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What is qualitative research.

Qualitative research methodologies seek to capture information that often can't be expressed numerically. These methodologies often include some level of interpretation from researchers as they collect information via observation, coded survey or interview responses, and so on. Researchers may use multiple qualitative methods in one study, as well as a theoretical or critical framework to help them interpret their data.

Qualitative research methods can be used to study:

How are political and social attitudes formed?
How do people make decisions?
What teaching or training methods are most effective?

Qualitative Research Approaches

Action research.

In this type of study, researchers will actively pursue some kind of intervention, resolve a problem, or affect some kind of change. They will not only analyze the results but will also examine the challenges encountered through the process.

Ethnography

Ethnographies are an in-depth, holistic type of research used to capture cultural practices, beliefs, traditions, and so on. Here, the researcher observes and interviews members of a culture — an ethnic group, a clique, members of a religion, etc. — and then analyzes their findings.

Grounded Theory

Researchers will create and test a hypothesis using qualitative data. Often, researchers use grounded theory to understand decision-making, problem-solving, and other types of behavior.

Narrative Research

Researchers use this type of framework to understand different aspects of the human experience and how their subjects assign meaning to their experiences. Researchers use interviews to collect data from a small group of subjects, then discuss those results in the form of a narrative or story.

Phenomenology

This type of research attempts to understand the lived experiences of a group and/or how members of that group find meaning in their experiences. Researchers use interviews, observation, and other qualitative methods to collect data.

Often used to share novel or unique information, case studies consist of a detailed, in-depth description of a single subject, pilot project, specific events, and so on.

Hossain, M.S., Runa, F., & Al Mosabbir, A. (2021). Impact of COVID-19 pandemic on rare diseases: A case study on thalassaemia patients in Bangladesh. Public Health in Practice, 2(100150), 1-3.
Nožina, M. (2021). The Czech Rhino connection: A case study of Vietnamese wildlife trafficking networks’ operations across central Europe. European Journal on Criminal Policy and Research, 27(2), 265-283.

Focus Groups

Researchers will recruit people to answer questions in small group settings. Focus group members may share similar demographics or be diverse, depending on the researchers' needs. Group members will then be asked a series of questions and have their responses recorded. While these responses may be coded and discussed numerically (e.g., 50% of group members responded negatively to a question), researchers will also use responses to provide context, nuance, and other details.

Dichabeng, P., Merat, N., & Markkula, G. (2021). Factors that influence the acceptance of future shared automated vehicles – A focus group study with United Kingdom drivers. Transportation Research: Part F, 82, 121–140.
Maynard, E., Barton, S., Rivett, K., Maynard, O., & Davies, W. (2021). Because ‘grown-ups don’t always get it right’: Allyship with children in research—From research question to authorship. Qualitative Research in Psychology, 18(4), 518–536.

Observational Study

Researchers will arrange to observe (usually in an unobtrusive way) a set of subjects in specific conditions. For example, researchers might visit a school cafeteria to learn about the food choices students make or set up trail cameras to collect information about animal behavior in the area.

He, J. Y., Chan, P. W., Li, Q. S., Li, L., Zhang, L., & Yang, H. L. (2022). Observations of wind and turbulence structures of Super Typhoons Hato and Mangkhut over land from a 356 m high meteorological tower. Atmospheric Research, 265(105910), 1-18.
Zerovnik Spela, Kos Mitja, & Locatelli Igor. (2022). Initiation of insulin therapy in patients with type 2 diabetes: An observational study. Acta Pharmaceutica, 72(1), 147–157.

Open-Ended Surveys

Unlike quantitative surveys, open-ended surveys require respondents to answer the questions in their own words.

Mujcic, A., Blankers, M., Yildirim, D., Boon, B., & Engels, R. (2021). Cancer survivors’ views on digital support for smoking cessation and alcohol moderation: a survey and qualitative study. BMC Public Health, 21(1), 1-13.
Smith, S. D., Hall, J. P., & Kurth, N. K. (2021). Perspectives on health policy from people with disabilities. Journal of Disability Policy Studies, 32(3), 224–232.

Structured or Semi-Structured Interviews

Researchers will recruit a small number of people who fit pre-determined criteria (e.g., people in a certain profession) and ask each the same set of questions, one-on-one. Semi-structured interviews will include opportunities for the interviewee to provide additional information they weren't asked about by the researcher.

Gibbs, D., Haven-Tang, C., & Ritchie, C. (2021). Harmless flirtations or co-creation? Exploring flirtatious encounters in hospitable experiences. Tourism & Hospitality Research, 21(4), 473–486.
Hongying Dai, Ramos, A., Tamrakar, N., Cheney, M., Samson, K., & Grimm, B. (2021). School personnel’s responses to school-based vaping prevention program: A qualitative study. Health Behavior & Policy Review, 8(2), 130–147.
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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.

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.

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Home Market Research

Qualitative Research Methods: Types, Analysis + Examples

Qualitative research is based on the disciplines of social sciences like psychology, sociology, and anthropology. Therefore, the qualitative research methods allow for in-depth and further probing and questioning of respondents based on their responses. The interviewer/researcher also tries to understand their motivation and feelings. Understanding how your audience makes decisions can help derive conclusions in market research.

What is qualitative research?

Qualitative research is defined as a market research method that focuses on obtaining data through open-ended and conversational communication .

This method is about “what” people think and “why” they think so. For example, consider a convenience store looking to improve its patronage. A systematic observation concludes that more men are visiting this store. One good method to determine why women were not visiting the store is conducting an in-depth interview method with potential customers.

For example, after successfully interviewing female customers and visiting nearby stores and malls, the researchers selected participants through random sampling . As a result, it was discovered that the store didn’t have enough items for women.

So fewer women were visiting the store, which was understood only by personally interacting with them and understanding why they didn’t visit the store because there were more male products than female ones.

Gather research insights

Types of qualitative research methods with examples

Qualitative research methods are designed in a manner that helps reveal the behavior and perception of a target audience with reference to a particular topic. There are different types of qualitative research methods, such as in-depth interviews, focus groups, ethnographic research, content analysis, and case study research that are usually used.

The results of qualitative methods are more descriptive, and the inferences can be drawn quite easily from the obtained data .

Qualitative research methods originated in the social and behavioral research sciences. Today, our world is more complicated, and it is difficult to understand what people think and perceive. Online research methods make it easier to understand that as it is a more communicative and descriptive analysis .

The following are the qualitative research methods that are frequently used. Also, read about qualitative research examples :

1. One-on-one interview

Conducting in-depth interviews is one of the most common qualitative research methods. It is a personal interview that is carried out with one respondent at a time. This is purely a conversational method and invites opportunities to get details in depth from the respondent.

One of the advantages of this method is that it provides a great opportunity to gather precise data about what people believe and their motivations . If the researcher is well experienced, asking the right questions can help him/her collect meaningful data. If they should need more information, the researchers should ask such follow-up questions that will help them collect more information.

These interviews can be performed face-to-face or on the phone and usually can last between half an hour to two hours or even more. When the in-depth interview is conducted face to face, it gives a better opportunity to read the respondents’ body language and match the responses.

2. Focus groups

A focus group is also a commonly used qualitative research method used in data collection. A focus group usually includes a limited number of respondents (6-10) from within your target market.

The main aim of the focus group is to find answers to the “why, ” “what,” and “how” questions. One advantage of focus groups is you don’t necessarily need to interact with the group in person. Nowadays, focus groups can be sent an online survey on various devices, and responses can be collected at the click of a button.

Focus groups are an expensive method as compared to other online qualitative research methods. Typically, they are used to explain complex processes. This method is very useful for market research on new products and testing new concepts.

3. Ethnographic research

Ethnographic research is the most in-depth observational research method that studies people in their naturally occurring environment.

This method requires the researchers to adapt to the target audiences’ environments, which could be anywhere from an organization to a city or any remote location. Here, geographical constraints can be an issue while collecting data.

This research design aims to understand the cultures, challenges, motivations, and settings that occur. Instead of relying on interviews and discussions, you experience the natural settings firsthand.

This type of research method can last from a few days to a few years, as it involves in-depth observation and collecting data on those grounds. It’s a challenging and time-consuming method and solely depends on the researcher’s expertise to analyze, observe, and infer the data.

4. Case study research

T he case study method has evolved over the past few years and developed into a valuable quality research method. As the name suggests, it is used for explaining an organization or an entity.

This type of research method is used within a number of areas like education, social sciences, and similar. This method may look difficult to operate; however , it is one of the simplest ways of conducting research as it involves a deep dive and thorough understanding of the data collection methods and inferring the data.

5. Record keeping

This method makes use of the already existing reliable documents and similar sources of information as the data source. This data can be used in new research. This is similar to going to a library. There, one can go over books and other reference material to collect relevant data that can likely be used in the research.

6. Process of observation

Qualitative Observation is a process of research that uses subjective methodologies to gather systematic information or data. Since the focus on qualitative observation is the research process of using subjective methodologies to gather information or data. Qualitative observation is primarily used to equate quality differences.

Qualitative observation deals with the 5 major sensory organs and their functioning – sight, smell, touch, taste, and hearing. This doesn’t involve measurements or numbers but instead characteristics.

Explore Insightfully Contextual Inquiry in Qualitative Research

Qualitative research: data collection and analysis

A. qualitative data collection.

Qualitative data collection allows collecting data that is non-numeric and helps us to explore how decisions are made and provide us with detailed insight. For reaching such conclusions the data that is collected should be holistic, rich, and nuanced and findings to emerge through careful analysis.

Whatever method a researcher chooses for collecting qualitative data, one aspect is very clear the process will generate a large amount of data. In addition to the variety of methods available, there are also different methods of collecting and recording the data.

For example, if the qualitative data is collected through a focus group or one-to-one discussion, there will be handwritten notes or video recorded tapes. If there are recording they should be transcribed and before the process of data analysis can begin.

As a rough guide, it can take a seasoned researcher 8-10 hours to transcribe the recordings of an interview, which can generate roughly 20-30 pages of dialogues. Many researchers also like to maintain separate folders to maintain the recording collected from the different focus group. This helps them compartmentalize the data collected.
In case there are running notes taken, which are also known as field notes, they are helpful in maintaining comments, environmental contexts, environmental analysis , nonverbal cues etc. These filed notes are helpful and can be compared while transcribing audio recorded data. Such notes are usually informal but should be secured in a similar manner as the video recordings or the audio tapes.

B. Qualitative data analysis

Qualitative data analysis such as notes, videos, audio recordings images, and text documents. One of the most used methods for qualitative data analysis is text analysis.

Text analysis is a data analysis method that is distinctly different from all other qualitative research methods, where researchers analyze the social life of the participants in the research study and decode the words, actions, etc.

There are images also that are used in this research study and the researchers analyze the context in which the images are used and draw inferences from them. In the last decade, text analysis through what is shared on social media platforms has gained supreme popularity.

Characteristics of qualitative research methods

Qualitative research methods usually collect data at the sight, where the participants are experiencing issues or research problems . These are real-time data and rarely bring the participants out of the geographic locations to collect information.
Qualitative researchers typically gather multiple forms of data, such as interviews, observations, and documents, rather than rely on a single data source .
This type of research method works towards solving complex issues by breaking down into meaningful inferences, that is easily readable and understood by all.
Since it’s a more communicative method, people can build their trust on the researcher and the information thus obtained is raw and unadulterated.

Qualitative research method case study

Let’s take the example of a bookstore owner who is looking for ways to improve their sales and customer outreach. An online community of members who were loyal patrons of the bookstore were interviewed and related questions were asked and the questions were answered by them.

At the end of the interview, it was realized that most of the books in the stores were suitable for adults and there were not enough options for children or teenagers.

By conducting this qualitative research the bookstore owner realized what the shortcomings were and what were the feelings of the readers. Through this research now the bookstore owner can now keep books for different age categories and can improve his sales and customer outreach.

Such qualitative research method examples can serve as the basis to indulge in further quantitative research , which provides remedies.

When to use qualitative research

Researchers make use of qualitative research techniques when they need to capture accurate, in-depth insights. It is very useful to capture “factual data”. Here are some examples of when to use qualitative research.

Developing a new product or generating an idea.
Studying your product/brand or service to strengthen your marketing strategy.
To understand your strengths and weaknesses.
Understanding purchase behavior.
To study the reactions of your audience to marketing campaigns and other communications.
Exploring market demographics, segments, and customer care groups.
Gathering perception data of a brand, company, or product.

LEARN ABOUT: Steps in Qualitative Research

Qualitative research methods vs quantitative research methods

The basic differences between qualitative research methods and quantitative research methods are simple and straightforward. They differ in:

Their analytical objectives
Types of questions asked
Types of data collection instruments
Forms of data they produce
Degree of flexibility

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Qualitative Research : Definition

Qualitative research is the naturalistic study of social meanings and processes, using interviews, observations, and the analysis of texts and images. In contrast to quantitative researchers, whose statistical methods enable broad generalizations about populations (for example, comparisons of the percentages of U.S. demographic groups who vote in particular ways), qualitative researchers use in-depth studies of the social world to analyze how and why groups think and act in particular ways (for instance, case studies of the experiences that shape political views).

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Last Updated: May 23, 2024 1:27 PM
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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?

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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Pritha Bhandari

16 Qualitative Methods Examples

qualitative research examples and definition, explained below

Qualitative research seeks to explore and understand individuals’ or groups’ experiences, behaviors, and social phenomena by collecting non-numerical data, such as text or images, and analyzing it in a narrative, descriptive manner.

Its strength is that it provides a deep understanding of human behavior, experiences, and social phenomena, enabling the exploration of nuances, contexts, and underlying factors that may not be evident through quantitative methods (Aurini, Heath & Howells, 2021 [ 1 ] ; Bhattacharya, 2017 [ 2 ] ).

However, its findings can be subjective, less generalizable due to smaller sample sizes, and may require a significant amount of time, effort, and expertise to collect and interpret the data accurately (Bhattacharya, 2017 [ 2 ] ; Hatch, 2023 [ 3 ] ).

Examples of qualitative research include conducting in-depth interviews to explore patients’ experiences with healthcare, utilizing focus groups to understand consumer perceptions of a product, engaging in ethnographic observation to study cultural practices, and employing case studies to investigate real-life phenomena in detail.

Qualitative Methods Examples

1. case studies.

A case study is a detailed investigation of a specific individual, group, or event over a defined period. It goes in depth in one specific case rather than achieving a broad range of participants or instances of a situation.

The main purpose of a case study is to provide an in-depth analysis and understanding of complex issues that cannot be fully captured through statistical models or broad sweeping quantitative approaches (Bhattacharya, 2017 [ 2 ] ; Lapan, Quartaroli & Riemer, 2011 [ 4 ] ).

This method often involves collecting and analyzing various forms of qualitative data such as interviews, observations, and documents.

The data is then used to construct a narrative about the case, identify themes or patterns, and draw conclusions. Case studies are often used in fields like psychology, business, and education, due to their ability to produce rich, detailed, and practical knowledge.

Real Case Study Example

Study: “Shoreline changes over last five decades and predictions for 2030 and 2040: a case study from Cuddalore, southeast coast of India.”

Explanation: This study is about estimating the shoreline changes over the past five decades in a part of the southeast coast of India at Cuddalore, and predicting the shoreline evolution for the years 2030 and 2040. This is a case study as it utilizes specific, localized data from Cuddalore to gain in-depth understanding and make future predictions about shoreline changes. However, as it’s a case study with only one location for analysis, it may not be applicable to other shorelines.

Citation: Natarajan, L., Sivagnanam, N., Usha, T., Chokkalingam, L., Sundar, S., Gowrappan, M., & Roy, P. D. (2021). Shoreline changes over last five decades and predictions for 2030 and 2040: a case study from Cuddalore, southeast coast of India. Earth Science Informatics , 14 , 1315-1325. ( Access Here )

See Also: Case Study Advantages and Disadvantages

2. Grounded Theory

Grounded theory is a research methodology that involves the collection and analysis of qualitative data with the aim of creating theories that are grounded in the data itself.

The defining feature of grounded theory is that it does not text a theory or hypothesis, unlike most other research approaches. Instead, it studies a phenomenon, allowing the theory to emerge naturally from the data (Atkinson, 2015 [ 5 ] ; Mills, Bonner & Francis, 2017 [ 6 ] ).

So, the study ends with a hypothesis by following the data rather than beginning with a hypothesis to be tested.

Researchers engaged in grounded theory begin with an area of study, then gather, code, and analyze the data, allowing the recurring patterns to evolve into a framework (Atkinson, 2015 [ 5 ] ; Mills, Bonner & Francis, 2017 [ 6 ] ).

This process continues up to the point of theoretical saturation, when no new information or themes are emerging from the data.

Real Grounded Theory Example

Study: “Developing a Leadership Identity.”

Developing a Leadership Identity by Komives et al (2005) employs a grounded theory approach to develop a thesis based on the data rather than testing a hypothesis. The researchers studied the leadership identity of 13 college students taking on leadership roles. Based on their interviews, the researchers theorized that the students’ leadership identities shifted from a hierarchical view of leadership to one that embraced leadership as a collaborative concept.

Citation: Komives, S. R., Owen, J. E., Longerbeam, S. D., Mainella, F. C., & Osteen, L. (2005). Developing a leadership identity: A grounded theory. Journal of college student development , 46 (6), 593-611. ( Access Here )

See More Grounded Theory Examples Here

3. Ethnography

Ethnography is a research method often used in anthropology, in which the researcher immerses themselves in the community or culture they are studying (Hammersley, 2018 [ 7 ] ; Jones & Smith, 2017 [ 8 ] ).

The researcher observes, interacts, and records the daily lives, behaviors, and social interactions of the community members from their perspective.

The primary aim of ethnography is to provide rich, holistic insights into people’s views and actions, as well as the nature (i.e., sights, sounds) of the location they inhabit, through the collection of detailed observations and interviews.

During the ethnographic study, the researcher usually lives within the community, allowing them to get deeper insights than they would get from just having occasional contact (Hammersley, 2018 [ 7 ] ; Jones & Smith, 2017 [ 8 ] ).

The result is a detailed description of the community’s social practices, beliefs, and experiences, often looking at such aspects as rituals, ceremonies, interactions, and daily life.

Real Ethnography Example

Study: “Liquidated: An Ethnography of Wall.”

Liquidated: An Ethnography of Wall Street by Karen Ho involves an anthropologist who embeds herself with Wall Street firms to study the culture of Wall Street bankers and how this culture affects the broader economy and world.

Citation: Ho, K. (2009). Liquidated: An Ethnography of Wall Street . Duke University Press. ( Access Here )

See More Ethnography Examples Here

4. Autoethnography

Autoethnography combines elements of autobiography and ethnography.

In autoethnography, researchers use their own personal experiences and reflections as the primary data source to gain insights into cultural, social, and individual phenomena (Pretorius & Cutri, 2019 [ 9 ] ).

The intent is to use personal narratives not only to understand the self, but also to understand the cultural context in which the self is situated.

By focusing on their own experiences, emotions, and responses within a specific cultural context, researchers seek to provide a rich, detailed, and personal account that sheds light on broader cultural norms , behaviors, and experiences (Pretorius & Cutri, 2019 [ 9 ] ).

This method is particularly common in social sciences and humanities, where understanding the complexity of human experiences and emotions is of principal importance.

Real Autoethnography Example

Study: “Living Without a Mobile Phone: An Autoethnography”

Living Without a Mobile Phone: An Autoethnography by Andres Luccero (2018) is one of the more captivating academic studies I’ve engaged with in recent months. It explores themes related to the benefits and struggles of voluntarily foregoing mobile phones (including the safety fears Luccero goes through) after systematically collecting field notes over a number of years.

Citation: Lucero, A. (2018). Living without a mobile phone: An autoethnography. In Proceedings of the 2018 Designing Interactive Systems Conference (pp. 765-776). ( Access Here )

See More Autoethnography Examples Here

5. Phenomenology

Phenomenology is a method that focuses on the commonality of a lived experience within a particular group.

The central aim is to interpret and describe the meaning of these experiences in order to capture the ‘essence’ of the phenomenon (Neubauer, Witkop & Varpio, 2019 [ 10 ] ; Zahavi, 2018 [ 11 ] ).

Researchers utilizing this method typically gather data through interviews, written stories, artefacts or other forms of personal narratives from the individuals who have experienced the phenomenon firsthand.

Then, through a process of reflecting on these first-person descriptions, researchers aim to draw out the underlying structures and themes of the experience and thereby provide a richer and deeper understanding of the phenomenon (Neubauer, Witkop & Varpio, 2019 [ 10 ] ; Zahavi, 2018 [ 11 ] ).

Phenomenology is often used in social science, psychology, and health sciences research.

Real Phenomenology Example

Study: “A phenomenological approach to experiences with technology”

A phenomenological approach to experiences with technology by Sebnem Cilesiz represents a good starting-point for formulating a phenomenological study. With its focus on the ‘essence of experience’, this piece presents methodological, reliability, validity, and data analysis techniques that phenomenologists use to explain how people experience technology in their everyday lives.

Citation: Cilesiz, S. (2011). A phenomenological approach to experiences with technology: Current state, promise, and future directions for research. Educational Technology Research and Development , 59 , 487-510. ( Access Here )

6. Narrative Research

Narrative research involves collecting and studying individuals’ lived experiences as told through their own stories. Detailed narratives help to produce detailed and nuanced accounts of phenomena (McAlpine, 2016 [ 12 ] .

This method is typically used when researchers want to capture detailed stories or life experiences related to the study’s focal area from the perspective of participants.

The research involves gathering data through methods such as interviews, diaries, personal notes, or letters, from which narratives are then constructed and analyzed for recurring themes and patterns (McAlpine, 2016 [ 12 ] .

A key value of narrative research is its emphasis on giving voice to participants’ experiences in their own words and context, making it a powerful approach to explore personal histories, cultural narratives, and complex social issues .

Real Narrative Research Example

Study: “Learning to Labour”

Learning to Labour by Paul Willis is perhaps one of the most famous examples of narrative research. In this study, Willis explored the personal identity narratives that working-class English boys created around work and school, demonstrating their choices to reject formal education and its middle-class values while many of them embraced hard work ethic for types of work they valued, namely, creative and productive physical labor.

Citation: Willis, P. E. (1981). Learning to Labor: How Working Class Kids Get Working Class Jobs. Columbia University Press. ( Access Here )

7. Action Research

Action Research is a participatory, problem-solving method which aims to improve concrete situations through a cycle of action and reflection (Jacobs, 2018 [ 13 ] ).

The core idea is that the researcher is not a passive observer but actively involved in the phenomenon being studied, working collaboratively with participants to solve real-world problems.

The cycle typically includes problem identification, planning for improvement, implementation of change, observation of the effects, and reflection on the process and results to adjust and refine the plan for the next cycle (Jacobs, 2018 [ 13 ] ).

This type of research is usually employed in education, healthcare, community development, or organizational studies, where the goal is to make practical improvements while also expanding knowledge.

Action research, thus, blurs the boundary between researcher and participant, prioritizing experiential learning, shared decision making and equitable relationships.

Real Action Research Example

Study: “Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing”

Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing by Ellison and Drew was a research study one of my research students completed in his own classroom under my supervision. He implemented a digital game-based approach to literacy teaching with boys and interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience.

Citation: Ellison, M., & Drew, C. (2020). Using digital sandbox gaming to improve creativity within boys’ writing. Journal of Research in Childhood Education , 34 (2), 277-287. ( Access Here )

See More Action Research Examples Here

8. Focus Group Research

Focus group research is a form of qualitative research where a group of people are asked about their attitudes, beliefs, experiences, and reactions to a specific subject, product, concept, or idea.

The interaction between the group members is observed and used for gathering data, as it can provide additional depth and complexity to the understanding of the topic being discussed (Guest, Namey & McKenna, 2017 [ 14 ] ; Kamberelis & Dimitriadis, 2013 [ 15 ] ).

Focus group usually involves 6-12 participants, led by a trained facilitator who guides the discussion and ensures everyone’s voice is heard.

Data collected in focus groups can be analyzed qualitatively to identify themes, patterns, or trends in people’s perceptions and experiences.

This research method is widely used in marketing, political studies, public health, and social sciences, due to its ability to provide rich, detailed and nuanced data.

Real Focus Group Example

Study: “Why people use herbal medicine: insights from a focus-group study in Germany.”

.This study investigates the reasons why people in Germany choose to use herbal medicine, including usage aims, factors associated with illness type, and sources of information. The study used a focus group approach, conducting six focus groups with 46 participants of varying ages, then analyzing the data using a content analysis method, which I’ll explain later in this article.

Citation: Welz, A. N., Emberger-Klein, A., & Menrad, K. (2018). Why people use herbal medicine: insights from a focus-group study in Germany. BMC complementary and alternative medicine , 18 , 1-9. ( Access Here )

See More Focus Group Examples Here

9. Semi-Structured Interviewing

Semi-structured interviewing is a common method of data collection in qualitative research where the interviewer directs the conversation using a predetermined set of open-ended questions, but with flexibility to explore topics in more depth (Aurini, Heath & Howells, 2021 [ 1 ] ; Bhattacharya, 2017 [ 2 ] ).

This type of interview does not follow a strict form, allowing the interviewee to express their thoughts and feelings more freely and the interviewer to adapt and probe further based on their responses.

Semi-structured interviews can cover a wide range of topics, gain detailed information, and provide a more nuanced understanding of the interviewee’s perspective and context.

While each interview is guided by a consistent list of topics (interview guide), the order can change depending on the flow of conversation, and additional questions can be asked for clarification or further exploration (Aurini, Heath & Howells, 2021 [ 1 ] .

Real Semi-Structured Interview Example

Study: “English professional football players concussion knowledge and attitude.”

The study examines the knowledge and attitude of English professional football players towards concussion and the misconceptions that exist about it. Semi-structured interviews were conducted to gather in-depth information about the players’ understanding of concussions and establish whether their intended behavior aligns with their knowledge.

Citation: Williams, J. M., Langdon, J. L., McMillan, J. L., & Buckley, T. A. (2016). English professional football players concussion knowledge and attitude. Journal of sport and health science , 5 (2), 197-204. ( Access Here )

10. Structured Interviewing

Structured interviewing is a quantitative research method where all participants are asked the same predetermined and standardized set of questions, with the same wording and in the same order (Aurini, Heath & Howells, 2021 [ 1 ] ; Bhattacharya, 2017 [ 2 ] ).

The structured interview format ensures that comparison and statistical analysis is possible since every respondent is asked exactly the same questions.

Response categories are also often predetermined and fixed, limiting the scope for exploring issues in depth, but permitting the gathering of consistent, comparable data (Aurini, Heath & Howells, 2021 [ 1 ] ; Bhattacharya, 2017 [ 2 ] ).

Structured interviewing reduces the potential impact of interviewer bias, enabling more objectivity in the responses.

This method is commonly used in large-scale surveys, market research, and social science research where researchers are interested in measuring trends, comparison between groups, or relationships between variables.

Real Structured Interview Example

Study: “Tell us about your leadership style: A structured interview approach for assessing leadership behavior constructs”

This study investigates the application of the structured interview method as a way to assess leadership behavior based on Yukl’s leadership taxonomy and examine its ability to predict leadership outcomes. The study uses structured interviews by having supervisors answer questions based on specific leadership constructs and situations, which are then analyzed and compared to other leadership measures such as self-assessments and subordinate ratings.

Citation: Heimann, A. L., Ingold, P. V., & Kleinmann, M. (2020). Tell us about your leadership style: A structured interview approach for assessing leadership behavior constructs. The Leadership Quarterly , 31 (4), 101364. ( Access Here )

11. Observational Research

Observational research is a qualitative research method where researchers observe participants in their natural setting without any direct involvement or intervention (Seim, 2021 [ 16 ] ; Lapan, Quartaroli & Riemer, 2011 [ 4 ] ).

The aim is to study people’s behavior, interactions, routines or events as they naturally occur, and as a result, gain a more authentic and holistic understanding of the phenomena being studied.

Methods of observation can vary vastly ranging from completely unobtrusive and passive observations, where participants are unaware they are being observed, to participant observations, where researchers immerse themselves into the groups to gain firsthand experience (Seim, 2021 [ 16 ] ).

The information gathered can be rich and detailed, including body language, expressions, and the context and sequence of events, offering insights that are not possible through traditional survey and experimental methods.

Real Observational Research Example

Study: “Influence of models’ reinforcement contingencies on the acquisition of imitative responses.”

The Bobo Doll Experiment by Albert Bandura is the quintessential observational study. Bandura had children watch adults interacting with a doll. Half saw adults acting roughly with the doll, the other half saw parents acting carefully with the doll. Then, Bandura observed children playing with a doll. His observations revealed that children’s observations of adult actions affect how the children will subsequently treat the doll.

Citation: Bandura, A. (1965). Influence of models’ reinforcement contingencies on the acquisition of imitative responses. Journal of Personality and Social Psychology, 1 (6), 589–595. ( Access Here )

See More Observational Research Examples Here

12. Delphi Method

The Delphi Method is a structured communication technique used in qualitative research that relies on a panel of experts (Brady, 2015 [ 17 ] ).

The process begins with researchers presenting a problem to the experts who respond individually, usually through a series of questionnaires or online surveys.

Responses are collected and summarized anonymously, then feedback is given to the group, allowing experts to revise their earlier answers based on the replies of their peers (Brady, 2015 [ 17 ] ).

Throughout multiple rounds, the group seeks to reach a consensus on the issue being investigated while minimizing bias because of group interaction.

The Delphi method is often used in predictive research, policy-making, decision-support, and system and technology forecasting where expert opinions are valuable.

Real Delphi Method Example

Study: “Assessing advisor competencies: A Delphi method study.”

This study aims to identify essential competencies for entry-level academic advisors. The Delphi method was employed through surveys administered to academic advisors with 5 or more years of experience, and their responses were analyzed to build consensus on the essential competencies for entry-level academic advisors. A consensus was reached on three essential competencies: Communication skills, interpersonal skills, and knowledge of university policies and resources.

Citation: Menke, D., Stuck, S., & Ackerson, S. (2018). Assessing advisor competencies: A Delphi method study. The Journal of the National Academic Advising Association , 38 (1), 12-21. ( Access Here )

13. Textual & Content Analysis

Textual analysis , also known as content analysis, is a qualitative research method used to interpret the content and meaning of textual material in a systematic way.

Researchers using this approach analyze the communication content (like books, essays, interviews, speeches, online posts, etc.) in order to decipher patterns, themes, biases, and other cultural, societal, or thematic elements.

A researcher might analyze the themes, symbols, motifs, dialogues, plot structures, or stylistic choices in a text, in an attempt to understand how these elements contribute to its overall meaning and potential effects on its audience.

I have a detailed explanation of how to conduct a qualitative content analysis in my article on inductive coding , and I also highly recommend Attride-Stirling’s (2001) [ 18 ] article on thematic network analysis for a step-by-step guide.

Textual analysis is commonly used in fields such as communication studies, literature, history, sociology, cultural studies, media studies, and more.

Real Textual Analysis Example

Study: “Making sense of “alternative”, “complementary”, “unconventional” and “integrative” medicine.”

This study analyzes the usage and evolution of terms like “alternative”, “complementary”, “unconventional” and “integrative” in medicine. It uses textual analysis by breaking down and examining the context, meaning, and usage of these terms in influential medical publications between 1970 and 2013 to understand their significance and implications in the discourse of unconventional medicine.

Citation: Ng, J. Y., Boon, H. S., Thompson, A. K., & Whitehead, C. R. (2016). Making sense of “alternative”, “complementary”, “unconventional” and “integrative” medicine: exploring the terms and meanings through a textual analysis. BMC complementary and alternative medicine , 16 (1), 1-18. ( Access Here )

See More Content Analysis Examples Here

14. Discourse Analysis

Discourse analysis is a qualitative research method used to analyze written, verbal, or sign language use or any significant semiotic event. It differs from textual analysis in its focus on the concept of emergent and dominant discourses , based on Foucauldian theory (Fairclough, 2013 [ 19 ] ).

The main purpose is to understand how language is used in real-life situations and uncover the social, cultural, and psychological structures that underlie the text or talk in its specific context (i.e. the discourses).

Discourse analysis considers language at several levels, such as sounds, words, sentences, speech acts, conversations, and narratives, and explores how these elements shape and are shaped by social practices, identities, relationships, and power dynamics.

It also looks beyond explicit meaning to explore implicit messages, underlying assumptions, and ideological standpoints that are conveyed through language.

This method is applied in a wide range of disciplines, including linguistics, psychology, sociology, anthropology, communication studies, and cognitive and cultural studies.

Real Discourse Analysis Example

Study: “How is Islam portrayed in western media? A critical discourse analysis perspective.”

How is Islam Portrayed in Western Media? By Poorebrahim and Zarei (2013) represents a typical critical discourse analysis. This study combs through a corpus of western media texts to explore the language forms that are used in relation to Islam and Muslims, finding that they are overly stereotyped, which may represent anti-Islam bias or failure to understand the Islamic world.

Citation: Poorebrahim, F., & Zarei, G. (2013). How is Islam portrayed in western media? A critical discourse analysis perspective. International Journal of Foreign Language Teaching and Research , 1 (2), 57-75. ( Access Here )

See More Discourse Analysis Examples Here

15. Life History Research

Life history research is a qualitative methodology that focuses on understanding people’s lives and experiences through their personal narratives over a prolonged period, usually their entire life (Goodson & Sykes, 2016 [ 20 ] ) .

The objective is to gain in-depth insight into the subjective experiences, cultural contexts, identity development, decision-making processes, and changes over time.

Methods commonly used in life history research include interviews, diaries, photo elicitation or other artifacts, aiming to capture a rich, detailed, and holistic account of the person’s life (Goodson & Sykes, 2016 [ 20 ] ).

In interpreting the data, researchers pay attention to how the individual makes sense of their life trajectory, the pivotal moments, their relationships, and how historical and sociocultural contexts influence their life events and perceptions.

The life history method is suitable for research in diverse fields such as education, psychology, sociology, anthropology, and health sciences, particularly when studying themes like identity, resilience, transformation, and moral development over time.

Study: “The study of life history: Gandhi.”

The Study of Life History: Gandhi by David Mandelbaum conducts a life history analysis of Gandhi by exploring his biographies and texts about his life. Through this analysis, Mandelbaum contextualized Gandhi’s life achievements and decisions in the banal experiences of fatherhood an nationhood, with an attempt to humanize the Indian hero and re-imagine his role in the development of modern India.

Citation: Mandelbaum, D. G. (1973). The study of life history: Gandhi. Current anthropology , 14 (3), 177-206. ( Access Here )

16. Semiotic Analysis

Semiotic analysis is like textual analysis, but has its own range of methods for examining how multimodal texts (images, video, movements) convey meaning in cultural contexts (Andersen et al., 2015 [ 21 ] ; Gualberto & Kress, 2019 [ 22 ] ).

The approach acknowledges that things (signs) can stand for something else and carry a particular meaning, especially within a social or cultural contexts.

So, this approach involves examining the signs and symbols that are used in various forms of communication, such as language, imagery, body language, music, and even things like fashion and food (Gualberto & Kress, 2019 [ 22 ] ).

The process of this method typically includes identifying the signs, exploring the system or code that organizes these signs (syntax), and interpreting how these signs work to inform or influence our ideas and beliefs (semantics).

By providing these insights, semiotic analysis helps researchers understand societal norms, cultural values , power relations, ideological beliefs, and more.

Study: “Visualizing teens and technology: A social semiotic analysis of stock photography and news media imagery.”

This study provides an analysis of how teenagers and their usage of digital media are visually represented in stock photography and news media imagery. Semiotic analysis is used to discern the meanings embedded in these visual representations and identify recurring patterns through the exploration of representational, compositional, and interpersonal meanings to uncover the underlying ideologies at play.

Citation: Thurlow, C., Aiello, G., & Portmann, L. (2020). Visualizing teens and technology: A social semiotic analysis of stock photography and news media imagery. New media & society , 22 (3), 528-549. ( Access Here )

Pros and Cons of Qualitative Research

Qualitative research offers a profound understanding of human behaviors , experiences, and the underlying factors driving these phenomena, which often cannot be achieved through quantitative methods.

By employing methods like in-depth interviews, focus groups, or ethnographic studies, most types of qualitative research allow for a detailed exploration of complex issues , providing rich, contextual insights (Bhattacharya, 2017 [ 2 ] ; Merriam & Tisdell, 2015 [ 23 ] ).

Furthermore, the flexible design of qualitative research enables researchers to adjust their approaches as new themes or patterns emerge during the study, allowing for a more nuanced understanding of the research topic.

However, one of the significant disadvantages of qualitative research is its potential for subjectivity (Hatch, 2023 [ 3 ] ; Weaver-Hightower, 2018 [ 24 ] ). The researcher’s perspectives and interactions with participants can influence the data collection and interpretation, possibly leading to biased or skewed findings.

Additionally, the inherent nature of qualitative research, which often relies on small, non-random samples, may result in findings that are not easily generalizable to a larger population (Bhattacharya, 2017 [ 2 ] ; Lapan, Quartaroli & Riemer, 2011 [ 4 ] ). This lack of generalizability can be a drawback when the goal is to make broader inferences or when comparing findings across different groups or settings.

The following table summarizes the pros and cons:

Read More about Qualitative Research Here

Before you Go

When doing qualitative research, you’ll need to know about qualitative variables. So, read my guide to qualitative variables next – it’ll help with writing your methodology section in your dissertation!

[1] Aurini, J. D., Heath, M., & Howells, S. (2021). The How To of Qualitative Research . SAGE Publications.

[2] Bhattacharya, K. (2017). Fundamentals of Qualitative Research: A Practical Guide . Taylor & Francis.

[3] Hatch, J. A. (2023). Doing Qualitative Research in Education Settings, Second Edition . State University of New York Press.

[4] Lapan, S. D., Quartaroli, M. T., & Riemer, F. J. (2011). Qualitative Research: An Introduction to Methods and Designs . Wiley.

[5] Atkinson, P. (2015). Grounded theory and the constant comparative method: Valid qualitative research strategies for educators. Journal of Emerging Trends in Educational Research and Policy Studies, 6 (1), 83-86. ( Source )

[6] Mills, J., Bonner, A., & Francis, K. (2017). Adopting a Constructivist Approach to Grounded Theory: Implications for Research Design. International Journal of Nursing Practice, 13 (2), 81-89. ( Source )

[7] Hammersley, M. (2018). What is ethnography? Can it survive? Should it?. Ethnography and education , 13 (1), 1-17. ( Source )

[8] Jones, J., & Smith, J. (2017). Ethnography: challenges and opportunities. Evidence-Based Nursing , 20 (4), 98-100. ( Source )

[9] Pretorius, L., & Cutri, J. (2019). Autoethnography: Researching personal experiences. Wellbeing in doctoral education: Insights and guidance from the student experience , 27-34. ( Source )

[10] Neubauer, B. E., Witkop, C. T., & Varpio, L. (2019). How phenomenology can help us learn from the experiences of others. Perspectives on medical education , 8 , 90-97. ( Source )

[11] Zahavi, D. (2018). Phenomenology: the basics . Routledge.

[12] McAlpine, L. (2016). Why might you use narrative methodology? A story about narrative. Eesti Haridusteaduste Ajakiri. Estonian Journal of Education , 4 (1), 32-57. ( Source )

[13] Jacobs, S. D. (2018). A history and analysis of the evolution of action and participatory action research. The Canadian Journal of Action Research , 19 (3), 34-52. ( Source )

[14] Guest, G., Namey, E., & McKenna, K. (2017). How many focus groups are enough? Building an evidence base for nonprobability sample sizes. Field methods , 29 (1), 3-22. ( Source )

[15] Kamberelis, G., & Dimitriadis, G. (2013). Focus Groups: From Structured Interviews to Collective Conversations . London: Routledge.

[16] Seim, J. (2021). Participant observation, observant participation, and hybrid ethnography. Sociological Methods & Research , 0049124120986209. ( Source )

[17] Brady, S. R. (2015). Utilizing and adapting the Delphi method for use in qualitative research. International Journal of Qualitative Methods , 14 (5), 1609406915621381.

[18] Attride-Stirling, J. (2001). Thematic networks: an analytic tool for qualitative research. Qualitative research , 1 (3), 385-405.

[19] Fairclough, N. (2013). Critical discourse analysis: The critical study of language . London: Routledge.

[20] Goodson, I., & Sikes, P. (2016). Techniques for doing life history. In The Routledge international handbook on narrative and life history (pp. 82-98). Routledge.

[21] Andersen, T. H., Boeriis, M., Maagerø, E., & Tonnessen, E. S. (2015). Social semiotics: Key figures, new directions . Routledge.

[22] Gualberto, C., & Kress, G. (2019). Social semiotics. The international encyclopedia of media literacy , 1-9.

[23] Merriam, S. B., & Tisdell, E. J. (2015). Qualitative Research: A Guide to Design and Implementation . Wiley.

[24] Weaver-Hightower, M. B. (2018). How to Write Qualitative Research . Taylor & Francis.

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Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

Provide an overview of the research problem and the need for a research methodology section
Outline the main research questions and objectives

II. Research Design

Explain the research design chosen and why it is appropriate for the research question(s) and objectives
Discuss any alternative research designs considered and why they were not chosen
Describe the research setting and participants (if applicable)

III. Data Collection Methods

Describe the methods used to collect data (e.g., surveys, interviews, observations)
Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
Detail any procedures or software used for data analysis

V. Ethical Considerations

Discuss any ethical issues that may arise from the research and how they were addressed
Explain how informed consent was obtained (if applicable)
Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

Summarize the key aspects of the research methodology section
Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

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6 Qualitative data examples for thorough market researchers

Types of qualitative data in market research, 6 qualitative data examples, get nuanced insights from qualitative market research.

There are plenty of ways to gather consumer insights for fresh campaigns and better products, but qualitative research is up there with the best sources of insight.

This guide is packed with examples of how to turn qualitative data into actionable insights, to spark your creativity and sharpen your research strategy. You’ll see how qualitative data, especially through surveys, opens doors to deeper understanding by inviting consumers to share their experiences and thoughts freely, in their own words — and how qualitative data can transform your brand.

Before we dig into some examples of how qualitative data can empower your teams to make focused, confident and quick decisions on anything from product to marketing, let’s go back to basics. We can categorize qualitative data into roughly three categories: binary, nominal and ordinal data. Here’s how each of them is used in qualitative data analysis.

Binary data

Binary data represents a choice between two distinct options, like ‘yes’ or ‘no’. In market research, this type of qualitative data is useful for filtering responses or making clear distinctions in consumer preferences.

Binary data in qualitative research is great for straightforward insights, but has its limits. Here’s a quick guide on when to use it and when to opt for qualitative data that is more detailed:

Binary data is great for:

Quick Yes/No questions : like “Have you used our app? Yes or No.”
Initial screening : to quickly sort participants for further studies.
Clear-cut answers : absolute factors, such as ownership or usage.

Avoid binary data for:

Understanding motivations : it lacks the depth to explore why behind actions.
Measuring intensity : can’t show how much someone likes or uses something.
Detail needed for product development : misses the nuanced feedback necessary for innovations.

example of methodology qualitative research

Nominal data

Nominal data categorizes responses without implying any order. For example, when survey respondents choose their favorite brand from a list, the data collected is nominal, offering insights into brand preferences among different demographics.

Some other examples of qualitative data that can be qualified as nominal are asking participants to name their primary information source about products in categories like social media, friends, or online reviews. Or in focus groups, discussing brand perceptions could classify brands into categories such as luxury, budget-friendly, or eco-conscious, based on participant descriptions.

Nominal data is great for:

Categorizing responses : such as types of consumer complaints (product quality, customer service, delivery issues).
Identifying preferences : like favorite product categories (beverages, electronics, apparel).
Segmentation : grouping participants based on attributes (first-time buyers, loyal customers).

Nominal data is not for:

Measuring quantities : it can’t quantify how much more one category is preferred over another.
Ordering or ranking responses : it doesn’t indicate which category is higher or lower in any hierarchy.
Detailed behavioral analysis : While it can group behaviors, it doesn’t delve into the frequency or intensity of those behaviors.

Ordinal data

Ordinal data introduces a sense of order, ranking preferences or satisfaction levels. In qualitative analysis, it’s particularly useful for understanding how consumers prioritize features or products, giving researchers a clearer picture of market trends.

Other examples of qualitative data analyses that use ordinal data, are for instance a study on consumer preferences for coffee flavors, participants might rank flavors in order of preference, providing insights into flavor trends. You can also get ordinal data from focus groups on things like customer satisfaction surveys or app usability, by asking users to rate their ease of use or happiness on an ordinal scale.

Ordinal data is great for:

Ranking preferences : asking participants to rank product features from most to least important.
Measuring satisfaction levels : using scales like “very satisfied,” “satisfied,” “neutral,” “dissatisfied,” “very dissatisfied.”
Assessing Agreement : with statements on a scale from “strongly agree” to “strongly disagree.”

Ordinal data is not for:

Quantifying differences : it doesn’t show how much more one rank is preferred over another, just the order.
Precise measurements : can’t specify the exact degree of satisfaction or agreement, only relative positions.

This mix of qualitative and quantitative data will give you a well-rounded view of participant attitudes and preferences.

The things you can do with qualitative data are endless. But this article shouldn’t turn into a work of literature, so we’ll highlight six ways to collect qualitative data and give you examples of how to use these qualitative research methods to get actionable results.

How to get qual insights with Attest

You can get to the heart of what your target customers think, with reliable qualitative insights from Attest Video Responses

1. Highlighting brand loyalty drivers with open-ended surveys and questionnaires

Open-ended surveys and questionnaires are great at finding out what makes customers choose and stick with a brand. Here’s why this qualitative data analysis tool is so good for gathering qualitative data on things like brand loyalty and customer experience:

Straight from the source

Open-ended survey responses show the actual thoughts and feelings of your target audience in their own words, while still giving you structure in your data analysis.

Understanding ‘why’

Numbers can show us how many customers are loyal; open-ended survey responses explain why they are. You can also easily add thematic analysis to the mix by counting certain keywords or phrases.

Guiding decisions

The insights from these surveys can help a brand decide where to focus its efforts, from making sure their marketing highlights what customers love most to improving parts of their product.

Surveys are one of the most versatile and efficient qualitative data collection methods out there. We want to bring the power of qualitative data analysis to every business and make it easy to gather qualitative data from the people who matter most to your brand. Check out our survey templates to hit the ground running. And you’re not limited to textual data as your only data source — we also enable you to gather video responses to get additional context from non verbal cues and more.

2. Trend identification with observation notes

Observation notes are a powerful qualitative data analysis tool for spotting trends as they naturally unfold in real-world settings. Here’s why they’re particularly valuable insights and effective for identifying new trends:

Real behavior

Observing people directly shows us how they actually interact with products or services, not just how they say they do. This can highlight emerging trends in consumer behavior or preferences before people can even put into words what they are doing and why.

Immediate insights

By watching how people engage with different products, we can quickly spot patterns or changes in behavior. This immediate feedback is invaluable for catching trends as they start.

Context matters

Observations give you context. You can see not just what people do, but where and how they do it. This context can be key to understanding why a trend is taking off.

Unprompted reactions

Since people don’t know they’re being observed for these purposes, their actions are genuine. This leads to authentic insights about what’s really catching on.

3. Understanding consumer sentiments through semi-structured interviews

Semi-structured interviews for qualitative data analysis are an effective method for data analysts to get a deep understanding of consumer sentiments. It provides a structured yet flexible approach to gather in-depth insights. Here’s why they’re particularly useful for this type of research question:

Personal connection

These interviews create a space for a real conversation, allowing consumers to share their feelings, experiences, and opinions about a brand or product in a more personal setting.

Flexibility

The format lets the interviewer explore interesting points that come up during the conversation, diving deeper into unexpected areas of discussion. This flexibility uncovers richer insights than strictly structured interviews.

Depth of understanding

By engaging in detailed discussions, brands can understand not just what consumers think but why they think that way and what stations their train of thought passes by.

Structure and surprise

Semi-structured interviews can be tailored to explore specific areas of interest while still allowing for new insights to emerge.

4. Using focus groups for informing market entry strategies

Using a focus group to inform market entry strategies provides a dynamic way to discover your potential customers’ needs, preferences, and perceptions before launching a product or entering a new market. Here’s how focus groups can be particularly effective for this kind of research goal:

Real conversations

Focus groups allow for real-time, interactive discussions, giving you a front-row seat to hear what your potential customers think and feel about your product or service idea.

Diverse Perspectives

By bringing together people from various backgrounds, a focus group can offer a wide range of views and insights, highlighting different consumer needs and contextual information that you might miss out on in a survey.

Spotting opportunities and challenges

The dynamic nature of focus groups can help uncover unique market opportunities or potential challenges that might not be evident through other research methods, like cultural nuances.

Testing ideas

A focus group is a great way to test and compare reactions to different market entry strategies, from pricing models to distribution channels, providing clear direction on what approach might work best.

5. Case studies to gain a nuanced understanding of consumers on a broad level

Case studies in qualitative research zoom in on specific stories from customers or groups using a product or service, great for gaining a nuanced understanding of consumers at a broad level. Here’s why case studies are a particularly effective qualitative data analysis tool for this type of research goal:

In-depth analysis

Case studies can provide a 360-degree look at the consumer experience, from initial awareness to post-purchase feelings.

This depth of insight reveals not just what consumers do, but why they do it, uncovering motivations, influences, and decision-making processes.

Longitudinal insight

Case studies can track changes in consumer behavior or satisfaction over time, offering a dynamic view of how perceptions evolve.

This longitudinal perspective is crucial for giving context to the lifecycle of consumer engagement with a brand.

Storytelling power

The narrative nature of case studies — when done right — makes them powerful tools for communicating complex consumer insights in an accessible and engaging way, which can be especially useful for internal strategy discussions or external marketing communications.

6. Driving product development with diary studies

Diary studies are a unique qualitative research method that involves participants recording their thoughts, experiences, or behaviors over a period of time, related to using a product or service. This qualitative data analysis method is especially valuable for driving product development for several reasons:

Real-time insights

Diary studies capture real-time user experiences and feedback as they interact with a product in their daily lives.

This ongoing documentation provides a raw, unfiltered view of how a product fits into the user’s routine, highlighting usability issues or unmet needs that might not be captured in a one-time survey or interview.

Realistic user journey mapping

By analyzing diary entries, you can map out the entire user journey, identifying critical touch points where users feel delighted, frustrated, or indifferent.

This then enables you to implement targeted improvements and innovations at the moments that matter most.

Identifying patterns

Over the course of a diary study, patterns in behavior, preferences, and challenges can emerge, which is great for thematic analysis.

It can guide product developers to prioritize features or fixes that will have the most significant impact on user satisfaction, which is especially great if they don’t know what areas to focus on first.

Qualitative research brings your consumers’ voices directly to your strategy table. The examples we’ve explored show how qualitative data analysis methods like surveys, interviews, and case studies illuminate the ‘why’ behind consumer choices, guiding more informed decisions. Using these insights means crafting products and messages that resonate deeply, ensuring your brand not only meets but exceeds consumer expectations.

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Choosing a Qualitative Research Approach

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Editor's Note: The online version of this article contains a list of further reading resources and the authors' professional information .

The Challenge

Educators often pose questions about qualitative research. For example, a program director might say: “I collect data from my residents about their learning experiences in a new longitudinal clinical rotation. If I want to know about their learning experiences, should I use qualitative methods? I have been told that there are many approaches from which to choose. Someone suggested that I use grounded theory, but how do I know this is the best approach? Are there others?”

What Is Known

Qualitative research is the systematic inquiry into social phenomena in natural settings. These phenomena can include, but are not limited to, how people experience aspects of their lives, how individuals and/or groups behave, how organizations function, and how interactions shape relationships. In qualitative research, the researcher is the main data collection instrument. The researcher examines why events occur, what happens, and what those events mean to the participants studied. 1 , 2

Qualitative research starts from a fundamentally different set of beliefs—or paradigms—than those that underpin quantitative research. Quantitative research is based on positivist beliefs that there is a singular reality that can be discovered with the appropriate experimental methods. Post-positivist researchers agree with the positivist paradigm, but believe that environmental and individual differences, such as the learning culture or the learners' capacity to learn, influence this reality, and that these differences are important. Constructivist researchers believe that there is no single reality, but that the researcher elicits participants' views of reality. 3 Qualitative research generally draws on post-positivist or constructivist beliefs.

Qualitative scholars develop their work from these beliefs—usually post-positivist or constructivist—using different approaches to conduct their research. In this Rip Out, we describe 3 different qualitative research approaches commonly used in medical education: grounded theory, ethnography, and phenomenology. Each acts as a pivotal frame that shapes the research question(s), the method(s) of data collection, and how data are analyzed. 4 , 5

Choosing a Qualitative Approach

Before engaging in any qualitative study, consider how your views about what is possible to study will affect your approach. Then select an appropriate approach within which to work. Alignment between the belief system underpinning the research approach, the research question, and the research approach itself is a prerequisite for rigorous qualitative research. To enhance the understanding of how different approaches frame qualitative research, we use this introductory challenge as an illustrative example.

The clinic rotation in a program director's training program was recently redesigned as a longitudinal clinical experience. Resident satisfaction with this rotation improved significantly following implementation of the new longitudinal experience. The program director wants to understand how the changes made in the clinic rotation translated into changes in learning experiences for the residents.

Qualitative research can support this program director's efforts. Qualitative research focuses on the events that transpire and on outcomes of those events from the perspectives of those involved. In this case, the program director can use qualitative research to understand the impact of the new clinic rotation on the learning experiences of residents. The next step is to decide which approach to use as a frame for the study.

The table lists the purpose of 3 commonly used approaches to frame qualitative research. For each frame, we provide an example of a research question that could direct the study and delineate what outcomes might be gained by using that particular approach.

Methodology Overview

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How You Can Start TODAY

1 Examine the foundations of the existing literature: As part of the literature review, make note of what is known about the topic and which approaches have been used in prior studies. A decision should be made to determine the extent to which the new study is exploratory and the extent to which findings will advance what is already known about the topic.
2 Find a qualitatively skilled collaborator: If you are interested in doing qualitative research, you should consult with a qualitative expert. Be prepared to talk to the qualitative scholar about what you would like to study and why . Furthermore, be ready to describe the literature to date on the topic (remember, you are asking for this person's expertise regarding qualitative approaches—he or she won't necessarily have content expertise). Qualitative research must be designed and conducted with rigor (rigor will be discussed in Rip Out No. 8 of this series). Input from a qualitative expert will ensure that rigor is employed from the study's inception.
3 Consider the approach: With a literature review completed and a qualitatively skilled collaborator secured, it is time to decide which approach would be best suited to answering the research question. Questions to consider when weighing approaches might include the following:
• Will my findings contribute to the creation of a theoretical model to better understand the area of study? ( grounded theory )
• Will I need to spend an extended amount of time trying to understand the culture and process of a particular group of learners in their natural context? ( ethnography )
• Is there a particular phenomenon I want to better understand/describe? ( phenomenology )

What You Can Do LONG TERM

1 Develop your qualitative research knowledge and skills : A basic qualitative research textbook is a valuable investment to learn about qualitative research (further reading is provided as online supplemental material). A novice qualitative researcher will also benefit from participating in a massive online open course or a mini-course (often offered by professional organizations or conferences) that provides an introduction to qualitative research. Most of all, collaborating with a qualitative researcher can provide the support necessary to design, execute, and report on the study.
2 Undertake a pilot study: After learning about qualitative methodology, the next best way to gain expertise in qualitative research is to try it in a small scale pilot study with the support of a qualitative expert. Such application provides an appreciation for the thought processes that go into designing a study, analyzing the data, and reporting on the findings. Alternatively, if you have the opportunity to work on a study led by a qualitative expert, take it! The experience will provide invaluable opportunities for learning how to engage in qualitative research.

Supplementary Material

The views expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Uniformed Services University of the Health Sciences, the Department of the Navy, the Department of Defense, or the US government.

References and Resources for Further Reading

Research Methodology

Methodology refers to the overarching strategy and rationale of your research. Developing your methodology involves studying the research methods used in your field and the theories or principles that underpin them, in order to choose the approach that best matches your research objectives. Methodology is the first step in planning a research project.

Qualitative Data Coding

What Is a Focus Group?

Reviewed by Olivia Guy-Evans, MSc

Cross-Cultural Research Methodology In Psychology

What is internal validity in research.

Reviewed by Saul Mcleod, PhD

Scientific Method

Qualitative research, experiments.

The scientific method is a step-by-step process used by researchers and scientists to determine if there is a relationship between two or more variables. Psychologists use this method to conduct psychological research, gather data, process information, and describe behaviors.

Learn More: Steps of the Scientific Method

Variables apply to experimental investigations. The independent variable is the variable the experimenter manipulates or changes. The dependent variable is the variable being tested and measured in an experiment, and is 'dependent' on the independent variable.

Learn More: Independent and Dependent Variables

When you perform a statistical test a p-value helps you determine the significance of your results in relation to the null hypothesis. A p-value less than 0.05 (typically ≤ 0.05) is statistically significant.

Learn More: P-Value and Statistical Significance

Qualitative research is a process used for the systematic collection, analysis, and interpretation of non-numerical data. Qualitative research can be used to gain a deep contextual understanding of the subjective social reality of individuals.

The experimental method involves the manipulation of variables to establish cause-and-effect relationships. The key features are controlled methods and the random allocation of participants into controlled and experimental groups.

Learn More: How the Experimental Method Works in Psychology

Frequent Asked Questions

What does p-value of 0.05 mean?

A p-value less than 0.05 (typically ≤ 0.05) is statistically significant. It indicates strong evidence against the null hypothesis, as there is less than a 5% probability the results have occurred by random chance rather than a real effect. Therefore, we reject the null hypothesis and accept the alternative hypothesis.

However, it is important to note that the p-value is not the only factor that should be considered when interpreting the results of a hypothesis test. Other factors, such as effect size, should also be considered.

Learn More: What A p-Value Tells You About Statistical Significance

What does z-score tell you?

A z-score describes the position of a raw score in terms of its distance from the mean when measured in standard deviation units. It is also known as a standard score because it allows the comparison of scores on different variables by standardizing the distribution. The z-score is positive if the value lies above the mean and negative if it lies below the mean.

Learn More: Z-Score: Definition, Calculation, Formula, & Interpretation

What is an independent vs dependent variable?

The independent variable is the variable the experimenter manipulates or changes and is assumed to have a direct effect on the dependent variable. For example, allocating participants to either drug or placebo conditions (independent variable) to measure any changes in the intensity of their anxiety (dependent variable).

Learn More : What are Independent and Dependent Variables?

What is the difference between qualitative and quantitative?

Quantitative data is numerical information about quantities and qualitative data is descriptive and regards phenomena that can be observed but not measured, such as language.

Learn More: What’s the difference between qualitative and quantitative research?

Explore Research Methodology

Businessman holding pencil at big complete checklist with tick marks

What Is Face Validity In Research? Importance & How To Measure

Criterion Validity: Definition & Examples

Convergent Validity: Definition and Examples

Content Validity in Research: Definition & Examples

Construct Validity In Psychology Research

Concurrent Validity In Psychology

Internal vs. External Validity In Psychology

Qualitative Research: Characteristics, Design, Methods & Examples

Demand Characteristics In Psychology: Definition, Examples & Control

Between-Subjects vs. Within-Subjects Study Design

Random Assignment in Psychology: Definition & Examples

Double-Blind Experimental Study And Procedure Explained

Observer Bias: Definition, Examples & Prevention

Sampling Bias: Types, Examples & How to Avoid It

Probability and statistical significance in ab testing. Statistical significance in a b experiments

What is The Null Hypothesis & When Do You Reject The Null Hypothesis

Between-Subjects Design: Overview & Examples

What Is A Case Control Study?

Case Study Research Method in Psychology

Cohort Study: Definition, Designs & Examples

Cluster Sampling: Definition, Method and Examples

Convenience Sampling: Definition, Method and Examples

Confounding Variables in Psychology: Definition & Examples

In experiments, scientists compare a control group and an experimental group that is identical in all respects. Unlike the experimental group, the control group is not exposed to the variable under investigation. It provides a baseline against which any changes in the experimental group can be compared.

Control Group vs Experimental Group

Controlled Experiment

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Correlation in Psychology: Meaning, Types, Examples & coefficient

Extraneous Variables In Research: Types & Examples

Ethnocentrism In Psychology: Examples, Disadvantages, & Cultural Relativism

Ethical Considerations In Psychology Research

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Open Access

Peer-reviewed

Research Article

Developing a hope-focused intervention to prevent mental health problems and improve social outcomes for young women who are not in education, employment, or training (NEET): A qualitative co-design study in deprived coastal communities in South-East England

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Primary Care and Public Health, Brighton and Sussex Medical School, University of Brighton, Falmer, Brighton, United Kingdom

Roles Conceptualization, Formal analysis, Funding acquisition, Methodology, Supervision, Writing – original draft, Writing – review & editing

Affiliation Research and Development, Sussex Partnership NHS Foundation Trust, Sussex Education Centre, Hove, United Kingdom

Roles Conceptualization, Formal analysis, Funding acquisition, Methodology, Writing – review & editing

Affiliation Centre for Health Services Studies, University of Kent, Canterbury, Kent, United Kingdom

Roles Data curation, Formal analysis, Investigation, Project administration, Writing – review & editing

Affiliation School of Psychology, University of Sussex, Falmer, Brighton, United Kingdom

Roles Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing – review & editing

Roles Data curation, Formal analysis, Investigation, Methodology, Writing – review & editing

Roles Data curation, Investigation, Project administration, Writing – review & editing

Roles Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing

Affiliations School of Psychology, University of Sussex, Falmer, Brighton, United Kingdom, Department of Child & Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom, NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust and King’s College London, London, United Kingdom

Clio Berry,
Julia Fountain,
Lindsay Forbes,
Leanne Bogen-Johnston,
Abigail Thomson,
Yelena Zylko,
Alice Tunks,
Sarah Hotham,
Daniel Michelson

Published: May 31, 2024
https://doi.org/10.1371/journal.pone.0304470
Peer Review
Reader Comments

Young women who are not in education, employment, or training (NEET) experience poorer health and social outcomes compared to non-NEET young women and to NEET young men, especially in deprived areas with intersecting inequalities. The evidence on effective public health approaches is scarce. Interventions that target hope, which NEET young women notably lack, offer a promising theory-driven and intuitive means to prevent mental health problems and improve social outcomes. Hope can be defined as a goal-focused mindset comprising self-agency (motivation and self-belief) and pathways (identifying routes to achieving goals). Hope is implicated in a variety of evidence-based psychosocial interventions for young people, but is not directly targeted by existing prevention programmes for NEET populations. The current study used a phased qualitative research design and participatory methods to model a hope-focused intervention for NEET young women. Phase 1 investigated population needs and intervention parameters through semi-structured interviews with 28 key informants living or working in disadvantaged coastal communities in South-East England. The sample comprised eight NEET young women, four family members, and 16 practitioners from relevant support organisations. Phase 2 refined intervention parameters and outcomes through co-design sessions with four NEET young women, followed by a theory of change workshop with 10 practitioners. The resulting intervention model is articulated as a mentor-supported, in-person psychosocial intervention that builds hope by enhancing positive sense of self and time spent in meaningful activities, before explicitly teaching the skills needed to identify, set, and pursue personally meaningful goals.

Citation: Berry C, Fountain J, Forbes L, Bogen-Johnston L, Thomson A, Zylko Y, et al. (2024) Developing a hope-focused intervention to prevent mental health problems and improve social outcomes for young women who are not in education, employment, or training (NEET): A qualitative co-design study in deprived coastal communities in South-East England. PLoS ONE 19(5): e0304470. https://doi.org/10.1371/journal.pone.0304470

Editor: Ali B. Mahmoud, St John’s University, UNITED STATES

Received: June 5, 2023; Accepted: May 13, 2024; Published: May 31, 2024

Copyright: © 2024 Berry et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data in the form of collected interview transcripts are not shared publicly due to ethical concerns regarding potential identifiability. These interview transcripts were collected from a small number of individuals, from specific populations within identified geographical regions. Participants were not asked to consent specifically to the public sharing of their verbatim transcripts in full. However, the full analysis with raw data in the form of verbatim quotes is presented as Supporting information and this analysis presents all relevant data. Full data for Phase 2 co-design participant rankings of proposed intervention components are presented Supporting information .

Funding: This study was funded by an Application Development Award (reference NIHR135316) from the Public Health Research Programme of the UK National Institute for Health and Care Research (NIHR; https://www.nihr.ac.uk/explore-nihr/funding-programmes/public-health-research.htm ), awarded to DM, CB, JF and LF. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Young people who are Not in Education, Employment, or Training (NEET) are a cause of major public health concern. In the UK, they account for approximately 14% of 16–24-year-olds [ 1 ]; globally this figure rises to approximately 1 in 5 young people, with young women significantly more likely to be NEET [ 2 ]. NEET young people experience significantly worse health outcomes and life chances than economically active and socially engaged peers [ 3 ]. Mental health problems are especially prevalent, with anxiety and depression around twice as common in the NEET group compared with young people generally [ 4 ]. Being NEET additionally puts young people at elevated risk of sequelae such as self-harm and psychiatric hospitalisation [ 4 – 6 ], and robustly predicts transition from mild mental health symptoms to disorders of diagnostic severity [ 7 , 8 ]. ‘Scarring’ effects are additionally observed, such that time spent NEET in adolescence is associated with chronic mental health problems, unemployment, and low wages over 20 years later [ 9 , 10 ].

In the UK, as globally, the number of NEET young women is increasing [ 1 ]. Risk factors and outcomes for NEET status show marked gendered inequalities. Young women have worse mental health than male peers at school, and poorer adjustment over post-school transitions [ 11 ]. Young women have a higher risk than young men of becoming NEET in the context of family unemployment, deprived backgrounds, when they themselves have poor educational achievement, and when they have caring responsibilities [ 12 – 17 ]. Once NEET, UK data [ 12 ] demonstrates that, compared to non-NEET young people and to NEET young men, NEET young women face complex constellations of cumulative disadvantage, including greater likelihood of chronic health conditions, comorbid health problems. NEET young women, compared to NEET young men, are more likely to experience psychological distress [ 18 , 19 ] poorer mental health [ 20 ], greater suicidality and self-harm [ 21 ]. Socio-occupational outcomes are poorer too in this group. NEET young women, relative to young men, experience reduced life satisfaction and sense of control [ 18 ], a reduced sense of positive identity [ 18 ], experience greater social isolation [ 13 ], and poorer social and relationship outcomes [ 18 ], with greater risk of sexual violence [ 12 ]. NEET young women are also more likely to encounter discouragement and stigma from potential employers, with a lack of flexible occupational opportunities that fit around caring responsibilities [ 13 , 22 ]. These multiple disadvantages are compounded for NEET young women in deprived areas [ 23 ], including in many coastal regions around the UK, which have relatively fewer jobs, under-performing schools, and poor infrastructure relative to in-land areas [ 24 ]. Poorer outcomes for young women, in turn, increase the risk that NEET status will persist over time [ 25 ].

Research and interventions specifically focused on NEET young women, especially in the UK context, remain relatively scarce, despite significant policy interest on the social welfare implications of being NEET [ 26 ]. One study reported on a qualitative evaluation of a computer coding intervention for NEET young women in England [ 27 ], showing promise with respect to enhancing sense of positive identity but not demonstrating wider health or social benefits. The research gap for NEET young women is especially problematic given that there is an ongoing crisis of youth support provision in the UK, especially in deprived areas such as the coast [ 28 ]. Even if youth mental health or social support services are available, NEET young people are less likely to be able to access and engage with them [ 29 ]. Moreover, generic psychosocial interventions appear less engaging and effective for the most disadvantaged NEET subgroups [ 17 ].

Whilst evidence suggests that NEET young women are more likely to experience prior and ongoing adversities, structural factors do not wholly dictate young people’s occupational trajectories [ 30 ]. Recent studies suggest that the greater risk of being NEET, and of having poor outcomes for different demographic groups, is at least partially explained by attitudinal differences [ 31 , 32 ]. There is also evidence for a reciprocal relationship between NEET status and mental health symptoms, where the perception (from oneself and others) of failing to ‘keep up’ can be harmful to mental health and discourage service use and social re-engagement [ 31 , 32 ]. Subjective perceptions related to self-worth and capacity to reach personal goals, therefore, represent important intermediate outcomes, especially among young people for whom immediate re-entry into education, training or work may be unrealistic [ 30 ].

Such self-perceptions can be understood as manifestations of the theoretical construct of hope. Hope can be defined as a way of thinking, which comprises self-agency (the ‘will’ or motivation and self-belief) and pathways (the ‘ways’ or goal route identification) directed towards a meaningful goal [ 33 ]. Hopeful self-agency predicts positive youth education and work outcomes [ 34 , 35 ], predicting success even more strongly than intelligence and cognitive ability [ 36 ], and protects against the effects of structural and social disadvantage and adversity [ 30 , 37 , 38 ]. NEET groups commonly lack self-belief and optimism about changing their circumstances, even when they are motivated to seek work or education [ 4 ]. Diminished hope is compounded by the projection of low expectations from family members and others [ 39 ], reflecting the intergenerational and systemic transmission of low hope [ 30 ]. A recent UK study found that NEET young people exhibited less hopeful self-agency compared with other groups, while greater self-agency reduced the longitudinal risk of being NEET [ 30 ]. NEET young women are again doubly disadvantaged: viewing themselves as less competent than NEET young men and reporting lower professional expectations [ 40 ]. Gendered differences are exacerbated in smaller, rural, and remote communities, in which young women experience a reduction in hope during late adolescence whilst young men experience growth [ 41 ].

Hope has been strongly implicated as a common mechanism in a variety of talking therapies [ 42 ], yet has been overlooked with respect to interventions for NEET young people. A previous systematic review concluded that there is a substantial gap in knowledge about what aspects of re-engagement interventions work or how [ 17 ]. This research agenda has been complicated by the confounding effects of multi-agency working, such that several organisations commonly interact with NEET young people at any one time [ 17 ]. There is a particular dearth of research on theory-driven interventions for the NEET population [ 17 ]. A focus on hope offers an opportunity to create a theory-driven approach to augment gendered inequalities that render young women more likely to become and stay NEET, with associated poor health and low aspirations for the future.

In a recent systematic review [ 42 ], we found that effective hope-focused interventions for youth depression commonly incorporated cognitive, behavioural, and interpersonal elements that (i) promoted hopeful thinking; (ii) identified meaningful goals and activities; and (iii) were delivered in a timely, hopeful, and inspiring way. The constituent practice elements were often brief (i.e., involving six or fewer sessions) and included (but were not limited to) structured goal setting, teaching problem-solving skills, and supporting young people to visualise positive futures. Our review additionally found that hope-enhancing interventions can be flexibly deployed, with evidence of effectiveness across health, social services, education, and community settings. Therefore, a hope-focused intervention approach has the potential to offer an efficient and scalable solution to promoting positive outcomes for NEET young women.

Moreover, a hope-focused stance is directly relevant to managing service engagement challenges associated with NEET groups, for hopefulness is implicated in increased help-seeking and intervention engagement in youth [ 42 ]. Engagement may be strengthened further by using other best practices identified from NEET-focused case studies [ 43 ]. These include: (i) offering flexible support with a high degree of personalisation; (ii) delivering programmes in ‘neutral’ community settings, without the stigma or other negative connotations of statutory services; (iii) encouraging non-hierarchical relationships between participants and providers; (iv) providing individual support for young people who experience multiple barriers to re-engagement and/or have been NEET long-term; and (v) involving community representatives and NEET young people in the design and possible delivery of programmes.

From these conceptual and practice-based starting points, we aimed to develop a low-cost, scalable hope-focused psychosocial intervention for NEET young women aged 16–24 years living in areas of coastal deprivation. Our iterative developmental approach involved working alongside NEET young women and other stakeholders to identify local population needs and intervention requirements; select and contextualise promising hope-focused practice components; and articulate how a hope-focused intervention might be implemented and scaled up to impact positively on mental health and social functioning. The specific research questions were:

What formats and settings are viable for delivering a brief, low-cost, hope-focused intervention to NEET young women aged 16–24 years in deprived coastal communities?
Who are possible non-specialists that could credibly deliver the intervention?
What are the most meaningful short- and long-term outcomes related to hope and its theorised effects on mental health and social functioning, and how can these be measured?
What is the theory of change for the intervention?

Materials and methods

Research design.

We applied a phased, qualitative design that drew on principles and practices of person-based intervention development [ 44 ] and partnership [ 45 ], i.e., incorporating the perspectives of the people who will use the intervention and the intended beneficiaries within design decisions. We took a critical realist stance [ 46 , 47 ], reflecting the premise that an objective reality exists (a realist ontology) but is imperfectly accessed through a lens of individual perception (a relativist epistemology). An iterative process of reflection and action entailed capturing local needs and priorities in formative interviews with varied stakeholders from coastal areas (Phase 1), followed by co-design sessions with NEET young women (Phase 2). We conceptualised co-design as involving intended end beneficiaries directly in defining key intervention parameters, with an emphasis on reciprocal democratic dialogue and equal participation [ 48 ]. In Phase 3, we conducted a Theory of Change (ToC) workshop with local practitioners. Finally, findings from primary data collection were synthesised along with pre-existing evidence from a recent systematic review [ 42 ], and additional scoping reviews, to inform the creation of an intervention ‘blueprint’ based around standardised intervention descriptors [ 49 ]. This approach is appropriate for critical realist research, i.e., considering data through the original premise of the study and adding further theories as indicated by iterative data gathering and analysis [ 46 ]. The study was overseen by an independent steering committee, representing members with scientific, clinical and/or lived expertise pertaining to youth and women’s mental health. This report has been developed in line with the GUIDED approach to reporting health intervention development [ 50 ].

Participants and setting

The study was conducted in two geographical regions in South-East England, Sussex and Kent, which contain socially and economically deprived coastal areas and higher than average populations of NEET young people at 16% each [ 1 ]. The study protocol was prospectively registered (17/06/2022; Research Registry reference 8016). Research ethics approval was obtained from the Health Research Authority (reference 22/HRA/0721, IRAS 310439) and the University of Sussex C-REC Committee (reference ER/DMM55/1). Participants provided informed consent using an online or paper-based consent form before taking part.

Phase 1 participants (N = 28) were sampled from three stakeholder groups: (i) 16-26-year-old women who self-identified as having lived experience of being NEET (n = 8) in the past 12 months (NEET status pertained to maximum age threshold of 25 years in some organisations in each study region); (ii) family members of this target group (n = 4); and (iii) practitioners from statutory service providers (e.g., public health, primary care, mental health services, social services, education and youth employment services) and community organisations (e.g., youth groups) (n = 16). Participants from groups (i) and (ii) were recruited by promoting the project on social media and advertising it in community spaces that the target group and/or their family members may visit (e.g., food banks and libraries). Group (iii) was recruited through email, telephone, and in-person contact attempts based on an initial scoping exercise of local services, followed by snowball sampling. Recruitment to Phases 2 and 3 involved inviting Phase 1 participants to continue their participation and seeking novel participants using the same strategies as in Phase 1. Youth participants in Phase 1 (n = 5, 62.5% Sussex and n = 3, 37.5% Kent) all self-identified as White and spoke English as a first language, and were primarily heterosexual, single, and living with parents. The mean (M) age was 20.13 years (standard deviation [SD] = 2.36). All young people described themselves as having experienced mental health problems and three (37.5%) identified an additional non-mental health-related disability (e.g., autism). Time spent NEET was variable: ≤6 months (n = 2, 25%); 7–12 months (n = 7, 50%); >12 months (n = 2, 25%). The four participating family members (n = 3, 75% Sussex; n = 1, 25% Kent) were mothers of NEET young women, two of whom lived with the young woman. These family members all self-identified as White and spoke English as their first language. The 16 practitioners involved in Phase 1 (n = 10, 62.5% Sussex; n = 6, 37.5% Kent; M age = 49.57 years, SD = 7.72; n = 9, 56.3% female) included psychiatric, primary care and public health practitioners, social, support and youth justice workers, and careers and employment advisors.

Phase 2 co-design sessions were conducted with n = 6 NEET young women, of whom three were involved in Phase 1. Due to an administrative error in correctly recording informed consent on two occasions, data were available from n = 4 NEET young women in Phase 2 (n = 3, 75% Sussex; n = 1, 25% Kent; M age = 18.75 years, SD = 2.87). Three of these four included participants had additionally participated in Phase 1. The Phase 3 ToC workshop included 10 new participants. Two additional practitioners (who had previously completed Phase 1 interviews) did not attend the workshop but contributed feedback by email. Two workshop participants also sent follow-up written feedback. Eight (66.67%) Phase 3 participants identified as female, the remainder as male.

Semi-structured interviews (M duration = 51 minutes, range 31–69) were conducted mainly online (two involving NEET young women were in person) using topic guides tailored to each stakeholder group. One interview with a NEET young woman was conducted with a peer researcher jointly involved alongside a non-peer researcher (see Table 1 ). More extensive involvement of peer researchers in interviews with young people was planned to improve rapport and richness of data but was ultimately not possible due to practical and personal circumstances affecting availability of trained peer researchers. Topic guides explored: (i) mental health and social problems experienced; (ii) links between contextual risk factors, hopefulness and trajectories of mental ill-health and social disability; (iii) desired outcomes for a hope-focused intervention; and (iv) facilitators and barriers to achieving these outcomes through current service provision. Additional questions for practitioners examined potential selection criteria and referral pathways for the putative intervention, as well as assets and existing practices that may support integration within local communities and service settings. All interviews were audio-recorded and transcribed verbatim.

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https://doi.org/10.1371/journal.pone.0304470.t001

Co-design sessions were facilitated using Zoom videoconferencing by one or two peer researchers and lasted for M = 54 minutes (range 35–85). These sessions were conducted separately with each NEET young woman since all participants preferred to contribute individually rather than participating in the focus group format that we first offered. The involvement of peer researchers was intended to provide a degree of impartiality from the other research team members and encourage critical discussion of intervention concepts and plans. Building on insights from Phase 1, these sessions explored preferred intervention content, providers/supporters, modes of delivery, activities, timing, dosing, settings, and important subjective and objective outcomes. In each session, participants viewed a slideshow with an accompanying audio-recording that summarised the project aim and Phase 1 findings. Following this presentation, participants were invited to reflect on the presentation content and wider relevant literature (based on our earlier evidence synthesis of hope-focused interventions [ 42 ]). The session facilitators presented further slides that included a draft intervention blueprint and module outline (derived from an interim Phase 1 analysis involving peer and non-peer researchers), including potential delivery approaches and example activities. Co-design sessions were recorded and transcribed verbatim. After each session, participants were invited to take part in three polls administrated using the online survey software Qualtrics, in which they provided three sets of rankings related to the importance of potential intervention modules, activities within each module, and outcomes.

A 90-minute ToC workshop [ 51 ] was conducted online with practitioners using Zoom videoconferencing software. The workshop was used to consider and refine the intervention model, and delineate short, medium, and longer-term intervention outcomes and how these would be achieved. We additionally explored opportunities for how to deliver the intervention in the current youth support landscape. Participants in the ToC workshop (n = 10) were first presented with a slideshow providing a synthesis of findings from the earlier phases and then invited to provide feedback. The process of collecting feedback followed a ‘backwards mapping’ approach [ 51 ] where participants started at the end of the intervention to identify the outcomes, and then critically assessed how and why these outcomes would be achieved through the hope-focused intervention. These discussions were initially conducted in small groups, with feedback collated through an online whiteboard (EasyRetro), and subsequently explained and refined in the larger group. The workshop was recorded and transcribed verbatim. A draft ToC was shared by email with workshop attendees and two Phase 1 practitioner participants who were not able to attend. Email feedback was then incorporated into an updated model.

Public and Community Involvement and Engagement (PCIE)

We embedded PCIE throughout this project to increase the relevance and quality of this research. Our reporting of PCIE activities is in line with the GRIPP2 framework [ 52 ]—identifying the methods, outcomes, benefits, and challenges of these activities. Our PCIE approach blended qualitative research with key informants together with PCIE and co-design activities [ 53 ]. Our research team included a PCIE lead (JF) with personal and professional experience of supporting NEET and vulnerable young women, who collaborated in the design and planning of the research study [ 54 ] and was a consistent presence in weekly research team meetings to embed a lived experience perspective in decision-making. In addition, PCIE advisors, peer researchers (YZ and AT), and PCIE consultants were involved in multi-dimensional project roles to ensure ‘authentic collaboration’ throughout the project lifecycle [ 55 ]. These roles and activities are described in Table 1. The outcomes of these activities included: shaping project informational materials to refer to hope as a ‘changeable mindset’ and use simpler language; streamlining the focus of Phase 1 interview topic guides; ensuring that the data collection processes were maximally inclusive and flexible (Phases 1 and 2); informing the selection of the specific foci and materials for Phase 2 co-design sessions (i.e., mentor delivery model, intervention modules and content, primary and secondary outcome selection); contributing to Phase 1 and leading Phase 2 data collection; and contributing as equal (Phase 1), and primary (Phase 2) data analysis partners. PCIE activity findings are additionally detailed and collated within integrated findings (see Table 3).

Data analysis

We used a deductive-inductive approach to data analysis, which enabled us to select from and integrate candidate intervention elements and delivery strategies (57,58). In keeping with our critical realist stance [ 46 , 47 ], we were interested in trying to elucidate ‘demi-regularities’ [ 46 , 47 ], i.e., points of convergence and divergence across stakeholder groups and project phases, and in considering the causal phenomena and wider social structures that may give rise to these patterns in meaning. These foci are important in the context of critical realism’s relativist epistemology ( versus its realist ontology) because multiple explanations for observed phenomena are possible [ 56 ].

Data were analysed iteratively for each phase, using a framework charting approach [ 57 ], and then integrated in a mixed methods matrix [ 58 ]. A framework analysis approach is appropriate for critical realist research because both prioritise meaning-making in the context of complex phenomena and position research (and its products) as purposively derived from the marriage of participant experiences and researcher interpretations [ 56 ]. Moreover, a framework analytic approach facilitates use of all data [ 57 ], including that which that does not “fit” with dominant narratives, but which nonetheless may be important [ 46 , 56 ]. The analysis was driven by our research questions and structured around items from the TIDieR framework [ 49 ], in keeping with our aim to develop an intervention blueprint detailing key intervention parameters. First, we coded the data deductively using the research questions and then structured the codes using the TIDieR items. We then identified meaningful subthemes under each TIDieR item, or research question in absence of a relevant TIDieR item. Theory is central to critical realist research [ 56 ]. We situated a priori the intervention within the cognitive model of hope [ 33 ], in which hope represents future-oriented goal-directed cognition comprising self-agency and pathways thinking. For procedural components (within the TIDieR “what” category), we structured codes pertaining to a published taxonomy [ 59 ] of specific therapeutic activities and techniques: categorising them as behavioural, cognitive, interpersonal, and non-specific, adding an ‘additional activities’ category for miscellaneous items. Subthemes in other TIDieR categories (or pertaining to research questions otherwise) were inductively coded.

For Phase 1, an initial meeting with the entire research team, including two peer researchers (YZ and AT), was held to discuss preliminary themes and impressions of the interview transcripts. We further refined the analysis in subsequent meetings with a smaller group and the first author (CB) drafted the final analytic framework. For Phase 2, three team members (YZ, AT, and CB) independently coded the co-design session transcripts. An analysis meeting was held including the final author to discuss codes and potential subthemes. Following this meeting, CB collated all codes into a common set of subthemes and shared the collated analysis with the peer researchers for validation. Results of Phases 1 and 2 are presented together. For Phase 3, findings were initially collated by the lead facilitator of the ToC workshop (SH). The ToC model was refined by CB following further analysis using the verbatim transcript of the workshop and participant email feedback. The ToC was designed to combine the purported outcomes of the hope-focused intervention (i.e., critical realism’s actual tendencies [ 56 ]) with structural influences that could impact these outcomes (i.e., generative mechanisms [ 56 ]). Findings from all three phases, plus relevant evidence from prior research and PCIE activities, were then integrated (Table 3). This tabulated synthesis was used to finalise the intervention blueprint (Table 4).

With respect to reflexivity, our analysis was influenced by the fact that our team comprises mainly White-identifying females. This matches the majority of the participants across all project phases. Many of our research team originate from Sussex or Kent, with all authors having lived and/or worked in at least one of these regions. All team members were thus familiar with growing up in coastal communities and/or inhabiting/working in these regions later in adult life. Multiple members of the team have experience of being NEET in adolescence or early adulthood, including whilst experiencing mental health problems, and in supporting NEET family members. The team additionally includes public health and mental health practitioners, with practice-based experiences of delivering psychosocial interventions to young women with social and mental health problems. Our approach to study design and analysis was influenced by these experiences, and the frequent degree with which the narratives of participants evoked personal and professional resonance.

Findings from Phase 1 (understanding population needs and intervention requirements) and Phase 2 (co-creating intervention parameters)

Integrated findings from Phases 1 and 2 are presented in Table 3 and summarised narratively below. More detailed results, including illustrative quotes, are presented in S1 and S2 Tables. Co-design participant rankings of proposed intervention modules, activities, and outcomes are presented in S1 – S3 Figs. A video summarising key results of Phases 1 and 2, with a particular focus on the narratives of NEET young women is additionally available: @Hopeinhealthresearch, https://www.youtube.com/watch?v=d03W9ax52QQ&t=10s .

WHY (intervention rationale, theory, and goal).

Results from the Phase 1 qualitative interviews and Phase 2 co-design sessions suggested that the cognitive model of hope aligned with participant experiences. When asked how they understood the word ‘hope/hopefulness’, Phase 1 participants from all groups spoke about hope as future-oriented, primarily cognitive in nature, and described it in relation to specific (usually functional) goals. Participants did additionally identify emotional components to hope, i.e., with respect to the intrapsychic experience of being hopeful and observable manifestations of hopefulness in other people. Young women (Phases 1 and 2) and practitioners (Phase 1) emphasised the importance of making the focus of the intervention on hope very explicit. They emphasised that this is less stigmatising than a diagnostically driven mental health intervention, and provides greater potential to prevent and ameliorate a spectrum of mental health problems. They suggested that prioritising EET engagement is not necessarily attractive nor helpful as an intervention focus. However, they acknowledged that many NEET young women would want to engage in EET activities and have goals aligned to these areas, thus all stakeholder groups (Phase 1) suggested that intervention providers should be equipped to offer activities for developing skills and knowledge for scaffolding EET (re)engagement. There was agreement across Phases 1 and 2 about the likely benefits of a structured, manualised, and modular programme to teach specific skills that are relevant to goal setting and pursuit as building blocks of hope. In Phase 2, NEET young women emphasised the potential for broad transferability of skills related to hope. All three groups (Phases 1 and 2) identified likely secondary outcomes to increasing hope of goal attainment, better functioning, and improved mental health and/or reduced mental health symptoms.

WHAT (materials and procedures).

Phase 1 and 2 interviewees agreed that intervention materials provided to NEET young women should be accessible, varied in style (e.g., paper-based and online), and used flexibly to suit different needs, preferences, and styles of learning. Concern was raised by young people and practitioners about materials being written using patronising or overly positive language that might seem glib or invalidating. With respect to procedures, all stakeholder groups (Phase 1) agreed that the intervention should be inclusive to as many NEET young women as possible, with late adolescence through to early adulthood as a relevant staging period due to the critical developmental transitions and challenges occurring in this time. There was broad agreement in Phases 1 and 2 about the value of organising behavioural, cognitive, and interpersonal content into structured modules. Goal-directed behaviour change was identified by all groups as a key focus after initial engagement work and psychoeducation. This would include helping young women to identify meaningful goals, break them down into small steps and clarify specific goal pathways, explore and mitigate barriers, re-select goals when needed, and reflect on progress. In Phase 1, gradual and responsive pacing was emphasised as crucial to avoid overwhelming participants who may be ambivalent about change and severely lacking in confidence. In both phases, explicit discussions about the nature of hope and its enhancement were advised to begin after initial work to develop a more positive sense of self, e.g., through identifying interests and strengths. As part of the process of orienting participants to the concept of hope, practitioners (Phase 1) emphasised the importance of personalising psychoeducation by exploring the unique meaning of hope to each young woman, their historical experiences of hope, and factors affecting current hopefulness. All three stakeholder groups (Phases 1 and 2) additionally recognised that NEET young women often have impoverished social worlds, and that interpersonal content would usefully address ways to increase social support and connectedness. This would include helping young women to identify and strengthen existing positive relationships within their social networks, as well as expanding networks by actively creating opportunities for new connections.

Phase 2 participants endorsed six proposed modules, each organised around a theme relevant to the enhancement and maintenance of hope, that would incorporate a mix of psychoeducational, behavioural, cognitive, and interpersonal content (see Table 4). There was agreement that the first module should focus on introducing the intervention model, building rapport, generating a more positive sense of self, sparking interest in structured activities, and enhancing mood. The next module was intended to introduce the concept of hope in greater depth (Module 2). This would then be followed by successive modules to develop relevant skills and enhance resources to support ongoing hopefulness: visualising a positive future and clarifying motivational values (Module 3); identify and work towards personally meaningful goals (4); increase social support for hope (5); and mitigate challenges and barriers to maintaining hope (6). Modules 1 and 3 were ranked as most important ( S2 Table and S1 Fig ), but there was support for all modules and their respective foci.

Although not ranked higher than other components, co-design participants appreciated psychoeducation (ideally presented using short videos) as necessary to introduce concepts and scaffold learning practicable skills. Highly rated module activities included: identifying interests, meaningful activities, and values; activity scheduling, identifying hopeful life periods and domains and sources of hope; guided goal visualisation and goal steps planning; and hopeful social network mapping (see S2 Table and S2 Fig ). Co-design participants also advocated the inclusion of lived experience perspectives as part of intervention materials and providing resources that the participants could use to explain the intervention approach and their progress to others around them. The participants suggested that the intervention could include components focused on EET activities and/or mental health problems as individually desired.

Participants identified the most important outcomes as hope (general and EET domain-specific), wellbeing, help-seeking intention, social relationships, and time spent in EET and other meaningful activities ( S2 Table and S3 Fig ). Participants identified that improving mental health and/or reducing risk of mental health problems is highly important but should not be the primary outcome.

WHO (intervention provider).

All three stakeholder groups (Phase 1 and 2) agreed that the intervention would be more effective and engaging if prospective participants were supported through the process by a trusted individual who was empathic, validating, non-judgemental, hopeful, encouraging and consistent. A supporter’s ability to form positive relationships was viewed as being more important than any particular professional training or qualifications. Training and qualifications were considered by practitioners (Phase 1) to potentially discourage NEET young women from sharing their experiences and engaging in support. Interpersonal continuity was strongly emphasised, and young people described a litany of experiences in which supportive interventions had ended abruptly, typically because of operational restrictions on longer-term support or staff turnover. NEET young women (Phase 1 and 2) and relatives (Phase 1) emphasised that NEET young women will vary with respect to the type of person they would want to support them with a hope-focused intervention; for some a peer would be preferred, but others would value someone with whom they have a professional relationship.

Practitioners (Phase 1) identified resource limitations to do with skilling-up existing staff from over-stretched statutory and community agencies and emphasised that the intervention’s reach and scalability could be aided by participation of trained lay community members. Relatives and practitioners (Phase 1) both suggested that engagement and continuity might be strongest if prospective intervention providers/supporters were already personally known to NEET young women, such as foster carers and existing residential support workers, rather than introducing a new cohort of specialist practitioners. Embedding the intervention in the community was also seen as critical to sustainability. NEET young women and practitioners (Phase 1) identified the importance of intervention providers being trained to deliver the intervention using a person-based and flexible approach. Practitioners emphasised the need for training in the intervention approach, but discouraged it being delivered by providers with extensive psychotherapy training as this may undermine supporters’ receptiveness to focusing on a novel approach to enhancing hope. All stakeholder groups (Phase 1) recommended that the intervention should be overseen/supervised by professional experts in youth work, even if the direct providers were non-specialists in the community.

Scenarios generated from Phase 1 were explored in greater detail in Phase 2. Particular traction was found with a ‘youth-initiated mentoring’ (YiM) model [ 60 , 61 ] in which young people would identify a trusted individual with whom they had a pre-existing relationship and who they would like to support them through the intervention. Co-design participants responded favourably to YiM, with two particular caveats. First, alternative mentors would need to be provided for young women who could not identify a mentor themselves. Second, careful attention (and training) would be needed around negotiating boundaries and ensuring confidentiality when introducing the intervention into a pre-existing/ongoing relationship.

HOW (mode of delivery).

Overall, a primarily one-to-one intervention was seen to be most accessible and attractive to the majority of NEET young women in Phases 1 and 2; offering a greater sense of privacy and safety and preserving a focus on individual need. However, the flexible use of small group-based activities, as part of the intervention and/or planned as part of activity scheduling more broadly, was also endorsed. Practitioners (Phase 1) additionally emphasised the benefits of including at least some self-directed components to make the intervention more accessible and create a space for NEET young women’s empowerment. There was additionally agreement in Phases 1 and 2 that sessions should ideally be in-person, but that flexibility would be needed to engage young women according to their dynamic preferences, offering remote voice or video-call sessions if preferred, for example, in the context of a period of heightened anxiety.

WHERE (location).

NEET young women and practitioners (Phase 1) emphasised that the hope-focused intervention should fit within the existing youth support system. They stated that individuals and services with whom NEET young women might come into contact should be aware of the intervention and able to support young women to access it. All three stakeholder groups (Phase 1) advised that the intervention should be easy and quick to access, without long waiting periods. Waiting lists themselves were seen to undermine hope and reaffirm and reinforce NEET young women’s feelings of hopelessness and worthlessness. All three stakeholder groups (Phase 1) agreed that information about the intervention should be disseminated clearly and accessibly online. It was also unanimously agreed (Phase 1) that in-person sessions should take place in accessible and non-stigmatising community locations with good transport links. Phase 1 practitioners and Phase 2 participants suggested that sessions could helpfully include meetings outdoors.

WHEN and HOW MUCH (sessions, schedule, duration, intensity, and dose).

In Phase 1, family members emphasised the importance of an intervention that involves regular sessions, so that young women feel it is something consistent and reliable. Practitioners (Phase 1) suggested that the intervention should begin with more frequent sessions, then reducing to a lesser intensity before finishing. Both practitioners and NEET young women in Phases 1 and 2 emphasised the importance of young women not feeling rushed to complete the intervention. Moreover, these participants additionally emphasised that all aspects of delivery (session number and duration, timing, pacing) should be flexible according to individual participants’ preferences. Phase 2 participants additionally recommended that activities which could be used beyond the formal end of the intervention would be beneficial.

TAILORING (personalisation).

Personalisation according to NEET young women’s goals, interests, preferences, and needs was espoused by all stakeholder groups in Phases 1 and 2. All stakeholder groups agreed that customisable and adaptable intervention activities would be essential to intervention engagement. Phase 2 participants recommended the provision of a menu of adaptable activities that could be completed in different formats such as writing, discussions, visualisations, and using creative arts. Co-design participants encouraged an early discussion as part of the intervention to determine session focus. Subsequently, activities should be selected and sequenced flexibly according to individual preferences and needs, building in ongoing opportunities for reviewing and returning to activities from earlier modules.

Phase 3 findings: Theory of change (ToC)

The ToC ( Table 2 ) sets out the inputs, participants, and assumptions underlying the hope-focused intervention and details the specific components and their links to purported outcomes. Key conclusions from the ToC workshop are integrated with all other evidentiary sources in Table 3 .

https://doi.org/10.1371/journal.pone.0304470.t002

https://doi.org/10.1371/journal.pone.0304470.t003

Phase 3 participants agreed with the utility of first focusing on time spent in meaningful activity and increasing positive sense of self, before moving on to explicit discussions about hope. Alongside this, the group stated that it might be challenging for young women to engage in the intervention if basic needs, for example, safe housing and sleep, were not met. Nonetheless, participants acknowledged that this might be their agenda as practitioners and that young women do not necessarily prioritise basic needs above their future goals. The group identified that communication skills are often an issue for young women and that the intervention could and should help improve these. Participants identified that using tools to capture outcomes is important to understand the impact of the intervention, but that this should also be done as part of the intervention itself, e.g., using metrics to discuss progress with young women, to enable productive conversations about how and why changes have (or have not) occurred. Finally, participants supported the use of the YiM model believing that this would help in the context of the lack of providers in coastal areas. Moreover, they emphasised that there would be particular benefit to mentors who had greater shared experience with NEET young women and could help to reduce social isolation among mentees.

Integrated findings and intervention blueprint

Phase 1–3 findings were integrated alongside PCIE and scientific evidence in Table 3 . These findings were used to refine the draft intervention blueprint, with the finalised version presented in Table 4 . The intervention is named ‘HOPEFUL’. The blueprint describes the key intervention parameters and includes the focus and content of six discrete yet interconnected modules. For each module, the blueprint articulates key concepts (psychoeducation components) and ‘core’ activities that are considered necessary to ensure that the intervention can be delivered (for example, discussing the intervention model and agreeing how the mentoring relationship will work in Module 1, and reviewing intervention progress in Module 6). The blueprint then identifies a menu of selectable activities, which can be adapted for delivery in different formats such as discussions and creative arts. The activities aim to facilitate the application of concepts learned about in the psychoeducation portion. Finally, optional ‘takeaway’ (i.e., homework) activities are provided, providing opportunities to practice the intervention techniques in a self-directed fashion and/or to involve others from the young women’s wider social networks, e.g., sharing their personal goals with supportive others. It is recognised that modules may require more than one meeting with a YiM, although some young women may prefer to complete intervention activities (or modules) in a more self-directed fashion overall. With this in mind, the intervention blueprint provides guidance for a range of 4–12 sessions, approximately hourly in length and held weekly, but emphasises collaborative flexibility in determining session number, duration, and pacing.

https://doi.org/10.1371/journal.pone.0304470.t004

This paper presents the development of a hope-focused intervention (HOPEFUL) for young women who are NEET with a focus on UK deprived coastal community living, but potentially with wider applications to NEET and other vulnerable young people. The participatory process of developing the intervention blueprint used a phased qualitative design involving NEET young women, their family members, and statutory and non-statutory service providers as key stakeholders. We aimed to identify a viable format and setting for delivering a brief, low-cost intervention that could be credibly delivered by non-specialists. We also sought to identify meaningful short and long-term outcomes within an overarching Theory of Change. The resultant blueprint articulates a primarily one-to-one, in-person intervention, with content organised into six modules that aim to enhance hope by increasing positive self-regard and meaningful activity, identifying values and helping to visualise a positive future, facilitating the identification and pursuit of personally meaningful goals, and maximising social support for hope. Support for engaging with the intervention content is provided through a youth-initiated mentor (YiM) approach, with additional opportunities for self-directed activities.

All stakeholder groups considered hope of paramount importance, both as a universal process in good mental health and functioning, and of specific relevance to NEET young women living in deprivation, for whom intergenerational and socio-cultural transmissions of pessimism regarding life opportunities are common [ 39 ]. All groups agreed that the intervention should be explicitly framed around the concept of hope, for this offers an intuitive, engaging, accessible and non-stigmatising focus for the intervention. This contrasts with the primary emphasis on returning to EET within established NEET-specific programmes [ 17 ], but is in keeping with self-perceptions as an accessible intermediate intervention target to support movement towards (re)entry into EET activities [ 30 ]. All stakeholder groups intuitively defined hope in alignment with the cognitive model [ 33 ], i.e., in terms of goal-oriented future-focused cognition, and recognised the important ways in which hope can be developed and maintained in the context of positive relationships. These congruences attest to the relevance and utility of a mentor-supported intervention that explicitly targets hope.

The proposed supportive role of a YiM is a particular innovation of the present study. This would be someone whom the NEET young person already knows (e.g., a relative, existing support worker, or sports coach) that they choose to support them with the intervention. In the Netherlands and USA where it originates, the YIM model has achieved impressive outcomes in improving academic and work functioning and physical and mental health in a variety of high-risk youth populations [ 61 , 62 ]. The YiM model has strong promise for use with young people in low-resource settings from other countries, including in the UK. It requires fewer resources compared to traditional mentoring or professional intervention [ 61 , 62 ], and uses existing assets to expand individual intervention benefits and propel them forward in time [ 63 ]. Moreover, this model could help to address the issue found in the present study and in other research [ 30 , 39 ], whereby NEET young people often experience projected hopelessness from their own families and wider communities. YiMs hold the potential to build support and social capital around NEET young women, increasing the resources available to them and helping them to maximise the extent to which they can draw on the support of caring adults [ 61 ], whilst engendering better access to relational hope and positive aspirations in their immediate surrounding networks.

The HOPEFUL intervention is in keeping with the ‘wise’ intervention approach [ 63 ]. Unlike traditional social reform, which targets either the individual or the environment, ‘wise’ interventions target how individuals engage with the wider system through augmenting basic psychological processes. HOPEFUL follows the five principles of wise interventions. First it is psychologically precise , by attempting to alter hope as a specific and intuitive form of meaning-making, i.e., encapsulating how agents engage with the social world. Second, it identifies psychological processes as one factor in complicated causal systems . This means that, for NEET young women to experience better health and functioning, the system around them must have the capacity for change. This may require other types of social reform, for example, NEET young women will stay NEET unless appropriate and accessible EET opportunities exist. Yet opportunity is not always taken up, and enhanced hope enables NEET young women to take advantage of this capacity where it does exist [ 42 ]. Third, HOPEFUL encourages recursive change , because what people believe about themselves and social situations readily becomes self-fulfilling and embedded in the structure of their lives [ 63 , 64 ], and hope as a trait that young people and research evidence suggest is especially self-reinforcing over time [ 42 ]. Fourth, HOPEFUL has been developed with attention to methodological rigour and process and, fifth, takes into account ethical considerations . The intervention is based on robust psychological science. It tries to sustainably and accessibly embed hope-inspiring support in the system around young women to avoid contributing to NEET young women’s perspective on being offered only short-term help with a high level of interpersonal turnover. Evaluation research should nonetheless now focus on the identification of any unexpected potential for harms.

As per other ‘wise’ interventions [ 63 ], HOPEFUL is designed to be minimally directive, intuitive and brief, and therefore, it is appropriate to position non-specialists in intervention support/delivery roles. This approach can be construed as an example of task-sharing, i.e., the deployment of non-specialists to expand the reach of statutory/community support provision. We envisage, for example, that local authority and voluntary sector practitioners could offer supervision to YiMs. The task-sharing approach has the potential to enhance implementation and scalability, because the YiM model means that HOPEFUL can be used at a population level, without a need for a new workforce to deliver it. Task-sharing approaches are not without implementation challenges, however, such as non-specialists lacking confidence in their competence, a lack of incentives to sustain involvement of non-specialists and other stakeholders beyond short-term research projects, and scepticism from specialist practitioners [ 65 ]. HOPEFUL, deployed using a YiM model, has the potential to mitigate at least some of these challenges due to the intuitive appeal of the hope focus and the established, trusting relationships on which the delivery approach depends. It is notable in the present study that professionals across a wide variety of health and other community services expressed a very high level of enthusiasm for the YiM model. HOPEFUL has been designed to be easy to understand and implement, to help build YiMs’ confidence in their capabilities to support its use. Moreover, the use of the YiM approach should help to sustain the benefits of the intervention beyond the immediate lifetime of an evaluative research programme and provide a vital bridge between fragmented formal services and informal community support networks. Scalability will be further enhanced by the creation of resource-efficient mentor training that requires little to no practitioner oversight or delivery; an approach used in other task-sharing initiatives, notably in Lower and Middle Income Countries (LMICs) [ 66 ]. These elements are reflected in the HOPEFUL intervention blueprint accordingly. The YiM approach may, nonetheless, create unique implementation challenges too. Therefore, attention needs to now turn to robust evaluation of intervention feasibility, effectiveness, and value for money. As hope is a basic and universal psychological process [ 67 ], learning from the evaluation of intervention effects and cost-effectiveness would be relevant to other vulnerable youth populations [ 42 ] and beyond.

In addition, important implications for the ongoing implementation of existing service provision arose in the present study. It was notable that NEET young women and their family members emphasised that simply the presence of available support was itself hope-inspiring. Where support provision occurs within the context of interpersonal continuity, young women feel more able to access it and more engaged in doing so. The importance in particular of feeling supported to work towards personally relevant goals was clear, as was the value of being able to do so at one’s own pace without feeling rushed or that service provision might be abruptly discontinued. It was notable that discourses relating to sex and gender-based issues seemed largely absent from the narratives of NEET young women themselves. Nonetheless, professionals emphasised this group’s particular need for provision that builds their hope, in the context of sex and gender-based inequities that maintain poor confidence and low life aspirations amongst young women.

Limitations and strengths

Several limitations are important to note. We recruited fewer family members in Phase 1 and fewer NEET young women as Phase 2 co-design participants than intended. Difficulties in recruiting NEET young people have been reported in previous studies [ 68 , 69 ] and, whilst we used multiple strategies to try to find and involve these participants, greater time to form relationships with more organisations and to promote the project more widely through social media may have resulted in greater participation of NEET young women and their relatives. We recognise that all NEET young women and their family members identified as White and spoke English as their first language. While minority ethnic groups make up a relatively small proportion of the population in the study localities, proactive efforts should be made in future studies to engage more ethnically diverse participants and explore any implications for intervention adaptations. Moreover, all the NEET young women interviewed in this study had completed GCSEs (or equivalent) or further study, and their needs and preferences may differ from NEET young people who have not completed such qualifications.

The involvement of people with lived experience in a number of roles was a strength of this study, albeit with challenges. Several recruited and appointed peer researchers withdrew for personal reasons. We were able to work flexibly nonetheless to engage people in peer researcher and other advisor and consultant roles, and hugely benefitted from working with these individuals. In particular, a peer researcher who was recruited fairly late in the project lifecycle played a central role in conducting and analysing the co-design sessions with NEET young women. We acknowledge that we presented co-design session participants with draft ideas for the intervention, rather than inviting ideas with no stimuli. However, we believe this to be an appropriate approach to co-design. Young people are well able to describe what they like and dislike about potential intervention components but may be less able to generate effective behaviour change techniques or design solutions themselves [ 44 ]. Indeed, when we asked young people in the Phase 1 qualitative interviews for ideas and preferences regarding a hope-focused intervention, we realised that participants found this to be a challenging task. We consider that our approach, in which we showed a draft intervention outline and invited critical commentary, was a strength of the current project. We found that this way of working elicited directly relevant reflections and actionable suggestions from co-design participants, but also critical comments such that they appeared to feel able to challenge and disagree with our ideas. We acknowledge that involvement of family members and professionals in complementary co-design sessions would have enabled more in-depth consideration from their perspectives.

The HOPEFUL intervention developed in this study offers a theory-driven practice innovation to prevent mental ill-health and improve social outcomes for a vulnerable and neglected group of NEET young women. By targeting a core ingredient that predicates goal-directed behaviour change and underpins well-being, this intervention has the potential to enhance hope as a means of helping NEET young women to thrive, and to augment how they interact with their surroundings. It has been designed with the potential for scalable implementation in mind, using simple and adaptable intervention materials and activities, and mobilising existing community members as intervention supporters rather than established practitioners. This intervention could complement other population-level initiatives that target wider structural challenges, such as poverty, isolation, lack of infrastructure, and gender-based violence and discrimination in under-resourced coastal areas and other areas of high disadvantage. Future research by our group will evaluate this intervention in practice.

Supporting information

S1 table. data analysis of phase 1 stakeholder research interviews conducted with neet young women, family members, and health and community practitioners..

Illustrative quotes are presented, labelled with participant number.

https://doi.org/10.1371/journal.pone.0304470.s001

S2 Table. Data analysis of Phase 2 co-design sessions conducted with NEET young women.

https://doi.org/10.1371/journal.pone.0304470.s002

S1 Fig. Intervention module importance rankings by Phase 2 co-design participants.

Module names are presented with module number in parentheses. Primary axis presents percentage of participants ranking each module 1 (most important) to 6 (least important). Secondary axis presents mean rank.

https://doi.org/10.1371/journal.pone.0304470.s003

S2 Fig. Intervention module activities importance rankings by Phase 2 co-design participants.

Module name and number presented as figure titles. Primary axes present percentage of participants ranking each module activity 1 (most important) to 4 (least important). Secondary axes present mean rank.

https://doi.org/10.1371/journal.pone.0304470.s004

S3 Fig. Intervention outcomes importance rankings by Phase 2 co-design participants.

Primary axis presents percentage of participants ranking each outcome 1 (most important) to 10 (least important). Secondary axis presents mean ranks.

https://doi.org/10.1371/journal.pone.0304470.s005

Acknowledgments

We are grateful to everyone who participated in this project. We wish to acknowledge the support for this study provided by the Youth Café and other members of the public who provided consultation input, additional project researchers based at the University of Sussex, and everyone who facilitated the involvement of participants in this project. We are grateful to the study steering committee who provided invaluable guidance in this work.

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43. Akinwale B, Allen D, Allen J, Buck D, Catchpole R, Connolly AM, et al. Reducing the number of young people not in employment, education or training (NEET). London; 2014. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/355771/Briefing3_NEETs_health_inequalities.pdf
46. Danermark B, Ekström M, Karlsson JC. Explaining society: Critical realism in the social sciences. Ekström M, Danermark B, Karlsson JCh, Jakobsen L, editors. London: Routledge; 2002.
51. Anderson AA. The Community Builder’s Approach to Theory of Change. New York; 2005.
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109. Hayes SC, Strosahl K, Wilson KG. Acceptance and commitment therapy: An experiential approach to behavior change. New York: Guilford Press; 1999. https://books.google.co.uk/books/about/Acceptance_and_Commitment_Therapy.html?id=ZCeB0JxG6EcC

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What Is Qualitative Research?
Qualitative research methods. 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 ...
Qualitative Research Methodologies
Qualitative research methodologies seek to capture information that often can't be expressed numerically. ... Qualitative research methods can be used to study: ... For example, researchers might visit a school cafeteria to learn about the food choices students make or set up trail cameras to collect information about animal behavior in the ...
Qualitative Research
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.
PDF A Guide to Using Qualitative Research Methodology
issue, then qualitative methods are often appropriate. Examples of topics that qualitative methodologies can address include: People's experiences of health needs, health care, accessing care and keeping healthy. Understanding different perspectives, such as those of professionals and patients. How experiences, attitudes and life
Chapter 1. Introduction
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 ...
Qualitative Research: Definition, Types, Methods and Examples
Qualitative research is defined as a market research method that focuses on obtaining data through open-ended and conversational communication. This method is about "what" people think and "why" they think so. For example, consider a convenience store looking to improve its patronage.
How to use and assess qualitative research methods
Abstract. This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions ...
What is Qualitative Research? Definition, Types, Examples, Methods, and
Qualitative research is defined as an exploratory method that aims to understand complex phenomena, often within their natural settings, by examining subjective experiences, beliefs, attitudes, and behaviors. Unlike quantitative research, which focuses on numerical measurements and statistical analysis, qualitative research employs a range of ...
What is Qualitative Research? Methods, Types, Approaches, And Examples
Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data. (Image by rawpixel.com on Freepik) Qualitative research is a type of method that researchers use depending on their study requirements. Research can be conducted using several methods, but before starting the process, researchers should understand the different methods available to decide the ...
Definition
Qualitative research is the naturalistic study of social meanings and processes, using interviews, observations, and the analysis of texts and images. In contrast to quantitative researchers, whose statistical methods enable broad generalizations about populations (for example, comparisons of the percentages of U.S. demographic groups who vote in particular ways), qualitative researchers use ...
PDF Introduction to Qualitative Research Methodology
and conduct selected qualitative research methods (Chapters 3 to 6) • Third, to enable you to process the textual data obtained through these methods, and to undertake preliminary steps ... examples to help you understand the ideas and reﬂ ect on their application. The chapters are also interspersed with Boxes, Examples, and Exercises to ...
Qualitative Study
Qualitative research is a type of research that explores and provides deeper insights into real-world problems.[1] Instead of collecting numerical data points or intervening or introducing treatments just like in quantitative research, qualitative research helps generate hypothenar to further investigate and understand quantitative data. Qualitative research gathers participants' experiences ...
Planning Qualitative Research: Design and Decision Making for New
While many books and articles guide various qualitative research methods and analyses, there is currently no concise resource that explains and differentiates among the most common qualitative approaches. We believe novice qualitative researchers, students planning the design of a qualitative study or taking an introductory qualitative research course, and faculty teaching such courses can ...
Characteristics of Qualitative Research
Qualitative research is a method of inquiry used in various disciplines, including social sciences, education, and health, to explore and understand human behavior, experiences, and social phenomena. It focuses on collecting non-numerical data, such as words, images, or objects, to gain in-depth insights into people's thoughts, feelings, motivations, and perspectives.
What is Qualitative in Qualitative Research
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 ...
What Is a Research Methodology?
In qualitative research, methods are often more flexible and subjective. For this reason, it's crucial to robustly explain the methodology choices you made. ... Example: Qualitative methods. In order to gain better insight into possibilities for future improvement of the fitness store's product range, semi-structured interviews were ...
What Is Qualitative Research?
Qualitative research methods. 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 ...
What is Qualitative Research? Methods and Examples
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 ...
16 Qualitative Methods Examples (2024)
See Also: Case Study Advantages and Disadvantages 2. Grounded Theory. Grounded theory is a research methodology that involves the collection and analysis of qualitative data with the aim of creating theories that are grounded in the data itself.. The defining feature of grounded theory is that it does not text a theory or hypothesis, unlike most other research approaches.
Research Methodology
Qualitative Research Methodology. This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.
Case Study Methodology of Qualitative Research: Key Attributes and
A case study is one of the most commonly used methodologies of social research. This article attempts to look into the various dimensions of a case study research strategy, the different epistemological strands which determine the particular case study type and approach adopted in the field, discusses the factors which can enhance the effectiveness of a case study research, and the debate ...
CHAPTER 3
Within the theoretical-empirical papers, approximately 67% were of qualitative nature, predominantly case studies (55,7%) as the main research method, although it can be suggested there is a ...
6 Qualitative Data Examples for Thorough Researchers
6 Qualitative data examples. The things you can do with qualitative data are endless. But this article shouldn't turn into a work of literature, so we'll highlight six ways to collect qualitative data and give you examples of how to use these qualitative research methods to get actionable results.
Choosing a Qualitative Research Approach
In this Rip Out, we describe 3 different qualitative research approaches commonly used in medical education: grounded theory, ethnography, and phenomenology. Each acts as a pivotal frame that shapes the research question (s), the method (s) of data collection, and how data are analyzed. 4, 5. Go to:
Research Methodology
Methodology refers to the overarching strategy and rationale of your research. Developing your methodology involves studying the research methods used in your field and the theories or principles that underpin them, in order to choose the approach that best matches your research objectives. Methodology is the first step in planning a research project.
Qualitative Significance as First-Class Evidence in the Design and
Qualitative data were collected by two members of the research team with expertise in qualitative methodology. Data collection, both quantitative and qualitative, followed the same procedure. The person in charge of administering the questionnaires or conducting the interviews contacted the research participant by telephone to arrange a date.
Developing a hope-focused intervention to prevent mental health
The current study used a phased qualitative research design and participatory methods to model a hope-focused intervention for NEET young women. Phase 1 investigated population needs and intervention parameters through semi-structured interviews with 28 key informants living or working in disadvantaged coastal communities in South-East England.
Pairwise summation as a method for the additive combination of
For example, use of a numerical reference associated with the qualitative probabilities (i.e., "Low" = 3, "Medium" = 4, and "High" = 5 (Islam et al., 2020)) introduces the assumption that all the qualitative probabilities are equidistant to one another in the probability space while in using the expert opinion or the higher estimate ...

Research Methodologies

Qualitative Research Methodologies

Library Help

Qualitative Research Approaches

Ethnography

Grounded Theory

Narrative Research

Phenomenology

Focus Groups

Observational Study

Open-Ended Surveys

Structured or Semi-Structured Interviews

Chapter 1. Introduction

Why an Open Access Textbook on Qualitative Research Methods?

What is Research?

What is Qualitative Research?

Examples of Qualitative Research

Example 1 : The End Game (ethnography + interviews)

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

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

How Is This Book Organized?

Chapter Descriptions

Recommended Reading: Other Qualitative Research Textbooks

Patton’s Ten Suggestions for Doing Qualitative Research

Qualitative Research Methods: Types, Analysis + Examples

What is qualitative research?

Types of qualitative research methods with examples

1. One-on-one interview

2. Focus groups

3. Ethnographic research

4. Case study research

5. Record keeping

6. Process of observation

Qualitative research: data collection and analysis

B. Qualitative data analysis

Characteristics of qualitative research methods

Qualitative research method case study

When to use qualitative research

Qualitative research methods vs quantitative research methods

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Qualitative Research : Definition

Events and Workshops

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What Is Qualitative Research? | Methods & Examples

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16 Qualitative Methods Examples

Qualitative Methods Examples

2. Grounded Theory

3. Ethnography

4. Autoethnography

5. Phenomenology

6. Narrative Research

7. Action Research

8. Focus Group Research

9. Semi-Structured Interviewing

10. Structured Interviewing

11. Observational Research

12. Delphi Method

13. Textual & Content Analysis

14. Discourse Analysis

15. Life History Research

16. Semiotic Analysis

Pros and Cons of Qualitative Research

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Research Methodology – Types, Examples and writing Guide

Research Methodology

Structure of Research Methodology

Research Methodology Types

Quantitative Research Methodology

Qualitative Research Methodology

Mixed-Methods Research Methodology