted in how we perceive people, greatly affecting how we interact, engage and support people as professionals. Because ‘Others’ are out, if you are ‘black’, you are out. Everything, Anglo. We’re very naive and ignorant population. Generally, we also see things through a very Anglo prism. [Service director/manager]

According to some providers, the Anglo worldview mentioned above has shaped health professionals’ and organisations’ attitudes, processes, and practices, especially within mainstream services.

Probably structural racism or institutional racism. [There are] so many awesome clinicians that we work with that are great. In the mainstream hospitals… unfortunately, … [some of the nurses and doctors] have absolutely no idea how the world works outside of their very small country. Despite they’re not outwardly out here, obviously, [they go] … about their day trying to be horrible and racist or whatever… and in their actions… [and] … they show that there is a long way to go… [Nurse]

One participant from a refugee background shared the following experiences:

[I think] some health professionals… are racist because I when [I] came I remember that I saw one professional… and he wanted me to speak English and no interpreter too [was available] so he said we are tired and fed up with all the refugees coming here and can’t speak English. Why are they here if they can’t speak English in the first place. In fact, I was very sad the whole day. He did not know our experience. [Refugee]

One provider participant from a refugee-focused health service envisaged a future in which services would be responsive and less racist:

I would like to see a time in the future when we do not have to do this work [referring to refugee-focused services] because the… [hospital] is just better and more responsive and less racist and less Anglo-centric. But good luck to me. [Nurse ]

Organisational health literacy frameworks have stressed the importance of organisational leadership support and priorities. However, for instance, participants collectively lamented that health literacy was not an organisational priority.

I think the commitment is not there [and] the leadership… do not see health literacy of people like… as a big thing because when the leaders decide to build health literacy, it becomes important priorities for them… [and] you can see that in their plans, procedures, and protocols… [ Community liaison officer]

Lack of interpreters was also mentioned as a barrier to responding to health literacy among refugee, provider, and stakeholder participants. Refugees, stakeholders, and providers mentioned that there are minor and emerging languages in which it is difficult to find interpreters.

When it comes to translation, they have materials in other languages, but the problem is the minor ones; they miss out and there are some that do not have interpreters at all which is one of the issues in trying to reach the vulnerable. [Refugee]

Some stakeholder participants confirmed the following:

... recently, I had a request for a language by one psychiatrist that I never heard in my entire life. We couldn’t find interpreter so we couldn’t assist the patient according to the policy. Policy says, you have to organise professional interpreter, [but] we didn’t have… so we had to ask family member to assist, which was not [a] good practise, but there was no simply other choice because there is no such a language registered in Australia. [Multicultural health worker]

Stakeholder participants specifically discussed that lack of or limited formal education and training on culture and mandatory cultural training for health providers and administrators are other barriers to culturally responsive care.

I think a big challenge is that… it’s not something that… they get formal training in… I think they do not have formal training in cultural stuff… training about [cultural] awareness for refugee communities was not mandatory. So, it could be tricky to get a group together. And it was really based on whether the manager of the service was interested and passionate about it and then they would get us in. [Community elder]

The participant further supported the importance of cultural training in working with refugees.

For example, doctors will come from North Shore to work in Blacktown and where a vast, diverse population from all different backgrounds exists. They have not really experienced that, and they do not know what to do because they have grown up in a completely white neighbourhood and do not have that formal training for cultural inclusiveness. [Multicultural health worker]

The description of the above five categories in the organisational context shows some interconnections. For instance, accepting the rigid system and its inadequacies indicates that for change to occur, health literacy has to be an organisational priority to drive change. If responding to health literacy is not a priority, it is left to the goodwill and empathy of providers to tailor care to patients’ needs (despite the system’s limitations).

Individual professional

Poor communication/limited use of interpreters with refugee patients and cultural knowledge gaps of providers were also identified at this level. Refugee participants expressed that there were always assumptions in communication and information sharing by health organisations and professionals.

One issue is that most of the GPs think everyone can… speak English and they do not like using interpreters, they do not have time to see if we have understood things, so many go out and they do not understand anything…. [Refugee]

The quote suggests inherent assumptions and generalisations in language services, such as the assumption that all patients could communicate in English, which is likely to prevent refugees from finding and understanding health information.

Providers’ limited use of interpreting services, especially in mainstream services, emerged as a converging concern and a critical barrier to primary health care organisations and providers’ response to health literacy. Language differences create the issue of provider-patient communication discordance.

So, we were interacting with the bigger health system, and it is still a struggle to get people to use interpreters to provide language support to this population. It is a fundamental requirement, but it is a serious challenge. This challenge is common in mainstream services… it is a huge barrier. [Service director/manager]

Knowledge gaps regarding understanding refugees’ cultural backgrounds, identities, and needs among individual health professionals were specifically mentioned in the interviews as barriers to culturally responsive care delivery. Stakeholders and refugees mentioned that many professionals did not have knowledge and experience working with cultural groups, such as Africans. Stakeholders and refugees specifically stated that many providers working with refugees have no knowledge about specific cultural belief systems and practices of refugees that shape their health and health care decisions. Again, they emphasised that many providers need to better understand how to engage people like African refugees who are culturally diverse, sensitive and have experienced significant trauma and loss.

…I think there are instances in which they [referring to providers] are mot culturally appropriate… [because] they tend to put all Africans in one box. So, what Somalians want… they think Sudanese also want because [we are] dark skinned. They don’t try to find out which part you are coming from, your beliefs, and all of that… they just group us together and say we are all the same. [Refugee]

Due to the perceived knowledge gaps, one stakeholder participant stressed that many providers need a rulebook regarding how to deal with specific cultural groups.

… it always comes back to not giving a rule. People want a rule book. This is how I deal with Ghanaians… this is how I deal with Kenyans… but being prepared to put themselves out of [their] beds and to understand that there are differences… and things aren’t necessarily going to be the same… [Multicultural health/resettlement worker]

Another stakeholder participant added the following:

So, some people think that there is a way to talk or to engage people with [refugee backgrounds] … they want to know the formula and really, there’s no formula. [Multicultural health/resettlement worker]

Refugees and stakeholders highlighted that most providers sometimes lack experience, skills, and confidence to communicate health information in a culturally sensitive manner. Again, they stressed that some providers were unaware of refugee patients’ cultural background and identity.

But look at the person who hardly knows any cultural background, who hardly understands where you’re coming from, who thinks that… people in the hospitals even struggle to engage [us] because they do not know [our] cultural issues to be able to understand [the] issues [we are facing]. [Refugee]

The above quotes imply the need for cultural competency, awareness skills, and training of providers. Training and skills will help build knowledge and confidence in engaging and communicating effectively and appropriately with refugee patients. Effective engagement and communication are essential for health literacy development and culturally responsive care.

Individual patient

Linguistics issues and service mistrust among refugees were reported at this level. The providers mentioned that most refugees had limited English proficiency in communicating effectively with providers who did not speak their native language. Refugees stressed that health literacy and cultural concerns in interpreting services are often ignored. Refugee participants argued that providers and organisations cannot assume that interpreters share the same culture with refugee patients because they speak the same language. Several dialects exist within the same language and interpreting services do not consider them.

… but for us Sudanese there’s another problem… there were no Sudanese interpreters, there was no African interpreters, so we were serviced by some other Arab nationalities… like Lebanese or Iraqis… [but] … there’s a difference also in the dialect… [Refugee]

The participant also talked about differences in English accents as a challenge in communication.

… We have our own African language, we have the Arabic language, which is the language of our country, Sudan, the general language, so English was not that familiar for ordinary people… unless you … [you go] to school… but… the accent here is very different. [Refugee]

Both providers and stakeholders alluded to mistrust as a barrier to organisational response to health literacy. It was revealed that most vulnerable groups, including refugees do not trust health services and professionals because of past experiences in their home countries and Australia. Providers felt that they needed people’s trust to help them build their health literacy and respond to their cultural needs, but when patients do not trust, the services and professionals’ engagement become compromised. Additionally, patients become less receptive to health information if they do not trust the system or professionals.

… trust is important… because they have lost trust before coming here. I remember some clients used to visit our services and they stopped, and I guess because they did not trust [us] because whenever I gave them some information and explained some medical issues, I noticed they did not believe or trust me. I think some of my colleagues here faced the same sometimes. [GP]

The factors discussed by the participants at the individual patient level showed some interrelationships between them. For example, linguistic issues may create negative experiences which could impact the trust people have in the services and professionals.

Socio-community context

One category was identified at this level based on the data: limited community collaboration and engagement. Refugees, community leaders, and elders expected opportunities for partnerships, collaborations, and the co-design of interventions to ensure that services meet their health knowledge and practices. Stakeholders lamented that health professionals and organisations operate a top-down approach and often fail to consult community elders, leaders, influential people, and community-based organisations in planning and designing health literacy activities and programs, creating a gap between services and communities.

The fact is that they failed to consult, in fact… they always fail to consult people like us, multicultural workers [and] community intermediaries. They mostly do what they want first and when things get worse, then they try to consult not realising that we work with [the community people] and they understand us more than them. [Multicultural health/resettlement worker]

The limited involvement of refugee communities may mean limited access to services by communities as many refugees consult community leaders for health information.

Navigating out of the barriers – suggested potential solutions

Participants were asked what should be done to address the barriers in implementing health literacy responsive policies, programs, and strategies; improve organisational response to health literacy; and help the refugee community navigate and access services that they need. Their suggested solutions are summarised into some key points in Table  1 .

This study aimed to explore the structural, systemic, organisational, personal, and community level factors that serve as barriers to organisational health literacy from the perspectives of primary health care services/organisations, professionals, and refugees. The study also identified potential solutions to address these barriers and improve service responsiveness for refugee populations in Australia. At the structural and system level, the study we found that the hierarchical structure of the broader health system which is perceived to be rigid, structural issues of time, and lack of funding and remuneration serve as barriers to implementing health literacy responsive policies, programs, and interventions. These factors indicate the importance of external structures, systems, and policies in organisational health literacy [ 3 , 11 , 26 ].

The findings further extend the literature on and challenge many organisational health literacy conceptualisations that recognise only organisational responsibility and context factors and neglect the impacts of external forces, such as broader health systems and structures and the role of external bodies, such as governments. Health system structures and policies are critically important, but are uncounted for most health literacy frameworks and self-assessments [ 2 , 3 , 19 , 35 ]. For instance, the Org-HLR [ 3 ] and the ten attributes of health literate health care organisation [ 2 ], which are popular organisational health literacy responsiveness models do not specifically consider the influence of the structure of the broader health care system on how organisations respond to patients’ health literacy. Although health organisations can implement policies and strategies to respond to health literacy issues and promote equitable access to health care and services, health literacy issues cannot be fixed exclusively at the health organisation level. Health organisations interact with and are produced and shaped by broader health system arrangements outside health care organisations [ 3 , 36 ]. The findings, therefore, suggests that organisational health literacy frameworks/models should consider other relevant levels such as the health care system to promote effective systemic and comprehensive response to patients’ health literacy.

The findings indicated that organisations needed external funding to implement health literacy responsive care interventions and projects within communities. Previous evidence suggests that becoming health literacy responsive is resource intensive because more programs, changes, and staff are required simultaneously within an organisation. This finding also supports Trezona et al. [ 3 ] organisational health literacy framework. The external funding environment shapes organisational health literacy (which is not within the organisation’s direct control), such as the role of governments and other relevant funding bodies in providing adequate and sustainable funding for implementing health literacy responsive care programs and policies within organisations [ 25 ]. Therefore, this finding demands health system policymakers to acknowledge that responding to health literacy of patients is not the responsibility of only health organisations but also requires well-structured and flexible health systems that provide reliable funding for health literacy promotion.

The findings emphasised the relevance of organisational context in responding to people’s health literacy issues, in support of previous studies [ 17 , 19 , 25 ]. Trezona et al. [ 3 ] stressed that an organisation’s policies, processes, and systems must be flexible and modifiable to ensure effective and responsive services, program planning, and delivery. In contrast, participants stressed that structures, policies, programs, and systems within primary health care organisations that are supposed to be flexible are relatively rigid, which does not allow for health literacy responsiveness shifts. These rigidities within primary health care organisations can be linked to the reported rigidity of the broader Australian health care system within which the organisations are located.

For instance, many professionals and stakeholders expressed concerns about their inability to respond to patients’ health literacy issues, especially marginalised ones with peculiar needs such as refugees. They attributed their inability to the complexities within the organisations resulting from the hierarchical and perceived rigid health care system in Australia. From this finding, for most health organisations, the transition to comprehensive health literacy responsiveness may be a complex, unfolding process over many years due to structural rigidities that do not allow for change and innovation [ 23 , 37 , 38 , 39 ]. Health organisations need flexible structures, processes and policies to promote organisational capability and functioning regarding organisational health literacy [ 3 ].

Also at the organisational level, we found for the first time that institutionalised othering, racism and discrimination influence organisational health literacy. Health literacy and the cultural needs of marginalised groups, such as African refugees, cannot be separated from the bigger picture and framework within which health organisations and professionals operate [ 40 ]. All participant groups reported perceived institutionalised othering, discrimination, and racism shape how organisations and professionals respond to health literacy of refugee patients. This finding can be linked to the reported racial, discriminatory, and Anglo-centric structures of the Australian health care system [ 41 ]. The Anglo worldview narrated by the participants may shape the attitudes, processes, and practices of health professionals and organisations, especially within the mainstream services that tend to favour others and discriminate against others regarding how they respond to and support different patients’ needs.

Moreover, the experiences of racism and discrimination, as highlighted by all participant groups, including health professionals, can also be linked to the broader African humanitarian resettlement in Australia, which remains a contested debate in public discourse, with conversations regarding increased levels of racism and discrimination [ 40 , 42 ]. Evidence suggests that delivering equitable and appropriate health services to refugees cannot be separated from the politicisation and racialisation of resettlement across Australian political and public spaces [ 43 ]. Thus, interviews reflect and resonate with this evidence, viewpoints, and other previous studies reporting experiences of racism and discrimination in primary health care settings and organisations in Australia [ 40 ]. Thus, the finding implies that focusing on individual attitudes and actions alone may not be enough to address racism and discrimination within health services [ 41 ]. Organisational and policy level changes and interventions are needed owing to the perceived institutionalised nature of the racism reported in this study. Interventions such as health policy reforms, effective organisational antiracism policies design and evaluation, effective community and stakeholder engagement, antiracist education and professional training, and effective and evidential cultural competence and sensitivity training may help to address institutionalised racism within health care settings [ 4 , 44 , 45 ].

Based on reports of perceived institutionalised racism, it is not surprising that mistrust was reported as a barrier to health literacy responsiveness because the perceived racist and discriminatory attitudes of some services may affect trust in both health care providers and organisations among refugee patients [ 46 ]. Trust influences engagement and access to health systems, services, and health care providers. Among refugees, trust is a crucial factor that influences the extent to which they familiarise themselves with health systems, the amount of health information they can share with and receive from health organisations and providers, and the degree of power and autonomy they can exercise [ 46 ]. Thus, for health professionals to support patients’ health literacy, trust is essential because health information is more receptive when there is trust. Other organisational and individual professional-level barriers were found in this study, including organisational leadership priority, and commitment, linguistic issues, and poor communication. However, these factors have been extensively reported and discussed in earlier systematic reviews [ 22 , 23 , 24 ] and a recent qualitative study in Germany [ 1 ]. Their confirmation in the present study suggests their importance in organisational health literacy and the need for organisations to address them.

At the individual professional and patient levels, this study showed that cultural and racial-specific factors, such as cultural knowledge gaps shape organisational health literacy. This finding represents a new insight and an important research area and policy discussion within the health literacy literature offered by the present analysis. Many refugee participants and stakeholders mentioned that, in most cases and times, health professionals lack knowledge and awareness about refugees’ experiences, needs, backgrounds, and identities. They also lack experience, skills, and confidence in engaging, interacting, and communicating with cultural groups such as refugees, in a culturally sensitive and appropriate manner.

Organisational health literacy requires organisations and providers to provide services that meet all people’s cultural and health literacy abilities, needs, and preferences and support individuals and communities, such as providing language support and services for effective engagement and communication [ 3 , 19 , 25 ]. This finding particularly supports the interrelationships of culture, language, and health literacy, especially among refugees who are from culturally and linguistically diverse backgrounds like African refugees. Evidence suggests that health literacy can be pursued within the reality of an individual’s culture, and vice versa [ 47 , 48 , 49 ].

Another new finding was how limited consultation with community leaders, organisations, and gatekeepers affects the delivery of health literacy responsive services. Stakeholders mentioned that programs and projects promoting health literacy responsive care among communities operate in a top-down manner. Community organisations, elders, and leaders expect opportunities for collaborative programs and service design to ensure that services meet the needs of the people; however, such avenues are mostly not provided by services. Therefore, there is a gap between services and communities in terms of access to health information and messages. This finding, therefore, indicates that health services and organisations should actively engage and co-design health literacy interventions with the population that they serve as suggested by some of the participants. The importance of stakeholder and community engagement and co-design of health literacy programs and interventions would include a better understanding of community health literacy strengths and weaknesses, tailored health literacy and culturally responsive service programs, and community ownership of programs and projects [ 2 , 3 , 50 ].

Moving forward: lessons reinforced and possible solutions

Collectively, the data provided by this study provide opportunities for improvement by organisations in terms of creating accessible, understandable, actionable, and useable health environments, information, and services. The study highlighted what is not working well, especially for refugees in terms of organisational health literacy. Participants listed potential solutions to address barriers and improve responsiveness and access to services, especially for refugees. The suggested solutions included prioritising language support services, such as the use of culturally appropriate interpreters and translators; consulting and co-designing organisational health literacy plans, services, and interventions with refugee patients and their communities; and prioritising and integrating health literacy and cultural factors into organisational plans and strategies. Other suggestions also included making changes in on-arrival policies, such as the orientation to allow for effective education about the health system, structural and system-level shifts that allow for flexibility for change, and modification of usual practices and policies to promote tailored services. In addition, providing a workforce with mandatory cultural awareness and competency training can help to address cultural and race-related barriers. In addition, employing peer health navigators and bilingual educators could be beneficial for easy navigation.

The next steps can be organisations taking and implementing these solutions to address the identified barriers found in this study, especially as most of the factors mentioned are modifiable. Regardless of how or where health organisations begin from, organisational health literacy is a critical tool for partnering with communities, families, and patients in pursuit of adequate access and health equity, especially for marginalised populations such as refugees. It is important for services to be aware that most refugee communities, families, and individual patients interact with health environments and information so that they can actively understand their health, access care, and make meaningful decisions. Thus, there is an added sense of moral and ethical urgency for organisations to act considering the observed racial, cultural, and ethnic inequities in health outcomes, which are to some extent caused by health system complexities and culturally insensitive care.

Implications

Creating a health services and environment for patient to easily navigate, access, and use is a complex and multidimensional task. Identifying and examining the barriers to organisational health literacy provides a good understanding of what is working and what requires further improvement to promote health equity, especially for the refugee population. The expectation is that a refugee patient knowledge and practices, resources, and needs will meet the health system and organisational demands and requirements. This is vital because studies show that services do not meet the health literacy and cultural needs of culturally and linguistically diverse groups, including refugees [ 51 ].

Primary health care organisations and professionals must engage refugee communities, families, and patients in co-designing interventions to promote easy service navigation and access. Primary health care organisations should often conduct health literacy responsiveness assessments to develop more equitable processes, policies, and practices that can lead to adequate access to services to promote health equity. Tools such as the Org-HLR [ 3 ] and the ten attributes of health literate health care organisation [ 2 ] can help organisations to assess and improve their responsiveness. This is especially true for African refugees, given that they are from a completely different health system and resettled into fragmented complex health care environments in Australia, as well as many challenges faced by them in navigating and accessing services. Resettlement is a significant determinant of health as it affects individuals’ health literacy and health beliefs [ 11 , 52 ]. It is, therefore, an essential, a moral, and a legal responsibility as enshrined in the human right to health [ 53 , 54 ] for organisations to ensure access to care for refugees by improving their health literacy.

Strengths and limitations

The study included multiple participant groups for diverse perspectives and insights on barriers to responding to health literacy at the primary health care level. This study adds value by offering concrete insights into addressing barriers to organisational health literacy. However, this study has some limitations in interpreting the findings. First, it focused on primary health care providers, stakeholders, and African refugees. It also focused on refugee patients who could communicate in English as part of the inclusion criteria. Further qualitative research involving other groups, such as the general population, refugees with no or limited English proficiency, health professionals in mainstream services, and hospital-based investigations, could be helpful. However, the conformity of the study findings with previous studies suggests that the present findings can be representative of other health care organisations in Australia and other settings with the same or similar health care systems and services. In addition, although the study findings were subjected to several discussions and comments, the results were not shared with participants.

Removing barriers to service navigation, access, and utilisation, especially for marginalised populations such as refugees, is crucial for promoting health equity, but proves to be challenging for many health systems and organisations. This study represents the first research on primary health care providers, other key stakeholders, and refugees’ perspectives regarding the barriers to responding to health literacy. Overall, the directed content analysis revealed interconnected barriers to health literacy responsive strategies and policies. This study identified for the first time that cultural and racial-specific factors, such as cultural knowledge gaps and lack of cultural training, service mistrust, institutionalised othering, discrimination, and racism, shape organisational health literacy. This study yielded concrete strategies and recommendations for overcoming barriers and improving health literacy responsiveness. The findings suggest that services and organisations could improve timely and appropriate health care access and utilisation for refugees through strategies such as co-design of services, programs and interventions with refugee communities, culturally sensitive language support services, mandatory cultural awareness and competency training and education, and integrating health literacy responsive care plans and strategies into organisational priorities.

Availability of data and materials

No datasets were generated or analysed during the current study.

Abbreviations

General practitioner

• Health literacy

Organisational health literacy responsiveness

• Primary health care

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Acknowledgements

The authors thank all participants, including African refugees, primary healthcare providers, and stakeholders. The author also wishes to acknowledge the exceptional contribution of Dr. Mitchell Smith toward recruitment. All the individuals and organisations that assisted with recruitment are duly acknowledged. We also especially appreciate Professor kylie valentine for providing guidance, reading this manuscript, and providing valuable comments.

The University of New South Wales supported this research training through a Scientia PhD Scholarship. Fieldwork was supported by the UNSW Arts and Social Sciences Higher Degree Research Essential Costs of Research Funding and Centre for Primary Health Care and Equity Discretionary Funding.

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PP conceptualised and designed the study, collected and analysed data, and wrote the manuscript. JL contributed to the conceptualisation, design, and writing. MH contributed to the conceptualisation, design, and writing. The authors read and approved the final manuscript.

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Peprah, P., Lloyd, J. & Harris, M. Responding to health literacy of refugees in Australian primary health care settings: a qualitative study of barriers and potential solutions. BMC Health Serv Res 24 , 757 (2024). https://doi.org/10.1186/s12913-024-11192-9

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What is Qualitative in Qualitative Research

Patrik aspers.

1 Department of Sociology, Uppsala University, Uppsala, Sweden

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

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

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

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

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

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

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

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

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

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

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

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

Towards a Definition of Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Analysis – What is Qualitative Research?

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

Qualitative and Quantitative

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

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

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

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

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

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

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

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

Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

Grounded Theory

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

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

Defining Qualitative Research

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

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

Distinctions

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

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

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

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

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

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

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

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

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

Improved Understanding

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

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

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

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

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

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

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

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

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

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

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

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

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

Acknowledgements

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

Biographies

is professor of sociology at the Department of Sociology, Uppsala University and Universität St. Gallen. His main focus is economic sociology, and in particular, markets. He has published numerous articles and books, including Orderly Fashion (Princeton University Press 2010), Markets (Polity Press 2011) and Re-Imagining Economic Sociology (edited with N. Dodd, Oxford University Press 2015). His book Ethnographic Methods (in Swedish) has already gone through several editions.

is associate professor of sociology at the Department of Media and Social Sciences, University of Stavanger. His research has been published in journals such as Social Psychology Quarterly, Sociological Theory, Teaching Sociology, and Music and Arts in Action. As an ethnographer he is working on a book on he social world of big-wave surfing.

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Contributor Information

Patrik Aspers, Email: [email protected] .

Ugo Corte, Email: [email protected] .

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