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• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

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

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

• Flexibility

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

• Natural settings

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

• Meaningful insights

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

• Generation of new ideas

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

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

• Unreliability

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

• Subjectivity

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

• Limited generalizability

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

• Labor-intensive

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

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

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

Research bias

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

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

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

There are five common approaches to qualitative research :

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

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

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

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

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

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Chapter 1. Introduction

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

Why an Open Access Textbook on Qualitative Research Methods?

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

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

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

What is Research?

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

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

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

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

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

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

What is Qualitative Research?

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

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

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

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

Examples of Qualitative Research

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

Example 1 : The End Game (ethnography + interviews)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

How Is This Book Organized?

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

Chapter Descriptions

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Recommended Reading: Other Qualitative Research Textbooks

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

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

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

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

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

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

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

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

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

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

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

Patton’s Ten Suggestions for Doing Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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The Oxford Handbook of Qualitative Research (2nd edn)

Patricia Leavy Independent Scholar Kennebunk, ME, USA

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The Oxford Handbook of Qualitative Research, second edition, presents a comprehensive retrospective and prospective review of the field of qualitative research. Original, accessible chapters written by interdisciplinary leaders in the field make this a critical reference work. Filled with robust examples from real-world research; ample discussion of the historical, theoretical, and methodological foundations of the field; and coverage of key issues including data collection, interpretation, representation, assessment, and teaching, this handbook aims to be a valuable text for students, professors, and researchers. This newly revised and expanded edition features up-to-date examples and topics, including seven new chapters on duoethnography, team research, writing ethnographically, creative approaches to writing, writing for performance, writing for the public, and teaching qualitative research.

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• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

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

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

• Flexibility

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

• Natural settings

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

• Meaningful insights

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

• Generation of new ideas

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

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

• Unreliability

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

• Subjectivity

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

• Limited generalisability

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

• Labour-intensive

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

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

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

There are five common approaches to qualitative research :

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

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

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

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

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

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Qualitative Research : 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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Introduction to qualitative research methods – Part I

Shagufta bhangu.

Department of Global Health and Social Medicine, King's College London, London, United Kingdom

Fabien Provost

Carlo caduff.

Qualitative research methods are widely used in the social sciences and the humanities, but they can also complement quantitative approaches used in clinical research. In this article, we discuss the key features and contributions of qualitative research methods.

INTRODUCTION

Qualitative research methods refer to techniques of investigation that rely on nonstatistical and nonnumerical methods of data collection, analysis, and evidence production. Qualitative research techniques provide a lens for learning about nonquantifiable phenomena such as people's experiences, languages, histories, and cultures. In this article, we describe the strengths and role of qualitative research methods and how these can be employed in clinical research.

Although frequently employed in the social sciences and humanities, qualitative research methods can complement clinical research. These techniques can contribute to a better understanding of the social, cultural, political, and economic dimensions of health and illness. Social scientists and scholars in the humanities rely on a wide range of methods, including interviews, surveys, participant observation, focus groups, oral history, and archival research to examine both structural conditions and lived experience [ Figure 1 ]. Such research can not only provide robust and reliable data but can also humanize and add richness to our understanding of the ways in which people in different parts of the world perceive and experience illness and how they interact with medical institutions, systems, and therapeutics.

Examples of qualitative research techniques

Qualitative research methods should not be seen as tools that can be applied independently of theory. It is important for these tools to be based on more than just method. In their research, social scientists and scholars in the humanities emphasize social theory. Departing from a reductionist psychological model of individual behavior that often blames people for their illness, social theory focuses on relations – disease happens not simply in people but between people. This type of theoretically informed and empirically grounded research thus examines not just patients but interactions between a wide range of actors (e.g., patients, family members, friends, neighbors, local politicians, medical practitioners at all levels, and from many systems of medicine, researchers, policymakers) to give voice to the lived experiences, motivations, and constraints of all those who are touched by disease.

PHILOSOPHICAL FOUNDATIONS OF QUALITATIVE RESEARCH METHODS

In identifying the factors that contribute to the occurrence and persistence of a phenomenon, it is paramount that we begin by asking the question: what do we know about this reality? How have we come to know this reality? These two processes, which we can refer to as the “what” question and the “how” question, are the two that all scientists (natural and social) grapple with in their research. We refer to these as the ontological and epistemological questions a research study must address. Together, they help us create a suitable methodology for any research study[ 1 ] [ Figure 2 ]. Therefore, as with quantitative methods, there must be a justifiable and logical method for understanding the world even for qualitative methods. By engaging with these two dimensions, the ontological and the epistemological, we open a path for learning that moves away from commonsensical understandings of the world, and the perpetuation of stereotypes and toward robust scientific knowledge production.

Developing a research methodology

Every discipline has a distinct research philosophy and way of viewing the world and conducting research. Philosophers and historians of science have extensively studied how these divisions and specializations have emerged over centuries.[ 1 , 2 , 3 ] The most important distinction between quantitative and qualitative research techniques lies in the nature of the data they study and analyze. While the former focus on statistical, numerical, and quantitative aspects of phenomena and employ the same in data collection and analysis, qualitative techniques focus on humanistic, descriptive, and qualitative aspects of phenomena.[ 4 ]

For the findings of any research study to be reliable, they must employ the appropriate research techniques that are uniquely tailored to the phenomena under investigation. To do so, researchers must choose techniques based on their specific research questions and understand the strengths and limitations of the different tools available to them. Since clinical work lies at the intersection of both natural and social phenomena, it means that it must study both: biological and physiological phenomena (natural, quantitative, and objective phenomena) and behavioral and cultural phenomena (social, qualitative, and subjective phenomena). Therefore, clinical researchers can gain from both sets of techniques in their efforts to produce medical knowledge and bring forth scientifically informed change.

KEY FEATURES AND CONTRIBUTIONS OF QUALITATIVE RESEARCH METHODS

In this section, we discuss the key features and contributions of qualitative research methods [ Figure 3 ]. We describe the specific strengths and limitations of these techniques and discuss how they can be deployed in scientific investigations.

Key features of qualitative research methods

One of the most important contributions of qualitative research methods is that they provide rigorous, theoretically sound, and rational techniques for the analysis of subjective, nebulous, and difficult-to-pin-down phenomena. We are aware, for example, of the role that social factors play in health care but find it hard to qualify and quantify these in our research studies. Often, we find researchers basing their arguments on “common sense,” developing research studies based on assumptions about the people that are studied. Such commonsensical assumptions are perhaps among the greatest impediments to knowledge production. For example, in trying to understand stigma, surveys often make assumptions about its reasons and frequently associate it with vague and general common sense notions of “fear” and “lack of information.” While these may be at work, to make such assumptions based on commonsensical understandings, and without conducting research inhibit us from exploring the multiple social factors that are at work under the guise of stigma.

In unpacking commonsensical understandings and researching experiences, relationships, and other phenomena, qualitative researchers are assisted by their methodological commitment to open-ended research. By open-ended research, we mean that these techniques take on an unbiased and exploratory approach in which learnings from the field and from research participants, are recorded and analyzed to learn about the world.[ 5 ] This orientation is made possible by qualitative research techniques that are particularly effective in learning about specific social, cultural, economic, and political milieus.

Second, qualitative research methods equip us in studying complex phenomena. Qualitative research methods provide scientific tools for exploring and identifying the numerous contributing factors to an occurrence. Rather than establishing one or the other factor as more important, qualitative methods are open-ended, inductive (ground-up), and empirical. They allow us to understand the object of our analysis from multiple vantage points and in its dispersion and caution against predetermined notions of the object of inquiry. They encourage researchers instead to discover a reality that is not yet given, fixed, and predetermined by the methods that are used and the hypotheses that underlie the study.

Once the multiple factors at work in a phenomenon have been identified, we can employ quantitative techniques and embark on processes of measurement, establish patterns and regularities, and analyze the causal and correlated factors at work through statistical techniques. For example, a doctor may observe that there is a high patient drop-out in treatment. Before carrying out a study which relies on quantitative techniques, qualitative research methods such as conversation analysis, interviews, surveys, or even focus group discussions may prove more effective in learning about all the factors that are contributing to patient default. After identifying the multiple, intersecting factors, quantitative techniques can be deployed to measure each of these factors through techniques such as correlational or regression analyses. Here, the use of quantitative techniques without identifying the diverse factors influencing patient decisions would be premature. Qualitative techniques thus have a key role to play in investigations of complex realities and in conducting rich exploratory studies while embracing rigorous and philosophically grounded methodologies.

Third, apart from subjective, nebulous, and complex phenomena, qualitative research techniques are also effective in making sense of irrational, illogical, and emotional phenomena. These play an important role in understanding logics at work among patients, their families, and societies. Qualitative research techniques are aided by their ability to shift focus away from the individual as a unit of analysis to the larger social, cultural, political, economic, and structural forces at work in health. As health-care practitioners and researchers focused on biological, physiological, disease and therapeutic processes, sociocultural, political, and economic conditions are often peripheral or ignored in day-to-day clinical work. However, it is within these latter processes that both health-care practices and patient lives are entrenched. Qualitative researchers are particularly adept at identifying the structural conditions such as the social, cultural, political, local, and economic conditions which contribute to health care and experiences of disease and illness.

For example, the decision to delay treatment by a patient may be understood as an irrational choice impacting his/her chances of survival, but the same may be a result of the patient treating their child's education as a financial priority over his/her own health. While this appears as an “emotional” choice, qualitative researchers try to understand the social and cultural factors that structure, inform, and justify such choices. Rather than assuming that it is an irrational choice, qualitative researchers try to understand the norms and logical grounds on which the patient is making this decision. By foregrounding such logics, stories, fears, and desires, qualitative research expands our analytic precision in learning about complex social worlds, recognizing reasons for medical successes and failures, and interrogating our assumptions about human behavior. These in turn can prove useful in arriving at conclusive, actionable findings which can inform institutional and public health policies and have a very important role to play in any change and transformation we may wish to bring to the societies in which we work.

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

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

Characteristics of Qualitative Research

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

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

The Collection of Data

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

The Analysis

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

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

Basic Research Design for Qualitative Studies

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

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

Strengths of Using Qualitative Methods

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

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

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

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

Limitations of Using Qualitative Methods

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

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

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

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Human Subject Research and Institutional Review Board Approval

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

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

Another Research Tip

Finding Examples of How to Apply Different Types of Research Methods

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

SAGE Research Methods Online and Cases

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

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

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Home » Qualitative Research – Methods, Analysis Types and Guide

Qualitative Research – Methods, Analysis Types and Guide

Table of Contents

Qualitative Research

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

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

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

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

Focus Groups

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

Ethnographic Studies

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

Text Analysis

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

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

Process of Observation

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

Record Keeping

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

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

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

Qualitative Research Analysis Methods

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

Thematic Analysis

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

Content Analysis

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

Discourse Analysis

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

Grounded Theory Analysis

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

Narrative Analysis

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

Phenomenological Analysis

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

Comparative Analysis

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

Applications of Qualitative Research

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

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

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

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

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

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

Purpose of Qualitative Research

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

Qualitative research can serve multiple purposes, including:

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

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

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

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

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

Advantages of Qualitative Research

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

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

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

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

Also see Research Methods

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You are here, an introduction to terminology used in qualitative and quantitative research.

The two basic research approaches exist in social science research, termed qualitative and quantitative approaches and these differ in the way in which the research is carried out:

Qualitative research is based on identifying a central phenomenon which could take the form of a concept area or a process. The research is centred on a research question which is often open in nature, at least at the start of the research. Information is then collected by the researcher using qualitative approaches to explore this further. The nature of qualitative research is to explore a research theme to develop understanding of factors influencing this issue.

Quantitative research is centred on ‘explaining or predicting relations among variables’ (Cresswell 2011: 63). As the name implies, qualitative research involves the collection and analysis of numerical data. Also a hypothesis may be used, particularly in an experimental approach which is tested using statistical procedures.

In both types of research, the research question informs the choice of methods and the wording and structure of this question is therefore extremely important. Key differences between qualitative and quantitative research problems are outlined below:

Quantitative research is based on a specific and narrow research question which is closed-ended and static and focuses on exploring the relationships between variables.

Qualitative research focuses on concepts and ideas and is more open-ended and the question tends to develop as the research progresses. In qualitative research it is common for the question itself to change and develop. Creswell (2011) terms this an ‘emerging process’ which is shaped by the responses of the participants during the research process.

A mixed methods approach is also possible in which both qualitative and quantitative approaches are employed.

The use of terminology in social science research is often inconsistent, and it is important to be aware of this to avoid confusion when reading research texts. In this MESHGuide the following terms will be used:

research methodology (which you may also see termed research strategies )

research methods

research tools

Thinking about the reasoning underpinning your research approach: Deductive or Inductive?

It is important to consider the nature of the link between the research question and the process of reasoning that underpins the research approach you propose to use to answer it, as this will influence your research design. There are two main types of reasoning: deductive and inductive. A deductive approach is based on theory testing, where an idea or theory is developed into a hypothesis which is tested by gathering evidence from which logical conclusions are drawn (see An introduction to terminology: Qualitative / quantitative research) . Inductive reasoning is traditionally associated with qualitative studies. In a qualitative context an inductive approach is based on theory building, in which evidence is gathered and analysed to identify patterns and processes. This leads to the development of hypotheses which may lead to theory generation (Newby, 2014). However it is also possible for qualitative studies to include elements of deductive reasoning designed to explore theoretical statements, although not in the same way as in quantitative research (Newby, 2014). Similarly, inductive reasoning can also be used in quantitative research at the stage of formulating the problem. Cohen et al. (2011) term this an inductive/deductive approach, where elements from both approaches are combined, with the process of induction in the development of the initial hypothesis which is subsequently tested and its implications explored through a process of deduction.

An overview of some of the terminology used in social science research

Research methodology (research strategies)

Quantitative approaches:

experimental design

Qualitative approaches:

case studies

action research

ethnography

phenomenology

grounded theory

• Research Design

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Qualitative vs Quantitative Research Methods & Data Analysis

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

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

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

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The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

• Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed numerically. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.
• Qualitative research gathers non-numerical data (words, images, sounds) to explore subjective experiences and attitudes, often via observation and interviews. It aims to produce detailed descriptions and uncover new insights about the studied phenomenon.

On This Page:

What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, 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. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human.  Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography .

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions.  This allows the respondent to talk in some depth, choosing their own words.  This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis .

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded .

Key Features

• Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
• Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
• The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
• The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
• The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

• Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
• The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
• Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
• The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

• Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
• Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
• Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
• Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things.  However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms. 

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

• Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
• The research aims for objectivity (i.e., without bias) and is separated from the data.
• The design of the study is determined before it begins.
• For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
• Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

• Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
• Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
• Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
• Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

• Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
• Useful for testing and validating already constructed theories.
• Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
• Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
• Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

• Mixed methods research
• Designing qualitative research
• Methods of data collection and analysis
• Introduction to quantitative and qualitative research
• Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
• Qualitative research in health care: Analysing qualitative data
• Qualitative data analysis: the framework approach
• Using the framework method for the analysis of
• Qualitative data in multi-disciplinary health research
• Content Analysis
• Grounded Theory
• Thematic Analysis

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Standards for reporting qualitative research: a synthesis of recommendations

Affiliation.

• 1 Dr. O'Brien is assistant professor, Department of Medicine and Office of Research and Development in Medical Education, University of California, San Francisco, School of Medicine, San Francisco, California. Dr. Harris is professor and head, Department of Medical Education, University of Illinois at Chicago College of Medicine, Chicago, Illinois. Dr. Beckman is professor of medicine and medical education, Department of Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota. Dr. Reed is associate professor of medicine and medical education, Department of Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota. Dr. Cook is associate director, Mayo Clinic Online Learning, research chair, Mayo Multidisciplinary Simulation Center, and professor of medicine and medical education, Mayo Clinic College of Medicine, Rochester, Minnesota.
• PMID: 24979285
• DOI: 10.1097/ACM.0000000000000388

Purpose: Standards for reporting exist for many types of quantitative research, but currently none exist for the broad spectrum of qualitative research. The purpose of the present study was to formulate and define standards for reporting qualitative research while preserving the requisite flexibility to accommodate various paradigms, approaches, and methods.

Method: The authors identified guidelines, reporting standards, and critical appraisal criteria for qualitative research by searching PubMed, Web of Science, and Google through July 2013; reviewing the reference lists of retrieved sources; and contacting experts. Specifically, two authors reviewed a sample of sources to generate an initial set of items that were potentially important in reporting qualitative research. Through an iterative process of reviewing sources, modifying the set of items, and coding all sources for items, the authors prepared a near-final list of items and descriptions and sent this list to five external reviewers for feedback. The final items and descriptions included in the reporting standards reflect this feedback.

Results: The Standards for Reporting Qualitative Research (SRQR) consists of 21 items. The authors define and explain key elements of each item and provide examples from recently published articles to illustrate ways in which the standards can be met.

Conclusions: The SRQR aims to improve the transparency of all aspects of qualitative research by providing clear standards for reporting qualitative research. These standards will assist authors during manuscript preparation, editors and reviewers in evaluating a manuscript for potential publication, and readers when critically appraising, applying, and synthesizing study findings.

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What is a Qualitative Research Article?

Qualitative research:

• focused on obtaining non-numerical data through open-ended and conversational communication
• can gain data through research, observation, interviews, surveys/questionnaires, focus groups, case studies

Ovid/CINAHL Qualitative Terms

Medical Subject Headings (MeSH) for Qualitative Research

MEDLINE has the following MeSH terms available, which can be used to retrieve qualitative research

Qualitative Research  - research that derives data from observation, interviews, or verbal interactions and focuses on the meanings and interpretations of the participants. Year introduced: 2003

Interviews as Topic  - conversations with an individual or individuals held in order to obtain information about their background and other personal biographical data, their attitudes and opinions, etc. It includes school admission or job interviews. Year introduced: 2008 (1980)

Focus Groups  - a method of data collection and a qualitative research tool in which a small group of individuals are brought together and allowed to interact in a discussion of their opinions about topics, issues, or questions. Year introduced: 1993]

Nursing Methodology Research  - research carried out by nurses concerning techniques and methods to implement projects and to document information, including methods of interviewing patients, collecting data, and forming inferences. The concept includes exploration of methodological issues such as human subjectivity and human experience. Year introduced: 1991(1989)

Anecdotes as Topic  - brief accounts or narratives of an incident or event. Year introduced: 2008(1963)]

Narration  - the act, process, or an instance of narrating, i.e., telling a story. In the context of MEDICINE or ETHICS, narration includes relating the particular and the personal in the life story of an individual. Year introduced: 2003

Video Recording  - the storing or preserving of video signals for television to be played back later via a transmitter or receiver. Recordings may be made on magnetic tape or discs (VIDEODISC RECORDING). Year introduced: 1984

Tape Recording  - recording of information on magnetic or punched paper tape. Year introduced: 1967(1964)

Personal Narratives as Topic  - works about accounts of individual experience in relation to a particular field or of participation in related activities. Year introduced: 2013

CINAHL's "Qualitative Studies" 

In 1988, the phrase "Qualitative Studies" was added to the CINAHL subject thesaurus, and it is applied to records describing "investigations which use sensory methods such as listening or observing to gather and organize data into patterns or themes." 

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Action Research

Ethnographic Research

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Grounded Theory

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Phenomenological Research

Exploding' (+) this term will include those headings in the search as well (searching them all together with OR):  (MH "Qualitative Studies+") 

Related Subject Headings 

There are a number of additional CINAHL Subject Headings that may indicate that a record is describes qualitative research.  For instance:

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Observational Method

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Ovid's Qualitative Publication Types

Medline records contain publication type metadata, allowing you to limit your search to only show records for publication types that are, by definition, most likely qualitative.  possible publication type values include:.

• Interview : work consisting of a conversation with an individual regarding his or her background and other personal and professional details, opinions on specific subjects posed by the interviewer, etc. Year introduced: 2008(1993)
• Diaries : works consisting of records, usually private, of writers' experiences, observations, feelings, attitudes, etc. They may also be works marked in calendar order in which to note appointments and the like. (From Random House Unabridged Dictionary, 2d ed.) Year introduced: 2008(1997)
• Anecdotes : works consisting of brief accounts or narratives of incidents or events. Year introduced: 2008(1999)
• Personal Narratives : works consisting of accounts of individual experience in relation to a particular field or of participation in related activities. Year introduced: 2013

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Qualitative Keywords

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(qualitative OR ethnograph* OR phenomenol* OR ethnonurs* OR grounded theor* OR purposive sample OR hermeneutic* OR heuristic* OR semiotics OR lived experience* OR narrative* OR life experiences OR cluster sample OR action research OR observational method OR content analysis OR thematic analysis OR constant comparative method OR field stud* OR theoretical sample OR discourse analysis OR focus group* OR ethnological research OR ethnomethodolog* OR interview*)

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• Open access
• Published: 06 September 2024

A qualitative study of experiences among young adults who increased their cannabis use during the COVID-19 pandemic

• Laura L. Struik 1 ,
• Alexia Armasu 2 ,
• Genevieve Fortin 3 , 4 ,
• Teodora Riglea 2 , 3 ,
• Jodi Kalubi 2 , 3 , 4 ,
• Olivier Ferlatte 3 , 4 ,
• Mounia Naja 2 ,
• Jennifer O’Loughlin 2 , 3 &
• Marie-Pierre Sylvestre 2 , 3  

BMC Public Health volume  24 , Article number:  2434 ( 2024 ) Cite this article

Metrics details

Young adults face unique vulnerabilities during major life disruptions like the COVID-19 pandemic. The pandemic contributed to increases in mental health challenges and substance use among young adults. This study explores the experiences of young adults who increased their cannabis use during the pandemic.

Participants were recruited from the Nicotine Dependence in Teens (NDIT) study, and qualitative data were collected through semi-structured interviews conducted via Zoom. A total of 25 participants (ages 33–34) reporting increased cannabis use during the pandemic were included. Thematic analysis and gender-based analysis was employed to extract key themes.

Five themes emerged: (1) No disruption in cannabis use; (2) Cannabis use to manage declines in mental health; (3) Cannabis use to break up pandemic boredom; (4) Cannabis use as an expression of freedom; (5) Cannabis use as “another way to chill out.”

Conclusions

This research provides valuable perspectives on how major life disruptions, like the COVID-19 pandemic, influence cannabis use among young adults. The findings offer guidance for public health initiatives and highlight avenues for further investigation.

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Introduction

The COVID-19 pandemic represented a major life disruption with unexpected changes to family dynamics (e.g., everyone at home), routines (e.g., school and extracurricular facilities closed), socialization (e.g., closure of restaurants and cancellation of social events), and employment (e.g., working at home and job loss) [ 1 , 2 ]. Because young adults are in a transitional life stage and often in the process of establishing themselves in these areas, they were particularly vulnerable to these disruptions, [ 3 ] and were among those most vulnerable to increasing substance use and mental health challenges in response to pandemic-induced distress [ 4 , 5 ]. A global cross-sectional survey of 1,653 participants ages 18–82 found that younger adults (age 18–34 years) were more vulnerable to pandemic-related stress, anxiety, and depression than older age groups [ 6 ].

Some evidence suggests that pandemic-related distress could have prompted increases in cannabis use to alleviate these negative effects [ 1 , 7 , 8 ]. For example, the Canadian Cannabis Survey in 2021 reported that 29% of Canadian cannabis users increased their cannabis use during the pandemic, which users attributed to boredom, stress, anxiety, lack of a regular schedule, and loneliness [ 9 ]. This appears to be especially true among young adults. According to a recent longitudinal study of changes in substance use before and during the pandemic, cannabis was the only substance that showed an increase in initiation and an increase in weekly/daily use among young adults age 30. [ 10 ] The experiences of young adults who increased their cannabis use during the pandemic to contextualize these numbers, however, remain unexplored.

There is emerging evidence that gender influences cannabis use. According to a systematic review, males are more likely to conform to “male typicality”, and are at higher risk of increased use during young adulthood than females [ 11 ]. In addition, gendered norms play different roles, with some protective of substance use (e.g., women are nurturing) and others conducive to substance use (e.g., women are relational) [ 11 ], lending to the conclusion that more more research is needed to understand the role of gender in cannabis use specifically. Some research has explored the role of gender in cannabis use during the pandemic. Compared to men, women reported greater increases in cannabis use to manage mental health challenges during the pandemic [ 12 , 13 , 14 , 15 ]. This may be due to women reporting higher rates of mental health issues during the pandemic compared to men [ 16 ]. Understanding the experiences of women and men during the pandemic is needed to unpack the relationship between gender and increased cannabis use during the pandemic.

Because cannabis was legalized in Canada in 2018, the pandemic paralleled rapid expansion of the cannabis market in cannabinoid composition (i.e., THC and CBD), potency of cannabis products, and delivery formats (e.g., inhalation, oral, topical) ( 17 – 18 ), which prompted an increase in cannabis use among young adults in particular [ 18 , 19 , 20 ]. Because most provinces and jurisdictions in Canada deemed cannabis retailers an essential service during the pandemic, [ 9 ] retailers were able to adapt by offering curbside pickup or online sales to reduce in-person interactions [ 21 ]. Understanding how such changes impacted cannabis use during the pandemic needs exploration.

Thus, there are numerous gaps in our understanding of cannabis use experiences among young adults during the pandemic. In this study, we addressed these gaps in an exploratory qualitative study of young adults who increased their cannabis use during the pandemic. Our objectives were to: (i) describe the cannabis use experiences of young adults during the pandemic; and (ii) investigate gender differences in their cannabis use experiences. Understanding these experiences is critical to informing the development of effective interventions to reduce the harms of cannabis use, particularly during major life disruptions.

Context – NDIT study

Participants were recruited from the Nicotine Dependence in Teens (NDIT) study, an ongoing investigation of 1294 participants recruited in 1999–2000 at ages 12–13 (grade 7 students). NDIT initially aimed to investigate the natural course and determinants of cigarette smoking and nicotine dependence in adolescence, [ 22 ] but quantitative data collection expanded to encompass use of other substances, lifestyle behaviours, genetics, anthropometrics measures, psychosocial factors, and mental health. Between 1999 and 2005 when participants (ages 12–17) were in high school, they completed self-report questionnaires every 3 months in a total of 20 data collection cycles. After high school, five additional data collection cycles have taken place to date (i.e., cycle 21 in 2007-08 at mean age 20.4 (SD = 0.8); cycle 22 in 2010-12 at mean age 24.0 (0.7); cycle 23 in 2017–2020 at mean age 30.6 (1.0); cycle 24 in 2020 -21 during the COVID-19 pandemic at mean age 33.6 (0.8) ; and cycle 25 at mean age 35.2 (0.61).

NDIT was approved by ethics committees at the Montreal Department of Public Health, McGill University and Centre hospitalier de l’Université de Montréal (2007–2384, 2017–6895, ND06.087). Parents/guardians provided written informed consent at baseline and participants, all of whom had attained legal age, provided consent post-high school.

Data collection

Participants who reported any increase in cannabis use in the past year during cycle 24 were eligible to participate in this qualitative study. From July to September 2021, a purposive sample of eligible English- and French-speaking males and females were invited to participate in 60-minute semi-structured interviews conducted via Zoom by AA and GF. During these interviews, participants were asked about how the pandemic influenced their mental health and health behaviors, including cannabis use. Herein, we present data on cannabis use during the pandemic among these young adults. These data are based on seven interview questions, including type, frequency, and context of use during the pandemic, reasons for use during the pandemic, and perceived positive and negative impacts of the pandemic on cannabis use.

Data analysis

All interviews were audio-recorded and transcribed by a third party. All transcripts were reviewed by research assistants for accuracy and then anonymized. We disaggregated the data by gender and analyzed the data using Braun and Clark’s thematic analysis approach [ 23 , 24 ], which comprises of six phases (familiarisation, initial code generation, theme generation, theme review, theme confirmation, and reporting). We positioned our analysis within a constructivist epistemology and interpretive/subjectivist ontology, meaning that the themes were developed through communication with the participants and through interpretations by the researchers. For phase one (familiarisation with the data), three researchers (GF, LS, and AA) read the transcripts and collaboratively iterated on what they were seeing in coding meetings. For phase two (initial code generation), we employed Nvivo qualitative data analysis software to generate descriptive codes for responses to the interview questions. For example, if a participant mentioned using cannabis to treat heightened anxiety during the pandemic, we created a broad code of “mental health” and then a sub-code of “anxiety”. One researcher (LS) then coded the transcripts for women, and another (AA) coded the transcripts for men (so that gender-based influences on cannabis experiences could be identified). During phase three (theme generation), after all transcripts were coded, we engaged in collaborative theme development meetings, wherein we discussed what meaning was shared across the entire sample and what meaning was unique to women or men as a collective, or even to individual participants. We did this iteratively until we established meaning saturation and no new themes emerged when reviewing the coded data. During phase four (theme review), we collaboratively iterated on the themes to ensure that nuances were appropriately captured. For phase five (naming themes), we discussed and generated a thematic framework to capture the themes and their relationships to each other.

The credibility of the study is established through content and methodological expertise among the study team members, and through the development of a codebook. The dependability of the study is ensured through a data analysis audit trail that we kept track of via research team reviews and summaries of transcripts, use of collaborative coding, and use of Nvivo data analysis software. The confirmability of the study findings is ensured through the frequent team meetings that were held to discuss and confirm consensus of the meaning of the findings throughout data analysis. The transferability of the study findings is enhanced through the robust sample size included in this study, with equal representation of males and females.

A total of 25 participants were included in this study (Table  1 ). Participants were all age 33 or 34, and just over half were female. All female participants identified as women and all male participants identified as men. All participants reported using cannabis daily or weekly in the past year. Most had more than high-school education in both female and male samples (91.7% and 84.6% respectively), and a household income above $50,000, which was slightly higher among males at 74.9% compared to 53.9%. Except for one, all participants were born in Canada. More female participants reported living alone (46.2%), being unemployed (38.5%), and having a history of a mental health diagnosis (53.8%). More male participants reported past year substance use of any kind compared to females. More females scored higher on depressive and anxiety symptoms than males.

Qualitative themes

Our findings revealed five themes that capture the influence of the pandemic on young adult cannabis use including: (1) no disruption in cannabis use; (2) cannabis use to manage declines in mental health; (3) cannabis use to break up pandemic boredom; (4) cannabis use as an expression of freedom; and (5) cannabis use as “another way to chill out”. Gender-specific findings in relation to these themes were identified.

No disruption in cannabis use

Men reported cannabis use as a more regular day-to-day activity than females. Thus, men were particularly vocal about experiencing little or no disruption in their use due to pandemic restrictions and lockdowns. Men reported that access to cannabis during the pandemic was not only unhindered, but became even easier. In addition to cannabis stores being considered an essential service in Quebec and allowed to remain open, these outlets quickly adapted to alternative and convenient modes of delivery, such as home delivery. Men reported enhanced accessibility as a major facilitating factor for use during the pandemic:

I mean already there was the accessibility. That’s one issue, that you can just go to the store and pick it up at any time. And it’s essential so it doesn’t close, while everything else does. (male, 1070001) ‘Cause if you ordered before 1:00 PM on their website, you would get it that evening. So I would literally like order it during the day and then at night, I’d order Uber Eats and my food and my weed would just get delivered to my door [laughs]. It was like “The future is here and it’s great”! [laughs] So yeah, that definitely contributed to like the more, easier access to it, like I didn’t even have to go to the store and have to deal with waiting in line, waiting in a huge line. Uh… and then going in the store, wearing a mask, all that stuff. (male, 115003)

Cannabis to manage declines in mental health

Participants frequently reported an increase in cannabis use during the pandemic because they struggled with heightened anxiety and stress in response to the impacts of the pandemic including job loss, working from home, having no childcare, and the overall stress of lockdowns:

Maybe [I used] a little bit more in terms of the anxiety that was coming up. So maybe I had a lot more bad nights during the pandemic than I would have had if there had been no pandemic. (female, 2580010) First time [I used cannabis] was just like curiosity and just kind of for fun. And the second time was COVID. That is actually the reason. (male, 80002)

Cannabis use to cope during the pandemic was particularly prevalent among women who were mothers. Women spoke to decreases in their mental health due to job-related stress combined with increased childcare responsibilities. They often described feeling out of control, and using cannabis was a way to cope with that feeling:

The biggest stressors for me were like the kids being home the whole time, or like for that stretch from March till the end of August of last year. And my work situation, just really feeling completely out of control. (female, 350001)

Many women, however, emphasized that they were using cannabis as an alternative to managing their mental health symptoms rather than to get high. Women with children made sure to emphasize that they did not use it in front of their children:

Well, a lot of times it’s when I have my kids my stress level is really, really high. So, around like 6 o’clock, I can’t take it anymore, so I go and smoke like three four puffs in the garage. (female, 1860010)

In addition, several women reported that endorsement by their doctor was important to their decision-making and comfort in using cannabis to treat their mental health symptoms:

[My Dr.] was like: “That’s good… if you can find something … to not be on Ativan every day instead.” (female, 1660001).

Cannabis as a way to break up pandemic boredom

Participants described feelings of boredom during the pandemic, which was largely blamed on their inability to engage in their usual day-to-day activities (e.g., going to work, gyms, or restaurants; socializing; participating in extracurricular activities). As a result, they described cannabis use as a tool that enabled them to face boredom and provided a means to entertain oneself during lockdowns and stay-at-home orders:

I think, it’s really just boredom, during the pandemic, not [laughs]-not having any action, like, it’s-it’s just that, basically. It wasn’t like, “Oh, my God, I’m sad right now, I want to like forget about it.” No, it was just like, “This is boring! Let’s try some things to like get a little buzz, a little effect.” (female, 720006).

In this vein, participants described using cannabis as something that became popular amongst a variety of social circles during the pandemic. They explained that all the new compositions (e.g., THC/CBD) and formats (e.g., edibles) of cannabis that were made widely available following the legalization of cannabis in Canada, prompted them to try new modes of consumption and new products because there was a sense among participants that cannabis was more acceptable and that everyone was trying it and discussing it:

During the pandemic, there was this new trend with candy. And I saw some very serious people - well, not very serious, but you know, very functional people, I mean, who work, who do, uh… who were talking to me about it, like, “Oh yeah, it’s really cool. It helps you relax.” So I tried it. I ordered a bottle-uh, a bottle-uh yeah, that’s right, a little bottle of candy. And yeah [laughs]! I thought it was like chill to try like at night. I was like, “Ah, this is cool! You know it’s relaxing.” Then I was taking something too that was- there was more- what do you call it? CBD… (female, 720006).

Cannabis use was also used to maintain social routines to combat pandemic boredom. One participant described smoking cannabis during video chats as a way to keep up his social connections:

So it was still kind of a social thing ‘cause I would be smoking in my room while my friends were on video calls, also smoking weed. So it’s like almost like we were doing the same thing that we were doing before, so it was– there was a little bit of social element. But again, it was only like once a week, but I was still smoking every day. (male, 1150003)

Cannabis use as an expression of freedom

Some participants, especially women, described cannabis use as an expression of freedom from the lockdowns. Nearly all participants reported first trying cannabis during adolescence. Therefore, using cannabis during the pandemic was paralleled with memories of when they were young and free. They described feeling like teenagers again, and wanting to be a bit wild when they felt so inhibited by the lockdowns. Some described using during lockdowns with others in their bubble, while others described using when there were breaks in the lockdowns at social gatherings as a way to celebrate:

We had gone out one night, and I felt like a teenager again. One of my friends had some edibles in the freezer, so me and my friends were like, “let’s try it”. (female, 710001) Uh, well I think, uh, there’s a kind of feeling like, “We got our freedom back”, you know. I must have been feeling a bit wild there you know like “anything goes” [laughs]! (female, 2090010)

“Another way to chill out”

Many participants reported using cannabis as a way of winding down from their hectic days, often referred to as an alternative to winding down with a glass of wine:

Oh I guess– I guess when I was using it, I was just kind of thinking…this is another way I can chill out. Like, can I do this or can I replace this with a glass of red wine, kind of thing? (female, 450003)

Some participants talked about how their alcohol consumption increased during the pandemic. They concluded that cannabis was a better alternative since they did not suffer from the side effects of excessive consumption like they did with alcohol (e.g., hangover):

Because initially…in the pandemic, it was more like let’s have drinks every night and that I feel has more of an effect on my state the following day, with a hangover, or it triggers a migraine. So I avoid that with cannabis. Which is I guess the lesser of two evils. (female, 350001)

While women reported using cannabis to wind down usually after tasks were completed and kids asleep, men often reported using cannabis earlier in the evening and as something to help them connect and feel more present with their family:

Like I don’t smoke a lot, you know I’d be like two or three puffs – and it really helps me to calm down and be present with my kids. (male, 420002)

Further, some women reported smoking cannabis as a way to connect with their husband or partner while they were winding down from the day. In fact, several women reported that they only started using it because their partner was using it:

Like I think for… in terms of smoking it, it just became… it was occasionally something to do cause my husband’s smoking it and… it was a nice way to like wind down in the evening kind of thing…it was enjoyable to do when it was… warm at night and we could sit outside and we would talk and we could you know smoke a little bit and chat and stuff like that. (female, 1660001)

Main findings

This study examined contextual factors that influenced cannabis use among young adults who reported an increase in cannabis use during a major life disruption, the COVID-19 pandemic. Themes in this study revealed that this disruption was associated with uninterrupted access to cannabis, a way to manage mental health, something that helped them manage boredom, something that reminded them of when they were young and free, and as another way to wind down. The findings also revealed some gender-based differences in use, whereby women expressed childcare and job-related strain as a key factor in increasing cannabis use. In addition, women were adamant about not exposing their children to cannabis, not using it to get high, and receiving their doctor’s approval to use cannabis to manage mental health symptoms. Finally, some women reported smoking cannabis (versus using oils or edibles) as a way to connect with their male partner.

Similar to other studies [ 8 , 27 , 28 ] young adults in this study reported increasing use to help them cope throughout the pandemic. For example, Clendennen et al. [ 27 ] found that increases in stress and symptoms of anxiety and depression predicted increases in cannabis use among young adults during the pandemic. Noteworthy in our study was the strain that mothers experienced. This may be due, in part, to the fact that childcare fell primarily on women during the pandemic [ 29 ]. According to a survey in the United States, compared to fathers, mothers reported that they were more likely to face professional hurdles, reduce their work hours, face difficulties in getting work done, and shoulder most of the caregiving burden [ 30 ]. The experiences of mothers in this study suggest a disproportionate impact of the pandemic on them regarding childcare, which could be attributed to normative gender-based roles (e.g., women are caregivers) that appeared to naturally fall into place when supports for women and working mothers (e.g., daycare) were no longer available. Our findings thus confirm that the lack of much needed targeted relief for mothers (e.g., social support, employment support) is an area for development.

Supportive of other studies, [ 31 ] young adults reported that cannabis use helped ease boredom during the pandemic. With limited opportunities for socialization, and the inability to engage in recreational activities that were part of their typical routine (e.g., going to the gym), young adults in this study used cannabis to break free and remedy their boredom. This method of coping with boredom raises concerns about the long-term impacts of the pandemic on substance use in general, including cannabis use behavior. It also raises questions about how young adults adapt to disruptions over time and if the increase in use in response to boredom was temporary. Regardless, these findings underscore the importance of recreational and social outlets for the young adult population.

The pandemic followed legalization of cannabis in Canada in 2018 closely [ 21 ], with new cannabis formats and potency options more readily available during the pandemic. This may have contributed to participants likening their cannabis use during the pandemic to their first use as teenagers, whereby new product options offered renewed novelty and excitement around cannabis. Similar to other studies [ 32 , 33 ], the effects of the pandemic on nostalgia for the “good old days” was expressed through engaging in activities that reminded participants of times when they were young and free (e.g., listening to music). Although there is evidence that nostalgia is protective of mental health and that it promoted happiness during the pandemic [ 34 , 35 ], the effects of cannabis use as a nostalgic activity needs more investigation.

The influence of gender on differential use and perceptions of cannabis was noteworthy. In particular, women appeared to be attuned to stigmatization associated with their use, emphasizing that they would not use around their children, were using it primarily to ease mental health symptoms rather than to get high, were more likely to use formats that did not produce smoke (e.g., oils and edibles), and reported that their doctor’s approval was important to them. Despite that legalization of cannabis has somewhat normalized cannabis use, social norms that associate cannabis use with masculinity problematizes cannabis use among women [ 36 ]. In an analysis of cannabis stigmas, Reid [ 37 ] cautioned against claims of normalization of cannabis use since qualitative accounts reveal increasing evidence that social stigmas are intersecting with particular groups who typically experience inequality, including women. Our qualitative findings underscore women’s accounts that reflect a desire to resist stigmatization of their use.

It was also interesting how cannabis use among men influenced uptake among their female partners. Women reported joining their partner in using cannabis as a way to connect and spend time together. Researchers examining heterosexual couples found that joint cannabis use appears to strengthen relationship functioning in the short term [ 38 ]. However, there is a gap in the literature regarding the impact of cannabis use among couples in the long term, as well as among couples whereby one partner started using cannabis because of the other partner.

Implications and future research

This study has implications for public health and future research. In relation to public health, the findings pinpoint actions that can be considered to support young adults through major life disruptions, like the COVID-19 pandemic. For example, promoting social and extracurricular outlets for young adults (e.g., discounts on camping or park passes), supporting mothers with childcare costs and relief (e.g., funding, space), creating supports in the context of job insecurity (e.g., lobby for government grants that could be activated during a global pandemic), and ensuring that doctors are educated on the effects of cannabis use should be a priority. Additionally, promoting healthy outlets to express nostalgia (e.g., through music or activities) may also be a productive way to promote resilience and happiness through challenging disruptions. In relation to future research, understanding the temporality of increased cannabis use during the pandemic, the potential benefits and pitfalls of using cannabis as a nostalgic activity, and the influence of partners on cannabis use are all areas which will benefit from future research.

Strengths and limitations

A strength of this study is that it is one of the first to explore how the pandemic influenced cannabis use among young adults through the voices of young adults. Another strength is the sample size and representation of women and men. As a result, a novel contribution of this study is an exploration of gender differences in the experience of cannabis use during the pandemic. A strength is also that the sample was drawn from a large pool of young adults in Quebec, Canada. Finally, the findings provide helpful directions for future research, and directions for public health advocates to consider when supporting young adults during major life disruptions, such as the pandemic.

Limitations include that this study involved a Quebec sample and Quebec had different rules around COVID-19 than other provinces, possibly limiting transferability of the findings. Another limitation is that the interviews were conducted in the summer of 2021, such that the full impact of the pandemic may not have been captured. However, the interviews were conducted after the lockdown, which represented a critical timeline during the pandemic. In addition, pandemic regulations during the summer, and access to the outdoors due to the weather, may have influenced participants’ cannabis use. Usage patterns and perceptions on cannabis use may have shifted after this time point (e.g., some users may have decided to quit or commit to a decrease in use). Finally, we did not measure the level of increase in cannabis use in this study sample.

This study examined how a major life disruption, the COVID-19 pandemic, influenced cannabis use among young adults. Our findings reveal the contextualized experiences of young women and men in navigating such a disruption and how it impacted their cannabis use. Young adults found that they did not experience any disruption in their ability to access cannabis, and they described increasing their use due to mental health struggles, feeling bored, as an expression of freedom during restrictions, and as a way to relax. These findings have important public health implications and identify key areas for future research.

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Acknowledgements

The authors would like to acknowledge the participants for their time and contributions.

The NDIT study was supported by the Canadian Cancer Society (grant numbers 010271, 017435, 704031) and the Canadian Institutes of Health Research (grant number 451832, 477288). LS is supported by a Canadian Cancer Society Emerging Scholar Award (grant number 707156). MPS is supported by Salary Awards from The Fonds de Recherche du Québec - Santé. JOL held a Tier 1 Canada Research Chair from 2004 to 2021. JK held a Doctoral Scholarship from the Québec Order of Nurses (Ordre des infirmières et infirmiers du Québec) from 2019 to 2022.

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L.S. conducted data analysis and wrote the main manuscript text. A.A. conducted data collection and analysis. G.F., J.K., and M-P.S. conducted data collection. O.F. supported data analysis. M.N. assisted with NDIT data cleaning. T.R. analyzed and prepared the demographic table. J.O. oversaw the study and provided access to NDIT. M-P.S. conceptualized the study. All authors contributed to and reviewed the manuscript.

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Struik, L.L., Armasu, A., Fortin, G. et al. A qualitative study of experiences among young adults who increased their cannabis use during the COVID-19 pandemic. BMC Public Health 24 , 2434 (2024). https://doi.org/10.1186/s12889-024-19886-9

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Perceived barriers and opportunities for the introduction of post-discharge malaria chemoprevention (PDMC) in five sub-Saharan countries: a qualitative survey amongst malaria key stakeholders

• Céline Audibert 1 &
• Hans Rietveld 1  

Malaria Journal volume  23 , Article number:  270 ( 2024 ) Cite this article

Metrics details

Post-discharge malaria chemoprevention (PDMC) is an intervention aimed at reducing morbidity and mortality in patients hospitalized with severe anaemia, with its effectiveness established in several clinical trials. The aim of this study was to better understand factors that would influence the scale up of this intervention, and to identify preferences for two delivery mechanisms, facility-based or community-based.

Forty-six qualitative individual interviews were conducted in five sub-Saharan countries amongst malaria key opinion leaders and national decision makers. Findings were analysed following a thematic inductive approach.

Half of participants were familiar with PDMC, with a satisfactory understanding of the intervention. Although PDMC was perceived as beneficial by most respondents, there was some unclarity on the target population. Both delivery approaches were perceived as valuable and potentially complementary. From an adoption perspective, relevant evidence generation, favorable policy environment, and committed funding were identified as key elements for the scale up of PDMC.

Conclusions

The findings suggest that although PDMC was perceived as a relevant tool to prevent malaria, further clarification was needed in terms of the relevant patient population, delivery mechanisms, and more evidence should be generated from implementation research to ensure policy adoption and funding.

Severe anaemia is a leading cause of paediatric hospital admission and mortality in sub-Saharan Africa [ 1 , 2 , 3 , 4 ]. Children under 5 years of age are most vulnerable with an in-hospital mortality rate ranging from 4 to 12% [ 5 , 6 , 7 ]. It is increasingly recognized that children with severe anaemia remain at high risk after discharge from hospital, with up to 33% of the children dying or being readmitted within the first 6 months following discharge [ 5 , 6 , 8 , 9 ]. Malaria infections in the post-discharge period have been shown to contribute to severe anaemia rebound, re-hospitalization, and morbidity [ 3 , 8 ].

Post-discharge malaria chemoprevention (PDMC) is the administration of a full anti-malarial treatment course at regular intervals to children who have recently been discharged from hospitals after being treated for severe anaemia [ 10 ]. Clinical trials conducted in The Gambia, Malawi, Kenya and Uganda involving 3,663 children with severe anaemia demonstrated that three months of PDMC significantly reduced mortality during the intervention period, as well as all-cause readmissions, readmissions due to severe malaria, and readmissions due to severe anaemia [ 11 , 12 , 13 , 14 ]. However, these benefits were limited to the intervention period and disappeared as the drug levels waned [ 12 ]. Three drug regimens were employed in these trials, involving monthly sulfadoxine-pyrimethamine (SP) delivery for an average duration of 3 months [ 13 ], monthly artemether-lumefantrine (AL) given at 4- and 8-weeks post-discharge [ 11 ], or monthly dihydroartemisinin-piperaquine (DHA-PQ) given at 2-, 6- and 10-weeks post-discharge [ 14 ]. Based on this evidence, the malaria prevention guidelines of the World Health Organization (WHO) include a conditional recommendation for the use of PDMC to prevent new malaria infections in children admitted with severe anaemia during the period after hospital discharge when they are at risk of readmission or death [ 10 ]. To date, PDMC has not been implemented at scale and has only been trialed in clinical studies and small-scale pilots [ 12 ].

Unlike other malaria prevention interventions, such as intermittent preventive treatment in pregnant women (IPTp), perennial malaria chemoprevention (PMC) or seasonal malaria chemoprevention (SMC), PDMC targets a smaller population of seriously ill patients with an estimated 57,000 to 314,000 children under 5 years of age hospitalized with severe malarial anaemia per year [ 15 ]. While PMC and IPTp are delivered through established health systems such as the Expanded Programme on Immunization (EPI) and Ante Natal Care (ANC) programs, there is no guidance on how to implement and deliver PDMC. One acceptability study conducted in Malawi showed that PDMC was highly accepted among caregivers of children under 5 years of age previously treated for severe anaemia [ 16 ]. This study also found that caregivers preferred community-based delivery of PDMC rather than collecting drugs for each treatment course at the hospital. Community-based delivery of PDMC to children recovering from severe anaemia also resulted in higher adherence compared to facility-based delivery in Malawi [ 17 ]. While these findings are important to identify how to best implement PDMC, they may not be applicable to the context of other countries. In addition, a community-based delivery strategy also presents with potential sustainability challenges caused by inadequate supervision, low remuneration, and irregular supplies [ 18 ]. It is, therefore, necessary to carefully consider how to implement PDMC and identify the most effective delivery mechanisms.

This work aimed to better understand factors influencing the adoption of PDMC in five sub-Saharan African countries. An important component of the survey was to identify the anticipated advantages, disadvantages, and preferences for various PDMC delivery strategies. The insights provided by the malaria key informants interviewed for this work may serve to guide policymakers in determining the most appropriate delivery strategy for their specific context.

Study setting

The study was conducted in five sub-Saharan African (SSA) countries. Countries were selected to offer a mix of geographical location, malaria burden, and level of experience with PDMC. Table 1 shows the characteristics of the selected countries. The malaria burden was determined based on the WHO’s identification of countries with the highest malaria burden and included in the High Burden to High Impact initiative (HBHI) [ 19 ]. Out of the 10 HBHI African countries, Nigeria and Uganda were selected due to the important number of severe malaria cases in these countries, and the fact that Uganda was involved in a PDMC clinical trial at the time of the study. This selection allowed to include two high burden countries, one involved in PDMC and one not yet trialing the intervention. The sample was completed with Kenya and Malawi as these countries were also involved in PDMC clinical trials [ 20 , 21 ]. Lastly, Senegal was selected as a representative of countries where PDMC was not trialed yet, and with a lower burden of malaria.

Research design

The study consisted in a series of one-on-one interviews with national malaria key informants. A qualitative approach was selected given the exploratory nature of the research question. The study consisted of semi-structured discussion guides that were adapted to the respondents’ familiarity with PDMC (Additional file 1 ). A short description of PDMC was provided to participants who were not familiar with the intervention (Additional file 2 ).

Respondent selection

The key informants selected for this survey consisted of a mix of representatives of national malaria programmes (NMCPs), acadaemia, funding partners, and policy makers. Potential survey participants were recruited through a mix of purposive and snowball approach. For the purposive sampling, authors generated a list of potential contacts through desk research and previous interactions with local malaria experts. This list was shared with the field partner and was expanded through snowballing: each participant was asked to identify other potential key informants in their network. Screening questions were used to qualify participants and ensure that they had sufficient knowledge or involvement with malaria. They were selected based on their role in their country’s malaria management pathway and were identified as individuals able to make decisions on policies, research, or resource allocations in the field of malaria. In order to be selected to participate in the survey, key informants had to be actively working in the field of malaria for at least 10 years and devoting at least 50% of their professional time on malaria. Their familiarity with PDMC was determined at the time of recruitment, based on self-reporting. Those who self-reported being unfamiliar with PDMC were given a short description of PDMC for them to review before the interview date (Additional file 2 ). Respondent selection was stopped when no new information was obtained from survey participants.

Quality insight collection

Two semi-structured discussion guides were prepared by the field partner and the authors to facilitate collection of qualitative insight, one for each familiarity level with PDMC (Additional file 1 ). The guides consisted of questions designed to capture information across five key learning dimensions: context, knowledge and awareness, attitudes and perceptions, implementation, and future state. The discussion guides were generated in English and translated in French for the interviews conducted in Senegal. The translation into French was executed by the field partner, and checked by the corresponding author who is a native French speaker. In each country, the field partner allocated a team of two moderators to conduct the interviews. They were trained during a three-day training session and any question that emerged during the session was discussed with the authors. The guides were piloted with a subset of respondents and a debrief workshop was organized with the authors. The guides were adapted to improve the interview flow and facilitate collection of information. The authors, field partner representatives and interviewers had no established relationship with study participants. Interviews were carried out either face to face or virtually depending on participant’s preference. Interviews were carried out in the participant’s preferred language, either English or French. Each interview lasted between 20 and 60 min and was audio-recorded to facilitate translation, transcription, and analysis. Interviews took place from August to December 2022.

The interview recordings were transcribed, and where applicable, translated from French to English by the field partner. All respondent information was stored separately from personal identifier information. Qualitative analysis was conducted on Dedoose (9.0.62) by a team of three coders. Coders were involved from the beginning of the project, participated in the preparation of the discussion guide, and were experienced in qualitative research and public health topics. Each transcript was coded deductively using pre-established codes derived from the research guide, and inductively by applying codes that emerged from the data as described by Thomas & Harden [ 22 ]. Inductive coding enabled a more contextualized approach and identification of country specific themes. Codes where then grouped thematically following the five components of the study: context, knowledge and awareness, attitudes and perceptions, and implementation, and future state. The code book was shared, discussed and validated with the authors. Interpretation of the codes led to the identification of key learning and recommendations addressing the research questions, which were presented to the authors by the field partner’s research team. Several review iterations took place in order to refine the analysis, and agree on a final report.

Ethical considerations

Ethical guidelines were followed by informing participants about the purpose of the research, how the information will be used, their right to withdraw at any stage of the interview process. Written informed consent was obtained from each participant, confidentiality was assured at all stages of the study and permission was asked for tape-recording. The study did not involve patients and did not collect patient characteristics. The purpose of the study was to collect key informants’ professional opinions and insights and did not collect personal data or sensitive information. As such, there was no institutional review board involved in approving the research.

Sample description

A total of 46 national malaria key informants were selected and interviewed, including 14 implementation partners, 11 policy makers, 7 academic researchers, 7 funding partners, and 7 MoH representatives. Table 2 provides a country breakdown of the participants per affiliation and level of familiarity with PDMC.

Familiarity, knowledge, and perception of PDMC

Out of the 46 national malaria key informants who were interviewed, half of them reported being familiar with PDMC, and the other half having little knowledge about the intervention (Table  2 ). Familiarity with PDMC was highest in respondents from Kenya and Malawi (60% and 70%, respectively) where PDMC clinical trials were ongoing. Level of familiarity with PDMC was the lowest in Nigeria (2 out of 10 participants), and less than half of participants from Uganda (44%) were familiar with PDMC although a clinical trial was ongoing in their country. Lastly, a majority of participants from Senegal (4 out of 7) felt familiar with PDMC. For those who were familiar with PDMC, the sources of information varied and included WHO guidelines, scientific literature and publications, international conferences, and interaction with researchers involved in PDMC trials.

Amongst those who said they had knowledge about PDMC, there was a general understanding that PDMC refers to the prescription of an oral anti-malarial to children diagnosed with severe malaria and severe anaemia for a period of 3 to 6 months after they are discharged. There was however some unclarity about who the target beneficiary should be, with many respondents emphasizing the use in severe malaria rather than severe anaemia. The anaemia was often perceived as a consequence of severe malaria. Survey participants from Malawi had the most accurate understanding of PDMC, and stated that the intervention aimed to prevent malaria infection in children who presented with severe anaemia.

“This is a treatment that is being provided to children who were once admitted due to severe anaemia, regardless of what the cause of anaemia, be it malaria or other causes.” (Funding partner, Malawi)

In terms of age range, most survey participants identified the 3 to 59 months old children as the obvious beneficiary of the intervention. A few respondents mentioned that it could be used in older children, especially in Senegal and Kenya.

Overall, PDMC was perceived as a beneficial intervention by most respondents. A continuum of benefit from the micro (child, caregiver, community) to the macro (health system and country) environment was mentioned. At the child level, PDMC was expected to reduce malaria-related mortality, morbidity and improve child survival and, therefore, improve quality of life. At the caregiver level, PDMC could improve family’s socioeconomic status by reducing the costs associated with hospital visits, reduce the amount of time spent caring for a sick child, and alleviate some of the emotional and mental burden associated with having to care for a sick child. PDMC’s benefits at community level would be to reduce the number of malaria carriers and, therefore, protect the whole population. It could also improve the community economic status as caregivers would fully participate in the labour market, and provide the opportunity to perform further awareness and information campaigns about malaria prevention. At the health care level, survey respondents expected PDMC to help optimize use of resources – financial, work force, and commodities – thanks to reduced readmissions. At the country level, the benefits would largely be linked to the macroenvironment through reduced malaria prevalence, and reduced financial burden associated to malaria.

Reactions to PDMC delivery approaches

Survey participants were asked to react to the two delivery approaches suggested by the WHO, namely the facility-based approach for which caregivers obtain PDMC drug from a health facility every month, and the community-based delivery where caregivers receive all courses of PDMC through community-based settings.

Respondents mentioned adherence, treatment continuity and trust as the main advantages of the facility-based approach. More specifically, a respondent in Malawi indicated that delivering PDMC through the health-facility would increase adherence by leveraging the trust that was built between caregivers and health care workers during the treatment of a child. Two respondents from Uganda felt that facility-delivery offers continuity in the treatment, stating that any accompanying treatment should be handled by the facility that took care of the child in the first place. Another indirect benefit is the fact that facility visits offer the opportunity to examine a child for other issues and conduct other health assessment on a monthly basis (respondents from Malawi and Uganda).

“...there is that constant interaction between service user and a healthcare worker. And I guess if you’re coming to pick medicine for this child, you’re coming with the child. So, I get a chance to look at this child. And I can look at other issues other than the malaria, we can track nutrition status.” (Implementing partner, Uganda)

The main challenges reported with facility delivery include time, cost and geographical constraints for caregivers, which may impact adherence to the intervention. Caregivers would have to return to the facility, incurring transportation cost and time away from work. This would negatively impact their economic situation and could prevent them from returning to the health facility to renew the drug prescription. Given that the visits are for follow-up rather than curative treatment, many respondents believed caregivers would be less likely to return, further affecting adherence.

When discussing the community-based approach, survey respondents identified three different delivery mechanisms:

Caregivers are given the entire PDMC treatment upon discharge, and community health workers (CHWs) perform regular follow-up to ensure that the medication is taken as prescribed.

Local CHWs are informed of the patient’s needs for the intervention and are in charge of storing and delivering PDMC through monthly visits to the child.

Caregivers visit fixed pre-determined locations that are close to their home, and where they can obtain the required treatment.

Regardless of the delivery mechanisms, the community-based approach was advocated by a majority of respondents primarily due to its cost effectiveness and expected increased adherence to treatment. Both benefits derived from the fact that the point of care would be close to the patients. Caregivers would not need to take time off work and pay travelling cost to go to the health care facility. In addition, CHWs in charge of the monthly follow-up would ensure that the treatment is taken as intended.

“Probably it would be best if you’re having these community health workers monitoring these kids, and then delivering the drugs themselves and ensuring that they’re being taken.” (Implementing partner, Uganda)

Survey participants indicated that PDMC implementation through the community-based approach should be straightforward to put in place as it would benefit from the existing community healthcare system. Some respondents from Senegal and Nigeria indicated that they have a robust community level delivery system thanks to the Seasonal Malaria Chemoprevention intervention. In Kenya, some respondents reported the successful use of CHWs to deliver treatment for other diseases such as HIV and tuberculosis that could be leveraged for the delivery of PDMC.

“We have a good community fabric, we have a good system, we have thousands of community actors, especially in the remote areas.” (Programme manager, Senegal)

One of the main challenges identified with community delivery was the absence of incentives for CHWs. Survey participants indicated that poor financial support could have a negative impact on CHWs engagement and motivation. CHWs level of understanding of the intervention was another potential challenge and would require significant amount of training to be addressed. Providing sufficient education was perceived as necessary by respondents to ensure that CHWs deliver the intervention appropriately, and to avoid risks of mis-dosing and error in administration. From an operational perspective, lack of proper patient management tools and records between facility and CHW, and inadequate drug storage and drug management mechanisms were identified as potential barriers to proper implementation of PDMC.

Several survey participants viewed the facility and community delivery approaches as complementary and believed these two delivery channels could be leveraged for the successful implementation of PDMC. In this hybrid approach, community delivery was seen as a supplement to the facility delivery, ensuring adherence and tracking of children enrolled in the intervention.

“You cannot do one over the other because then you have missed opportunities. If a child comes to the facility, you check if they have been discharged recently and if they are due for their PDMC dosage. If yes, you give at the facility. If you’re doing the village clinical and outreach clinic, you also check. Therefore, I don’t think that one is better than the other.” (Programme manager, Malawi)

A few survey respondents also indicated that this hybrid approach should include the private sector, capitalizing on the presence of drug stores and pharmacies at community level. The exact mechanisms of how to engage with the private sector were not discussed.

“In Uganda 61% of the population seeks care from the private sector. You need to look at pharmacies and drug stores.” (Programme Manager, Uganda)

Adoption of PDMC: from evidence generation to policymaking and funding

Recommendations from survey participants on what would be required to facilitate the adoption of PDMC were collected. The three key areas that emerged were the generation of evidence, the regulatory environment, and the funding landscape.

Evidence generation

Respondents indicated that the type of evidence required would depend on the stage of PDMC implementation. At inception, baseline data on incidence and prevalence, as well as information about epidemiological transitions would be needed to support government and donor buy-in. Next, the roll-out phase of PDMC implementation would require the most diverse and complete set of data, including clinical indicators, intervention effectiveness studies, adverse events monitoring, drug use surveillance, and behavioural studies to monitor willingness to adopt, adherence and compliance. In terms of clinical indicators, survey participants expect to see data on readmissions due to severe malaria after PDMC, readmissions due to severe anaemia, level of parasitaemia in children receiving PDMC, degree of anaemia, mortality rates. As for intervention effectiveness studies, they should provide information about pre and post intervention evaluation, impact at household level, administrative evaluation and follow-up evaluation. These indicators would be used to inform PDMC scale up and to monitor its implementation. Lastly, data on drug resistance, pharmacovigilance, cost effectiveness, intervention effectiveness, impact on school attendance, changes in knowledge, awareness, attitude and practice regarding PDMC would be needed during the scale up phase to support the sustainability of the intervention.

Importantly, the list of evidence identified by survey participants were described as the ideal set of indicators. Respondents warned that a number of challenges typically limit the production of the required evidence. The difficulties mentioned include: (1) the data collection methods which remain paper based in many settings, limiting access to information at community level; (2) the administrative burden of adding a new intervention to an already long and demanding list of data collection tools, which could result in the confusion of similarly perceived intervention (SMC, PMC); (3) insufficient training or competencies in data collection, resulting in poor accuracy of the data collected; (4) transitioning a data collection tool designed for a clinical setting to a community setting, and (5) potential disconnect between the public and the private sector, with data from the private sector not being systematically integrated into the national health information system.

Policy environment

From a policy perspective, there was a consensus that PDMC should be embedded in the existing malaria management guidelines and should be in line with the national malaria strategic plan. The National Malaria Elimination/Control Programme (NME/CP) under the Ministry of Health was identified as the primary owner of the plan and should be in charge of producing PDMC implementation guidelines. Updating the guidelines was identified as a potential bottleneck since the process requires the involvement of different stakeholders, which can take time. The following stakeholders, in addition to NME/CP representatives, were identified by survey participants as playing a role in the policy making and implementation processes: political leaders, Ministry of Finance, WHO, division of child and adolescent health, division of community health, donor and implementing partners (PMI, Global Fund), state and local government in Nigeria, academic institutions. The exact role played by each stakeholder was not clearly outlined and would require a complete mapping.

At the time of the survey, none of the participating countries had included PDMC in their guidelines. Malawi appeared to be the most advanced in the process, but a survey participant indicated that progress had stopped due to lack of sufficient evidence:

“WHO approval does not mean we automatically implement, we still have to go through our country policy introduction stages. We still have to pick up from where we left. We need to go back to the Malaria Advisory Board, present the data that was missing then. Once we convince this team, we will proceed to senior management in the Ministry of Health. When they get convinced, they will approve the introduction of post-discharge chemoprevention.” (Policy Maker, Malawi)

Some survey participants also indicated that the funding of the intervention could be a potential barrier to the adoption of new malaria policy. Countries who are dependent on donor funding need to comply with the requirement of the donors. Without the endorsement of donors to fund PDMC, it could be challenging to include this intervention in the guidelines.

Funding landscape

Across all countries, respondents agreed that a co-financing model between governments and interested partners would be the best way to fund and drive the adoption of PDMC, ideally under the overarching responsibility of governments. However, several respondents noted that countries still largely rely on donor funds, which limits governments’ ability to lead the implementation of the intervention. Some respondents suggested that the initial intervention development phase should be financially supported by donors, with governments planning to cover the cost once the PDMC intervention is in place. Lack of political will from Ministries of Health to fund PDMC was seen as a barrier to implementation by respondents from all five countries. Donor buy-in was identified as another barrier to PDMC implementation, especially in Senegal and Uganda where most of malaria programmes are donor-funded according to survey participants. Defining funding priorities and ensuring sufficient financing were identified as potential issues for PDMC implementation by respondents in Malawi, Senegal and Uganda. Limited funds could make it difficult to secure resources for sufficient and sustainable drug procurement, health care professional training and community engagement. As with many preventive measures, PDMC will compete with malaria treatment, as well as treatment for other high priority diseases such as Covid-19. Lastly, some survey participants from Kenya and Uganda mentioned corruption and fund misappropriation as potential barriers to PDMC funding.

PDMC and risk of drug resistance

Overall, more than half of respondents expressed concerns about potential drug resistance as a result of PDMC, although there were some country disparities. Respondents from Nigeria were the most concerned about the potential emergence of drug resistance as a consequence of PDMC. This concern was driven by fear of inappropriate treatment administration, self-medication, and treatment noncompliance. Some respondents also attributed the emergence of drug resistance to the already widespread use of malaria drugs (SP and AL) in various interventions and as first-line therapy.

“…there is a whole lot of intervention using SP and then AL is what we are using for treatment, and you are using it for prevention, so we are prone to resistance faster.” (Policy Maker, Nigeria)

Respondents from other countries than Nigeria expressed mixed views about the risk of drug resistance as a consequence of PDMC. Those concerned by resistance feared that prolonged exposure to malaria drugs, poor compliance and adherence to treatment, could result in selective pressure within the population and trigger drug resistance. Respondents from Malawi flagged that their country was shifting away from SP and AL to DHA-PQ for first line treatment of malaria because of emerging resistance to SP and AL. It will, therefore, not be possible to use DHA-PQ for PDMC as it is becoming their preferred drug for first-line treatment.

Survey participants who were less concerned by the potential emergence of drug resistance indicated that the target population for PDMC was too small to trigger resistance. Respondents from Senegal were the least concerned by this issue, and indicated that although the risk of resistance exists, they believed it could be managed and controlled through surveillance, protocols that are well designed and adhered to, and regular drug efficacy testing.

“We are not within the framework of a campaign where we distribute mass drugs to an entire population of children. […] It is a distribution which obeys a precondition which is hospitalization! […] But all in all, we cannot fail to do what is called pharmacovigilance for the molecules that we are going to use. We should at least be able to reinforce surveillance and vigilance.” (Programme manager, Senegal) “I don’t think the number of severe malaria cases being given chemoprophylaxis would significantly contribute to a rapid increase in drug resistance.” (Implementing partner, Kenya)

Survey respondents made the following recommendations to prevent the emergence of drug resistance during PDMC implementation: a) Use different drugs for PDMC and treatment, and rotate them frequently. b) Develop strong behaviour change messaging to emphasize the importance of adherence and compliance. c) Regularly conduct drug efficacy and resistance testing. d) Increase usage monitoring. e) Ensure that health facilities and CHWs implement good follow-up practices and check that the treatment is administered correctly.

This review investigated the perception of national malaria key opinion leaders and decision makers on PDMC, including participants from countries where PDMC was not undergoing pilot testing during the study period. Overall, all participants demonstrated a satisfactory level of comprehension regarding PDMC, even those coming from countries where the programme was not piloted. This positive outcome contrasts with a 2019 study, which revealed that key opinion leaders in Nigeria, Senegal, and Uganda possessed limited knowledge about PDMC and struggled to accurately describe the intervention at that time [ 23 ]. This increase in knowledge and understanding of PDMC can be attributed to several factors, including the updated WHO guidelines released in June 2022—shortly preceding the survey—and the dissemination of information through various clinical trials' publications and presentations. Moreover, key opinion leaders and decision-makers perceived PDMC as a beneficial intervention with the potential to positively impact the entire continuum of care, spanning from individual patients to the broader healthcare system. This positive perception from key decision-makers is a promising first step for the programme's adoption and scale-up.

Despite the generally good understanding of PDMC, some ambiguity surfaced regarding the intervention's target group. Many participants expressed uncertainty, with some intending to apply PDMC to patients hospitalized for severe malaria and severe anaemia, while others focused solely on severe anaemia cases. Since severe anaemia is a perceived consequence of severe malaria, some participants deemed PDMC suitable for patients with severe malaria. This raises potential challenges for PDMC adoption. The primary challenge lies in determining the right target for evidence generation. Key informants emphasized the necessity of generating sufficient evidence to support the adoption and scaling up of PDMC implementation. Without consensus on the target group, it becomes challenging to produce the required evidence for inclusion in treatment guidelines and accurately monitor intervention performance. Another challenge pertains to funding. The WHO recommendations specify that PDMC should be used in children under 5 years of age hospitalized with severe anaemia only [ 10 ]. Deviating from these recommendations by extending PDMC to severe malaria cases could jeopardize securing funding from donors. Participants from a recent stakeholder engagement meeting held by the PDMC Saves Lives consortium recommended expanding the target group to include children hospitalized with "severe anaemia or severe malaria" [ 12 ]. They also felt important to include cerebral malaria in the target group in order to not neglect this equally vulnerable group from the post discharge malaria chemoprevention as continuum of care. The consequences of these recommendations from a regulatory and funding perspectives remain to be seen.

Determining how to deliver PDMC is a pivotal question touching on various aspects of product adoption. Since PDMC is administered to severely ill patients, ensuring the timing and frequency of preventive treatment is crucial. Adherence emerged as a significant concern raised by survey participants. The two envisioned delivery mechanisms—facility-based and community-based— come with concerns about treatment adherence. For facility-based delivery, concerns centered on caregivers not returning to the healthcare facility every month due to geographical distance and associated costs. Community-based delivery raised fears of mistakes in dosing or administration frequency by healthcare providers, potentially leading to incorrect treatment. While survey participants believed that community-based delivery would enhance adherence, citing proximity to patients and the simplicity of the procedure, potential challenges included the substantial training required for Community Health Workers (CHWs). This is consistent with a recent study indicating that community-based delivery of PDMC resulted in higher adherence than facility-based delivery [ 17 ]. However, the amount and frequency of training must be considered, as training all CHWs at the national level could be more expensive than training health facility staff in delivering PDMC. In addition, in areas where cases of severe malaria and severe anaemia are not frequent, CHWs would require frequent refresher training to ensure that they maintain a sufficient level of knowledge about PDMC. These training considerations will have an impact on the cost-effectiveness of the intervention and need to be investigated further. It could be envisaged to have a hybrid approach were both facility and community-based deliveries is offered. Criteria such as robustness of the CHWs system, cost of training, distance from heath care facilities, will need to be taken into consideration when selecting where to set up a facility delivery or a community-based approach.

Choosing the appropriate drug for PDMC was another topic of discussion during the survey, constituting a critical aspect of the intervention. Several factors need consideration in this selection process. First, the growing evidence of anti-malarial resistance prompted the use of different drugs for treatment and prevention. The three drugs that have been trialed for PDMC to date, namely SP, AL and DHA-PQ, all demonstrated efficacy in reducing mortality and readmissions during the intervention period [ 11 , 13 , 14 ]. Out of these, only AL and DHA-PQ are used in first-line treatment. The question arises whether it makes sense to use them for PDMC. The argument in favor is the small number of patients using PDMC, reducing the risk of resistance emergence. As the WHO guidelines do not provide recommendations on which drug to use for PDMC, it will be up to the countries to decide which drug class to use depending on their strategy to fight resistance to malaria drugs. Another consideration is the ease of training and supply chain management; if the drug selected for PDMC is the same as for treatment, training, procurement and distribution become simpler as dosing and administration methods are already known. This ties back to the earlier discussion on the delivery channel, especially if CHWs are involved, as using a familiar drug simplifies training and the need for refresher training.

Strengths and limitations

The main limitation of this study was the small number of participants and countries. Therefore, caution should be used when generalizing results of this subset of respondents to the entire malaria-endemic regions of SSA. However, this was mitigated by the fact that survey participants were selected for their knowledge and influential role in malaria management. In addition, not all subcategories were represented in each country, For example, no MoH representatives were interviewed in Kenya, and no policy makers in Senegal. This was largely due to the difficulty to schedule appointments with these representatives during the period allocated to the survey. Despite this limitation, the overall sample composition was well balanced, and no country-level analysis was performed. Absence of end users such as health care professionals, CHWs and caregivers, is a second limitation of the study. While the view of the end users is important to capture when considering the implementation of the intervention, the rationale for their exclusion was that their perceptions are better captured through feasibility studies, which was not the scope of this study. Lastly, the study relies on participants’ self-reported familiarity and knowledge of PDMC which could introduce a recall bias. To address this limitation, a narrative was prepared to describe what PDMC was, and interviewers were instructed to use the showcard whenever they felt that survey participants did not have a clear understanding of PDMC. The information presented on the showcard could have influenced the perceptions and opinions expressed by those who read it.

This survey offers an updated view of the perception of key opinion leaders and decision-makers on PDMC as a way to prevent malaria in vulnerable children. Despite increased awareness and positive perception of the intervention, half of the participants were unfamiliar with the intervention. In addition, the study identified an ambiguity regarding the target population which could impact evidence generation and funding prospects. The study also highlighted the need to carefully investigate PDMC delivery mechanisms as it has a critical role on adherence and significant consequences on cost of implementation associated with training of healthcare providers and drug supply. Lastly, the emergence of anti-malarial drug resistance calls for a careful selection of the drug to be used for this intervention. Overall, the study provides valuable insights for policymakers navigating PDMC adoption, and stresses the need for country-specific cost effectiveness analysis to adapt the intervention to locally-relevant malaria endemicity and healthcare system context.

Availability of data and materials

All data generated or analysed during this study are included in this published article and its supplementary information files.

Abbreviations

Artemether-lumefantrine

Ante natal care

Community health workers

Dihydroartemisinin-piperaquine

Expanded programme on immunization

Intermittent preventive treatment in pregnant women (IPTp)

Ministry of Health

National Malaria Control Programme

National Malaria Elimination/Control Programme

• Post-discharge malaria chemoprevention

Perennial malaria chemoprevention

Seasonal malaria chemoprevention

Sulfadoxime pyrimethamine

• Sub-Saharan Africa

World Health Organization

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Acknowledgements

The authors thank Dalberg Research for their valuable contributions to the survey.

This research received no external funding.

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CA and HR were involved in the survey conceptualization, validation and analysis. CA supervised the field partner and prepared the original manuscript draft. CA and HR read and approved the final manuscript.

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Correspondence to Céline Audibert .

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Ethics approval and consent to participate.

The study did not involve patients and did not collect patient characteristics. The purpose of the study was to collect malaria key informants’ professional opinions and insights and did not collect personal data or sensitive information. As such, there was no institutional review board involved in approving the research. Written informed consent was obtained from each participant.

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Additional file 1. discussion guide, provided as wordfile. provides the list of questions that were used in the survey., 12936_2024_5100_moesm2_esm.docx.

Additional file 2. Description of PDMC approach, provided as Wordfile. Showcard that was provided to survey participants not familiar with PDMC, as background information.

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Insights into research activities of senior dental students in the Middle East: A multicenter preliminary study

• Mohammad S. Alrashdan 1 , 2 ,
• Abubaker Qutieshat 3 , 4 ,
• Mohamed El-Kishawi 5 ,
• Abdulghani Alarabi 6 ,
• Lina Khasawneh 7 &
• Sausan Al Kawas 1  

BMC Medical Education volume  24 , Article number:  967 ( 2024 ) Cite this article

Metrics details

Despite the increasing recognition of the importance of research in undergraduate dental education, limited studies have explored the nature of undergraduate research activities in dental schools in the Middle East region. This study aimed to evaluate the research experience of final year dental students from three dental schools in the Middle East.

A descriptive, cross-sectional study was conducted among final-year dental students from three institutions, namely Jordan University of Science and Technology, University of Sharjah (UAE), and Oman Dental College. Participants were asked about the nature and scope of their research projects, the processes involved in the research, and their perceived benefits of engaging in research.

A total of 369 respondents completed the questionnaire.  Cross-sectional studies represented the most common research type  (50.4%), with public health (29.3%) and dental education (27.9%) being the predominant domains. More than half of research proposals were developed via discussions with instructors (55.0%), and literature reviews primarily utilized PubMed (70.2%) and Google Scholar (68.5%). Regarding statistical analysis, it was usually carried out with instructor’s assistance (45.2%) or using specialized software (45.5%). The students typically concluded their projects with a manuscript (58.4%), finding the discussion section most challenging to write (42.0%). The research activity was considered highly beneficial, especially in terms of teamwork and communication skills, as well as data interpretation skills, with 74.1% of students reporting a positive impact on their research perspectives.

Conclusions

The research experience was generally positive among surveyed dental students. However, there is a need for more diversity in research domains, especially in qualitative studies, greater focus on guiding students in research activities s, especially in manuscript writing and publication. The outcomes of this study could provide valuable insights for dental schools seeking to improve their undergraduate research activities.

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Introduction

The importance of research training for undergraduate dental students cannot be overstressed and many reports have thoroughly discussed the necessity of incorporating research components in the dental curricula [ 1 , 2 , 3 , 4 ]. A structured research training is crucial to ensure that dental graduates will adhere to evidence-based practices and policies in their future career and are able to critically appraise the overwhelming amount of dental and relevant medical literature so that only rigorous scientific outcomes are adopted. Furthermore, a sound research background is imperative for dental graduates to overcome some of the reported barriers to scientific evidence uptake. This includes the lack of familiarity or uncertain applicability and the lack of agreement with available evidence [ 5 ]. There is even evidence that engagement in research activities can improve the academic achievements of students [ 6 ]. Importantly, many accreditation bodies around the globe require a distinct research component with clear learning outcomes to be present in the curriculum of the dental schools [ 1 ].

Research projects and courses have become fundamental elements of modern biomedical education worldwide. The integration of research training in biomedical academic programs has evolved over the years, reflecting the growing recognition of research as a cornerstone of evidence-based practice [ 7 ]. Notwithstanding the numerous opportunities presented by the inclusion of research training in biomedical programs, it poses significant challenges such as limited resources, varying levels of student preparedness, and the need for faculty development in research mentorship [ 8 , 9 ]. Addressing these challenges is essential to maximize the benefits of research training and to ensure that all students can engage meaningfully in research activities.

While there are different models for incorporating research training into biomedical programs, including dentistry, almost all models share the common goals of equipping students with basic research skills and techniques, critical thinking training and undertaking research projects either as an elective or a summer training course, or more commonly as a compulsory course required for graduation [ 2 , 4 , 10 ].

Dental colleges in the Middle East region are not an exception and most of these colleges are continuously striving to update their curricula to improve the undergraduate research component and cultivate a research-oriented academic teaching environment. Despite these efforts, there remains a significant gap in our understanding of the nature and scope of student-led research in these institutions, the challenges they face, and the perceived benefits of their research experiences. Furthermore, a common approach in most studies in this domain is to confine data collection to a single center from a single country, which in turn limits the value of the outcomes. Therefore, it is of utmost importance to conduct studies with representative samples and preferably multiple institutions in order to address the existing knowledge gaps, to provide valuable insights that can inform future curricular improvements and to support the development of more effective research training programs in dental education across the region. Accordingly, this study was designed and conducted to elucidate some of these knowledge gaps.

The faculty of dentistry at Jordan University of Science and Technology (JUST) is the biggest in Jordan and adopts a five-year bachelor’s program in dental surgery (BDS). The faculty is home to more than 1600 undergraduate and 75 postgraduate students. The college of dental medicine at the University of Sharjah (UoS) is also the biggest in the UAE, with both undergraduate and postgraduate programs, local and international accreditation and follows a (1 + 5) program structure, whereby students need to finish a foundation year and then qualify for the five-year BDS program. Furthermore, the UoS dental college applies an integrated stream-based curriculum. Finally, Oman Dental College (ODC) is the sole dental school in Oman and represents an independent college that does not belong to a university body.

The aim of this study was to evaluate the research experience of final year dental students from three major dental schools in the Middle East, namely JUST from Jordan, UoS from the UAE, and ODC from Oman. Furthermore, the hypothesis of this study was that research activities conducted at dental schools has no perceived benefit for final year dental students.

The rationale for selecting these three dental schools stems from the diversity in the dental curriculum and program structure as well as the fact that final year BDS students are required to conduct a research project as a prerequisite for graduation in the three schools. Furthermore, the authors from these dental schools have a strong scholarly record and have been collaborating in a variety of academic and research activities.

Materials and methods

The current study is a population-based descriptive cross-sectional observational study. The study was conducted using an online self-administered questionnaire and targeted final-year dental students at three dental schools in the Middle East region: JUST from Jordan, UoS from the UAE, and ODC from Oman. The study took place in the period from January to June 2023.

For inclusion in the study, participants should have been final-year dental students at the three participating schools, have finished their research project and agreed to participate. Exclusion criteria included any students not in their final year, those who have not conducted or finished their research projects and those who refused to participate.

The study was approved by the institutional review board of JUST (Reference: 724–2022), the research ethics committee of the UoS (Reference: REC-22-02-22-3) as well as ODC (Reference: ODC-MA-2022-166). The study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [ 11 ]. The checklist is available as a supplementary file.

Sample size determination was based on previous studies with a similar design and was further confirmed with a statistical formula. A close look at the relevant literature reveals that such studies were either targeting a single dental or medical school or multiple schools and the sample size generally ranged from 158 to 360 [ 4 , 8 , 9 , 10 , 12 ]. Furthermore, to confirm the sample size, the following 2-step formula for finite population sample size calculation was used [ 13 ]:

Wherein Z is the confidence level at 95% =1.96, P is the population proportion = 0.5, and E is the margin of error = 0.05. Based on this formula, the resultant initial sample size was 384.

Wherein n is the initial sample size = 384, N is the total population size (total number of final year dental students in the 3 schools) = 443. Based on this formula, the adjusted sample size was 206.

An online, self-administered questionnaire comprising 13 questions was designed to assess the research experience of final year dental students in the participating schools. The questionnaire was initially prepared by the first three authors and was then reviewed and approved by the other authors. The questionnaire was developed following an extensive review of relevant literature to identify the most critical aspects of research projects conducted at the dental or medical schools and the most common challenges experienced by students with regards to research project design, research components, attributes, analysis, interpretation, drafting, writing, and presentation of the final outcomes.

The questionnaire was then pretested for both face and content validity. Face validity was assessed by a pilot study that evaluated clarity, validity, and comprehensiveness in a small cohort of 30 students. Content validity was assessed by the authors, who are all experienced academics with remarkable research profiles and experience in supervising undergraduate and postgraduate research projects. The authors critically evaluated each item and made the necessary changes whenever required. Furthermore, Cronbach’s alpha was used to assess the internal consistency/ reliability of the questionnaire and the correlation between the questionnaire items was found to be 0.79. Thereafter, online invitations along with the questionnaire were sent out to a total of 443 students, 280 from JUST, 96 from UoS and 67 from ODC, which represented the total number of final year students at the three schools. A first reminder was sent 2 weeks later, and a second reminder was sent after another 2 weeks.

In addition to basic demographic details, the questionnaire comprised questions related to the type of study conducted, the scope of the research project, whether the research project was proposed by the students or the instructors or both, the literature review part of the project, the statistical analysis performed, the final presentation of the project, the writing up of the resultant manuscript if applicable, the perceived benefits of the research project and finally suggestions to improve the research component for future students.

The outcomes of the study were the students’ research experience in terms of research design, literature review, data collection, analysis, interpretation and presentation, students’ perceived benefits from research, students’ perspective towards research in their future career and students’ suggestions to improve their research experience.

The exposures were the educational and clinical experience of students, research supervision by mentors and faculty members, and participation in extracurricular activities, while the predictors were the academic performance of students, previous research experience and self-motivation.

The collected responses were entered into a Microsoft Excel spreadsheet and analyzed using SPSS Statistics software, version 20.0 (SPSS Inc., Chicago, IL, USA). Descriptive data were presented as frequencies and percentages. For this study, only descriptive statistics were carried out as the aim was not to compare and contrast the three schools but rather to provide an overview of the research activities at the participating dental schools.

The heatmap generated to represent the answers for question 11 (perceived benefits of the research activity) was created using Python programming language (Python 3.11) and the pandas, seaborn, and matplotlib libraries. The heatmap was customized to highlight the count and percentage of responses in each component, with the highest values shown in red and the lowest values shown in blue.

Potentially eligible participants in this study were all final year dental students at the three dental schools (443 students, 280 from JUST, 96 from UoS and 67 from ODC). All potentially eligible participants were confirmed to be eligible and were invited to participate in the study.

The total number of participants included in the study, i.e. the total number of students who completed the questionnaire and whose responses were analyzed, was 369 (223 from JUST, 80 from UoS and 66 from ODC). The overall response rate was 83.3% (79.6% from JUST, 83.3% from UoS and 98.5% from ODC).

The highest proportion of participants were from JUST ( n  = 223, 60.4%), followed by UoS ( n  = 80, 21.7%), and then ODC ( n  = 66, 17.9%). The majority of the participants were females ( n  = 296, 80.4%), while males represented a smaller proportion ( n  = 73, 19.6%). It is noteworthy that these proportions reflect the size of the cohorts in each college.

With regards to the type of study, half of final-year dental students in the 3 colleges participated in observational cross-sectional studies (i.e., population-based studies) ( n  = 186, 50.4%), while literature review projects were the second most common type ( n  = 83, 22.5%), followed by experimental studies ( n  = 55, 14.9%). Longitudinal studies randomized controlled trials, and other types of studies (e.g., qualitative studies, case reports) were less common, with ( n  = 5, 1.4%), ( n  = 10, 2.7%), and ( n  = 30, 8.1%) participation rates, respectively. Distribution of study types within each college is shown Fig.  1 .

Distribution in percent of study types within each college. JUST: Jordan University of Science and Technology, UOS: University of Sharjah, ODC: Oman Dental College

The most common scope of research projects among final-year dental students was in public health/health services ( n  = 108, 29.3%) followed by dental education/attitudes of students or faculty ( n  = 103, 27.9%) (Fig.  2 ). Biomaterials/dental materials ( n  = 62, 16.8%) and restorative dentistry ( n  = 41, 11.1%) were also popular research areas. Oral diagnostic sciences (oral medicine/oral pathology/oral radiology) ( n  = 28, 7.6%), oral surgery ( n  = 12, 3.2%) and other research areas ( n  = 15, 4.1%) were less common among the participants. Thirty-two students (8.7%) were engaged in more than one research project.

Percentages of the scope of research projects among final-year dental students. JUST: Jordan University of Science and Technology, UOS: University of Sharjah, ODC: Oman Dental College

The majority of research projects were proposed through a discussion and agreement between the students and the instructor (55.0%). Instructors proposed the topic for 36.6% of the research projects, while students proposed the topic for the remaining 8.4% of the projects.

Most dental students (79.1%) performed the literature review for their research projects using internet search engines. Material provided by the instructor was used for the literature review by 15.5% of the students, while 5.4% of the students did not perform a literature review. More than half of the students ( n  = 191, 51.7%) used multiple search engines in their literature search. The most popular search engines for literature review among dental students were PubMed (70.2% of cases) and Google Scholar (68.5% of cases). Scopus was used by 12.8% of students, while other search engines were used by 15.6% of students.

The majority of dental students ( n  = 276, 74.8%) did not utilize the university library to gain access to the required material for their research. In contrast, 93 students (25.2%) reported using the university library for this purpose.

Dental students performed statistical analysis in their projects primarily by receiving help from the instructor ( n  = 167, 45.2%) or using specialized software ( n  = 168, 45.5%). A smaller percentage of students ( n  = 34, 9.4%) consulted a professional statistician for assistance with statistical analysis. at the end of the research project, 58.4% of students ( n  = 215) presented their work in the form of a manuscript or scientific paper. Other methods of presenting the work included PowerPoint presentations ( n  = 80, 21.7%) and discussions with the instructor ( n  = 74, 19.8%).

For those students who prepared a manuscript at the conclusion of their project, the most difficult part of the writing-up was the discussion section ( n  = 155, 42.0%), followed by the methodology section ( n  = 120, 32.5%), a finding that was common across the three colleges. Fewer students found the introduction ( n  = 13, 3.6%) and conclusion ( n  = 10, 2.7%) sections to be challenging. Additionally, 71 students (19.2%) were not sure which part of the manuscript was the most difficult to prepare (Fig.  3 ).

Percentages of the most difficult part reported by dental students during the writing-up of their projects. JUST: Jordan University of Science and Technology, UOS: University of Sharjah, ODC: Oman Dental College

The dental students’ perceived benefits from the research activity were evaluated across seven components, including literature review skills, research design skills, data collection and interpretation, manuscript writing, publication, teamwork and effective communication, and engagement in continuing professional development.

The majority of students found the research activity to be beneficial or highly beneficial in most of the areas, with the highest ratings observed in teamwork and effective communication, where 33.5% rated it as beneficial and 32.7% rated it as highly beneficial. Similarly, in the area of data collection and interpretation, 33.0% rated it as beneficial and 27.5% rated it as highly beneficial. In the areas of literature review skills and research design skills, 28.6% and 34.0% of students rated the research activity as beneficial, while 25.3% and 22.7% rated it as highly beneficial, respectively. Students also perceived the research activity to be helpful for the manuscript writing, with 27.9% rating it as beneficial and 19.2% rating it as highly beneficial.

When it comes to publication, students’ perceptions were more variable, with 22.0% rating it as beneficial and 11.3% rating it as highly beneficial. A notable 29.9% rated it as neutral, and 17.9% reported no benefit. Finally, in terms of engaging in continuing professional development, 26.8% of students rated the research activity as beneficial and 26.2% rated it as highly beneficial (Fig.  4 ).

Heatmap of the dental students’ perceived benefits from the research activity

The research course’s impact on students’ perspectives towards being engaged in research activities or pursuing a research career after graduation was predominantly positive, wherein 274 students (74.1%) reported a positive impact on their research perspectives. However, 79 students (21.5%) felt that the course had no impact on their outlook towards research engagement or a research career. A small percentage of students ( n  = 16, 4.4%) indicated that the course had a negative impact on their perspective towards research activities or a research career after graduation.

Finally, when students were asked about their suggestions to improve research activities, they indicated the need for more training and orientation ( n  = 127, 34.6%) as well as to allow more time for students to finish their research projects ( n  = 87, 23.6%). Participation in competitions and more generous funding were believed to be less important factors to improve students` research experience ( n  = 78, 21.2% and n  = 63, 17.1%, respectively). Other factors such as external collaborations and engagement in research groups were even less important from the students` perspective (Fig.  5 ).

Precentages of dental students’ suggestions to improve research activities at their colleges

To the best of our knowledge, this report is the first to provide a comprehensive overview of the research experience of dental students from three leading dental colleges in the Middle East region, which is home to more than 50 dental schools according to the latest SCImago Institutions Ranking ® ( https://www.scimagoir.com ). The reasonable sample size and different curricular structure across the participating colleges enhanced the value of our findings not only for dental colleges in the Middle East, but also to any dental college seeking to improve and update its undergraduate research activities. However, it is noteworthy that since the study has included only three dental schools, the generalizability of the current findings would be limited, and the outcomes are preliminary in nature.

Cross-sectional (epidemiological) studies and literature reviews represented the most common types of research among our cohort of students, which can be attributed to the feasibility, shorter time and low cost required to conduct such research projects. On the contrary, longitudinal studies and randomized trials, both known to be time consuming and meticulous, were the least common types. These findings concur with previous reports, which demonstrated that epidemiological studies are popular among undergraduate research projects [ 4 , 10 ]. In a retrospective study, Nalliah et al. also demonstrated a remarkable increase in epidemiological research concurrent with a decline in the clinical research in dental students` projects over a period of 4 years [ 4 ]. However, literature reviews, whether systematic or scoping, were not as common in some dental schools as in our cohort. For instance, a report from Sweden showed that literature reviews accounted for less than 10% of total dental students` projects [ 14 ]. Overall, qualitative research was seldom performed among our cohort, which is in agreement with a general trend in dental research that has been linked to the low level of competence and experience of dental educators to train students in qualitative research, as this requires special training in social research [ 15 , 16 ].

In terms of the research topics, public health research, research in dental education and attitudinal research were the most prevalent among our respondents. In agreement with our results, research in health care appears common in dental students` projects [ 12 ]. In general, these research domains may reflect the underlying interests of the faculty supervisors, who, in our case, were actively engaged in the selection of the research topic for more than 90% of the projects. Other areas of research, such as clinical dentistry and basic dental research are also widely reported [ 4 , 10 , 14 , 17 ].

The selection of a research domain is a critical step in undergraduate research projects, and a systematic approach in identifying research gaps and selecting appropriate research topics is indispensable and should always be given an utmost attention by supervisors [ 18 ].

More than half of the projects in the current report were reasonably selected based on a discussion between the students and the supervisor, whereas 36% were selected by the supervisors. Otuyemi et al. reported that about half of undergraduate research topics in a Nigerian dental school were selected by students themselves, however, a significant proportion of these projects (20%) were subsequently modified by supervisors [ 19 ]. The autonomy in selecting the research topic was discussed in a Swedish report, which suggested that such approach can enhance the learning experience of students, their motivation and creativity [ 20 ]. Flexibility in selecting the research topic as well as the faculty supervisor, whenever feasible, should be offered to students in order to improve their research experience and gain better outcomes [ 12 ].

Pubmed and Google Scholar were the most widely used search engines for performing a literature review. This finding is consistent with recent reviews which classify these two search systems as the most commonly used ones in biomedical research despite some critical limitations [ 21 , 22 ]. It is noteworthy that students should be competent in critical appraisal of available literature to perform the literature review efficiently. Interestingly, only 25% of students used their respective university library`s access to the search engines, which means that most students retrieved only open access publications for their literature reviews, a finding that requires attention from faculty mentors to guide students to utilize the available library services to widen their accessibility to available literature.

Statistical analysis has classically been viewed as a perceived obstacle for undergraduate students to undertake research in general [ 23 , 24 ] and recent literature has highlighted the crucial need of biomedical students to develop necessary competencies in biostatistics during their studies [ 25 ]. One obvious advantage of conducting research in our cohort is that 45.5% of students used a specialized software to analyze their data, which means that they did have at least an overview of how data are processed and analyzed to reach their final results and inferences. Unfortunately, the remaining 54.5% of students were, partially or completely, dependent on the supervisor or a professional statistician for data analysis. It is noteworthy that the research projects were appropriately tailored to the undergraduate level, focusing on fundamental statistical analysis methods. Therefore, consulting a professional statistician for more complex analyses was done only if indicated, which explains the small percentage of students who consulted a professional statistician.

Over half of participating students (58.4%) prepared a manuscript at the end of their research projects and for these students, the discussion section was identified as the most challenging to prepare, followed by the methodology section. These findings can be explained by the students’ lack of knowledge and experience related to conducting and writing-up scientific research. The same was reported by Habib et al. who found dental students’ research knowledge to be less than that of medical students [ 26 ]. The skills of critical thinking and scientific writing are believed to be of paramount importance to biomedical students and several strategies have been proposed to enhance these skills especially for both English and non-English speaking students [ 27 , 28 , 29 ].

Dental students in the current study reported positive attitude towards research and found the research activity to be beneficial in several aspects of their education, with the most significant benefits in the areas of teamwork, effective communication, data collection and interpretation, literature review skills, and research design skills. Similar findings were reported by previous studies with most of participating students reporting a positive impact of their research experience [ 4 , 10 , 12 , 30 ]. Furthermore, 74% of students found that their research experience had a positive impact on their perspectives towards engagement in research in the future. This particular finding may be promising in resolving a general lack of interest in research by dental students, as shown in a previous report from one of the participating colleges in this study (JUST), which demonstrated that only 2% of students may consider a research career in the future [ 31 ].

Notably, only 11.3% of our students perceived their research experience as being highly beneficial with regards to publication. Students` attitudes towards publishing their research appear inconsistent in literature and ranges from highly positive rates in developed countries [ 4 ] to relatively low rates in developing countries [ 8 , 32 , 33 ]. This can be attributed to lack of motivation and poor training in scientific writing skills, a finding that has prompted researchers to propose strategies to tackle such a gap as mentioned in the previous section.

Finally, key suggestions by the students to improve the research experience were the provision of more training and orientation, more time to conduct the research, as well as participation in competitions and more funding opportunities. These findings are generally in agreement with previous studies which demonstrated that dental students perceived these factors as potential barriers to improving their research experience [ 8 , 10 , 17 , 30 , 34 ].

A major limitation of the current study is the inclusion of only three dental schools from the Middle East which my limit the generalizability and validity of the findings. Furthermore, the cross-sectional nature of the study would not allow definitive conclusions to be drawn as students’ perspectives were not evaluated before and after the research project. Potential confounders in the study include the socioeconomic status of the students, the teaching environment, previous research experience, and self-motivation. Moreover, potential sources of bias include variations in the available resources and funding to students’ projects and variations in the quality of supervision provided. Another potential source of bias is the non-response bias whereby students with low academic performance or those who were not motivated might not respond to the questionnaire. This potential source of bias was managed by sending multiple reminders to students and aiming for the highest response rate and largest sample size possible.

In conclusion, the current study evaluated the key aspects of dental students’ research experience at three dental colleges in the Middle East. While there were several perceived benefits, some aspects need further reinforcement and revision including the paucity of qualitative and clinical research, the need for more rigorous supervision from mentors with focus on scientific writing skills and research presentation opportunities. Within the limitations of the current study, these outcomes can help in designing future larger scale studies and provide valuable guidance for dental colleges to foster the research component in their curricula. Further studies with larger and more representative samples are required to validate these findings and to explore other relevant elements in undergraduate dental research activities.

Data availability

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

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Acknowledgements

The authors would like to acknowledge final year dental students at the three participating colleges for their time completing the questionnaire.

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Alrashdan, M.S., Qutieshat, A., El-Kishawi, M. et al. Insights into research activities of senior dental students in the Middle East: A multicenter preliminary study. BMC Med Educ 24 , 967 (2024). https://doi.org/10.1186/s12909-024-05955-5

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Educational paradigm shift: assessing the prospects of a master's course in green energy transition

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• Volume 5 , article number  247 , ( 2024 )

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• Baibhaw Kumar   ORCID: orcid.org/0000-0003-0466-0711 1 ,
• Katalin Voith   ORCID: orcid.org/0000-0002-7681-1286 1 ,
• Krisztina Sándor 2 ,
• Zoltán Szamosi   ORCID: orcid.org/0000-0002-5494-0212 1 &
• Marti Rosas-Casals   ORCID: orcid.org/0000-0002-5243-2601 3  

This study examines the integration of emerging engineering technologies into STEM education with a focus on the green energy transition. Using a mixed-methods approach, including an international student survey conducted via Google Forms, the research identifies key factors influencing the demand for an innovative Master's program in Green Energy. Quantitative analysis through JASP software reveals a significant positive correlation between student interest in renewable energy related MSc courses and the perception of improved job opportunities in the green energy sector. Furthermore, the survey results indicate that students prioritize the inclusion of Mechanical, Electrical, and IT skills in the curriculum. Qualitative feedback highlights the critical need for practical skills in new research areas such as nanotechnology, quantum chemistry, Carbon capture, and Solar/Wind-based energy sources to meet the evolving demands of the green energy industry. These findings suggest that academic programs must be restructured to align more closely with the skills required for sustainable energy systems, thereby bridging the gap between academic preparation and market readiness.

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1 Introduction

Since the twentieth century, the perception of executive education programmes has changed, with an emphasis on executive master’s in business administration (EMBA) programs—the first of which was founded at Harvard in 1908—being the main focus. Specialized master's programmes that target fields like the Management of Technology (MoT), Technology Management (TM), and Engineering Management (EM) have been more popular over the past ten years in an effort to close the gap between business and technology [ 1 ]. There has been a notable upsurge in the creation of cutting-edge master's programmes outside the fields of traditional business and technology that are intended to address urgent global concerns, particularly those related to energy and sustainability. The need to give professionals the tools they need to deal with the complexity of energy transition and sustainability is highlighted by programmes like the Masters of Energy and Sustainability [ 2 ] and the partnership between the University of APEC (UNAPEC) and the University of Puerto Rico-Mayagüez (UPRM) for a Master’s Programme on Sustainable Energy [ 3 ]. The necessity for a paradigm shift in educational offerings becomes increasingly apparent when considering the rapid growth of the renewable energy sector, catalyzed by the advent of Industry 4.0. As smart technologies, including artificial intelligence, Big Data, the Internet of Things, and augmented reality [ 4 ] become integral to the renewable energy landscape, there is a burgeoning need for educational programs that prepare individuals to harness these technologies effectively [ 5 ]. Furthermore, the intersection of industrial symbiosis (IS), energy efficiency (EE), and green economy policies within energy-intensive industries (EIIs) emphasizes the crucial connection between policy objectives and the skills needed for green jobs. This linkage, as proposed by [ 6 ], stresses the importance of aligning educational programs with evolving market demands, ensuring a skilled workforce capable of driving investment [ 7 ], technical innovation [ 8 ], economic diversification, and job creation. In their analysis of active learning for postgraduate students via online platforms, Lamon et al. discovered that deep learning requires careful scaffolding of online learning and that the effect of switching to online learning on commitment and performance should be taken into account, particularly when targeting less experienced students [ 9 ]. The learning materials and methods used in curricula and lectures must be modified to better convey knowledge to students in light of ever-changing circumstances, such as current business concerns and course content [ 10 ] for development of analytical thinking [ 11 ].

These days, a lot of students find mathematical modelling to be a difficult and complex assignment and struggle with its complexities. To solve energy engineering challenges metacognition is important. Hidayat et al. evaluated if the many sub-dimensions of metacognition can predict the sub-constructs of a student's true modelling ability [ 12 ]. The transformative nature of education in response to these challenges is underscored by the emergence of digitally connected and renewables-based energy systems, often referred to as 'Smart Local Energy Systems' [ 13 ] highlight the imperative to generate, supply, manage, and balance energy across all vectors, while concurrently delivering social, environmental, and economic benefits to local communities. Mechanical engineering is at the centre of the seismic shift towards renewable energy technologies. This discipline is essential since it leads innovation and plays a key role in creating a sustainable future. Mechanical engineering is at forefront in leading the way for the world's shift to renewable energy, as the information supplied makes clear. It is using its clout to maximise the possibilities of wind, solar, hydro, geothermal, and other renewable resources. In the context of the green energy transition, mechanical engineering's dedication to pushing the limits of design innovation is one of its main advantages. Optimization techniques, a cornerstone of mechanical engineering, further enhance the impact of this discipline in the realm of renewable energy. The importance of mechanical engineering is growing as the need for sustainable energy solutions around the world increases. It is not only a wise strategic choice, but also an absolute must to fund educational and training initiatives that provide participants with not only mechanical engineering but renewable energy fundamentals-based skills and knowledge for Industry 4.0. The development of a workforce capable of navigating the complex green energy transition environment and advancing global sustainability and resilience will be greatly aided by such programmes [ 14 ].

A recent study by Habek et al. [ 14 ] combined three prestigious universities in Europe to determine the sustainability-related subjects incorporated into mechanical engineering curricula. There is still an opportunity for improvement because not all Master's students from the three universities who completed their mechanical engineering degrees were exposed to sustainability subjects in one or more required courses. A retrospective evaluation of the course design for students enrolled in the new graduate-level course "Local Renewable Energy Policy Course" was carried out by researchers at the University of Michigan [ 15 ]. According to the findings, training students to lead on climate change requires more than just understanding why the climate is changing; it also entails giving them a thorough understanding of the complex and useful skill sets that graduates will likely need to fill in the types of leadership roles that will likely arise in the future. For graduate students, this begs the question of what technologies and skills the Next Wave of Energy Innovation will demand [ 16 ]. And, who else can write their opinions on such curriculum developments more effectively than they themselves?

There comes a point at which it becomes clear that a Master's Course in Green Energy Transition is necessary in the light of this changing educational landscape. Henceforth, this article aims to evaluate the program's prospects from the viewpoint of international students, assessing its capacity to address the multidimensional challenges posed by the global transition to sustainable and renewable energy sources. Undertaking a survey study is imperative for the initiation of a pioneering Master's level course focused on "Green Energy Transition". This investigative approach is grounded in the necessity to discern and respond to the diverse expectations, preferences, and academic needs of the prospective international student cohort. By engaging in a meticulous survey, authors endeavor to tailor the curriculum suggestions to the specific interests and career aspirations of the diverse demographic, thereby ensuring its direct relevance to their professional trajectory. The global perspective brought by international students is invaluable, with their varied cultural and educational backgrounds poised to enrich the discourse on green energy transition. In addition to assessing any perceived deficits in skills on the part of the students, the purpose of this survey is to optimize educational methods in order to create an inclusive pedagogical approach that caters to the varied learning preferences of the cohort. Information obtained from the survey will not just shape the program's design, but also strategically direct marketing strategies to appeal to a varied and skilled group of students. In its basic form, this survey acts as a compass to steer the development of a state-of-the-art academic programme that fulfils the demands of foreign students while also adding to the global conversation on creative and sustainable approaches in the field of green energy transition. The prime objectives of the study are:

To Evaluate the level of interest among international students in enrolling in a Master's course specializing in green energy transition through statistical analysis.

Identify and analyze potential emerging engineering technologies or interdisciplinary fields that will significantly influence the future of green energy transition.

Gather insights that inform curriculum development by exploring the student’s mindset and suggestions which could be crucial for mastering in green energy transition.

In pursuit of these objectives, the survey aims to establish a comprehensive understanding of international students' perspectives, enabling the Faculty of Mechanical Engineering and Informatics at the University of Miskolc to design and implement a master's program in green energy transition that not only meets but exceeds the expectations of its diverse and globally-oriented student body.

2 Overview of green energy in engineering education

The evolution of energy transition concepts within engineering curricula has been integral to preparing the future of engineering pedagogy and their contrivances presented by the shift towards sustainable and renewable energy sources [ 17 ] provides a comprehensive analysis of technological transitions, including energy transitions, from an evolutionary and reconfiguration perspective, highlighting the multi-level changes involving technology, user practices, regulation, industrial networks, infrastructure, and culture. This framework is critical for understanding how engineering education must adapt to incorporate these multidimensional aspects of energy transitions. In preparing a national-level representative questionnaire survey for Hungary, [ 18 ] looked at a variety of topics, including self-reported and actual knowledge, correlations between various energy sources, typical energy attitudes of different social groups, and characteristic stereotypes. There was an exceptional level of understanding regarding wind, solar, and hydropower, as well as a strong correlation between them. A consistent rise in engineering education for sustainability was found in a review study. The literature revealed four main conceptual themes: curriculum assessment and benchmarks, curriculum reform, engineering competencies, pedagogy, and curriculum, and sustainable technologies [ 19 ]. The review emphasizes how curricular reform must be ongoing in order to properly move engineering education towards sustainability [ 20 ].

Furthermore, the study by [ 21 ] on optimizing the complementarity between small hydropower plants and solar PV systems introduces engineering students to innovative approaches in renewable energy system design, emphasizing the importance of integrating various renewable resources for sustainable energy production and related skills. These concepts have become increasingly relevant in engineering curricula, reflecting the industry's move towards more diversified and sustainable energy solutions. This means that in order to educate engineering graduates about the fresh challenges they will face as practicing engineers, educators must update their courses and curriculum [ 22 ].

2.1 Global trends in green energy pedagogy at universities

Global trends and activities in green energy education at universities have been strongly impacted by the growing importance of renewable energy sources as a means of addressing the interrelated problems of climate change, energy poverty, and sustainable development. In order to equip the upcoming generation of professionals to address these intricate difficulties, there is now a greater emphasis on integrating renewable energy into academic curricula and research agendas as a result of this shift in focus. [ 23 ] highlight the critical role that renewable energy plays in the global energy transition in a seminal work that clarifies the technical and economic aspects of a faster energy transition and the interdependent relationships between renewable energy and energy efficiency. Measurements of the knowledge and awareness of Indonesian VHS (Vocational High School) students were conducted by Muslim et al. [ 24 ]. Based on factors including gender, parents, the island, public versus private schools, and the VHS's areas of specialisation, the knowledge and awareness level of the children is thoroughly examined. The findings indicate that VHS students now have awareness levels in the "fair" category and a knowledge level in the "good" category regarding renewable energy. In another attempt at the university level, [ 25 ] conducted a comparison of various Canadian programmes, such as the Energy Programme at the University of Toronto, the Sustainable and Renewable Energy Engineering Degree at Carleton University, the Electrical Energy Systems Option at the University of British Columbia, and the Energy and Environment Specialisation at the University of Calgary. to assess each program's contribution to the development of the "T-shaped" engineer using a multicriteria framework intended to gauge learning objectives. The programme comparison demonstrates that there is a great deal of opportunity and design flexibility when it comes to incorporating sustainable energy systems thinking into energy engineering education, despite the enormous constraints placed on active curriculum development, such as accreditation requirements, budgets, and faculty availability. According to a Polish study by I. Ocetkiewicz et al., [ 26 ] very few Polish instructors were able to include lessons on green energy in their curriculum. It's unclear how and to what degree educators wish to incorporate sustainable consumption issues into their curricula. While it is important for the future of the global energy economy concerns, the study draws attention to these challenges in the curricula. It is also suggested that teachers be informed about the appropriate work methods and formats, software for knowledge, and ways to incorporate the subject matter into the curricula.

However, it's not as adequately reflected in the discussions on the transformation of the traditional curricula in the pedagogy of engineering that such discussions and research, reflect the increasing emphasis on renewable energy topics within engineering and are coherent with the policies supporting the United Nations (UN) sustainable development goals which are critical in shaping future jobs for Industry 4.0. Moreover, the global renewable energy development analysis by [ 27 ] sheds light on the political, technical, economic, and social perspectives influencing renewable energy policy and development across different regions. Such analyses are crucial for educational institutions aiming to prepare students for the global energy market's complexities, emphasizing the need for a comprehensive understanding of the factors driving renewable energy adoption. To equip students with skills that govern future industrial innovation and growth. The integration of green energy topics into engineering pedagogy is nothing but a response to the energy sector's dynamic evolution, driven by technological advancements, policy shifts, and the global push for sustainability. Engineering curricula are increasingly incorporating these multidisciplinary aspects, preparing graduates to contribute effectively to the energy transition. The subsequent section discusses the local developments in Europe.

2.2 Initiatives in Europe

The European Commission urges EU member states to prioritize education for the green transition and sustainable development and supports the teaching of renewable energy at European institutions. In addition to publishing the European Competence Framework on Sustainability (GreenComp) ( https://green-comp.eu/ ), which outlines the knowledge, abilities, and attitudes that students of all ages must develop in order to make the transition to a greener economy, the Commission maintains a specialized working group on sustainability in education. The EU's Erasmus + , Horizon Europe, and other financing programmes offer financial support. For elementary and secondary schools, the Commission also offers free educational resources on energy, the environment, and climate change as listed in Table  1 . On the other hand, no precise information about the European Commission's position on renewable energy education in European universities is available [ 28 ].

The European Union has initiated several programs and frameworks to foster the integration of sustainability and environmental consciousness into the educational landscape. Among these, the Education for Climate Coalition stands out as a growing network comprising educators, students, and organizations dedicated to environmental sustainability and climate change. This coalition plays a pivotal role in networking [ 29 ], allowing for the exchange of ideas, resources, and best practices among its participants. Complementing this, the Council Recommendation on learning for the “Green Transition” and sustainable development assists educational entities to weave sustainability into their curricula, emphasizing training [ 30 ] as a core component. This recommendation underscores the necessity for educators to develop and implement sustainability-focused training and education programs.

The European sustainability competence framework delineates the necessary mindsets, expertise, and skills for learners of all ages, aiming at competence development [ 31 ]. It is a guide for educational institutions to mold individuals who can contribute effectively to the green economy. Meanwhile, the working group on vocational education and training and the green transition (VET) focuses on generating valuable communications and inputs for policy formation, targeting higher education and vocational training [ 32 ]. It addresses sustainability and green transition as critical components of vocational education and training. The Erasmus + and European Solidarity Corps program bolsters these efforts by supporting a variety of initiatives related to sustainability in training and education. This includes staff and student exchanges, research, and volunteer work, thereby enhancing staff, student exchange, and mobility [ 33 ]. To facilitate the financial aspects of these educational reforms, the Invest-EU programme provides a funding mechanism [ 34 ] that enables Member States to secure funds for skill development and to build sustainable educational infrastructures. The “Researchers at Schools” initiative opens up avenues for research activities [ 35 ], where discussions on climate change and sustainable development can take place directly in the educational setting, involving educators, students, and young researchers in the conversation. The Erasmus + Discover-EU Green route aims to inspire young individuals to explore [ 36 ] and plan their travels with a consciousness towards sustainability, thereby promoting a greener way to discover Europe. Lastly, the EU Learning Corner offers primary and secondary schools a repository of instructional materials on climate change, sustainability, and environmental crises, targeting primary learning [ 37 ].

Assessing these initiatives, it is evident that the EU is taking a comprehensive approach to integrate green education across various levels and sectors. These programs collectively establish a robust framework for educators and learners to engage with sustainability and environmental issues. These EU initiatives collectively provide a rich ecosystem of resources, frameworks, and opportunities that can be leveraged by universities and engineering departments to develop comprehensive and cutting-edge courses on green energy transition, equipping students with the necessary knowledge and skills for the sustainable energy sector.

3 Methodology

The Fig.  1 illustrates the methodological framework employed in the study, structured as a logical flowchart that delineates the sequence and rationale of the research survey process. At the top, "Survey Development" is the initial phase where the research instruments are designed. The queries "How?" and "When?" adjacent to this phase suggest that this section details the procedural and temporal aspects of the survey—how the survey was created and when it was distributed.

Methodology adopted for the study

Following this, the "Quantitative Assessment" phase likely involves statistical analysis of the collected data, with the question "Why?" indicating a need to justify the use of quantitative methods. This could mean explaining the rationale for the selection of certain statistical tests or metrics used in evaluating the survey data. The subsequent phase, "Qualitative Assessment – RQ(a) and RQ(b)," implies a deeper analysis of open-ended survey responses pertaining to two specific research questions (a and b). The accompanying "Why?" suggests this section elaborates on the reasons for employing qualitative analysis, possibly to understand the context and nuances behind the quantitative data or to explore themes that numbers alone cannot elucidate.

At the bottom, "Results, Discussion, and Conclusion" is the final phase where the outcomes of both assessments are presented, and their implications are discussed. The "What?" question indicates that this section should summarize the findings (what the study found), discuss their significance, and provide a concluding synthesis that encapsulates the entire research process and its contributions to the field.

3.1 Survey development and rationale

In addition to collecting helpful feedback for improving a proposed Master's course in green energy transition, the survey instrument was painstakingly designed to capture a wide range of insights on emerging engineering technologies and interdisciplinary fields that are expected to significantly influence the future of green energy transition. Recognizing the pivotal role of diverse perspectives in shaping comprehensive and inclusive educational programs, the survey was developed using Google Forms for its accessibility, ease of use, and widespread acceptance, ensuring a user-friendly interface for participants across the globe. Comprising 17 carefully crafted questions, the survey was structured to assess a variety of dimensions, including demographic diversity, educational backgrounds, and specific insights related to the green energy sector around 107 students took part. The questions were framed to gather detailed information on the participants' home country, gender, level of education, and field of study. The purpose of gathering this demographic data was to guarantee that a diverse range of international students were represented, adding a wealth of viewpoints and experiences to the data. The survey data collection was done in January 2024 with one month time period, to allow ample time for participants to provide thoughtful and reflective responses.

The awareness that the switch to green energy is a worldwide challenge requiring creative solutions and interdisciplinary methods forms the basis for the survey's development. The survey seeks to identify new pedagogical approaches, technology, and trends that are applicable to various geographical locations and educational situations by leveraging the perspectives of foreign students. This method promotes inclusivity while guaranteeing that the course material stays up to date with educational and technological developments in the sphere of the transition to green energy.

3.2 Quantitative assessment

Surveys that consider Likert-based questions generally are considered as ordinal data, hence, for our survey quantitative assessment, it was adequate to use non-parametric tests such as Spearman's rho or Kendall's tau for correlation analysis. JASP software ( https://jasp-stats.org/ ) offers both frequentist and Bayesian inference on the same statistical models, including descriptive, T-Tests, ANOVA, Mixed Models, Regression, Frequencies, Factors, and many others. Therefore, for Likert survey results, non-parametric tests such as Spearman's rho or Kendall's tau can be used in JASP for correlation analysis. In this assessment, we evaluated the Correlation coefficients using Pearson’s r, Spearman’s rho, and Kendall’s Tau B, along with their associated p-values.

The survey questions were coded to enable statistical analysis by categorizing responses into quantifiable data. Each question and its corresponding options were assigned numerical values or labels. For instance, Likert scale responses ("Strongly Disagree" to "Strongly Agree") were coded from 1 to 5. Multiple-choice questions with categorical responses were also numerically coded ("One Year" = 1, "Two Year" = 2). These codings facilitated the use of statistical software (JASP) for quantitative analysis, allowing us to compute correlations, descriptive statistics, and other analyses to interpret the data effectively.

Table 2 . presents a structured overview of survey questions and their corresponding answer options designed to gather data on perceptions of the green energy transition and related educational programs. It includes questions on the importance of emerging technologies for future careers, interest in Master's programs in Green Energy, preferred program duration, crucial skills for the green energy industry, preferred learning approaches, influencing factors for pursuing advanced education, potential barriers, and the relevance of different engineering fields. The coded responses facilitate quantitative analysis, allowing for the extraction of meaningful insights through statistical software. This enables the assessment of trends, correlations, and overall attitudes towards the green energy sector among international students.

In this study, we tested the relationships between several variables related to students' perceptions of new Master's courses in green energy. To do this, we employed statistical correlation analyses, which involve assessing whether there is a significant relationship between these variables. The foundation of this analysis is the null hypothesis, which posits that there is no significant correlation between the variables—in other words, that any observed relationships are due to random chance rather than a true underlying association.

The relevance of the null hypothesis in this study is crucial. By comparing the observed correlation coefficients to this null hypothesis, we can determine whether the relationships we observe in the data are statistically significant. A lower p-value indicates stronger evidence against the null hypothesis, suggesting that the correlations we observe are unlikely to have occurred by chance and are more likely indicative of real, meaningful relationships. Testing against the null hypothesis thus allows us to validate our findings and draw more reliable conclusions about the factors influencing student interest in green energy education.

3.3 Qualitative assessment

Emerging developments like carbon capture and storage, floating offshore wind farms, decentralised energy systems, nanotechnology, etc., bode well for the future of renewable energy technologies [ 38 ]. Review studies indicate that the engineering community must comprehend the developments in renewable technology. But it wouldn't be feasible without considering what today's students think and suggest about these developing fields. A few case studies that have been conducted on students from a variety of areas to get their view on the adoption of renewable energy courses while taking students' suggestions into consideration have inspired the study's second research topic. Students from backgrounds in agriculture (Iran)[ 39 ], economies (Poland)[ 40 ], vocational education (Indonesia) [ 41 ], etc. are some examples. Giving us justification to take this point of view into account in our evaluation. Henceforth, the survey consisted of two open-ended questions to encourage detailed, qualitative responses, allowing participants to express their views freely on the subjects of emerging technologies and course improvements. These questions were:

RQ(a): Are there any emerging engineering technologies or interdisciplinary fields that you believe will significantly influence the future of green energy transition?

RQ(b): Any suggestions for improving the proposed Master's course in Green Energy Transition?

The approach used to examine the answers to these open-ended questions is based on thematic analysis, a versatile technique for finding, examining, and summarising patterns (themes) in the survey data that has been gathered. The authors chose the Thematic analysis for its feasibility in exploring the perspectives of international students across a diverse dataset, allowing for the in-depth exploration of participants' thoughts and opinions on emerging technologies and educational improvements.

The qualitative analysis commenced with a comprehensive review of all survey responses, ensuring a deep understanding of the participants' insights into emerging engineering technologies and course improvement suggestions. This initial familiarization phase was crucial for grasping the responses' depth and complexity. Following this, the coding process involved meticulously labeling segments of text to highlight relevant information, with the codes refined through an iterative process as new patterns emerged. These codes were then organized into themes that accurately reflected the data's core aspects, with specific technologies and interdisciplinary fields identified for RQ(a), and pedagogical suggestions for RQ(b). A thorough review of these themes ensured their validity and alignment with the dataset. Each theme was carefully defined and named to encapsulate the data's essence succinctly. The final phase involved synthesizing the findings into a coherent analysis, linking the identified themes to the research questions, and situating them within the broader scientific literature. This streamlined approach allowed for a focused and efficient analysis, yielding meaningful insights into the subjects at hand.

This methodology provides a structured yet flexible approach to qualitative analysis, enabling a deep dive into the perspectives of individuals within the STEM community on crucial topics. By systematically organizing and interpreting the survey responses, this approach facilitates a comprehensive understanding of the collective vision for the future of green energy transition and education.

4.1 Background information

The survey attracted predominantly male participants with a strong representation of engineering and earth sciences, hailing from diverse geographic locations. The academic level of the participants span from bachelor's degree to doctoral degree level, indicating a breadth of academic engagement in the topic of green energy transition. A total of 107 students filled the survey coming from various faculties with a response rate of 53.5%.

Figure  2 presents a graphical summary of the demographic and academic background of participants in a survey designed to gauge student perspectives on master's level courses in the field of green energy transition. The survey results are depicted through four distinct parts labelled (a) through (d).

The first chart is a pie chart indicating the gender distribution of the survey respondents. The majority, at 68.6%, are male, followed by 30.5% female, and a small fraction, 1%, choosing not to disclose their gender.

Next to this pie chart is a world map, indicating the global distribution of the participants, with varying shades of blue representing the concentration of students from different regions. With the highest participation from Middle Eastern countries followed by South Asia.

The third element of Fig.  2 is a multi-colored pie chart detailing the academic disciplines of the respondents. A significant portion of the respondents, 35.2%, come from the field of Mechanical and Informatics Engineering, which is likely relevant due to the mechanical aspects of energy systems. Earth Science students make up 23.9%, indicating a strong representation from a field directly concerned with the environmental impact of energy production. Other fields include Business Management (11.4%), Material science (7.6%), and smaller percentages from fields such as Law, Chemical Engineering, and Chemistry. This diverse disciplinary representation suggests a comprehensive interest in green energy across various sectors of academia.

The last chart is another pie chart displaying the highest degree obtained by the respondents. The majority, 67.6%, are from a Master's degree program, while 23.6% are pursuing a Doctoral degree, and 8.6% are from a Bachelor’s level of studies. This distribution underscores the involvement of both early-career and advanced scholars in the green energy transition topic, reflecting a range of insights and experiences pertinent to master's level education.

Representation of demographic diversification of student respondents

4.2 Quantitative findings

4.2.1 future career prospects and job expectations.

The amount of higher education courses offered in comparison to the industry's strong demand for practical training indicates that there is a mismatch between the given education and the demand for competent people in general [ 42 ]. The quantitative assessment of the survey responses, focusing on "Future Career" prospects and "Job Opportunities," provides insightful data on the participants' perceptions regarding their educational experience and potential employability post-graduation. The data is depicted through histogram graphs and is complemented by descriptive statistics and frequency distributions. The histogram presented in Fig.  3 . for "Future Career" indicates that the majority of participants feel positively about their career prospects after completing their education. With the responses of participants falling in the 'Agree' category and a significant number in 'Strongly Agree', it is evident that the sentiment is generally optimistic. The descriptive statistics support this, showing a high mean score of 8.571 out of 10, which signifies a strong positive perception. The standard deviation of 1.379 suggests that responses are relatively consistent and there is limited variability in the participants' confidence regarding their future career prospects.

Student’s opinion on future career prospects and job expectations in context with the master’s course

In the "Job Opportunities" category, the histogram reveals a similar positive trend, with the majority of participants agreeing or strongly agreeing that their education will yield job opportunities. The mean score here is slightly lower at 8.133, with a higher standard deviation of 1.716, which indicates a somewhat wider spread of opinions compared to the "Future Career" prospects. This wider spread suggests that while optimism is prevalent, there is more variation in participants' certainty regarding the direct translation of their education into job opportunities. A comparative analysis of the two histograms shows that students are slightly more confident in their general "Future Career" prospects than in the specific "Job Opportunities" available to them post-graduation. This distinction could reflect an understanding that while career opportunities in their field may be abundant, the immediate availability of jobs post-study may not be as certain. The frequency distributions provide additional context to the histograms, with "Future Career" showing a strong concentration of responses in the 'Agree' and 'Strongly Agree' categories, accounting for over 90% of the responses. "Job Opportunities" displays a similar pattern, with these positive categories comprising approximately 85% of responses. It is noteworthy that very few respondents disagreed or strongly disagreed with the positive statements about their future career and job prospects, indicating a general consensus of positive outcomes from their education.

4.2.2 Importance and interest in engineering aspects

The quantitative assessment further explores students' opinions on the significance of Mechanical, Electrical, and IT (Information Technology) subjects in a Master's course and their overall interest in a new MSc (Master of Science) program. The histogram depicted in Fig.  4 the "Importance of Mechanical/Electrical/IT" shows a substantial number of participants recognizing the importance of these subjects, with a dominant number of respondents in the 'Strongly Agree' category. This indicates a significant acknowledgment of the relevance of Mechanical, Electrical, and IT disciplines within the Master's curriculum. The descriptive statistics corroborate this with a high mean value of 8.952 out of 10, which signals a strong positive acknowledgment of these disciplines' importance. The relatively low standard deviation of 0.774 points to a consistent agreement among participants regarding this view. Regarding the "Interest in New MSc Course," the histogram displays a more evenly distributed set of student’s responses, with the majority of participants agreeing or strongly agreeing, yet with a notable number of neutral responses. This suggests that while there is a general interest in the new MSc course, there is also a significant level of uncertainty or ambivalence among the students. The mean score of 6.952 indicates a moderate level of interest, with a relatively higher standard deviation of 2.594 suggesting greater variability in participants' interest levels compared to their views on the importance of Mechanical/Electrical/IT subjects.

Student’s opinion on the importance of Mechanical/Electrical/IT in the master’s course and their general interest in the course

Comparing the two histograms, it is evident that students show a stronger consensus on the importance of Mechanical, Electrical, and IT subjects in the Master's course than their interest in the new MSc course. This could reflect a scenario where students recognize the value of these subjects but may need additional information or motivation to commit to a new MSc program. The frequency distributions for both parameters further detail these perceptions. For the "Importance of Mechanical/Electrical/IT," the distribution is heavily skewed towards agreement, with approximately 94% of participants rating this as 'Agree' or 'Strongly Agree.' In contrast, the "Interest in New MSc Course" responses are more varied, with 'Agree' and 'Strongly Agree' making up about 73% of the responses, but with a substantial proportion of participants remaining neutral.

4.3 Correlation study

The provided correlation is in Fig.  5  summarizes the results of a survey investigating students' opinions on new master's level courses in green energy. It looks at the relationships between four different variables: future career, job opportunity, interest in the new MSc course, and the importance of Mechanical/Electrical/IT. The use of Spearman’s rho, Kendall's Tau B, and Pearson’s r together, despite similar coefficients, is justified by their distinct purposes and underlying assumptions. Pearson's r measures linear relationships between variables assuming normally distributed data. In contrast, Spearman’s rho and Kendall’s Tau B assess monotonic relationships, suitable for ordinal data or non-parametric distributions. Including all three metrics provides a comprehensive view, ensuring robustness and validity in various data conditions, thereby enhancing the reliability and interpretability of the results. This triangulation approach helps to confirm findings across different statistical assumptions and methodologies.

Correlation coefficients are calculated using Pearson’s r, Spearman’s rho, and Kendall’s Tau B, along with their associated p-values

From the results of the assessment as shown in the Fig.  5 we infer that:

Future career: There are no correlation values present in this row because it has been used as a reference or control variable.

Job opportunity: According to Pearson's r = 0.341, p < 0.001, the first parameter, which represents students' perceptions of job opportunities after completing the new master's course, has a moderately positive correlation with the interest in new MSc courses. This suggests that as perceived job opportunities rise, so does interest in new MSc courses. This holds true for both Kendall's Tau B and Spearman's rho, and all p-values are significant (p < 0.001), indicating a strong association.

Interest in new MSc course:Shows a moderate positive correlation with job opportunity (Pearson’s r = 0.495, p < 0.001), which is the strongest observed correlation in this table. This suggests a strong relationship where an increased interest in new MSc courses is associated with the perception of better job opportunities. There's also a positive correlation with the importance of Mechanical/Electrical/IT (Pearson’s r = 0.268, p = 0.006), indicating that students who find these fields important are more likely to be interested in new MSc courses related to green energy.

Importance of Mechanical/Electrical/IT: It does not show significant correlations with future career, job opportunity, or interest in new MSc course as per Pearson's r and Kendall's Tau B, except for a very weak correlation with interest in new MSc course which is statistically significant (Kendall’s Tau B = 0.230, p = 0.007). However, these low correlation values, coupled with non-significant p-values in Pearson's r, suggest that there is no strong evidence to claim a meaningful relationship between these fields' importance and the other variables. The p-values show that these results are statistically significant and unlikely to be the result of chance because they are all below the standard alpha threshold of 0.05. It's crucial to remember that correlation does not indicate causation, thus these findings should be understood as demonstrating relationships as opposed to direct impacts.

The correlation plot is a matrix of scatter plots where each cell represents the relationship between two variables. The diagonal histograms show the distribution of each variable. Above the diagonal in Fig.  6 , the Pearson's r correlation coefficient is provided along with its significance level, while below the diagonal, there's information on the correlation's p-value and t-test result based on analysis in JASP software heat map plot. The significance values indicate how likely it is that the observed correlation occurred by chance, with a lower p-value indicating a shred of stronger evidence against the null hypothesis of no correlation.

Co-relation and heat map plots of the data

Figure  6 provides a heatmap that visually represents the strength and direction of these correlations. In this heatmap, color intensity indicates the strength of the relationship: darker colors represent stronger correlations, while lighter colors indicate weaker ones. The heatmap also shows whether the correlations are positive (blue) or negative (red). This visual representation helps to quickly identify which relationships are most significant.

4.4 Qualitative findings

The results are assessed through the lens of their relevance to the research questions, the coherence of the identified themes, and their implications for the future of STEM education and the green energy transition. The analysis not only highlights the specific technologies and interdisciplinary fields seen as pivotal by the STEM community but also provides actionable insights into how a Master's course in Green Energy Transition can be improved to meet the evolving needs of the sector. The qualitative analysis of the survey data, focusing on emerging engineering technologies and interdisciplinary fields expected to influence the future of green energy transition, alongside suggestions for improving a proposed Master's course in Green Energy Transition, reveals insightful patterns and themes. This analysis follows the thematic analysis methodology outlined earlier, emphasizing an in-depth understanding of the STEM community's perspectives.

4.4.1 Emerging technologies and fields RQ(a)

The responses to the first research question highlighted several key technologies and fields:

Nanotechnology: Mentioned multiple times, nanotechnology is perceived as a crucial driver for the future of green energy, pointing to its potential to enhance materials efficiency and energy storage solutions.

Quantum chemistry: Highlighted alongside nanotechnology, quantum chemistry is seen as instrumental in understanding and developing new materials and their mechanics for energy production and storage.

Offshore eolic (Wind) energy: This suggests a growing interest in expanding renewable energy sources, specifically the potential of offshore wind farms to contribute significantly to green energy transition.

Carbon capture, utilization, and storage (CCUS): Identified by its acronym and variations (like "C capturing"), CCUS is recognized for its potential to mitigate greenhouse gas emissions from existing and future energy systems.

These technologies and fields underscore a significant inclination toward innovation in material science, renewable energy sources, and carbon management, reflecting a broader vision for a sustainable energy future.

4.4.2 Suggestions for Master's course improvement RQ(b)

The suggestions for improving the proposed Master's course in Green Energy Transition, though fewer, offer valuable insights into curriculum development:

Comprehensive infrastructure focus: One response emphasized the importance of including infrastructure design and management within the course, suggesting a " blueprint " for urban green cities. This indicates a demand for practical, application-oriented learning that prepares students for the infrastructural challenges of green energy transition.

Mechanical background: Highlighting the importance of strong foundational knowledge in mechanical, this suggestion points to the interdisciplinary nature of green energy studies, where material science, mechanical modelling, software modelling and simulations plays a critical role.

The lack of responses in some entries suggests either satisfaction with the proposed course as is or a hesitation to suggest improvements without more information. However, the feedback provided stresses the importance of a curriculum that is both comprehensive and interdisciplinary, equipping students with the theoretical knowledge and practical skills needed for the green energy sector.

5 Discussion

We refer to similar studies to provide context and validate our findings. A recent study at Democritus University of Thrace in Greece demonstrated that students support renewables and recognize the need for a green transition in curricula, particularly among final-year students [ 43 ]. Additionally, a comparative study involving Canadian, Romanian, and Turkish students found similar levels of awareness and understanding regarding the environmental impact of renewable and nuclear power plants, with response percentages generally within 10% of each other [ 44 ]. These findings align closely with our results, reinforcing the importance of integrating green energy topics into educational programs globally. This consistency across diverse geographical contexts underscores the widespread recognition of the significance of renewable energy education in preparing students for future careers in the green energy sector.

5.1 Comparative analysis and implications

The findings from our survey on emerging engineering technologies and the suggestions for improving a Master's course in “Green Energy Transition” offer significant insights when compared with existing literature. In sustainable energy education, it is often highlighted in literature the significance of incorporating interdisciplinary methods and implementing the latest technologies in curriculum development. Similar to our findings, studies have highlighted nanotechnology, renewable energy sources such as wind energy, and carbon capture and storage (CCUS) as pivotal areas for the future of green energy [ 45 , 46 ].

This comparative analysis confirms the relevance of our survey findings and underscores the alignment between current educational demands and the broader academic and industrial trends in green energy transition.

5.1.1 Impact on curriculum development

The insights gathered from the survey underscore the necessity for curriculum developers to incorporate a blend of theoretical knowledge and practical skills in green energy programs. By highlighting specific areas such as nanotechnology, quantum chemistry, and CCUS, the findings direct educational institutions to focus on these emerging fields, ensuring that students are equipped with the knowledge and skills needed to navigate and contribute to the green energy transition. Additionally, the call for an interdisciplinary approach, combining engineering with environmental science, policy studies, and material science, suggests a shift towards a more holistic educational framework that mirrors the multifaceted nature of sustainability challenges.

5.1.2 Contribution to the Broader discourse on sustainability education

The study adds empirical support to the ongoing conversation about sustainability education by highlighting how crucial it is to incorporate interdisciplinary studies and emerging technologies into green energy curricula. This is consistent with the increasing acknowledgment that sustainability education is pivotal in propelling society's shift towards sustainable practices. By involving international students in this discussion, the study adds a richer perspective to the debate and emphasizes the importance of inclusive educational practices as well as the global nature of sustainability issues.

5.2 Inference from correlation study

The heatmap and correlation plots collectively suggest that while students' perceptions of future careers and job opportunities are related, the perceived importance of certain subjects does not strongly correlate with these variables. The strongest relationship is between “Job Opportunity” and “Interest”, indicating that practical outcomes like job prospects are a significant factor in students' interest in the MSc course. The lack of significant correlation between Importance and other variables might indicate that while students acknowledge the significance of Mechanical/Electrical/IT, this recognition does not necessarily impact their career optimism or interest in the course as strongly as job opportunities do. This finding is important for curriculum developers to consider when designing course content and marketing educational programs to potential students.

5.3 Limitations and Future Research

While the study provides valuable insights into the future of green energy transition and education, it is not without limitations. The reliance on a self-selected group of international students may introduce bias, as participants who are already interested or involved in sustainability issues may be more likely to respond. Furthermore, the survey's scope, limited to participants' perceptions and suggestions, may not fully capture the complexities of integrating emerging technologies into curriculum development. Recognizing these limitations is crucial for interpreting the findings within the appropriate context and for guiding future research efforts. To have a more thorough grasp of the requirements and difficulties in sustainability education, future studies may look at expanding the participant base to include a larger range of stakeholders, such as educators, business experts, and legislators. Additionally, ongoing studies may shed light on how new technologies and multidisciplinary teaching methods are incorporated into green energy curricula over time, as well as how this influences students' professional choices and contributions to the green energy industry. Additionally, research concentrating on the execution and results of the proposed curriculum modifications would be extremely beneficial, providing proof of how well these innovations work to improve student's educational experiences and readiness for the shift to green energy.

6 Conclusion

This study concludes with a critical examination of emerging engineering technologies and interdisciplinary fields anticipated to significantly influence the green energy transition, alongside eliciting suggestions for enhancing a proposed master's course in Green Energy Transition. Through a methodical survey leveraging Google Forms, we engaged international students to provide a mosaic of insights reflective of diverse global perspectives. As educators, there is a responsibility to bridge the gap between academic offerings and the professional and personal aspirations of students, ensuring that educational pathways in green energy transition are accessible, relevant, and appealing to a broad spectrum of students. The most significant finding is the positive relationship between the opinion on job opportunities and the interest of students in the discussed master’s course on green transition. This suggests that students may be motivated to pursue further education if they believe it will enhance their job prospects, particularly in the field of green energy in the fast-developing green Industry 4.0. There seems to be a minor association between the importance of technical fields and interest in new courses, but this link is weaker and may require further investigation to understand its implications. The qualitative analysis of survey responses provides valuable insights into the technologies and interdisciplinary fields viewed as pivotal to the green energy transition, along with constructive feedback on improving a master's course tailored to this transition. Aligning educational programs with these emerging trends and incorporating practical, interdisciplinary approaches to learning will be key in preparing the next generation of leaders in green energy.

Data availability

The full data of the survey in an Excel file is available from the corresponding author on request.

Code availability

Not applicable.

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This paper was supported by the János Bolyai Scholarship of the Hungarian Academy of Sciences.

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All authors listed in this paper— Baibhaw Kumar (B.K.), Katalin Voith (K.V.), Krisztina Sándor (K.S.), Zoltán Szamosi (Z.S.), and Marti Rosas-Casals (M.R.)—have made contributions to the research and comply with the established authorship criteria. B.K. significantly contributed to the conception, design, and data analysis, and was primarily responsible for drafting the manuscript. K.V. contributed to the study's design and software development, providing critical revisions to ensure intellectual integrity. Z.S. was integral in data interpretation and software creation, offering substantial revisions for a robust analysis. K.S. aided in data acquisition and analysis and participated in drafting and revising the manuscript to include important intellectual content. M.R. focused on data analysis and interpretation, critically reviewing and revising the manuscript to ensure accuracy and integrity. All authors have approved the final manuscript for publication.

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Kumar, B., Voith, K., Sándor, K. et al. Educational paradigm shift: assessing the prospects of a master's course in green energy transition. Discov Sustain 5 , 247 (2024). https://doi.org/10.1007/s43621-024-00458-1

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