qualitative research sample example

18 Qualitative Research Examples

Qualitative research is an approach to scientific research that involves using observation to gather and analyze non-numerical, in-depth, and well-contextualized datasets.

It serves as an integral part of academic, professional, and even daily decision-making processes (Baxter & Jack, 2008).

Methods of qualitative research encompass a wide range of techniques, from in-depth personal encounters, like ethnographies (studying cultures in-depth) and autoethnographies (examining one’s own cultural experiences), to collection of diverse perspectives on topics through methods like interviewing focus groups (gatherings of individuals to discuss specific topics).

Qualitative Research Examples

1. ethnography.

Definition: Ethnography is a qualitative research design aimed at exploring cultural phenomena. Rooted in the discipline of anthropology , this research approach investigates the social interactions, behaviors, and perceptions within groups, communities, or organizations.

Ethnographic research is characterized by extended observation of the group, often through direct participation, in the participants’ environment. An ethnographer typically lives with the study group for extended periods, intricately observing their everyday lives (Khan, 2014).

It aims to present a complete, detailed and accurate picture of the observed social life, rituals, symbols, and values from the perspective of the study group.

Example of Ethnographic Research

Title: “ The Everyday Lives of Men: An Ethnographic Investigation of Young Adult Male Identity “

Citation: Evans, J. (2010). The Everyday Lives of Men: An Ethnographic Investigation of Young Adult Male Identity. Peter Lang.

Overview: This study by Evans (2010) provides a rich narrative of young adult male identity as experienced in everyday life. The author immersed himself among a group of young men, participating in their activities and cultivating a deep understanding of their lifestyle, values, and motivations. This research exemplified the ethnographic approach, revealing complexities of the subjects’ identities and societal roles, which could hardly be accessed through other qualitative research designs.

Read my Full Guide on Ethnography Here

2. Autoethnography

Definition: Autoethnography is an approach to qualitative research where the researcher uses their own personal experiences to extend the understanding of a certain group, culture, or setting. Essentially, it allows for the exploration of self within the context of social phenomena.

Unlike traditional ethnography, which focuses on the study of others, autoethnography turns the ethnographic gaze inward, allowing the researcher to use their personal experiences within a culture as rich qualitative data (Durham, 2019).

The objective is to critically appraise one’s personal experiences as they navigate and negotiate cultural, political, and social meanings. The researcher becomes both the observer and the participant, intertwining personal and cultural experiences in the research.

Example of Autoethnographic Research

Title: “ A Day In The Life Of An NHS Nurse “

Citation: Osben, J. (2019). A day in the life of a NHS nurse in 21st Century Britain: An auto-ethnography. The Journal of Autoethnography for Health & Social Care. 1(1).

Overview: This study presents an autoethnography of a day in the life of an NHS nurse (who, of course, is also the researcher). The author uses the research to achieve reflexivity, with the researcher concluding: “Scrutinising my practice and situating it within a wider contextual backdrop has compelled me to significantly increase my level of scrutiny into the driving forces that influence my practice.”

Read my Full Guide on Autoethnography Here

3. Semi-Structured Interviews

Definition: Semi-structured interviews stand as one of the most frequently used methods in qualitative research. These interviews are planned and utilize a set of pre-established questions, but also allow for the interviewer to steer the conversation in other directions based on the responses given by the interviewee.

In semi-structured interviews, the interviewer prepares a guide that outlines the focal points of the discussion. However, the interview is flexible, allowing for more in-depth probing if the interviewer deems it necessary (Qu, & Dumay, 2011). This style of interviewing strikes a balance between structured ones which might limit the discussion, and unstructured ones, which could lack focus.

Example of Semi-Structured Interview Research

Title: “ Factors influencing adherence to cancer treatment in older adults with cancer: a systematic review “

Citation: Puts, M., et al. (2014). Factors influencing adherence to cancer treatment in older adults with cancer: a systematic review. Annals of oncology, 25 (3), 564-577.

Overview: Puts et al. (2014) executed an extensive systematic review in which they conducted semi-structured interviews with older adults suffering from cancer to examine the factors influencing their adherence to cancer treatment. The findings suggested that various factors, including side effects, faith in healthcare professionals, and social support have substantial impacts on treatment adherence. This research demonstrates how semi-structured interviews can provide rich and profound insights into the subjective experiences of patients.

4. Focus Groups

Definition: Focus groups are a qualitative research method that involves organized discussion with a selected group of individuals to gain their perspectives on a specific concept, product, or phenomenon. Typically, these discussions are guided by a moderator.

During a focus group session, the moderator has a list of questions or topics to discuss, and participants are encouraged to interact with each other (Morgan, 2010). This interactivity can stimulate more information and provide a broader understanding of the issue under scrutiny. The open format allows participants to ask questions and respond freely, offering invaluable insights into attitudes, experiences, and group norms.

Example of Focus Group Research

Title: “ Perspectives of Older Adults on Aging Well: A Focus Group Study “

Citation: Halaweh, H., Dahlin-Ivanoff, S., Svantesson, U., & Willén, C. (2018). Perspectives of older adults on aging well: a focus group study. Journal of aging research .

Overview: This study aimed to explore what older adults (aged 60 years and older) perceived to be ‘aging well’. The researchers identified three major themes from their focus group interviews: a sense of well-being, having good physical health, and preserving good mental health. The findings highlight the importance of factors such as positive emotions, social engagement, physical activity, healthy eating habits, and maintaining independence in promoting aging well among older adults.

5. Phenomenology

Definition: Phenomenology, a qualitative research method, involves the examination of lived experiences to gain an in-depth understanding of the essence or underlying meanings of a phenomenon.

The focus of phenomenology lies in meticulously describing participants’ conscious experiences related to the chosen phenomenon (Padilla-Díaz, 2015).

In a phenomenological study, the researcher collects detailed, first-hand perspectives of the participants, typically via in-depth interviews, and then uses various strategies to interpret and structure these experiences, ultimately revealing essential themes (Creswell, 2013). This approach focuses on the perspective of individuals experiencing the phenomenon, seeking to explore, clarify, and understand the meanings they attach to those experiences.

Example of Phenomenology Research

Title: “ A phenomenological approach to experiences with technology: current state, promise, and future directions for research ”

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

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

6. Grounded Theory

Definition: Grounded theory is a systematic methodology in qualitative research that typically applies inductive reasoning . The primary aim is to develop a theoretical explanation or framework for a process, action, or interaction grounded in, and arising from, empirical data (Birks & Mills, 2015).

In grounded theory, data collection and analysis work together in a recursive process. The researcher collects data, analyses it, and then collects more data based on the evolving understanding of the research context. This ongoing process continues until a comprehensive theory that represents the data and the associated phenomenon emerges – a point known as theoretical saturation (Charmaz, 2014).

Example of Grounded Theory Research

Title: “ Student Engagement in High School Classrooms from the Perspective of Flow Theory “

Citation: Shernoff, D. J., Csikszentmihalyi, M., Shneider, B., & Shernoff, E. S. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychology Quarterly, 18 (2), 158–176.

Overview: Shernoff and colleagues (2003) used grounded theory to explore student engagement in high school classrooms. The researchers collected data through student self-reports, interviews, and observations. Key findings revealed that academic challenge, student autonomy, and teacher support emerged as the most significant factors influencing students’ engagement, demonstrating how grounded theory can illuminate complex dynamics within real-world contexts.

7. Narrative Research

Definition: Narrative research is a qualitative research method dedicated to storytelling and understanding how individuals experience the world. It focuses on studying an individual’s life and experiences as narrated by that individual (Polkinghorne, 2013).

In narrative research, the researcher collects data through methods such as interviews, observations , and document analysis. The emphasis is on the stories told by participants – narratives that reflect their experiences, thoughts, and feelings.

These stories are then interpreted by the researcher, who attempts to understand the meaning the participant attributes to these experiences (Josselson, 2011).

Example of Narrative Research

Title: “Narrative Structures and the Language of the Self”

Citation: McAdams, D. P., Josselson, R., & Lieblich, A. (2006). Identity and story: Creating self in narrative . American Psychological Association.

Overview: In this innovative study, McAdams et al. (2006) employed narrative research to explore how individuals construct their identities through the stories they tell about themselves. By examining personal narratives, the researchers discerned patterns associated with characters, motivations, conflicts, and resolutions, contributing valuable insights about the relationship between narrative and individual identity.

8. Case Study Research

Definition: Case study research is a qualitative research method that involves an in-depth investigation of a single instance or event: a case. These ‘cases’ can range from individuals, groups, or entities to specific projects, programs, or strategies (Creswell, 2013).

The case study method typically uses multiple sources of information for comprehensive contextual analysis. It aims to explore and understand the complexity and uniqueness of a particular case in a real-world context (Merriam & Tisdell, 2015). This investigation could result in a detailed description of the case, a process for its development, or an exploration of a related issue or problem.

Example of Case Study Research

Title: “ Teacher’s Role in Fostering Preschoolers’ Computational Thinking: An Exploratory Case Study “

Citation: Wang, X. C., Choi, Y., Benson, K., Eggleston, C., & Weber, D. (2021). Teacher’s role in fostering preschoolers’ computational thinking: An exploratory case study. Early Education and Development , 32 (1), 26-48.

Overview: This study investigates the role of teachers in promoting computational thinking skills in preschoolers. The study utilized a qualitative case study methodology to examine the computational thinking scaffolding strategies employed by a teacher interacting with three preschoolers in a small group setting. The findings highlight the importance of teachers’ guidance in fostering computational thinking practices such as problem reformulation/decomposition, systematic testing, and debugging.

Read about some Famous Case Studies in Psychology Here

9. Participant Observation

Definition: Participant observation has the researcher immerse themselves in a group or community setting to observe the behavior of its members. It is similar to ethnography, but generally, the researcher isn’t embedded for a long period of time.

The researcher, being a participant, engages in daily activities, interactions, and events as a way of conducting a detailed study of a particular social phenomenon (Kawulich, 2005).

The method involves long-term engagement in the field, maintaining detailed records of observed events, informal interviews, direct participation, and reflexivity. This approach allows for a holistic view of the participants’ lived experiences, behaviours, and interactions within their everyday environment (Dewalt, 2011).

Example of Participant Observation Research

Title: Conflict in the boardroom: a participant observation study of supervisory board dynamics

Citation: Heemskerk, E. M., Heemskerk, K., & Wats, M. M. (2017). Conflict in the boardroom: a participant observation study of supervisory board dynamics. Journal of Management & Governance , 21 , 233-263.

Overview: This study examined how conflicts within corporate boards affect their performance. The researchers used a participant observation method, where they actively engaged with 11 supervisory boards and observed their dynamics. They found that having a shared understanding of the board’s role called a common framework, improved performance by reducing relationship conflicts, encouraging task conflicts, and minimizing conflicts between the board and CEO.

10. Non-Participant Observation

Definition: Non-participant observation is a qualitative research method in which the researcher observes the phenomena of interest without actively participating in the situation, setting, or community being studied.

This method allows the researcher to maintain a position of distance, as they are solely an observer and not a participant in the activities being observed (Kawulich, 2005).

During non-participant observation, the researcher typically records field notes on the actions, interactions, and behaviors observed , focusing on specific aspects of the situation deemed relevant to the research question.

This could include verbal and nonverbal communication , activities, interactions, and environmental contexts (Angrosino, 2007). They could also use video or audio recordings or other methods to collect data.

Example of Non-Participant Observation Research

Title: Mental Health Nurses’ attitudes towards mental illness and recovery-oriented practice in acute inpatient psychiatric units: A non-participant observation study

Citation: Sreeram, A., Cross, W. M., & Townsin, L. (2023). Mental Health Nurses’ attitudes towards mental illness and recovery‐oriented practice in acute inpatient psychiatric units: A non‐participant observation study. International Journal of Mental Health Nursing .

Overview: This study investigated the attitudes of mental health nurses towards mental illness and recovery-oriented practice in acute inpatient psychiatric units. The researchers used a non-participant observation method, meaning they observed the nurses without directly participating in their activities. The findings shed light on the nurses’ perspectives and behaviors, providing valuable insights into their attitudes toward mental health and recovery-focused care in these settings.

11. Content Analysis

Definition: Content Analysis involves scrutinizing textual, visual, or spoken content to categorize and quantify information. The goal is to identify patterns, themes, biases, or other characteristics (Hsieh & Shannon, 2005).

Content Analysis is widely used in various disciplines for a multitude of purposes. Researchers typically use this method to distill large amounts of unstructured data, like interview transcripts, newspaper articles, or social media posts, into manageable and meaningful chunks.

When wielded appropriately, Content Analysis can illuminate the density and frequency of certain themes within a dataset, provide insights into how specific terms or concepts are applied contextually, and offer inferences about the meanings of their content and use (Duriau, Reger, & Pfarrer, 2007).

Example of Content Analysis

Title: Framing European politics: A content analysis of press and television news .

Citation: Semetko, H. A., & Valkenburg, P. M. (2000). Framing European politics: A content analysis of press and television news. Journal of Communication, 50 (2), 93-109.

Overview: This study analyzed press and television news articles about European politics using a method called content analysis. The researchers examined the prevalence of different “frames” in the news, which are ways of presenting information to shape audience perceptions. They found that the most common frames were attribution of responsibility, conflict, economic consequences, human interest, and morality.

Read my Full Guide on Content Analysis Here

12. Discourse Analysis

Definition: Discourse Analysis, a qualitative research method, interprets the meanings, functions, and coherence of certain languages in context.

Discourse analysis is typically understood through social constructionism, critical theory , and poststructuralism and used for understanding how language constructs social concepts (Cheek, 2004).

Discourse Analysis offers great breadth, providing tools to examine spoken or written language, often beyond the level of the sentence. It enables researchers to scrutinize how text and talk articulate social and political interactions and hierarchies.

Insight can be garnered from different conversations, institutional text, and media coverage to understand how topics are addressed or framed within a specific social context (Jorgensen & Phillips, 2002).

Example of Discourse Analysis

Title: The construction of teacher identities in educational policy documents: A critical discourse analysis

Citation: Thomas, S. (2005). The construction of teacher identities in educational policy documents: A critical discourse analysis. Critical Studies in Education, 46 (2), 25-44.

Overview: The author examines how an education policy in one state of Australia positions teacher professionalism and teacher identities. While there are competing discourses about professional identity, the policy framework privileges a  narrative that frames the ‘good’ teacher as one that accepts ever-tightening control and regulation over their professional practice.

Read my Full Guide on Discourse Analysis Here

13. Action Research

Definition: Action Research is a qualitative research technique that is employed to bring about change while simultaneously studying the process and results of that change.

This method involves a cyclical process of fact-finding, action, evaluation, and reflection (Greenwood & Levin, 2016).

Typically, Action Research is used in the fields of education, social sciences , and community development. The process isn’t just about resolving an issue but also developing knowledge that can be used in the future to address similar or related problems.

The researcher plays an active role in the research process, which is normally broken down into four steps: 

• developing a plan to improve what is currently being done
• implementing the plan
• observing the effects of the plan, and
• reflecting upon these effects (Smith, 2010).

Example of Action Research

Title: Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing

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

Overview: This was a research study one of my research students completed in his own classroom under my supervision. He implemented a digital game-based approach to literacy teaching with boys and interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience.

Read my Full Guide on Action Research Here

14. Semiotic Analysis

Definition: Semiotic Analysis is a qualitative method of research that interprets signs and symbols in communication to understand sociocultural phenomena. It stems from semiotics, the study of signs and symbols and their use or interpretation (Chandler, 2017).

In a Semiotic Analysis, signs (anything that represents something else) are interpreted based on their significance and the role they play in representing ideas.

This type of research often involves the examination of images, sounds, and word choice to uncover the embedded sociocultural meanings. For example, an advertisement for a car might be studied to learn more about societal views on masculinity or success (Berger, 2010).

Example of Semiotic Research

Title: Shielding the learned body: a semiotic analysis of school badges in New South Wales, Australia

Citation: Symes, C. (2023). Shielding the learned body: a semiotic analysis of school badges in New South Wales, Australia. Semiotica , 2023 (250), 167-190.

Overview: This study examines school badges in New South Wales, Australia, and explores their significance through a semiotic analysis. The badges, which are part of the school’s visual identity, are seen as symbolic representations that convey meanings. The analysis reveals that these badges often draw on heraldic models, incorporating elements like colors, names, motifs, and mottoes that reflect local culture and history, thus connecting students to their national identity. Additionally, the study highlights how some schools have shifted from traditional badges to modern logos and slogans, reflecting a more business-oriented approach.

15. Qualitative Longitudinal Studies

Definition: Qualitative Longitudinal Studies are a research method that involves repeated observation of the same items over an extended period of time.

Unlike a snapshot perspective, this method aims to piece together individual histories and examine the influences and impacts of change (Neale, 2019).

Qualitative Longitudinal Studies provide an in-depth understanding of change as it happens, including changes in people’s lives, their perceptions, and their behaviors.

For instance, this method could be used to follow a group of students through their schooling years to understand the evolution of their learning behaviors and attitudes towards education (Saldaña, 2003).

Example of Qualitative Longitudinal Research

Title: Patient and caregiver perspectives on managing pain in advanced cancer: a qualitative longitudinal study

Citation: Hackett, J., Godfrey, M., & Bennett, M. I. (2016). Patient and caregiver perspectives on managing pain in advanced cancer: a qualitative longitudinal study.  Palliative medicine ,  30 (8), 711-719.

Overview: This article examines how patients and their caregivers manage pain in advanced cancer through a qualitative longitudinal study. The researchers interviewed patients and caregivers at two different time points and collected audio diaries to gain insights into their experiences, making this study longitudinal.

Read my Full Guide on Longitudinal Research Here

16. Open-Ended Surveys

Definition: Open-Ended Surveys are a type of qualitative research method where respondents provide answers in their own words. Unlike closed-ended surveys, which limit responses to predefined options, open-ended surveys allow for expansive and unsolicited explanations (Fink, 2013).

Open-ended surveys are commonly used in a range of fields, from market research to social studies. As they don’t force respondents into predefined response categories, these surveys help to draw out rich, detailed data that might uncover new variables or ideas.

For example, an open-ended survey might be used to understand customer opinions about a new product or service (Lavrakas, 2008).

Contrast this to a quantitative closed-ended survey, like a Likert scale, which could theoretically help us to come up with generalizable data but is restricted by the questions on the questionnaire, meaning new and surprising data and insights can’t emerge from the survey results in the same way.

Example of Open-Ended Survey Research

Title: Advantages and disadvantages of technology in relationships: Findings from an open-ended survey

Citation: Hertlein, K. M., & Ancheta, K. (2014). Advantages and disadvantages of technology in relationships: Findings from an open-ended survey.  The Qualitative Report ,  19 (11), 1-11.

Overview: This article examines the advantages and disadvantages of technology in couple relationships through an open-ended survey method. Researchers analyzed responses from 410 undergraduate students to understand how technology affects relationships. They found that technology can contribute to relationship development, management, and enhancement, but it can also create challenges such as distancing, lack of clarity, and impaired trust.

17. Naturalistic Observation

Definition: Naturalistic Observation is a type of qualitative research method that involves observing individuals in their natural environments without interference or manipulation by the researcher.

Naturalistic observation is often used when conducting research on behaviors that cannot be controlled or manipulated in a laboratory setting (Kawulich, 2005).

It is frequently used in the fields of psychology, sociology, and anthropology. For instance, to understand the social dynamics in a schoolyard, a researcher could spend time observing the children interact during their recess, noting their behaviors, interactions, and conflicts without imposing their presence on the children’s activities (Forsyth, 2010).

Example of Naturalistic Observation Research

Title: Dispositional mindfulness in daily life: A naturalistic observation study

Citation: Kaplan, D. M., Raison, C. L., Milek, A., Tackman, A. M., Pace, T. W., & Mehl, M. R. (2018). Dispositional mindfulness in daily life: A naturalistic observation study. PloS one , 13 (11), e0206029.

Overview: In this study, researchers conducted two studies: one exploring assumptions about mindfulness and behavior, and the other using naturalistic observation to examine actual behavioral manifestations of mindfulness. They found that trait mindfulness is associated with a heightened perceptual focus in conversations, suggesting that being mindful is expressed primarily through sharpened attention rather than observable behavioral or social differences.

Read my Full Guide on Naturalistic Observation Here

18. Photo-Elicitation

Definition: Photo-elicitation utilizes photographs as a means to trigger discussions and evoke responses during interviews. This strategy aids in bringing out topics of discussion that may not emerge through verbal prompting alone (Harper, 2002).

Traditionally, Photo-Elicitation has been useful in various fields such as education, psychology, and sociology. The method involves the researcher or participants taking photographs, which are then used as prompts for discussion.

For instance, a researcher studying urban environmental issues might invite participants to photograph areas in their neighborhood that they perceive as environmentally detrimental, and then discuss each photo in depth (Clark-Ibáñez, 2004).

Example of Photo-Elicitation Research

Title: Early adolescent food routines: A photo-elicitation study

Citation: Green, E. M., Spivak, C., & Dollahite, J. S. (2021). Early adolescent food routines: A photo-elicitation study. Appetite, 158 .

Overview: This study focused on early adolescents (ages 10-14) and their food routines. Researchers conducted in-depth interviews using a photo-elicitation approach, where participants took photos related to their food choices and experiences. Through analysis, the study identified various routines and three main themes: family, settings, and meals/foods consumed, revealing how early adolescents view and are influenced by their eating routines.

Features of Qualitative Research

Qualitative research is a research method focused on understanding the meaning individuals or groups attribute to a social or human problem (Creswell, 2013).

Some key features of this method include:

• Naturalistic Inquiry: Qualitative research happens in the natural setting of the phenomena, aiming to understand “real world” situations (Patton, 2015). This immersion in the field or subject allows the researcher to gather a deep understanding of the subject matter.
• Emphasis on Process: It aims to understand how events unfold over time rather than focusing solely on outcomes (Merriam & Tisdell, 2015). The process-oriented nature of qualitative research allows researchers to investigate sequences, timing, and changes.
• Interpretive: It involves interpreting and making sense of phenomena in terms of the meanings people assign to them (Denzin & Lincoln, 2011). This interpretive element allows for rich, nuanced insights into human behavior and experiences.
• Holistic Perspective: Qualitative research seeks to understand the whole phenomenon rather than focusing on individual components (Creswell, 2013). It emphasizes the complex interplay of factors, providing a richer, more nuanced view of the research subject.
• Prioritizes Depth over Breadth: Qualitative research favors depth of understanding over breadth, typically involving a smaller but more focused sample size (Hennink, Hutter, & Bailey, 2020). This enables detailed exploration of the phenomena of interest, often leading to rich and complex data.

Qualitative vs Quantitative Research

Qualitative research centers on exploring and understanding the meaning individuals or groups attribute to a social or human problem (Creswell, 2013).

It involves an in-depth approach to the subject matter, aiming to capture the richness and complexity of human experience.

Examples include conducting interviews, observing behaviors, or analyzing text and images.

There are strengths inherent in this approach. In its focus on understanding subjective experiences and interpretations, qualitative research can yield rich and detailed data that quantitative research may overlook (Denzin & Lincoln, 2011).

Additionally, qualitative research is adaptive, allowing the researcher to respond to new directions and insights as they emerge during the research process.

However, there are also limitations. Because of the interpretive nature of this research, findings may not be generalizable to a broader population (Marshall & Rossman, 2014). Well-designed quantitative research, on the other hand, can be generalizable.

Moreover, the reliability and validity of qualitative data can be challenging to establish due to its subjective nature, unlike quantitative research, which is ideally more objective.

Compare Qualitative and Quantitative Research Methodologies in This Guide Here

In conclusion, qualitative research methods provide distinctive ways to explore social phenomena and understand nuances that quantitative approaches might overlook. Each method, from Ethnography to Photo-Elicitation, presents its strengths and weaknesses but they all offer valuable means of investigating complex, real-world situations. The goal for the researcher is not to find a definitive tool, but to employ the method best suited for their research questions and the context at hand (Almalki, 2016). Above all, these methods underscore the richness of human experience and deepen our understanding of the world around us.

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Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ What are Pedagogical Skills? - 15 Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 44 Maslow’s Hierarchy of Needs Examples
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ Bronfenbrenner's Ecological Systems Theory (Pros & Cons)
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ Social Exchange Theory: Definition and Examples

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Chapter 5. Sampling

Introduction.

Most Americans will experience unemployment at some point in their lives. Sarah Damaske ( 2021 ) was interested in learning about how men and women experience unemployment differently. To answer this question, she interviewed unemployed people. After conducting a “pilot study” with twenty interviewees, she realized she was also interested in finding out how working-class and middle-class persons experienced unemployment differently. She found one hundred persons through local unemployment offices. She purposefully selected a roughly equal number of men and women and working-class and middle-class persons for the study. This would allow her to make the kinds of comparisons she was interested in. She further refined her selection of persons to interview:

I decided that I needed to be able to focus my attention on gender and class; therefore, I interviewed only people born between 1962 and 1987 (ages 28–52, the prime working and child-rearing years), those who worked full-time before their job loss, those who experienced an involuntary job loss during the past year, and those who did not lose a job for cause (e.g., were not fired because of their behavior at work). ( 244 )

The people she ultimately interviewed compose her sample. They represent (“sample”) the larger population of the involuntarily unemployed. This “theoretically informed stratified sampling design” allowed Damaske “to achieve relatively equal distribution of participation across gender and class,” but it came with some limitations. For one, the unemployment centers were located in primarily White areas of the country, so there were very few persons of color interviewed. Qualitative researchers must make these kinds of decisions all the time—who to include and who not to include. There is never an absolutely correct decision, as the choice is linked to the particular research question posed by the particular researcher, although some sampling choices are more compelling than others. In this case, Damaske made the choice to foreground both gender and class rather than compare all middle-class men and women or women of color from different class positions or just talk to White men. She leaves the door open for other researchers to sample differently. Because science is a collective enterprise, it is most likely someone will be inspired to conduct a similar study as Damaske’s but with an entirely different sample.

This chapter is all about sampling. After you have developed a research question and have a general idea of how you will collect data (observations or 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. You might remember studying sampling in a quantitative research course. Sampling is important here too, but it works a bit differently. Unlike quantitative research, qualitative research involves nonprobability sampling. This chapter explains why this is so and what qualities instead make a good sample for qualitative research.

Quick Terms Refresher

• The population is the entire group that you want to draw conclusions about.
• The sample is the specific group of individuals that you will collect data from.
• Sampling frame is the actual list of individuals that the sample will be drawn from. Ideally, it should include the entire target population (and nobody who is not part of that population).
• Sample size is how many individuals (or units) are included in your sample.

The “Who” of Your Research Study

After you have turned your general research interest into an actual research question and identified an approach you want to take to answer that question, you will need to specify the people you will be interviewing or observing. In most qualitative research, the objects of your study will indeed be people. In some cases, however, your objects might be content left by people (e.g., diaries, yearbooks, photographs) or documents (official or unofficial) or even institutions (e.g., schools, medical centers) and locations (e.g., nation-states, cities). Chances are, whatever “people, places, or things” are the objects of your study, you will not really be able to talk to, observe, or follow every single individual/object of the entire population of interest. You will need to create a sample of the population . Sampling in qualitative research has different purposes and goals than sampling in quantitative research. Sampling in both allows you to say something of interest about a population without having to include the entire population in your sample.

We begin this chapter with the case of a population of interest composed of actual people. After we have a better understanding of populations and samples that involve real people, we’ll discuss sampling in other types of qualitative research, such as archival research, content analysis, and case studies. We’ll then move to a larger discussion about the difference between sampling in qualitative research generally versus quantitative research, then we’ll move on to the idea of “theoretical” generalizability, and finally, we’ll conclude with some practical tips on the correct “number” to include in one’s sample.

Sampling People

To help think through samples, let’s imagine we want to know more about “vaccine hesitancy.” We’ve all lived through 2020 and 2021, and we know that a sizable number of people in the United States (and elsewhere) were slow to accept vaccines, even when these were freely available. By some accounts, about one-third of Americans initially refused vaccination. Why is this so? Well, as I write this in the summer of 2021, we know that some people actively refused the vaccination, thinking it was harmful or part of a government plot. Others were simply lazy or dismissed the necessity. And still others were worried about harmful side effects. The general population of interest here (all adult Americans who were not vaccinated by August 2021) may be as many as eighty million people. We clearly cannot talk to all of them. So we will have to narrow the number to something manageable. How can we do this?

First, we have to think about our actual research question and the form of research we are conducting. I am going to begin with a quantitative research question. Quantitative research questions tend to be simpler to visualize, at least when we are first starting out doing social science research. So let us say we want to know what percentage of each kind of resistance is out there and how race or class or gender affects vaccine hesitancy. Again, we don’t have the ability to talk to everyone. But harnessing what we know about normal probability distributions (see quantitative methods for more on this), we can find this out through a sample that represents the general population. We can’t really address these particular questions if we only talk to White women who go to college with us. And if you are really trying to generalize the specific findings of your sample to the larger population, you will have to employ probability sampling , a sampling technique where a researcher sets a selection of a few criteria and chooses members of a population randomly. Why randomly? If truly random, all the members have an equal opportunity to be a part of the sample, and thus we avoid the problem of having only our friends and neighbors (who may be very different from other people in the population) in the study. Mathematically, there is going to be a certain number that will be large enough to allow us to generalize our particular findings from our sample population to the population at large. It might surprise you how small that number can be. Election polls of no more than one thousand people are routinely used to predict actual election outcomes of millions of people. Below that number, however, you will not be able to make generalizations. Talking to five people at random is simply not enough people to predict a presidential election.

In order to answer quantitative research questions of causality, one must employ probability sampling. Quantitative researchers try to generalize their findings to a larger population. Samples are designed with that in mind. Qualitative researchers ask very different questions, though. Qualitative research questions are not about “how many” of a certain group do X (in this case, what percentage of the unvaccinated hesitate for concern about safety rather than reject vaccination on political grounds). Qualitative research employs nonprobability sampling . By definition, not everyone has an equal opportunity to be included in the sample. The researcher might select White women they go to college with to provide insight into racial and gender dynamics at play. Whatever is found by doing so will not be generalizable to everyone who has not been vaccinated, or even all White women who have not been vaccinated, or even all White women who have not been vaccinated who are in this particular college. That is not the point of qualitative research at all. This is a really important distinction, so I will repeat in bold: Qualitative researchers are not trying to statistically generalize specific findings to a larger population . They have not failed when their sample cannot be generalized, as that is not the point at all.

In the previous paragraph, I said it would be perfectly acceptable for a qualitative researcher to interview five White women with whom she goes to college about their vaccine hesitancy “to provide insight into racial and gender dynamics at play.” The key word here is “insight.” Rather than use a sample as a stand-in for the general population, as quantitative researchers do, the qualitative researcher uses the sample to gain insight into a process or phenomenon. The qualitative researcher is not going to be content with simply asking each of the women to state her reason for not being vaccinated and then draw conclusions that, because one in five of these women were concerned about their health, one in five of all people were also concerned about their health. That would be, frankly, a very poor study indeed. Rather, the qualitative researcher might sit down with each of the women and conduct a lengthy interview about what the vaccine means to her, why she is hesitant, how she manages her hesitancy (how she explains it to her friends), what she thinks about others who are unvaccinated, what she thinks of those who have been vaccinated, and what she knows or thinks she knows about COVID-19. The researcher might include specific interview questions about the college context, about their status as White women, about the political beliefs they hold about racism in the US, and about how their own political affiliations may or may not provide narrative scripts about “protective whiteness.” There are many interesting things to ask and learn about and many things to discover. Where a quantitative researcher begins with clear parameters to set their population and guide their sample selection process, the qualitative researcher is discovering new parameters, making it impossible to engage in probability sampling.

Looking at it this way, sampling for qualitative researchers needs to be more strategic. More theoretically informed. What persons can be interviewed or observed that would provide maximum insight into what is still unknown? In other words, qualitative researchers think through what cases they could learn the most from, and those are the cases selected to study: “What would be ‘bias’ in statistical sampling, and therefore a weakness, becomes intended focus in qualitative sampling, and therefore a strength. The logic and power of purposeful sampling like in selecting information-rich cases for study in depth. Information-rich cases are those from which one can learn a great deal about issues of central importance to the purpose of the inquiry, thus the term purposeful sampling” ( Patton 2002:230 ; emphases in the original).

Before selecting your sample, though, it is important to clearly identify the general population of interest. You need to know this before you can determine the sample. In our example case, it is “adult Americans who have not yet been vaccinated.” Depending on the specific qualitative research question, however, it might be “adult Americans who have been vaccinated for political reasons” or even “college students who have not been vaccinated.” What insights are you seeking? Do you want to know how politics is affecting vaccination? Or do you want to understand how people manage being an outlier in a particular setting (unvaccinated where vaccinations are heavily encouraged if not required)? More clearly stated, your population should align with your research question . Think back to the opening story about Damaske’s work studying the unemployed. She drew her sample narrowly to address the particular questions she was interested in pursuing. Knowing your questions or, at a minimum, why you are interested in the topic will allow you to draw the best sample possible to achieve insight.

Once you have your population in mind, how do you go about getting people to agree to be in your sample? In qualitative research, it is permissible to find people by convenience. Just ask for people who fit your sample criteria and see who shows up. Or reach out to friends and colleagues and see if they know anyone that fits. Don’t let the name convenience sampling mislead you; this is not exactly “easy,” and it is certainly a valid form of sampling in qualitative research. The more unknowns you have about what you will find, the more convenience sampling makes sense. If you don’t know how race or class or political affiliation might matter, and your population is unvaccinated college students, you can construct a sample of college students by placing an advertisement in the student paper or posting a flyer on a notice board. Whoever answers is your sample. That is what is meant by a convenience sample. A common variation of convenience sampling is snowball sampling . This is particularly useful if your target population is hard to find. Let’s say you posted a flyer about your study and only two college students responded. You could then ask those two students for referrals. They tell their friends, and those friends tell other friends, and, like a snowball, your sample gets bigger and bigger.

Researcher Note

Gaining Access: When Your Friend Is Your Research Subject

My early experience with qualitative research was rather unique. At that time, I needed to do a project that required me to interview first-generation college students, and my friends, with whom I had been sharing a dorm for two years, just perfectly fell into the sample category. Thus, I just asked them and easily “gained my access” to the research subject; I know them, we are friends, and I am part of them. I am an insider. I also thought, “Well, since I am part of the group, I can easily understand their language and norms, I can capture their honesty, read their nonverbal cues well, will get more information, as they will be more opened to me because they trust me.” All in all, easy access with rich information. But, gosh, I did not realize that my status as an insider came with a price! When structuring the interview questions, I began to realize that rather than focusing on the unique experiences of my friends, I mostly based the questions on my own experiences, assuming we have similar if not the same experiences. I began to struggle with my objectivity and even questioned my role; am I doing this as part of the group or as a researcher? I came to know later that my status as an insider or my “positionality” may impact my research. It not only shapes the process of data collection but might heavily influence my interpretation of the data. I came to realize that although my inside status came with a lot of benefits (especially for access), it could also bring some drawbacks.

—Dede Setiono, PhD student focusing on international development and environmental policy, Oregon State University

The more you know about what you might find, the more strategic you can be. If you wanted to compare how politically conservative and politically liberal college students explained their vaccine hesitancy, for example, you might construct a sample purposively, finding an equal number of both types of students so that you can make those comparisons in your analysis. This is what Damaske ( 2021 ) did. You could still use convenience or snowball sampling as a way of recruitment. Post a flyer at the conservative student club and then ask for referrals from the one student that agrees to be interviewed. As with convenience sampling, there are variations of purposive sampling as well as other names used (e.g., judgment, quota, stratified, criterion, theoretical). Try not to get bogged down in the nomenclature; instead, focus on identifying the general population that matches your research question and then using a sampling method that is most likely to provide insight, given the types of questions you have.

There are all kinds of ways of being strategic with sampling in qualitative research. Here are a few of my favorite techniques for maximizing insight:

• Consider using “extreme” or “deviant” cases. Maybe your college houses a prominent anti-vaxxer who has written about and demonstrated against the college’s policy on vaccines. You could learn a lot from that single case (depending on your research question, of course).
• Consider “intensity”: people and cases and circumstances where your questions are more likely to feature prominently (but not extremely or deviantly). For example, you could compare those who volunteer at local Republican and Democratic election headquarters during an election season in a study on why party matters. Those who volunteer are more likely to have something to say than those who are more apathetic.
• Maximize variation, as with the case of “politically liberal” versus “politically conservative,” or include an array of social locations (young vs. old; Northwest vs. Southeast region). This kind of heterogeneity sampling can capture and describe the central themes that cut across the variations: any common patterns that emerge, even in this wildly mismatched sample, are probably important to note!
• Rather than maximize the variation, you could select a small homogenous sample to describe some particular subgroup in depth. Focus groups are often the best form of data collection for homogeneity sampling.
• Think about which cases are “critical” or politically important—ones that “if it happens here, it would happen anywhere” or a case that is politically sensitive, as with the single “blue” (Democratic) county in a “red” (Republican) state. In both, you are choosing a site that would yield the most information and have the greatest impact on the development of knowledge.
• On the other hand, sometimes you want to select the “typical”—the typical college student, for example. You are trying to not generalize from the typical but illustrate aspects that may be typical of this case or group. When selecting for typicality, be clear with yourself about why the typical matches your research questions (and who might be excluded or marginalized in doing so).
• Finally, it is often a good idea to look for disconfirming cases : if you are at the stage where you have a hypothesis (of sorts), you might select those who do not fit your hypothesis—you will surely learn something important there. They may be “exceptions that prove the rule” or exceptions that force you to alter your findings in order to make sense of these additional cases.

In addition to all these sampling variations, there is the theoretical approach taken by grounded theorists in which the researcher samples comparative people (or events) on the basis of their potential to represent important theoretical constructs. The sample, one can say, is by definition representative of the phenomenon of interest. It accompanies the constant comparative method of analysis. In the words of the funders of Grounded Theory , “Theoretical sampling is sampling on the basis of the emerging concepts, with the aim being to explore the dimensional range or varied conditions along which the properties of the concepts vary” ( Strauss and Corbin 1998:73 ).

When Your Population is Not Composed of People

I think it is easiest for most people to think of populations and samples in terms of people, but sometimes our units of analysis are not actually people. They could be places or institutions. Even so, you might still want to talk to people or observe the actions of people to understand those places or institutions. Or not! In the case of content analyses (see chapter 17), you won’t even have people involved at all but rather documents or films or photographs or news clippings. Everything we have covered about sampling applies to other units of analysis too. Let’s work through some examples.

Case Studies

When constructing a case study, it is helpful to think of your cases as sample populations in the same way that we considered people above. If, for example, you are comparing campus climates for diversity, your overall population may be “four-year college campuses in the US,” and from there you might decide to study three college campuses as your sample. Which three? Will you use purposeful sampling (perhaps [1] selecting three colleges in Oregon that are different sizes or [2] selecting three colleges across the US located in different political cultures or [3] varying the three colleges by racial makeup of the student body)? Or will you select three colleges at random, out of convenience? There are justifiable reasons for all approaches.

As with people, there are different ways of maximizing insight in your sample selection. Think about the following rationales: typical, diverse, extreme, deviant, influential, crucial, or even embodying a particular “pathway” ( Gerring 2008 ). When choosing a case or particular research site, Rubin ( 2021 ) suggests you bear in mind, first, what you are leaving out by selecting this particular case/site; second, what you might be overemphasizing by studying this case/site and not another; and, finally, whether you truly need to worry about either of those things—“that is, what are the sources of bias and how bad are they for what you are trying to do?” ( 89 ).

Once you have selected your cases, you may still want to include interviews with specific people or observations at particular sites within those cases. Then you go through possible sampling approaches all over again to determine which people will be contacted.

Content: Documents, Narrative Accounts, And So On

Although not often discussed as sampling, your selection of documents and other units to use in various content/historical analyses is subject to similar considerations. When you are asking quantitative-type questions (percentages and proportionalities of a general population), you will want to follow probabilistic sampling. For example, I created a random sample of accounts posted on the website studentloanjustice.org to delineate the types of problems people were having with student debt ( Hurst 2007 ). Even though my data was qualitative (narratives of student debt), I was actually asking a quantitative-type research question, so it was important that my sample was representative of the larger population (debtors who posted on the website). On the other hand, when you are asking qualitative-type questions, the selection process should be very different. In that case, use nonprobabilistic techniques, either convenience (where you are really new to this data and do not have the ability to set comparative criteria or even know what a deviant case would be) or some variant of purposive sampling. Let’s say you were interested in the visual representation of women in media published in the 1950s. You could select a national magazine like Time for a “typical” representation (and for its convenience, as all issues are freely available on the web and easy to search). Or you could compare one magazine known for its feminist content versus one antifeminist. The point is, sample selection is important even when you are not interviewing or observing people.

Goals of Qualitative Sampling versus Goals of Quantitative Sampling

We have already discussed some of the differences in the goals of quantitative and qualitative sampling above, but it is worth further discussion. The quantitative researcher seeks a sample that is representative of the population of interest so that they may properly generalize the results (e.g., if 80 percent of first-gen students in the sample were concerned with costs of college, then we can say there is a strong likelihood that 80 percent of first-gen students nationally are concerned with costs of college). The qualitative researcher does not seek to generalize in this way . They may want a representative sample because they are interested in typical responses or behaviors of the population of interest, but they may very well not want a representative sample at all. They might want an “extreme” or deviant case to highlight what could go wrong with a particular situation, or maybe they want to examine just one case as a way of understanding what elements might be of interest in further research. When thinking of your sample, you will have to know why you are selecting the units, and this relates back to your research question or sets of questions. It has nothing to do with having a representative sample to generalize results. You may be tempted—or it may be suggested to you by a quantitatively minded member of your committee—to create as large and representative a sample as you possibly can to earn credibility from quantitative researchers. Ignore this temptation or suggestion. The only thing you should be considering is what sample will best bring insight into the questions guiding your research. This has implications for the number of people (or units) in your study as well, which is the topic of the next section.

What is the Correct “Number” to Sample?

Because we are not trying to create a generalizable representative sample, the guidelines for the “number” of people to interview or news stories to code are also a bit more nebulous. There are some brilliant insightful studies out there with an n of 1 (meaning one person or one account used as the entire set of data). This is particularly so in the case of autoethnography, a variation of ethnographic research that uses the researcher’s own subject position and experiences as the basis of data collection and analysis. But it is true for all forms of qualitative research. There are no hard-and-fast rules here. The number to include is what is relevant and insightful to your particular study.

That said, humans do not thrive well under such ambiguity, and there are a few helpful suggestions that can be made. First, many qualitative researchers talk about “saturation” as the end point for data collection. You stop adding participants when you are no longer getting any new information (or so very little that the cost of adding another interview subject or spending another day in the field exceeds any likely benefits to the research). The term saturation was first used here by Glaser and Strauss ( 1967 ), the founders of Grounded Theory. Here is their explanation: “The criterion for judging when to stop sampling the different groups pertinent to a category is the category’s theoretical saturation . Saturation means that no additional data are being found whereby the sociologist can develop properties of the category. As he [or she] sees similar instances over and over again, the researcher becomes empirically confident that a category is saturated. [They go] out of [their] way to look for groups that stretch diversity of data as far as possible, just to make certain that saturation is based on the widest possible range of data on the category” ( 61 ).

It makes sense that the term was developed by grounded theorists, since this approach is rather more open-ended than other approaches used by qualitative researchers. With so much left open, having a guideline of “stop collecting data when you don’t find anything new” is reasonable. However, saturation can’t help much when first setting out your sample. How do you know how many people to contact to interview? What number will you put down in your institutional review board (IRB) protocol (see chapter 8)? You may guess how many people or units it will take to reach saturation, but there really is no way to know in advance. The best you can do is think about your population and your questions and look at what others have done with similar populations and questions.

Here are some suggestions to use as a starting point: For phenomenological studies, try to interview at least ten people for each major category or group of people . If you are comparing male-identified, female-identified, and gender-neutral college students in a study on gender regimes in social clubs, that means you might want to design a sample of thirty students, ten from each group. This is the minimum suggested number. Damaske’s ( 2021 ) sample of one hundred allows room for up to twenty-five participants in each of four “buckets” (e.g., working-class*female, working-class*male, middle-class*female, middle-class*male). If there is more than one comparative group (e.g., you are comparing students attending three different colleges, and you are comparing White and Black students in each), you can sometimes reduce the number for each group in your sample to five for, in this case, thirty total students. But that is really a bare minimum you will want to go. A lot of people will not trust you with only “five” cases in a bucket. Lareau ( 2021:24 ) advises a minimum of seven or nine for each bucket (or “cell,” in her words). The point is to think about what your analyses might look like and how comfortable you will be with a certain number of persons fitting each category.

Because qualitative research takes so much time and effort, it is rare for a beginning researcher to include more than thirty to fifty people or units in the study. You may not be able to conduct all the comparisons you might want simply because you cannot manage a larger sample. In that case, the limits of who you can reach or what you can include may influence you to rethink an original overcomplicated research design. Rather than include students from every racial group on a campus, for example, you might want to sample strategically, thinking about the most contrast (insightful), possibly excluding majority-race (White) students entirely, and simply using previous literature to fill in gaps in our understanding. For example, one of my former students was interested in discovering how race and class worked at a predominantly White institution (PWI). Due to time constraints, she simplified her study from an original sample frame of middle-class and working-class domestic Black and international African students (four buckets) to a sample frame of domestic Black and international African students (two buckets), allowing the complexities of class to come through individual accounts rather than from part of the sample frame. She wisely decided not to include White students in the sample, as her focus was on how minoritized students navigated the PWI. She was able to successfully complete her project and develop insights from the data with fewer than twenty interviewees. [1]

But what if you had unlimited time and resources? Would it always be better to interview more people or include more accounts, documents, and units of analysis? No! Your sample size should reflect your research question and the goals you have set yourself. Larger numbers can sometimes work against your goals. If, for example, you want to help bring out individual stories of success against the odds, adding more people to the analysis can end up drowning out those individual stories. Sometimes, the perfect size really is one (or three, or five). It really depends on what you are trying to discover and achieve in your study. Furthermore, studies of one hundred or more (people, documents, accounts, etc.) can sometimes be mistaken for quantitative research. Inevitably, the large sample size will push the researcher into simplifying the data numerically. And readers will begin to expect generalizability from such a large sample.

To summarize, “There are no rules for sample size in qualitative inquiry. Sample size depends on what you want to know, the purpose of the inquiry, what’s at stake, what will be useful, what will have credibility, and what can be done with available time and resources” ( Patton 2002:244 ).

How did you find/construct a sample?

Since qualitative researchers work with comparatively small sample sizes, getting your sample right is rather important. Yet it is also difficult to accomplish. For instance, a key question you need to ask yourself is whether you want a homogeneous or heterogeneous sample. In other words, do you want to include people in your study who are by and large the same, or do you want to have diversity in your sample?

For many years, I have studied the experiences of students who were the first in their families to attend university. There is a rather large number of sampling decisions I need to consider before starting the study. (1) Should I only talk to first-in-family students, or should I have a comparison group of students who are not first-in-family? (2) Do I need to strive for a gender distribution that matches undergraduate enrollment patterns? (3) Should I include participants that reflect diversity in gender identity and sexuality? (4) How about racial diversity? First-in-family status is strongly related to some ethnic or racial identity. (5) And how about areas of study?

As you can see, if I wanted to accommodate all these differences and get enough study participants in each category, I would quickly end up with a sample size of hundreds, which is not feasible in most qualitative research. In the end, for me, the most important decision was to maximize the voices of first-in-family students, which meant that I only included them in my sample. As for the other categories, I figured it was going to be hard enough to find first-in-family students, so I started recruiting with an open mind and an understanding that I may have to accept a lack of gender, sexuality, or racial diversity and then not be able to say anything about these issues. But I would definitely be able to speak about the experiences of being first-in-family.

—Wolfgang Lehmann, author of “Habitus Transformation and Hidden Injuries”

Examples of “Sample” Sections in Journal Articles

Think about some of the studies you have read in college, especially those with rich stories and accounts about people’s lives. Do you know how the people were selected to be the focus of those stories? If the account was published by an academic press (e.g., University of California Press or Princeton University Press) or in an academic journal, chances are that the author included a description of their sample selection. You can usually find these in a methodological appendix (book) or a section on “research methods” (article).

Here are two examples from recent books and one example from a recent article:

Example 1 . In It’s Not like I’m Poor: How Working Families Make Ends Meet in a Post-welfare World , the research team employed a mixed methods approach to understand how parents use the earned income tax credit, a refundable tax credit designed to provide relief for low- to moderate-income working people ( Halpern-Meekin et al. 2015 ). At the end of their book, their first appendix is “Introduction to Boston and the Research Project.” After describing the context of the study, they include the following description of their sample selection:

In June 2007, we drew 120 names at random from the roughly 332 surveys we gathered between February and April. Within each racial and ethnic group, we aimed for one-third married couples with children and two-thirds unmarried parents. We sent each of these families a letter informing them of the opportunity to participate in the in-depth portion of our study and then began calling the home and cell phone numbers they provided us on the surveys and knocking on the doors of the addresses they provided.…In the end, we interviewed 115 of the 120 families originally selected for the in-depth interview sample (the remaining five families declined to participate). ( 22 )

Was their sample selection based on convenience or purpose? Why do you think it was important for them to tell you that five families declined to be interviewed? There is actually a trick here, as the names were pulled randomly from a survey whose sample design was probabilistic. Why is this important to know? What can we say about the representativeness or the uniqueness of whatever findings are reported here?

Example 2 . In When Diversity Drops , Park ( 2013 ) examines the impact of decreasing campus diversity on the lives of college students. She does this through a case study of one student club, the InterVarsity Christian Fellowship (IVCF), at one university (“California University,” a pseudonym). Here is her description:

I supplemented participant observation with individual in-depth interviews with sixty IVCF associates, including thirty-four current students, eight former and current staff members, eleven alumni, and seven regional or national staff members. The racial/ethnic breakdown was twenty-five Asian Americans (41.6 percent), one Armenian (1.6 percent), twelve people who were black (20.0 percent), eight Latino/as (13.3 percent), three South Asian Americans (5.0 percent), and eleven people who were white (18.3 percent). Twenty-nine were men, and thirty-one were women. Looking back, I note that the higher number of Asian Americans reflected both the group’s racial/ethnic composition and my relative ease about approaching them for interviews. ( 156 )

How can you tell this is a convenience sample? What else do you note about the sample selection from this description?

Example 3. The last example is taken from an article published in the journal Research in Higher Education . Published articles tend to be more formal than books, at least when it comes to the presentation of qualitative research. In this article, Lawson ( 2021 ) is seeking to understand why female-identified college students drop out of majors that are dominated by male-identified students (e.g., engineering, computer science, music theory). Here is the entire relevant section of the article:

Method Participants Data were collected as part of a larger study designed to better understand the daily experiences of women in MDMs [male-dominated majors].…Participants included 120 students from a midsize, Midwestern University. This sample included 40 women and 40 men from MDMs—defined as any major where at least 2/3 of students are men at both the university and nationally—and 40 women from GNMs—defined as any may where 40–60% of students are women at both the university and nationally.… Procedure A multi-faceted approach was used to recruit participants; participants were sent targeted emails (obtained based on participants’ reported gender and major listings), campus-wide emails sent through the University’s Communication Center, flyers, and in-class presentations. Recruitment materials stated that the research focused on the daily experiences of college students, including classroom experiences, stressors, positive experiences, departmental contexts, and career aspirations. Interested participants were directed to email the study coordinator to verify eligibility (at least 18 years old, man/woman in MDM or woman in GNM, access to a smartphone). Sixteen interested individuals were not eligible for the study due to the gender/major combination. ( 482ff .)

What method of sample selection was used by Lawson? Why is it important to define “MDM” at the outset? How does this definition relate to sampling? Why were interested participants directed to the study coordinator to verify eligibility?

Final Words

I have found that students often find it difficult to be specific enough when defining and choosing their sample. It might help to think about your sample design and sample recruitment like a cookbook. You want all the details there so that someone else can pick up your study and conduct it as you intended. That person could be yourself, but this analogy might work better if you have someone else in mind. When I am writing down recipes, I often think of my sister and try to convey the details she would need to duplicate the dish. We share a grandmother whose recipes are full of handwritten notes in the margins, in spidery ink, that tell us what bowl to use when or where things could go wrong. Describe your sample clearly, convey the steps required accurately, and then add any other details that will help keep you on track and remind you why you have chosen to limit possible interviewees to those of a certain age or class or location. Imagine actually going out and getting your sample (making your dish). Do you have all the necessary details to get started?

Table 5.1. Sampling Type and Strategies

Further Readings

Fusch, Patricia I., and Lawrence R. Ness. 2015. “Are We There Yet? Data Saturation in Qualitative Research.” Qualitative Report 20(9):1408–1416.

Saunders, Benjamin, Julius Sim, Tom Kinstone, Shula Baker, Jackie Waterfield, Bernadette Bartlam, Heather Burroughs, and Clare Jinks. 2018. “Saturation in Qualitative Research: Exploring Its Conceptualization and Operationalization.”  Quality & Quantity  52(4):1893–1907.

• Rubin ( 2021 ) suggests a minimum of twenty interviews (but safer with thirty) for an interview-based study and a minimum of three to six months in the field for ethnographic studies. For a content-based study, she suggests between five hundred and one thousand documents, although some will be “very small” ( 243–244 ). ↵

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.

The actual list of individuals that the sample will be drawn from. Ideally, it should include the entire target population (and nobody who is not part of that population).  Sampling frames can differ from the larger population when specific exclusions are inherent, as in the case of pulling names randomly from voter registration rolls where not everyone is a registered voter.  This difference in frame and population can undercut the generalizability of quantitative results.

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

The large group of interest to the researcher.  Although it will likely be impossible to design a study that incorporates or reaches all members of the population of interest, this should be clearly defined at the outset of a study so that a reasonable sample of the population can be taken.  For example, if one is studying working-class college students, the sample may include twenty such students attending a particular college, while the population is “working-class college students.”  In quantitative research, clearly defining the general population of interest is a necessary step in generalizing results from a sample.  In qualitative research, defining the population is conceptually important for clarity.

A sampling strategy in which the sample is chosen to represent (numerically) the larger population from which it is drawn by random selection.  Each person in the population has an equal chance of making it into the sample.  This is often done through a lottery or other chance mechanisms (e.g., a random selection of every twelfth name on an alphabetical list of voters).  Also known as random sampling .

The selection of research participants or other data sources based on availability or accessibility, in contrast to purposive sampling .

A sample generated non-randomly by asking participants to help recruit more participants the idea being that a person who fits your sampling criteria probably knows other people with similar criteria.

Broad codes that are assigned to the main issues emerging in the data; identifying themes is often part of initial coding . 

A form of case selection focusing on examples that do not fit the emerging patterns. This allows the researcher to evaluate rival explanations or to define the limitations of their research findings. While disconfirming cases are found (not sought out), researchers should expand their analysis or rethink their theories to include/explain them.

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).

The result of probability sampling, in which a sample is chosen to represent (numerically) the larger population from which it is drawn by random selection.  Each person in the population has an equal chance of making it into the random sample.  This is often done through a lottery or other chance mechanisms (e.g., the random selection of every twelfth name on an alphabetical list of voters).  This is typically not required in qualitative research but rather essential for the generalizability of quantitative research.

A form of case selection or purposeful sampling in which cases that are unusual or special in some way are chosen to highlight processes or to illuminate gaps in our knowledge of a phenomenon.   See also extreme case .

The point at which you can conclude data collection because every person you are interviewing, the interaction you are observing, or content you are analyzing merely confirms what you have already noted.  Achieving saturation is often used as the justification for the final sample size.

The accuracy with which results or findings can be transferred to situations or people other than those originally studied.  Qualitative studies generally are unable to use (and are uninterested in) statistical generalizability where the sample population is said to be able to predict or stand in for a larger population of interest.  Instead, qualitative researchers often discuss “theoretical generalizability,” in which the findings of a particular study can shed light on processes and mechanisms that may be at play in other settings.  See also statistical generalization and theoretical generalization .

A term used by IRBs to denote all materials aimed at recruiting participants into a research study (including printed advertisements, scripts, audio or video tapes, or websites).  Copies of this material are required in research protocols submitted to IRB.

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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Home Market Research

Qualitative Research Methods: Types, Analysis + Examples

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

What is qualitative research?

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

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

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

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

Gather research insights

Types of qualitative research methods with examples

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

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

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

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

1. One-on-one interview

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

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

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

2. Focus groups

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

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

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

3. Ethnographic research

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

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

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

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

4. Case study research

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

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

5. Record keeping

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

6. Process of observation

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

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

Explore Insightfully Contextual Inquiry in Qualitative Research

Qualitative research: data collection and analysis

A. qualitative data collection.

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

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

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

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

B. Qualitative data analysis

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

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

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

Characteristics of qualitative research methods

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

Qualitative research method case study

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

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

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

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

When to use qualitative research

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

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

LEARN ABOUT: Steps in Qualitative Research

Qualitative research methods vs quantitative research methods

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

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

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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

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Qualitative research is a powerful tool that helps you unlock insights into the user experience—quintessential to building effective products and services. It provides a deeper understanding of complex behaviors, needs, and motivations. But what is qualitative research, and when is it ideal to use it? Let’s explore its methodologies and implementation with a few qualitative research examples.

What is qualitative research?

Qualitative research is a behavioral research method that seeks to understand the undertones, motivations, and subjective interpretations inherent in human behavior. It involves gathering nonnumerical data, such as text, audio, and video, allowing you to explore nuances and patterns that quantitative data can’t capture.

Instead of focusing on how many or how much, qualitative research questions delve into the why and how. This approach is instrumental in gaining a comprehensive understanding of a particular context, issue, or phenomenon from the perspective of those experiencing it. Examples of qualitative research questions include “How did you feel when you first used our product?” and “Could you describe your experience when you purchased a product from our website?”

Qualitative research methodology

Qualitative research design employs a variety of methodologies to collect and analyze data. The primary objective is to gather detailed and nuanced insights rather than generalizable findings. Steps include the following:

• Formulating research questions:  Qualitative research begins by identifying specific research questions to guide the study. These questions should align with the research objectives and provide a clear focus for data collection and analysis.  
• Selection of participants:  Participant selection is a critical step in qualitative research. You must recruit participants who provide relevant and diverse perspectives on the research topic. It involves purposive sampling, where participants are chosen based on their knowledge or experiences related to the research questions. ​​​​​​
• Data collection:  Qualitative research uses various methods to collect data, such as interviews, focus groups, observation, and document analysis. You often employ multiple methods to comprehensively understand the research topic.
• Data analysis:  Once the data is collected, it’s analyzed to identify recurring themes, patterns, and meanings. This analysis uses coding, thematic analysis, and constant comparison. The goal is to uncover the underlying perspectives of the participant.
• Interpretation and reporting:  This is the final step in which findings are synthesized and interpreted, revealing their significance to the research questions. You can present your findings through descriptive narratives, quotes, and illustrative examples to provide a rich understanding of the research topic. 

Types of qualitative research methods

The best qualitative research method primarily depends on your research questions and objectives. Different methods uncover different discernments.

One-on-one interviews

You often use one-on-one interviews to delve deep into a topic or understand individual experiences or perspectives. An interviewer asks a participant open-ended questions to understand their perspective, thoughts, feelings, and experiences regarding a specific topic, product, or service. Read about open ended vs closed ended questions to learn which questions will be most effective in an interview.

Say you’re developing a new electric vehicle mode. You can conduct one-on-one interviews to understand user experiences, probing into aspects such as comfort, design, driving experience, and more.

Focus groups

In-person or remote focus groups involve a small group of people (usually 6–10) discussing a given topic or question under the guidance of a moderator. This method is beneficial when you want to understand group dynamics or collective views. The interaction among group members can disclose awarenesses that may not arise in one-on-one interviews.

In the gaming industry, for example, you can use focus groups to explore player reactions to a new game design. You can encourage group interaction to spark discussions about usability, game mechanics, graphics, storyline, and other aspects.

Case study research

Case study research provides an in-depth analysis of a particular case (an individual, group, organization, event, etc.) within its real-life context. It’s a valuable method for exploring something in-depth and in its natural setting.

For instance, a healthcare case study could explore implementing a new electronic health record system in a hospital, focusing on challenges, successes, and lessons learned.

Ethnographic research

Ethnographic research (or an ethnographic stud y) involves an immersive investigation into a group’s behaviors, culture, and practices. It requires you to engage directly with the participants over a prolonged period in their natural environment. It can help uncover how people interact with products or services in natural settings.

A gaming organization may choose to study players in their natural gaming environments (such as home, game cafes, or e-sport tournaments) to understand their gaming habits, social interactions, and responses to specific features. These insights can inform the development of more engaging and user-friendly games.

Process of observation

The process of observation typically doesn’t involve the same level of immersion as ethnographic research. You observe and record behavior related to a specific context or activity. It can be in natural settings (naturalistic observation) or a controlled environment. It’s more about observing and recording specific behaviors or situations rather than cultural norms or dynamics.

For example, a consumer technology organization could observe how users interact with a new software interface, noting challenges, efficiencies, and overall user experience.

Record keeping

Record keeping refers to collecting and analyzing documents, records, and artifacts that provide an understanding of the study area. Record keeping allows you to access historical and contextual data that can be examined and reexamined. It’s a nonobtrusive method, meaning it doesn’t involve direct contact with the participants, nor does it affect or alter the situation you’re studying.

An online retailer might examine shopping cart abandonment records to identify at what point in the buying process customers tend to drop off. This information can help streamline the checkout process and improve conversion rates.

Qualitative research: Data collection and analysis

Data collection and analysis in qualitative research are closely linked processes that help generate meaningful and useful results.

Data collection

Data collection involves gathering rich, detailed materials to explain and understand the subject. These include interview transcripts, meeting notes, personal diaries, and photographs. 

There are various qualitative data collection methods to consider depending on your research questions and the context of your study. For example, you could use one-on-one interviews to understand personal user experiences with a financial services app. However, focus groups may be more appropriate to discuss user preferences in a new media and entertainment platform.

Data analysis

Once data are collected, the analysis process begins. It’s where you extract patterns, themes, and insights from the collected data. It’s one of the most critical aspects of qualitative research, turning raw, unstructured data into valuable insights.

Qualitative data analysis usually takes place with several steps, such as:

• Organizing and preparing the data for analysis
• Reading through the data
• Coding the data
• Generating themes or categories
• Interpreting the findings and 
• Representing the data

Your choice of qualitative data analysis method depends on your research questions and the data type you collected. Common analysis methods include thematic, content, discourse, and narrative analysis. Some research platforms provide AI features that can do much of this analysis for researchers to speed up insight gathering.

When to use qualitative research

Qualitative techniques are ideal for understanding human experiences and perspectives. Here are common situations where qualitative research is invaluable:

• Exploring customer motivations, needs, behaviors, and pain points
• Gathering in-depth user feedback on products and services
• Understanding decision-making and buyer journeys
• Discovering barriers to adoption and satisfaction
• Developing hypotheses for future quantitative research
• Testing concepts , interfaces, or designs
• Identifying problems and improvement opportunities
• Learning about group norms, cultures, and social interactions
• Collecting evidence to develop theories and models
• Capturing complex, nuanced insights beyond numbers

Qualitative research methods vs. quantitative research methods

Qualitative and quantitative research  differ in their approach to data collection, analysis, and the nature of the findings. Here are some key differences:

• Data collection:  Qualitative research uses in-depth interviews , focus groups, observations, and analysis of documents to gather data. In contrast, quantitative research relies on structured surveys, experiments, and standard measurements.
• Analysis:  Qualitative research involves analyzing textual or visual data through coding, categorization, and theme identification techniques. Quantitative research uses statistical analysis to examine numerical data for patterns, correlations, and trends.
• Sample size:  Qualitative research typically involves smaller sample sizes, often selected through purposive sampling to ensure diversity and relevance. Quantitative research uses larger sample sizes to ensure statistical power and generalizability.
• Generalizability:  Qualitative research seeks in-depth insight into specific contexts or groups and does not prioritize generalizability. On the other hand, quantitative research seeks to draw conclusions that apply to a broader context.
• Findings:  Qualitative research generates descriptive and explanatory results that provide a deeper understanding of phenomena. Quantitative research produces numerical data that allows for statistical inferences and comparisons.
• Theory development:  Qualitative research often contributes to theory development by generating new concepts, theories, or frameworks based on the rich and context-specific data collected. However, quantitative research tests preexisting theories and hypotheses using statistical models.

Advantages and strengths of qualitative research

Qualitative research enriches your research process and outcomes, making it an invaluable tool in many fields, including UX research, marketing, and digital product development. 

In-depth understanding

Qualitative research provides a rich, detailed, in-depth understanding of the research subject.  Proactive qualitative research  takes this further with ongoing data collection, allowing organizations to continuously capture insights and adapt strategies based on evolving user needs.

Contextual data

Qualitative research collects contextually relevant data. It captures nuances that might be missed in numerically-based quantitative data, allowing you to understand the contexts in which behaviors and interactions occur.

Flexibility

The methods used in qualitative research, like interviews and focus groups, enable you to explore different topics in depth and adapt your approach based on the participants’ responses.

Human perspective

Qualitative research lets you capture human experiences and thoughts. It’s advantageous in fields such as UX research, where the human perspective is critical. 

Hypothesis generation

The exploratory nature of qualitative research helps you identify new areas for exploration or generate hypotheses you can test using quantitative methods.

Trendspotting

Qualitative research reveals trends in thought and opinions, diving deeper into the problem. This is helpful when trying to understand behaviors, culture, and user interactions.

Disadvantages and limitations of qualitative research

While qualitative research offers many advantages, it’s essential to acknowledge its limitations. 

Time-consuming

Collecting and analyzing qualitative data, particularly from in-depth interviews or focus groups, requires significant time investment.

Qualitative research relies on the skills and judgment of the researcher, introducing potential bias into the research process. The researcher may actively shape the research by posing questions, interpreting data, and influencing the findings.

Requires skilled researchers

The quality of qualitative research heavily depends on the researcher’s skills, experience, and perspective. A less experienced researcher may overlook important nuances, potentially affecting the depth and accuracy of the findings.

Lacks generalizability

Qualitative research often involves a smaller, nonrepresentative sample size than quantitative research. Therefore, the findings may not be generalizable to a larger context.

Limited numeric representation

Qualitative research usually focuses on words, observations, or experiences, so it doesn’t provide the numeric estimates often desired in research studies.

Challenging to replicate and standardize

Qualitative research’s inherent flexibility and context dependence make it challenging to repeat the study under the same conditions. This flexibility can often make it hard to standardize. Researchers approach and conduct the study in various ways, leading to inconsistent results and interpretations.

Difficult to measure reliability and validity

Assessing reliability and validity is more difficult with qualitative research since it relies on subjective human interpretation and has few established metrics and statistical tools compared to quantitative research. Triangulation and member checking add credibility but lack the discreteness of quantitative measures. However, there have been advancement s in the measurement of qualitative research that help to quantify its impact. 

Qualitative research gives you the opportunity to dive deep into human behavior, experiences, and perceptions. It offers a prolific, intricate perspective that quantifiable data alone can’t provide. Combine qualitative research methodologies with techniques like  A/B testing  to gain a more holistic understanding of user experiences and preferences. 

Despite its limitations, the depth and richness of data procured through qualitative research are undeniable assets. By understanding and utilizing its diverse methods, you will uncover detailed insights from your target audience and enhance your products or services to meet their needs. 

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Why is qualitative research important?

Qualitative research delves into subjective experiences and social contexts, providing in-depth insights and understanding. It provides a deep understanding of individuals’ needs, motivations, and preferences, allowing organizations to develop products and services that meet customer expectations.

What’s the difference between quantitative and qualitative methods?

Quantitative methods focus on numerical data and statistical analysis, aiming for generalizability and objectivity. Qualitative methods explore meanings, experiences, and behaviors, seeking in-depth understanding and detailed descriptions.

What are the main qualitative research approaches?

The main qualitative research approaches include one-on-one interviews, focus groups, case study research, ethnographic research, observation, and record-keeping. Each approach offers unique benefits and applications.

What is data collection?

Data collection in qualitative research involves gathering information through various methods such as interviews, focus groups, observations, and document analysis. It’s a critical step in generating meaningful insights and understanding human experiences.

How do you analyze qualitative data?

What are the ethical considerations in qualitative research.

Ethical considerations refer to the protection of participants’ rights, privacy, and confidentiality. You must obtain informed consent, maintain anonymity, and handle sensitive information responsibly. Additionally, maintaining transparency, addressing power imbalances, and conducting research unbiased and respectfully are vital ethical considerations in qualitative research.

How can I incorporate qualitative research into my study or project?

To incorporate qualitative research into your study, you must first define your research objectives to guide the choice of methodology. Next, choose a suitable qualitative method, such as interviews or focus groups. Then, collect and analyze the data using appropriate techniques and, finally, interpret and present the findings clearly and meaningfully. Remember to be mindful of the ethical considerations throughout the process.

How do you effectively communicate and present qualitative research findings to stakeholders?

For a quality presentation, create engaging visual representations, such as infographics or data visualizations, and use storytelling techniques to highlight key insights. Also, prepare concise and informative reports and organize interactive presentations or workshops to facilitate discussion and understanding.

How do you translate qualitative research findings into actionable insights?

Identify key themes linked to research goals and propose strategic solutions to address core needs and barriers. These solutions should be tailored to specific needs.

How can I ensure the validity and reliability of qualitative research findings?

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Qualitative Research: Characteristics, Design, Methods & Examples

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MSc, Health Psychology, University of Nottingham

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

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

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

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

Qualitative research can be used to:

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

Examples of qualitative research questions include: 

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

Characteristics 

Naturalistic setting.

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

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

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

Reality is socially constructed

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

The primacy of subject matter 

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

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

Variables are complex, interwoven, and difficult to measure

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

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

Emic (insider’s point of view)

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

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

Interpretive analysis

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

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

Collecting Qualitative Data

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

Observations

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

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

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

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

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

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

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

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

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

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

Focus groups 

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

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

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

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

Ethnography

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

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

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

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

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

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

Qualitative Data Analysis Methods

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

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

Grounded theory

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

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

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

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

Content analysis

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

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

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

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

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

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

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

Discourse analysis

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

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

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

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

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

Thematic analysis

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

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

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

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

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

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

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

Phases of Thematic Analysis

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

Template analysis

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

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

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

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

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

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

Frame analysis

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

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

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

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

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

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

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

Preventing Bias in Qualitative Research

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

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

Co-coding 

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

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

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

Member checking

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

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

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

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

Reflexivity in qualitative research

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

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

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

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

Reflexivity Example

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

Establishing Trustworthiness in Qualitative Research

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

Credibility in Qualitative Research

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

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

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

Transferability in Qualitative Research

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

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

Dependability in Qualitative Research

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

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

Confirmability in Qualitative Research

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

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

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

Audit Trails in Qualitative Research

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

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

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

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

Discovery of unexpected data

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

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

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

Flexibility

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

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

Naturalistic settings

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

Limitations

Time-consuming .

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

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

Subjectivity 

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

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

Limited generalizability

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

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

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

Extraneous variables

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

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

What sample size should qualitative research be?

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

Are surveys qualitative or quantitative?

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

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

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

What are the ethical considerations of qualitative research?

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

What is triangulation in qualitative research?

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

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

Why is qualitative research important?

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

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

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

What is coding data in qualitative research?

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

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

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

What is the difference between qualitative and quantitative research?

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

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

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

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

What is trustworthiness in qualitative research?

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

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

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

What is data saturation in qualitative research?

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

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

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

Why is sampling in qualitative research important?

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

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

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

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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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• Introduction

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. [1] Instead of collecting numerical data points or intervening or introducing treatments just like in quantitative research, qualitative research helps generate hypothenar to further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a standalone study, purely relying on qualitative data, or part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and applications of qualitative research.

Qualitative research, at its core, asks open-ended questions whose answers are not easily put into numbers, such as "how" and "why." [2] Due to the open-ended nature of the research questions, qualitative research design is often not linear like quantitative design. [2] One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. [3] Phenomena such as experiences, attitudes, and behaviors can be complex to capture accurately and quantitatively. In contrast, a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a particular time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify, and it is essential to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore "compete" against each other and the philosophical paradigms associated with each other, qualitative and quantitative work are neither necessarily opposites, nor are they incompatible. [4] While qualitative and quantitative approaches are different, they are not necessarily opposites and certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated.

Qualitative Research Approaches

Ethnography

Ethnography as a research design originates in social and cultural anthropology and involves the researcher being directly immersed in the participant’s environment. [2] Through this immersion, the ethnographer can use a variety of data collection techniques to produce a comprehensive account of the social phenomena that occurred during the research period. [2] That is to say, the researcher’s aim with ethnography is to immerse themselves into the research population and come out of it with accounts of actions, behaviors, events, etc, through the eyes of someone involved in the population. Direct involvement of the researcher with the target population is one benefit of ethnographic research because it can then be possible to find data that is otherwise very difficult to extract and record.

Grounded theory

Grounded Theory is the "generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior." [5] Unlike quantitative research, which is deductive and tests or verifies an existing theory, grounded theory research is inductive and, therefore, lends itself to research aimed at social interactions or experiences. [3] [2] In essence, Grounded Theory’s goal is to explain how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.

Phenomenology

Phenomenology is the "study of the meaning of phenomena or the study of the particular.” [5] At first glance, it might seem that Grounded Theory and Phenomenology are pretty similar, but the differences can be seen upon careful examination. At its core, phenomenology looks to investigate experiences from the individual's perspective. [2] Phenomenology is essentially looking into the "lived experiences" of the participants and aims to examine how and why participants behaved a certain way from their perspective. Herein lies one of the main differences between Grounded Theory and Phenomenology. Grounded Theory aims to develop a theory for social phenomena through an examination of various data sources. In contrast, Phenomenology focuses on describing and explaining an event or phenomenon from the perspective of those who have experienced it.

Narrative research

One of qualitative research’s strengths lies in its ability to tell a story, often from the perspective of those directly involved in it. Reporting on qualitative research involves including details and descriptions of the setting involved and quotes from participants. This detail is called a "thick" or "rich" description and is a strength of qualitative research. Narrative research is rife with the possibilities of "thick" description as this approach weaves together a sequence of events, usually from just one or two individuals, hoping to create a cohesive story or narrative. [2] While it might seem like a waste of time to focus on such a specific, individual level, understanding one or two people’s narratives for an event or phenomenon can help to inform researchers about the influences that helped shape that narrative. The tension or conflict of differing narratives can be "opportunities for innovation." [2]

Research Paradigm

Research paradigms are the assumptions, norms, and standards underpinning different research approaches. Essentially, research paradigms are the "worldviews" that inform research. [4] It is valuable for qualitative and quantitative researchers to understand what paradigm they are working within because understanding the theoretical basis of research paradigms allows researchers to understand the strengths and weaknesses of the approach being used and adjust accordingly. Different paradigms have different ontologies and epistemologies. Ontology is defined as the "assumptions about the nature of reality,” whereas epistemology is defined as the "assumptions about the nature of knowledge" that inform researchers' work. [2] It is essential to understand the ontological and epistemological foundations of the research paradigm researchers are working within to allow for a complete understanding of the approach being used and the assumptions that underpin the approach as a whole. Further, researchers must understand their own ontological and epistemological assumptions about the world in general because their assumptions about the world will necessarily impact how they interact with research. A discussion of the research paradigm is not complete without describing positivist, postpositivist, and constructivist philosophies.

Positivist versus postpositivist

To further understand qualitative research, we must discuss positivist and postpositivist frameworks. Positivism is a philosophy that the scientific method can and should be applied to social and natural sciences. [4] Essentially, positivist thinking insists that the social sciences should use natural science methods in their research. It stems from positivist ontology, that there is an objective reality that exists that is wholly independent of our perception of the world as individuals. Quantitative research is rooted in positivist philosophy, which can be seen in the value it places on concepts such as causality, generalizability, and replicability.

Conversely, postpositivists argue that social reality can never be one hundred percent explained, but could be approximated. [4] Indeed, qualitative researchers have been insisting that there are “fundamental limits to the extent to which the methods and procedures of the natural sciences could be applied to the social world,” and therefore, postpositivist philosophy is often associated with qualitative research. [4] An example of positivist versus postpositivist values in research might be that positivist philosophies value hypothesis-testing, whereas postpositivist philosophies value the ability to formulate a substantive theory.

Constructivist

Constructivism is a subcategory of postpositivism. Most researchers invested in postpositivist research are also constructivist, meaning they think there is no objective external reality that exists but instead that reality is constructed. Constructivism is a theoretical lens that emphasizes the dynamic nature of our world. "Constructivism contends that individuals' views are directly influenced by their experiences, and it is these individual experiences and views that shape their perspective of reality.” [6]  constructivist thought focuses on how "reality" is not a fixed certainty and how experiences, interactions, and backgrounds give people a unique view of the world. Constructivism contends, unlike positivist views, that there is not necessarily an "objective"reality we all experience. This is the ‘relativist’ ontological view that reality and our world are dynamic and socially constructed. Therefore, qualitative scientific knowledge can be inductive as well as deductive.” [4]

So why is it important to understand the differences in assumptions that different philosophies and approaches to research have? Fundamentally, the assumptions underpinning the research tools a researcher selects provide an overall base for the assumptions the rest of the research will have. It can even change the role of the researchers. [2] For example, is the researcher an "objective" observer, such as in positivist quantitative work? Or is the researcher an active participant in the research, as in postpositivist qualitative work? Understanding the philosophical base of the study undertaken allows researchers to fully understand the implications of their work and their role within the research and reflect on their positionality and bias as it pertains to the research they are conducting.

Data Sampling 

The better the sample represents the intended study population, the more likely the researcher is to encompass the varying factors. The following are examples of participant sampling and selection: [7]

• Purposive sampling- selection based on the researcher’s rationale for being the most informative.
• Criterion sampling selection based on pre-identified factors.
• Convenience sampling- selection based on availability.
• Snowball sampling- the selection is by referral from other participants or people who know potential participants.
• Extreme case sampling- targeted selection of rare cases.
• Typical case sampling selection based on regular or average participants. 

Data Collection and Analysis

Qualitative research uses several techniques, including interviews, focus groups, and observation. [1] [2] [3] Interviews may be unstructured, with open-ended questions on a topic, and the interviewer adapts to the responses. Structured interviews have a predetermined number of questions that every participant is asked. It is usually one-on-one and appropriate for sensitive topics or topics needing an in-depth exploration. Focus groups are often held with 8-12 target participants and are used when group dynamics and collective views on a topic are desired. Researchers can be participant-observers to share the experiences of the subject or non-participants or detached observers.

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or the participants' environment, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed, which may then be coded manually or using computer-assisted qualitative data analysis software or CAQDAS such as ATLAS.ti or NVivo. [8] [9] [10]

After the coding process, qualitative research results could be in various formats. It could be a synthesis and interpretation presented with excerpts from the data. [11] Results could also be in the form of themes and theory or model development.

Dissemination

The healthcare team can use two reporting standards to standardize and facilitate the dissemination of qualitative research outcomes. The Consolidated Criteria for Reporting Qualitative Research or COREQ is a 32-item checklist for interviews and focus groups. [12] The Standards for Reporting Qualitative Research (SRQR) is a checklist covering a more comprehensive range of qualitative research. [13]

Applications

Many times, a research question will start with qualitative research. The qualitative research will help generate the research hypothesis, which can be tested with quantitative methods. After the data is collected and analyzed with quantitative methods, a set of qualitative methods can be used to dive deeper into the data to better understand what the numbers truly mean and their implications. The qualitative techniques can then help clarify the quantitative data and also help refine the hypothesis for future research. Furthermore, with qualitative research, researchers can explore poorly studied subjects with quantitative methods. These include opinions, individual actions, and social science research.

An excellent qualitative study design starts with a goal or objective. This should be clearly defined or stated. The target population needs to be specified. A method for obtaining information from the study population must be carefully detailed to ensure no omissions of part of the target population. A proper collection method should be selected that will help obtain the desired information without overly limiting the collected data because, often, the information sought is not well categorized or obtained. Finally, the design should ensure adequate methods for analyzing the data. An example may help better clarify some of the various aspects of qualitative research.

A researcher wants to decrease the number of teenagers who smoke in their community. The researcher could begin by asking current teen smokers why they started smoking through structured or unstructured interviews (qualitative research). The researcher can also get together a group of current teenage smokers and conduct a focus group to help brainstorm factors that may have prevented them from starting to smoke (qualitative research).

In this example, the researcher has used qualitative research methods (interviews and focus groups) to generate a list of ideas of why teens start to smoke and factors that may have prevented them from starting to smoke. Next, the researcher compiles this data. The research found that, hypothetically, peer pressure, health issues, cost, being considered "cool," and rebellious behavior all might increase or decrease the likelihood of teens starting to smoke.

The researcher creates a survey asking teen participants to rank how important each of the above factors is in either starting smoking (for current smokers) or not smoking (for current nonsmokers). This survey provides specific numbers (ranked importance of each factor) and is thus a quantitative research tool.

The researcher can use the survey results to focus efforts on the one or two highest-ranked factors. Let us say the researcher found that health was the primary factor that keeps teens from starting to smoke, and peer pressure was the primary factor that contributed to teens starting smoking. The researcher can go back to qualitative research methods to dive deeper into these for more information. The researcher wants to focus on keeping teens from starting to smoke, so they focus on the peer pressure aspect.

The researcher can conduct interviews and focus groups (qualitative research) about what types and forms of peer pressure are commonly encountered, where the peer pressure comes from, and where smoking starts. The researcher hypothetically finds that peer pressure often occurs after school at the local teen hangouts, mostly in the local park. The researcher also hypothetically finds that peer pressure comes from older, current smokers who provide the cigarettes.

The researcher could further explore this observation made at the local teen hangouts (qualitative research) and take notes regarding who is smoking, who is not, and what observable factors are at play for peer pressure to smoke. The researcher finds a local park where many local teenagers hang out and sees that the smokers tend to hang out in a shady, overgrown area of the park. The researcher notes that smoking teenagers buy their cigarettes from a local convenience store adjacent to the park, where the clerk does not check identification before selling cigarettes. These observations fall under qualitative research.

If the researcher returns to the park and counts how many individuals smoke in each region, this numerical data would be quantitative research. Based on the researcher's efforts thus far, they conclude that local teen smoking and teenagers who start to smoke may decrease if there are fewer overgrown areas of the park and the local convenience store does not sell cigarettes to underage individuals.

The researcher could try to have the parks department reassess the shady areas to make them less conducive to smokers or identify how to limit the sales of cigarettes to underage individuals by the convenience store. The researcher would then cycle back to qualitative methods of asking at-risk populations their perceptions of the changes and what factors are still at play, and quantitative research that includes teen smoking rates in the community and the incidence of new teen smokers, among others. [14] [15]

Qualitative research functions as a standalone research design or combined with quantitative research to enhance our understanding of the world. Qualitative research uses techniques including structured and unstructured interviews, focus groups, and participant observation not only to help generate hypotheses that can be more rigorously tested with quantitative research but also to help researchers delve deeper into the quantitative research numbers, understand what they mean, and understand what the implications are. Qualitative research allows researchers to understand what is going on, especially when things are not easily categorized. [16]

• Issues of Concern

As discussed in the sections above, quantitative and qualitative work differ in many ways, including the evaluation criteria. There are four well-established criteria for evaluating quantitative data: internal validity, external validity, reliability, and objectivity. Credibility, transferability, dependability, and confirmability are the correlating concepts in qualitative research. [4] [11] The corresponding quantitative and qualitative concepts can be seen below, with the quantitative concept on the left and the qualitative concept on the right:

• Internal validity: Credibility
• External validity: Transferability
• Reliability: Dependability
• Objectivity: Confirmability

In conducting qualitative research, ensuring these concepts are satisfied and well thought out can mitigate potential issues from arising. For example, just as a researcher will ensure that their quantitative study is internally valid, qualitative researchers should ensure that their work has credibility. 

Indicators such as triangulation and peer examination can help evaluate the credibility of qualitative work.

• Triangulation: Triangulation involves using multiple data collection methods to increase the likelihood of getting a reliable and accurate result. In our above magic example, the result would be more reliable if we interviewed the magician, backstage hand, and the person who "vanished." In qualitative research, triangulation can include telephone surveys, in-person surveys, focus groups, and interviews and surveying an adequate cross-section of the target demographic.
• Peer examination: A peer can review results to ensure the data is consistent with the findings.

A "thick" or "rich" description can be used to evaluate the transferability of qualitative research, whereas an indicator such as an audit trail might help evaluate the dependability and confirmability.

• Thick or rich description:  This is a detailed and thorough description of details, the setting, and quotes from participants in the research. [5] Thick descriptions will include a detailed explanation of how the study was conducted. Thick descriptions are detailed enough to allow readers to draw conclusions and interpret the data, which can help with transferability and replicability.
• Audit trail: An audit trail provides a documented set of steps of how the participants were selected and the data was collected. The original information records should also be kept (eg, surveys, notes, recordings).

One issue of concern that qualitative researchers should consider is observation bias. Here are a few examples:

• Hawthorne effect: The effect is the change in participant behavior when they know they are being observed. Suppose a researcher wanted to identify factors that contribute to employee theft and tell the employees they will watch them to see what factors affect employee theft. In that case, one would suspect employee behavior would change when they know they are being protected.
• Observer-expectancy effect: Some participants change their behavior or responses to satisfy the researcher's desired effect. This happens unconsciously for the participant, so it is essential to eliminate or limit the transmission of the researcher's views.
• Artificial scenario effect: Some qualitative research occurs in contrived scenarios with preset goals. In such situations, the information may not be accurate because of the artificial nature of the scenario. The preset goals may limit the qualitative information obtained.
• Clinical Significance

Qualitative or quantitative research helps healthcare providers understand patients and the impact and challenges of the care they deliver. Qualitative research provides an opportunity to generate and refine hypotheses and delve deeper into the data generated by quantitative research. Qualitative research is not an island apart from quantitative research but an integral part of research methods to understand the world around us. [17]

• Enhancing Healthcare Team Outcomes

Qualitative research is essential for all healthcare team members as all are affected by qualitative research. Qualitative research may help develop a theory or a model for health research that can be further explored by quantitative research. Much of the qualitative research data acquisition is completed by numerous team members, including social workers, scientists, nurses, etc. Within each area of the medical field, there is copious ongoing qualitative research, including physician-patient interactions, nursing-patient interactions, patient-environment interactions, healthcare team function, patient information delivery, etc. 

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Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

Disclosure: Janelle Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Grace Brannan declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Tenny S, Brannan JM, Brannan GD. Qualitative Study. [Updated 2022 Sep 18]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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CRO Guide   >  Chapter 3.1

Qualitative Research: Definition, Methodology, Limitation & Examples

Qualitative research is a method focused on understanding human behavior and experiences through non-numerical data. Examples of qualitative research include:

• One-on-one interviews,
• Focus groups, Ethnographic research,
• Case studies,
• Record keeping,
• Qualitative observations

In this article, we’ll provide tips and tricks on how to use qualitative research to better understand your audience through real world examples and improve your ROI. We’ll also learn the difference between qualitative and quantitative data.

Table of Contents

Marketers often seek to understand their customers deeply. Qualitative research methods such as face-to-face interviews, focus groups, and qualitative observations can provide valuable insights into your products, your market, and your customers’ opinions and motivations. Understanding these nuances can significantly enhance marketing strategies and overall customer satisfaction.

What is Qualitative Research

Qualitative research is a market research method that focuses on obtaining data through open-ended and conversational communication. This method focuses on the “why” rather than the “what” people think about you. Thus, qualitative research seeks to uncover the underlying motivations, attitudes, and beliefs that drive people’s actions. 

Let’s say you have an online shop catering to a general audience. You do a demographic analysis and you find out that most of your customers are male. Naturally, you will want to find out why women are not buying from you. And that’s what qualitative research will help you find out.

In the case of your online shop, qualitative research would involve reaching out to female non-customers through methods such as in-depth interviews or focus groups. These interactions provide a platform for women to express their thoughts, feelings, and concerns regarding your products or brand. Through qualitative analysis, you can uncover valuable insights into factors such as product preferences, user experience, brand perception, and barriers to purchase.

Types of Qualitative Research Methods

Qualitative research methods are designed in a manner that helps reveal the behavior and perception of a target audience regarding a particular topic.

The most frequently used qualitative analysis methods are one-on-one interviews, focus groups, ethnographic research, case study research, record keeping, and qualitative observation.

1. One-on-one interviews

Conducting one-on-one interviews is one of the most common qualitative research methods. One of the advantages of this method is that it provides a great opportunity to gather precise data about what people think and their motivations.

Spending time talking to customers not only helps marketers understand who their clients are, but also helps with customer care: clients love hearing from brands. This strengthens the relationship between a brand and its clients and paves the way for customer testimonials.

• A company might conduct interviews to understand why a product failed to meet sales expectations.
• A researcher might use interviews to gather personal stories about experiences with healthcare.

These interviews can be performed face-to-face or on the phone and usually last between half an hour to over two hours. 

When a one-on-one interview is conducted face-to-face, it also gives the marketer the opportunity to read the body language of the respondent and match the responses.

2. Focus groups

Focus groups gather a small number of people to discuss and provide feedback on a particular subject. The ideal size of a focus group is usually between five and eight participants. The size of focus groups should reflect the participants’ familiarity with the topic. For less important topics or when participants have little experience, a group of 10 can be effective. For more critical topics or when participants are more knowledgeable, a smaller group of five to six is preferable for deeper discussions.

The main goal of a focus group is to find answers to the “why”, “what”, and “how” questions. This method is highly effective in exploring people’s feelings and ideas in a social setting, where group dynamics can bring out insights that might not emerge in one-on-one situations.

• A focus group could be used to test reactions to a new product concept.
• Marketers might use focus groups to see how different demographic groups react to an advertising campaign.

One advantage that focus groups have is that the marketer doesn’t necessarily have to interact with the group in person. Nowadays focus groups can be sent as online qualitative surveys on various devices.

Focus groups are an expensive option compared to the other qualitative research methods, which is why they are typically used to explain complex processes.

3. Ethnographic research

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

This method aims at understanding the cultures, challenges, motivations, and settings that occur.

• A study of workplace culture within a tech startup.
• Observational research in a remote village to understand local traditions.

Ethnographic research requires the marketer to adapt to the target audiences’ environments (a different organization, a different city, or even a remote location), which is why geographical constraints can be an issue while collecting data.

This type of research can last from a few days to a few years. It’s challenging and time-consuming and solely depends on the expertise of the marketer to be able to analyze, observe, and infer the data.

4. Case study research

The case study method has grown into a valuable qualitative research method. This type of research method is usually used in education or social sciences. It involves a comprehensive examination of a single instance or event, providing detailed insights into complex issues in real-life contexts.  

• Analyzing a single school’s innovative teaching method.
• A detailed study of a patient’s medical treatment over several years.

Case study research may seem difficult to operate, but it’s actually one of the simplest ways of conducting research as it involves a deep dive and thorough understanding of the data collection methods and inferring the data.

5. Record keeping

Record keeping is similar to going to the library: you go over books or any other reference material to collect relevant data. This method uses already existing reliable documents and similar sources of information as a data source.

• Historical research using old newspapers and letters.
• A study on policy changes over the years by examining government records.

This method is useful for constructing a historical context around a research topic or verifying other findings with documented evidence.

6. Qualitative observation

Qualitative observation is a method that uses subjective methodologies to gather systematic information or data. This method deals with the five major sensory organs and their functioning, sight, smell, touch, taste, and hearing.

• Sight : Observing the way customers visually interact with product displays in a store to understand their browsing behaviors and preferences.
• Smell : Noting reactions of consumers to different scents in a fragrance shop to study the impact of olfactory elements on product preference.
• Touch : Watching how individuals interact with different materials in a clothing store to assess the importance of texture in fabric selection.
• Taste : Evaluating reactions of participants in a taste test to identify flavor profiles that appeal to different demographic groups.
• Hearing : Documenting responses to changes in background music within a retail environment to determine its effect on shopping behavior and mood.

Below we are also providing real-life examples of qualitative research that demonstrate practical applications across various contexts:

Qualitative Research Real World Examples

Let’s explore some examples of how qualitative research can be applied in different contexts.

1. Online grocery shop with a predominantly male audience

Method used: one-on-one interviews.

Let’s go back to one of the previous examples. You have an online grocery shop. By nature, it addresses a general audience, but after you do a demographic analysis you find out that most of your customers are male.

One good method to determine why women are not buying from you is to hold one-on-one interviews with potential customers in the category.

Interviewing a sample of potential female customers should reveal why they don’t find your store appealing. The reasons could range from not stocking enough products for women to perhaps the store’s emphasis on heavy-duty tools and automotive products, for example. These insights can guide adjustments in inventory and marketing strategies.

2. Software company launching a new product

Method used: focus groups.

Focus groups are great for establishing product-market fit.

Let’s assume you are a software company that wants to launch a new product and you hold a focus group with 12 people. Although getting their feedback regarding users’ experience with the product is a good thing, this sample is too small to define how the entire market will react to your product.

So what you can do instead is holding multiple focus groups in 20 different geographic regions. Each region should be hosting a group of 12 for each market segment; you can even segment your audience based on age. This would be a better way to establish credibility in the feedback you receive.

3. Alan Pushkin’s “God’s Choice: The Total World of a Fundamentalist Christian School”

Method used: ethnographic research.

Moving from a fictional example to a real-life one, let’s analyze Alan Peshkin’s 1986 book “God’s Choice: The Total World of a Fundamentalist Christian School”.

Peshkin studied the culture of Bethany Baptist Academy by interviewing the students, parents, teachers, and members of the community alike, and spending eighteen months observing them to provide a comprehensive and in-depth analysis of Christian schooling as an alternative to public education.

The study highlights the school’s unified purpose, rigorous academic environment, and strong community support while also pointing out its lack of cultural diversity and openness to differing viewpoints. These insights are crucial for understanding how such educational settings operate and what they offer to students.

Even after discovering all this, Peshkin still presented the school in a positive light and stated that public schools have much to learn from such schools.

Peshkin’s in-depth research represents a qualitative study that uses observations and unstructured interviews, without any assumptions or hypotheses. He utilizes descriptive or non-quantifiable data on Bethany Baptist Academy specifically, without attempting to generalize the findings to other Christian schools.

4. Understanding buyers’ trends

Method used: record keeping.

Another way marketers can use quality research is to understand buyers’ trends. To do this, marketers need to look at historical data for both their company and their industry and identify where buyers are purchasing items in higher volumes.

For example, electronics distributors know that the holiday season is a peak market for sales while life insurance agents find that spring and summer wedding months are good seasons for targeting new clients.

5. Determining products/services missing from the market

Conducting your own research isn’t always necessary. If there are significant breakthroughs in your industry, you can use industry data and adapt it to your marketing needs.

The influx of hacking and hijacking of cloud-based information has made Internet security a topic of many industry reports lately. A software company could use these reports to better understand the problems its clients are facing.

As a result, the company can provide solutions prospects already know they need.

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Qualitative Research Approaches

Once the marketer has decided that their research questions will provide data that is qualitative in nature, the next step is to choose the appropriate qualitative approach.

The approach chosen will take into account the purpose of the research, the role of the researcher, the data collected, the method of data analysis , and how the results will be presented. The most common approaches include:

• Narrative : This method focuses on individual life stories to understand personal experiences and journeys. It examines how people structure their stories and the themes within them to explore human existence. For example, a narrative study might look at cancer survivors to understand their resilience and coping strategies.
• Phenomenology : attempts to understand or explain life experiences or phenomena; It aims to reveal the depth of human consciousness and perception, such as by studying the daily lives of those with chronic illnesses.
• Grounded theory : investigates the process, action, or interaction with the goal of developing a theory “grounded” in observations and empirical data. 
• Ethnography : describes and interprets an ethnic, cultural, or social group;
• Case study : examines episodic events in a definable framework, develops in-depth analyses of single or multiple cases, and generally explains “how”. An example might be studying a community health program to evaluate its success and impact.

How to Analyze Qualitative Data

Analyzing qualitative data involves interpreting non-numerical data to uncover patterns, themes, and deeper insights. This process is typically more subjective and requires a systematic approach to ensure reliability and validity. 

1. Data Collection

Ensure that your data collection methods (e.g., interviews, focus groups, observations) are well-documented and comprehensive. This step is crucial because the quality and depth of the data collected will significantly influence the analysis.

2. Data Preparation

Once collected, the data needs to be organized. Transcribe audio and video recordings, and gather all notes and documents. Ensure that all data is anonymized to protect participant confidentiality where necessary.

3. Familiarization

Immerse yourself in the data by reading through the materials multiple times. This helps you get a general sense of the information and begin identifying patterns or recurring themes.

Develop a coding system to tag data with labels that summarize and account for each piece of information. Codes can be words, phrases, or acronyms that represent how these segments relate to your research questions.

• Descriptive Coding : Summarize the primary topic of the data.
• In Vivo Coding : Use language and terms used by the participants themselves.
• Process Coding : Use gerunds (“-ing” words) to label the processes at play.
• Emotion Coding : Identify and record the emotions conveyed or experienced.

5. Thematic Development

Group codes into themes that represent larger patterns in the data. These themes should relate directly to the research questions and form a coherent narrative about the findings.

6. Interpreting the Data

Interpret the data by constructing a logical narrative. This involves piecing together the themes to explain larger insights about the data. Link the results back to your research objectives and existing literature to bolster your interpretations.

7. Validation

Check the reliability and validity of your findings by reviewing if the interpretations are supported by the data. This may involve revisiting the data multiple times or discussing the findings with colleagues or participants for validation.

8. Reporting

Finally, present the findings in a clear and organized manner. Use direct quotes and detailed descriptions to illustrate the themes and insights. The report should communicate the narrative you’ve built from your data, clearly linking your findings to your research questions.

Limitations of qualitative research

The disadvantages of qualitative research are quite unique. The techniques of the data collector and their own unique observations can alter the information in subtle ways. That being said, these are the qualitative research’s limitations:

1. It’s a time-consuming process

The main drawback of qualitative study is that the process is time-consuming. Another problem is that the interpretations are limited. Personal experience and knowledge influence observations and conclusions.

Thus, qualitative research might take several weeks or months. Also, since this process delves into personal interaction for data collection, discussions often tend to deviate from the main issue to be studied.

2. You can’t verify the results of qualitative research

Because qualitative research is open-ended, participants have more control over the content of the data collected. So the marketer is not able to verify the results objectively against the scenarios stated by the respondents. For example, in a focus group discussing a new product, participants might express their feelings about the design and functionality. However, these opinions are influenced by individual tastes and experiences, making it difficult to ascertain a universally applicable conclusion from these discussions.

3. It’s a labor-intensive approach

Qualitative research requires a labor-intensive analysis process such as categorization, recording, etc. Similarly, qualitative research requires well-experienced marketers to obtain the needed data from a group of respondents.

4. It’s difficult to investigate causality

Qualitative research requires thoughtful planning to ensure the obtained results are accurate. There is no way to analyze qualitative data mathematically. This type of research is based more on opinion and judgment rather than results. Because all qualitative studies are unique they are difficult to replicate.

5. Qualitative research is not statistically representative

Because qualitative research is a perspective-based method of research, the responses given are not measured.

Comparisons can be made and this can lead toward duplication, but for the most part, quantitative data is required for circumstances that need statistical representation and that is not part of the qualitative research process.

While doing a qualitative study, it’s important to cross-reference the data obtained with the quantitative data. By continuously surveying prospects and customers marketers can build a stronger database of useful information.

Quantitative vs. Qualitative Research

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Quantitative and qualitative research are two distinct methodologies used in the field of market research, each offering unique insights and approaches to understanding consumer behavior and preferences.

As we already defined, qualitative analysis seeks to explore the deeper meanings, perceptions, and motivations behind human behavior through non-numerical data. On the other hand, quantitative research focuses on collecting and analyzing numerical data to identify patterns, trends, and statistical relationships.  

Let’s explore their key differences: 

Nature of Data:

• Quantitative research : Involves numerical data that can be measured and analyzed statistically.
• Qualitative research : Focuses on non-numerical data, such as words, images, and observations, to capture subjective experiences and meanings.

Research Questions:

• Quantitative research : Typically addresses questions related to “how many,” “how much,” or “to what extent,” aiming to quantify relationships and patterns.
• Qualitative research: Explores questions related to “why” and “how,” aiming to understand the underlying motivations, beliefs, and perceptions of individuals.

Data Collection Methods:

• Quantitative research : Relies on structured surveys, experiments, or observations with predefined variables and measures.
• Qualitative research : Utilizes open-ended interviews, focus groups, participant observations, and textual analysis to gather rich, contextually nuanced data.

Analysis Techniques:

• Quantitative research: Involves statistical analysis to identify correlations, associations, or differences between variables.
• Qualitative research: Employs thematic analysis, coding, and interpretation to uncover patterns, themes, and insights within qualitative data.

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Research Question

Ai generator.

A research question serves as the foundation of any academic study, driving the investigation and framing the scope of inquiry. It focuses the research efforts, ensuring that the study addresses pertinent issues systematically. Crafting a strong research question is essential as it directs the methodology, data collection, and analysis, ultimately shaping the study’s conclusions and contributions to the field.

What is a Research Question?

A research question is the central query that guides a study, focusing on a specific problem or issue. It defines the purpose and direction of the research, influencing the methodology and analysis. A well-crafted research question ensures the study remains relevant, systematic, and contributes valuable insights to the field.

Types of Research Questions

Research questions are a crucial part of any research project. They guide the direction and focus of the study. Here are the main types of research questions:

1. Descriptive Research Questions

These questions aim to describe the characteristics or functions of a specific phenomenon or group. They often begin with “what,” “who,” “where,” “when,” or “how.”

• What are the common symptoms of depression in teenagers?

2. Comparative Research Questions

These questions compare two or more groups or variables to identify differences or similarities.

• How do the academic performances of students in private schools compare to those in public schools?

3. Correlational Research Questions

These questions seek to identify the relationships between two or more variables. They often use terms like “relationship,” “association,” or “correlation.”

• Is there a relationship between social media usage and self-esteem among adolescents?

4. Causal Research Questions

These questions aim to determine whether one variable causes or influences another. They are often used in experimental research.

• Does a new teaching method improve student engagement in the classroom?

5. Exploratory Research Questions

These questions are used when the researcher is exploring a new area or seeking to understand a complex phenomenon. They are often open-ended.

• What factors contribute to the success of start-up companies in the tech industry?

6. Predictive Research Questions

These questions aim to predict future occurrences based on current or past data. They often use terms like “predict,” “forecast,” or “expect.”

• Can high school GPA predict college success?

7. Evaluative Research Questions

These questions assess the effectiveness or impact of a program, intervention, or policy .

• How effective is the new community outreach program in reducing homelessness?

8. Ethnographic Research Questions

These questions are used in qualitative research to understand cultural phenomena from the perspective of the participants.

• How do cultural beliefs influence healthcare practices in rural communities?

9. Case Study Research Questions

These questions focus on an in-depth analysis of a specific case, event, or instance.

• What were the critical factors that led to the failure of Company X?

10. Phenomenological Research Questions

These questions explore the lived experiences of individuals to understand a particular phenomenon.

• What is the experience of living with chronic pain?

Research Question Format

A well-formulated research question is essential for guiding your study effectively. Follow this format to ensure clarity and precision:

• Begin with a broad subject area.
• Example: “Education technology”
• Define a specific aspect or variable.
• Example: “Impact of digital tools”
• Decide if you are describing, comparing, or investigating relationships.
• Example: “Effectiveness”
• Identify who or what is being studied.
• Example: “High school students”
• Formulate the complete question.
• Example: “How effective are digital tools in enhancing the learning experience of high school students?”

Sample Format: “How [specific aspect] affects [target population] in [context]?” Example: “How does the use of digital tools affect the academic performance of high school students in urban areas?”

Research Question Examples

Research questions in business.

• “What are the primary factors influencing customer loyalty in the retail industry?”
• “How does employee satisfaction differ between remote work and in-office work environments in tech companies?”
• “What is the relationship between social media marketing and brand awareness among small businesses?”
• “How does implementing a four-day workweek impact productivity in consulting firms?”
• “What are the emerging trends in consumer behavior post-COVID-19 in the e-commerce sector?”
• “Why do some startups succeed in attracting venture capital while others do not?”
• “How effective is corporate social responsibility in enhancing brand reputation for multinational companies?”
• “How do decision-making processes in family-owned businesses differ from those in publicly traded companies?”
• “What strategies do successful entrepreneurs use to scale their businesses in competitive markets?”
• “How does supply chain management affect the operational efficiency of manufacturing firms?”

Research Questions in Education

• “What are the most common challenges faced by first-year teachers in urban schools?”
• “How do student achievement levels differ between traditional classrooms and blended learning environments?”
• “What is the relationship between parental involvement and student academic performance in elementary schools?”
• “How does the implementation of project-based learning affect critical thinking skills in middle school students?”
• “What are the emerging trends in the use of artificial intelligence in education?”
• “Why do some students perform better in standardized tests than others despite similar instructional methods?”
• “How effective is the flipped classroom model in improving student engagement and learning outcomes in high school science classes?”
• “How do teachers’ professional development programs impact teaching practices and student outcomes in rural schools?”
• “What strategies can be employed to reduce the dropout rate among high school students in low-income areas?”
• “How does classroom size affect the quality of teaching and learning in elementary schools?”

Research Questions in Health Care

• “What are the most common barriers to accessing mental health services in rural areas?”
• “How does patient satisfaction differ between telemedicine and in-person consultations in primary care?”
• “What is the relationship between diet and the incidence of type 2 diabetes in adults?”
• “How does regular physical activity influence the recovery rate of patients with cardiovascular diseases?”
• “What are the emerging trends in the use of wearable technology for health monitoring?”
• “Why do some patients adhere to their medication regimen while others do not despite similar health conditions?”
• “How effective are community-based health interventions in reducing obesity rates among children?”
• “How do interdisciplinary team meetings impact patient care in hospitals?”
• “What strategies can be implemented to reduce the spread of infectious diseases in healthcare settings?”
• “How does nurse staffing level affect patient outcomes in intensive care units?”

Research Questions in Computer Science

• “What are the key features of successful machine learning algorithms used in natural language processing?”
• “How does the performance of quantum computing compare to classical computing in solving complex optimization problems?”
• “What is the relationship between software development methodologies and project success rates in large enterprises?”
• “How does the implementation of cybersecurity protocols impact the frequency of data breaches in financial institutions?”
• “What are the emerging trends in blockchain technology applications beyond cryptocurrency?”
• “Why do certain neural network architectures outperform others in image recognition tasks?”
• “How effective are different code review practices in reducing bugs in open-source software projects?”
• “How do agile development practices influence team productivity and product quality in software startups?”
• “What strategies can improve the scalability of distributed systems in cloud computing environments?”
• “How does the choice of programming language affect the performance and maintainability of enterprise-level software applications?”

Research Questions in Psychology

• “What are the most common symptoms of anxiety disorders among adolescents?”
• “How does the level of job satisfaction differ between remote workers and in-office workers?”
• “What is the relationship between social media use and self-esteem in teenagers?”
• “How does cognitive-behavioral therapy (CBT) affect the severity of depression symptoms in adults?”
• “What are the emerging trends in the treatment of post-traumatic stress disorder (PTSD)?”
• “Why do some individuals develop resilience in the face of adversity while others do not?”
• “How effective are mindfulness-based interventions in reducing stress levels among college students?”
• “How does group therapy influence the social skills development of children with autism spectrum disorder?”
• “What strategies can improve the early diagnosis of bipolar disorder in young adults?”
• “How do sleep patterns affect cognitive functioning and academic performance in high school students?”

More Research Question Examples

Research question examples for students.

• “What are the primary study habits of high-achieving college students?”
• “How do academic performances differ between students who participate in extracurricular activities and those who do not?”
• “What is the relationship between time management skills and academic success in high school students?”
• “How does the use of technology in the classroom affect students’ engagement and learning outcomes?”
• “What are the emerging trends in online learning platforms for high school students?”
• “Why do some students excel in standardized tests while others struggle despite similar study efforts?”
• “How effective are peer tutoring programs in improving students’ understanding of complex subjects?”
• “How do different teaching methods impact the learning process of students with learning disabilities?”
• “What strategies can help reduce test anxiety among middle school students?”
• “How does participation in group projects affect the development of collaboration skills in university students?”

Research Question Examples for College Students

• “What are the most common stressors faced by college students during final exams?”
• “How does academic performance differ between students who live on campus and those who commute?”
• “What is the relationship between part-time employment and GPA among college students?”
• “How does participation in study abroad programs impact cultural awareness and academic performance?”
• “What are the emerging trends in college students’ use of social media for academic purposes?”
• “Why do some college students engage in academic dishonesty despite awareness of the consequences?”
• “How effective are university mental health services in addressing students’ mental health issues?”
• “How do different learning styles affect the academic success of college students in online courses?”
• “What strategies can be employed to improve retention rates among first-year college students?”
• “How does participation in extracurricular activities influence leadership skills development in college students?”

Research Question Examples in Statistics

• “What are the most common statistical methods used in medical research?”
• “How does the accuracy of machine learning models compare to traditional statistical methods in predicting housing prices?”
• “What is the relationship between sample size and the power of a statistical test in clinical trials?”
• “How does the use of random sampling affect the validity of survey results in social science research?”
• “What are the emerging trends in the application of Bayesian statistics in data science?”
• “Why do some datasets require transformation before applying linear regression models?”
• “How effective are bootstrapping techniques in estimating the confidence intervals of small sample data?”
• “How do different imputation methods impact the results of analyses with missing data?”
• “What strategies can improve the interpretation of interaction effects in multiple regression analysis?”
• “How does the choice of statistical software affect the efficiency of data analysis in academic research?”

Research Question Examples in Socialogy

• “What are the primary social factors contributing to urban poverty in major cities?”
• “How does the level of social integration differ between immigrants and native-born citizens in urban areas?”
• “What is the relationship between educational attainment and social mobility in different socioeconomic classes?”
• “How does exposure to social media influence political participation among young adults?”
• “What are the emerging trends in family structures and their impact on child development?”
• “Why do certain communities exhibit higher levels of civic engagement than others?”
• “How effective are community policing strategies in reducing crime rates in diverse neighborhoods?”
• “How do socialization processes differ in single-parent households compared to two-parent households?”
• “What strategies can be implemented to reduce racial disparities in higher education enrollment?”
• “How does the implementation of public housing policies affect the quality of life for low-income families?”

Research Question Examples in Biology

• “What are the primary characteristics of the various stages of mitosis in eukaryotic cells?”
• “How do the reproductive strategies of amphibians compare to those of reptiles?”
• “What is the relationship between genetic diversity and the resilience of plant species to climate change?”
• “How does the presence of pollutants in freshwater ecosystems impact the growth and development of aquatic organisms?”
• “What are the emerging trends in the use of CRISPR technology for gene editing in agricultural crops?”
• “Why do certain bacteria develop antibiotic resistance more rapidly than others?”
• “How effective are different conservation strategies in protecting endangered species?”
• “How do various environmental factors influence the process of photosynthesis in marine algae?”
• “What strategies can enhance the effectiveness of reforestation programs in tropical rainforests?”
• “How does the method of seed dispersal affect the spatial distribution and genetic diversity of plant populations?”

Research Question Examples in History

• “What were the key social and economic factors that led to the Industrial Revolution in Britain?”
• “How did the political systems of ancient Athens and ancient Sparta differ in terms of governance and citizen participation?”
• “What is the relationship between the Renaissance and the subsequent scientific revolution in Europe?”
• “How did the Treaty of Versailles contribute to the rise of Adolf Hitler and the onset of World War II?”
• “What are the emerging perspectives on the causes and impacts of the American Civil Rights Movement?”
• “Why did the Roman Empire decline and eventually fall despite its extensive power and reach?”
• “How effective were the New Deal programs in alleviating the effects of the Great Depression in the United States?”
• “How did the processes of colonization and decolonization affect the political landscape of Africa in the 20th century?”
• “What strategies did the suffragette movement use to secure voting rights for women in the early 20th century?”
• “How did the logistics and strategies of the D-Day invasion contribute to the Allied victory in World War II?”

Importance of Research Questions

Research questions are fundamental to the success and integrity of any study. Their importance can be highlighted through several key aspects:

• Research questions provide a clear focus and direction for the study, ensuring that the researcher remains on track.
• Example: “How does online learning impact student engagement in higher education?”
• They establish the boundaries of the research, determining what will be included or excluded.
• Example: “What are the effects of air pollution on respiratory health in urban areas?”
• Research questions dictate the choice of research design, methodology, and data collection techniques.
• Example: “What is the relationship between physical activity and mental health in adolescents?”
• They make the objectives of the research explicit, providing clarity and precision to the study’s goals.
• Example: “Why do some startups succeed in securing venture capital while others fail?”
• Well-crafted research questions emphasize the significance and relevance of the study, justifying its importance.
• Example: “How effective are public health campaigns in increasing vaccination rates among young adults?”
• They enable a systematic approach to inquiry, ensuring that the study is coherent and logically structured.
• Example: “What are the social and economic impacts of remote work on urban communities?”
• Research questions offer a framework for analyzing and interpreting data, guiding the researcher in making sense of the findings.
• Example: “How does social media usage affect self-esteem among teenagers?”
• By addressing specific gaps or exploring new areas, research questions ensure that the study contributes meaningfully to the existing body of knowledge.
• Example: “What are the emerging trends in the use of artificial intelligence in healthcare?”
• Clear and precise research questions increase the credibility and reliability of the research by providing a focused approach.
• Example: “How do educational interventions impact literacy rates in low-income communities?”
• They help in clearly communicating the purpose and findings of the research to others, including stakeholders, peers, and the broader academic community.
• Example: “What strategies are most effective in reducing youth unemployment in developing countries?”

Research Question vs. Hypothesis

Chracteristics of research questions.

Research questions are fundamental to the research process as they guide the direction and focus of a study. Here are the key characteristics of effective research questions:

1. Clear and Specific

• The question should be clearly articulated and specific enough to be understood without ambiguity.
• Example: “What are the effects of social media on teenagers’ mental health?” rather than “How does social media affect people?”

2. Focused and Researchable

• The question should be narrow enough to be answerable through research and data collection.
• Example: “How does participation in extracurricular activities impact academic performance in high school students?” rather than “How do activities affect school performance?”

3. Complex and Analytical

• The question should require more than a simple yes or no answer and should invite analysis and discussion.
• Example: “What factors contribute to the success of renewable energy initiatives in urban areas?” rather than “Is renewable energy successful?”

4. Relevant and Significant

• The question should address an important issue or problem in the field of study and contribute to knowledge or practice.
• Example: “How does climate change affect agricultural productivity in developing countries?” rather than “What is climate change?”

5. Feasible and Practical

• The question should be feasible to answer within the constraints of time, resources, and access to information.
• Example: “What are the challenges faced by remote workers in the tech industry during the COVID-19 pandemic?” rather than “What are the challenges of remote work?”

6. Original and Novel

• The question should offer a new perspective or explore an area that has not been extensively studied.
• Example: “How do virtual reality technologies influence empathy in healthcare training?” rather than “What is virtual reality?”
• The question should be framed in a way that ensures the research can be conducted ethically.
• Example: “What are the impacts of privacy laws on consumer data protection in the digital age?” rather than “How can we collect personal data more effectively?”

8. Open-Ended

• The question should encourage detailed responses and exploration, rather than limiting answers to a simple yes or no.
• Example: “In what ways do cultural differences affect communication styles in multinational companies?” rather than “Do cultural differences affect communication?”

9. Aligned with Research Goals

• The question should align with the overall objectives of the research project or study.
• Example: “How do early childhood education programs influence long-term academic achievement?” if the goal is to understand educational impacts.

10. Based on Prior Research

• The question should build on existing literature and research, identifying gaps or new angles to explore.
• Example: “What strategies have proven effective in reducing urban air pollution in European cities?” after reviewing current studies on air pollution strategies.

Benefits of Research Question

Research questions are fundamental to the research process and offer numerous benefits, which include the following:

1. Guides the Research Process

A well-defined research question provides a clear focus and direction for your study. It helps in determining what data to collect, how to collect it, and how to analyze it.

Benefit: Ensures that the research stays on track and addresses the specific issue at hand.

2. Clarifies the Purpose of the Study

Research questions help to articulate the purpose and objectives of the study. They make it clear what the researcher intends to explore, describe, compare, or test.

Benefit: Helps in communicating the goals and significance of the research to others, including stakeholders and funding bodies.

3. Determines the Research Design

The type of research question informs the research design, including the choice of methodology, data collection methods, and analysis techniques.

Benefit: Ensures that the chosen research design is appropriate for answering the specific research question, enhancing the validity and reliability of the results.

4. Enhances Literature Review

A well-crafted research question provides a framework for conducting a thorough literature review. It helps in identifying relevant studies, theories, and gaps in existing knowledge.

Benefit: Facilitates a comprehensive understanding of the topic and ensures that the research is grounded in existing literature.

5. Focuses Data Collection

Research questions help in identifying the specific data needed to answer them. This focus prevents the collection of unnecessary data and ensures that all collected data is relevant to the study.

Benefit: Increases the efficiency of data collection and analysis, saving time and resources.

6. Improves Data Analysis

Having a clear research question aids in the selection of appropriate data analysis methods. It helps in determining how the data will be analyzed to draw meaningful conclusions.

Benefit: Enhances the accuracy and relevance of the findings, making them more impactful.

7. Facilitates Hypothesis Formation

In quantitative research, research questions often lead to the development of hypotheses that can be tested statistically.

Benefit: Provides a basis for hypothesis testing, which is essential for establishing cause-and-effect relationships.

8. Supports Result Interpretation

Research questions provide a lens through which the results of the study can be interpreted. They help in understanding what the findings mean in the context of the research objectives.

Benefit: Ensures that the conclusions drawn from the research are aligned with the original aims and objectives.

9. Enhances Reporting and Presentation

A clear research question makes it easier to organize and present the research findings. It helps in structuring the research report or presentation logically.

Benefit: Improves the clarity and coherence of the research report, making it more accessible and understandable to the audience.

10. Encourages Critical Thinking

Formulating research questions requires critical thinking and a deep understanding of the subject matter. It encourages researchers to think deeply about what they want to investigate and why.

Benefit: Promotes a more thoughtful and analytical approach to research, leading to more robust and meaningful findings.

How to Write a Research Question

Crafting a strong research question is crucial for guiding your study effectively. Follow these steps to write a clear and focused research question:

Identify a Broad Topic:

Start with a general area of interest that you are passionate about or that is relevant to your field. Example: “Climate change”

Conduct Preliminary Research:

Explore existing literature and studies to understand the current state of knowledge and identify gaps. Example: “Impact of climate change on agriculture”

Narrow Down the Topic:

Focus on a specific aspect or issue within the broad topic to make the research question more manageable. Example: “Effect of climate change on crop yields”

Consider the Scope:

Ensure the question is neither too broad nor too narrow. It should be specific enough to be answerable but broad enough to allow for thorough exploration. Example: “How does climate change affect corn crop yields in the Midwest United States?”

Determine the Research Type:

Decide whether your research will be descriptive, comparative, relational, or causal, as this will shape your question. Example: “How does climate change affect corn crop yields in the Midwest United States over the past decade?”

Formulate the Question:

Write a clear, concise question that specifies the variables, population, and context. Example: “What is the impact of increasing temperatures and changing precipitation patterns on corn crop yields in the Midwest United States from 2010 to 2020?”

Ensure Feasibility:

Make sure the question can be answered within the constraints of your resources, time, and data availability. Example: “How have corn crop yields in the Midwest United States been affected by climate change-related temperature increases and precipitation changes between 2010 and 2020?”

Review and Refine:

Evaluate the question for clarity, focus, and relevance. Revise as necessary to ensure it is well-defined and researchable. Example: “What are the specific impacts of temperature increases and changes in precipitation patterns on corn crop yields in the Midwest United States from 2010 to 2020?”

What is a research question?

A research question is a specific query guiding a study’s focus and objectives, shaping its methodology and analysis.

Why is a research question important?

It provides direction, defines scope, ensures relevance, and guides the methodology of the research.

How do you formulate a research question?

Identify a topic, narrow it down, conduct preliminary research, and ensure it is clear, focused, and researchable.

What makes a good research question?

Clarity, specificity, feasibility, relevance, and the ability to guide the research effectively.

Can a research question change?

Yes, it can evolve based on initial findings, further literature review, and the research process.

What is the difference between a research question and a hypothesis?

A research question guides the study; a hypothesis is a testable prediction about the relationship between variables.

How specific should a research question be?

It should be specific enough to provide clear direction but broad enough to allow for comprehensive investigation.

What are examples of good research questions?

Examples include: “How does social media affect academic performance?” and “What are the impacts of climate change on agriculture?”

Can a research question be too broad?

Yes, a too broad question can make the research unfocused and challenging to address comprehensively.

What role does a research question play in literature reviews?

It helps identify relevant studies, guides the search for literature, and frames the review’s focus.

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Research funding in the Middle East and North Africa: analyses of acknowledgments in scientific publications indexed in the Web of Science (2008–2021)

• Open access
• Published: 28 May 2024

Cite this article

You have full access to this open access article

• Jamal El-Ouahi   ORCID: orcid.org/0000-0002-3458-7503 1 , 2  

1 Altmetric

Funding acknowledgments are important objects of study in the context of science funding. This study uses a mixed-methods approach to analyze the funding acknowledgments found in 2.3 million scientific publications published between 2008 and 2021 by authors affiliated with research institutions in the Middle East and North Africa (MENA). The aim is to identify the major funders, assess their contribution to national scientific publications, and gain insights into the funding mechanism in relation to collaboration and publication. Publication data from the Web of Science is examined to provide key insights about funding activities. Saudi Arabia and Qatar lead the region, as about half of their publications include acknowledgments to funding sources. Most MENA countries exhibit strong linkages with foreign agencies, mainly due to a high level of international collaboration. The distinction between domestic and international publications reveals some differences in terms of funding structures. For instance, Turkey and Iran are dominated by one or two major funders whereas a few other countries like Saudi Arabia showcase multiple funders. Iran and Kuwait are examples of countries where research is mainly funded by domestic funders. The government and academic sectors mainly fund scientific research in MENA whereas the industry sector plays little or no role in terms of research funding. Lastly, the qualitative analyses provide more context into the complex funding mechanism. The findings of this study contribute to a better understanding of the funding structure in MENA countries and provide insights to funders and research managers to evaluate the funding landscape.

Avoid common mistakes on your manuscript.

Introduction

Funding organizations play a significant role in the advancement of science (Braun, 1998 ). In addition to funding provided to public universities and research institutions, they also fund researchers on specific and selective programs. Latour and Woolgar ( 1986 ) argue that scientific facts are not simply “discovered” but actively constructed through social processes in the laboratory. Funding acknowledgments in scientific papers are part of these processes. They give credit to individuals and organizations that contributed to the research. They are also used for self-promotion by researchers to show their connections to prestigious organizations, influential colleagues and well-funded projects (Latour & Woolgar, 1986 ). Analyzing funding acknowledgments can reveal hidden networks of scientific collaborations, social dynamics within and between research teams but also the social context and the dynamics that shaped the research reported in scientific publications (Cronin & Weaver, 1995 ). Since 2008, funding acknowledgments found in scientific publications have been captured in the Web of Science (Clarivate, 2022 ). Such data enables researchers to conduct analyses on funding sources (Alvarez-Bornstein & Montesi, 2021 ; Giles & Councill, 2004 ; Paul-Hus et al., 2016 ). Early research on funding acknowledgments analyzed the coverage by country, disciplines, and document types as well as methods to unify funding organizations (Álvarez-Bornstein et al., 2017 ; Costas & van Leeuwen, 2012 ; Sirtes & Riechert, 2014 ). Later, research analyzing funding acknowledgments focused on funding mechanisms. Möller ( 2019 ) identified the major funders and their contribution to the nationwide performance in five European countries. Wang et al. ( 2012 ) compared the research funding systems in ten countries and found that China is dominated by a single funder whereas the United Kingdom has more funding sources. Other studies focused on specific groups of countries such as the G9 countries (Huang & Huang, 2018 ), the Global South (Chankseliani, 2023 ), the BRICS (Shueb & Gul, 2023 ), or specific countries (Alvarez & Caregnato, 2018 , 2021 ; Álvarez-Bornstein et al., 2018 ; Costas & Yegros-Yegros, 2013 ; Díaz-Faes & Bordons, 2014 ; Gao et al., 2019 ; Gök et al., 2016 ). More recently, Chataway et al. ( 2019 ) analyzed the trends in science funding support in Sub-Saharan Africa and found that the levels of funding and cross-country engagement were low and that there was a need for capacity building. They also noted that there was a growing interest towards science funding in Sub-Saharan Africa at the national, regional, and international levels.

Traditionally, economies in MENA have been dependent and centralized around natural resources (World Bank, 2019 ). In the Middle East and North Africa (MENA), nations have been looking to become knowledge-based economies (OECD, 1996 ). For example, oil-exporting countries established research funds and new universities as part of their transition to knowledge economies (Currie-Alder, 2019 ). A report from UNESCO ( 2015 ) provides some insights into the funding of science in MENA. At that time, the investment in Research and Development reported by UNESCO was reported as low in the region. However, some changes were already taking place in terms of funding allocation, priority setting and promotion of collaboration to address large-scale societal challenges (Currie-Alder, 2019 ). Considerable investments in science and technology capacity have been made recently in MENA countries to promote research and innovation (Schmoch et al., 2016 ; Shin et al., 2012 ; Siddiqi et al., 2016 ). These investments resulted in the expansion of research funds over the past two decades in several Arabic-speaking countries (Currie-Alder, 2015 ; Currie-Alder et al., 2018 ) with research assessments privileging “collaboration with distant, scientifically proficient partners abroad, in order to connect with global networks and rise in international rankings of academic quality”.

To the best of my knowledge, no analysis of funding acknowledgments found in scientific publications has been conducted to better understand the structure and the trends of scientific funding for this specific region. This study aligns with a larger framework of scholarly communication where acknowledgments are used along authorship and citations as the “reward triangle” (Cronin & Weaver, 1995 ). This framework allows “a more nuanced understanding of scholarly communication and interaction” (Cronin, 1995 ). Analyses of funding acknowledgments reveal the broader research science ecosystem that sustains research activities. In this broader ecosystem, Cronin’s concept of “subauthors” encompasses the significant contributions and roles played by people and organizations in both the development of research and the writing of scientific papers (Cronin et al., 2003 ). Acknowledgments have also been frequently considered as “super citations” (Cronin et al., 1993 ). Acknowledgments and citations show a high level of cultural consensus, and both describe networks of interactions and influence (Cronin & Weaver, 1995 ). Since funding acknowledgments “provide a revealing window onto trends in collaboration beyond co-authorship” (Cronin & Weaver, 1995 ), their study may also inform research managers and policy makers by guiding funding strategies or by unveiling hidden synergies and influence that cannot be identified through regular co-authorship or citation analyses.

In the context of recent investments made in science and technology in MENA countries, this study compares the contribution of their research funders from the research publications perspective. This article explores the structure and the recent trends in science funding in MENA with reflections at the regional and national levels. This study also aims to better understand the funding mechanism in science with regard to collaboration and publishing.

More specifically, in this study, I address the following research questions:

To what extent has the funding structure evolved over the past few years in MENA?

What are the characteristics of the major funders in MENA, in terms of type and location?

These aspects provide insights into the landscape of funders in MENA. These insights are also particularly helpful for policymakers to better understand the funding structures in various national science systems.

This paper is organized as follows. “Data and methods” Section  describes the data and the methods used to analyze the funding acknowledgments in the MENA region. Then, the results of the analyses are presented in “Findings” Section Finally, the findings of this study are briefly discussed in “Discussion and conclusions” Section .

Data and methods

Geographic coverage.

According to the World Bank ( 2019 ), MENA consists of the following countries: Algeria, Bahrain, Djibouti, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Palestine, Qatar, Saudi Arabia (KSA), Syria, Tunisia, the United Arab Emirates (UAE) and Yemen. Pakistan, Afghanistan, and Turkey are also considered in this study as they are commonly included in the MENA region (MENAP and MENAT).

Data source

This analysis is based on the scientific publications indexed in the Web of Science Core Collection (WoS) which contains greater coverage of funding acknowledgments than other data sources such as Scopus or PubMed (Kokol & Vošner, 2018 ; Liu, 2020 ; Mugabushaka et al., 2022 ; Sterligov et al., 2020 ). All document types published between 2008 and 2021 with at least one author affiliated with an institution in MENA and indexed in one of the citation indexes of WoS are considered in this study. 2.3 M publications satisfy these criteria as of 31 October 2022.

Table 1 lists the number of publications (P) indexed in WoS for all the countries in MENA between 2008 and 2021 along with the proportion of international co-authorship (%Int). Countries with similar output levels in terms of scientific publications are shaded in Table  1 with the same color.

As also shown in Table  1 , it is worth reminding that these countries have different sizes in terms of population, Gross Domestic Product (GDP), Research and Development Expenditure (RDE as % of GDP) (World Bank, 2023 ), and funding structures that we aim to better understand in this study.

Data unification

WoS contains four fields with funding information (Clarivate, 2023 ):

Funding Text (FT): funding acknowledgments of the authors.

Funding Details (FD): descriptive grant data acquired from external grant repositories.

Grant Number (FG)

Funder (FO): name of the funding organization.

This study is based on the Funder names found in the Funding Text. Out of the 2.3 M publications in the dataset under study, close to 1.6 M (68%) do not contain funding data. A semi-automated process with human and manual quality checks was used to unify the non-unified FO names found in the remaining publications. This process is represented in Fig.  1 .

Semi-automated process of the standardization of funders names

There are many different variant names for each funding organization with many linked to only one or two publications. During this unification process, the objective was to identify and unify all the funders for each MENA country which contribute to at least 1% of the publications at the national level.

The first step of this unification process consists of extracting the FO variant names from the publications of the dataset under study. The frequency of occurrence is calculated for each variant. Next, the FO variant names are preprocessed by removing duplicates resulting in 41,182 unique variant names. A key step in the unification process is to create a controlled vocabulary of variant names by considering the most frequently used ones as proposed by Wang and Shapira ( 2011 ) and Sirtes ( 2013 ). The most frequent variants are then clustered by using fuzzy matching techniques provided by the Dataiku platform (Dataiku, 2023 ). 5,242 initial clusters are obtained as a result. These clusters are manually verified, and the incorrectly matched variant names are excluded from their initial clusters. The fuzzy matching algorithm is then reapplied on the labels of the obtained clusters, until no more clusters are created. The clustering is manually checked after each iteration.

The full names of the funders, found by searching the labels of the clusters on the web, were preferred as the unified names over their acronyms to avoid confusion between funders sharing the same acronyms across different countries. For example: “Ministry of Higher Education and Scientific Research” was preferred over “MOHESR”. When possible, based on the funding text, the country of origin of the funder is added for clarity to such ambiguous names. Also, in many cases, authors only mention the names of the funding programs in their acknowledgments. In such instances, the program names were searched on the Internet and linked to the preferred name of the corresponding FO in the controlled vocabulary.

For each unified name a country was assigned. The country of the funder is not always mentioned in the acknowledgments. Based on the funder’s name, a search on the internet allowed to find the relevant country of the funder. This information is used in the analyses to classify a funder as either domestic or foreign , from the perspective of the country of the related publications, but also as a funder located in or outside the MENA region. It is worth noting that some funders or programs are international. In such case, the relevant region or group of countries’ names were assigned (e.g. Europe, Arabia, South Asia…).

Then, a type was assigned to each funder by using the existing classification of funders defined by Clarivate and available in WoS and InCites (Clarivate, 2023 ): Academic, Academic System, Corporate, Global Corporate, Government, Health, National Academy, Nonprofit, Partnership, Research Council, and Research Institute. In most cases, applying this typology to funders was done as follows. For instance, if the name of a funder contained the string “Universi”, then the Academic type was assigned to this agency. Similarly, when “Minist” was found, the Government type was assigned. If “Hospital” or “hopit” was found in the agency name, the funder was classified as Health . Similarly, “council”, “conseil”, “conselho”, “consejo” were searched to assign the relevant type. Names of funders containing “Assoc” or “Foundation” or “Fondation” were classified as Nonprofit unless related to the government. Other strings such as “Inc”, “Corp”, “GMBH”, “LLC”, “Co Ltd” were evidence of a Corporate type, with the Global Corporate type defined as a company that operates in two or more countries. For the rest, similarly to the location assignment, web searches were used to assign the relevant type to the remaining funders.

As a simple example, “University Mohammed VI Polytechnic” is the official name of a university located in Morocco acknowledged as a funder and the preferred name of the following variant names:

Mohammed VI Polytechnic University

Mohammed VI Polytechnic University at Ben Guerir Morocco

Mohammed VI Polytechnic University de Benguerir Morocco

Mohammed VI Polytechnic University Morocco

Mohammed VI Polytechnic University of Benguerir

Mohammed VI Polytechnic University of Benguerir Morocco

Mohammed VI Polytechnic University UM6P of Ben Guerir Morocco

Mohammed VI Polytechnic University UM6P of Benguerir Morocco

University of Mohammed VI Polytechnic

University of Mohammed VI Polytechnic Ben Guerir Morocco

Welcome Grant From The Mohammed VI Polytechnic University UM6P of Ben Guerir Morocco

Welcome Grant of The Mohammed VI Polytechnic University UM6P

Mohammed VI Polytechnic University UM6P

University Mohammed VI Polytechnic

The following variant names could not be unified nor assigned to a single funder and a single country as there are multiple entities with the same name located in different countries around the world:

Deanship of the Scientific Research

Department of Obstetrics and Gynecology

Department of Scientific Research

Ministry of Public Health

Ministry of Science and Education

University of Technology

These variants were not included in the dataset under study.

Unified funders in MENA

Table 2 lists the number of unified funders in MENA before and after the unification process along with the share they represent across the region. 1,254 names of funders from 69 countries were already unified in WoS as of 31 October 2022, with 236 of them located in 8 MENA countries, mainly in Turkey and to a lesser extent in Egypt. After the unification, the dataset under study contains 1,039 unified names of funders from the 22 MENA countries as of 16 March 2023. The list of unified funders with their type and country is available in a data repository (El-Ouahi, 2023 ).

After the unification process, the unified names of the funders cover now all the MENA countries with Iran and Turkey dominating the region in terms of number of funders, followed by Pakistan, Saudi Arabia and Egypt. The number of funders varies between countries, reflecting differences in the size of countries in terms of funding capacity or publication level (as shown in Table  1 ) and also in funding structures.

Counting method and proportion of papers with funding acknowledgments

Various analyses were conducted using WoS data. A full counting method was used in this study, i.e., co-authored publications at the country level are fully counted as a publication of each country. Similarly, publications with acknowledgments of multiple funders at the country level were fully counted for each funder.

The number of funders and their contribution to each country’s publications depends also on the presence of foreign funding organizations which have provided funds to international co-authors. The foreign funding agencies acknowledged in scientific publications of MENA countries might have been acknowledged by international co-authors who collaborated with researchers based in MENA. Hence, in this study, an important distinction is made between the contribution of funders to international publications (IP, i.e., a country publication with at least one international co-author) and the contribution the funders have when considering only domestic publications (DP, i.e., a country publication without international co-authors).

The proportion of papers with funding acknowledgments (PWFAs) for a given country is defined as the number of papers from this country with funding acknowledgments divided by the total number of papers counted for that same country. The proportion of papers with funding acknowledgments is calculated for domestic publications (%DPWFA) and for international publications (%IPWFA).

Limitations

The analysis of funding acknowledgments is a complex task because such data is usually included in a separate section of a scientific paper in a non-structured way along with other types of acknowledgments (Cronin, 1995 ). Thus, analyzing funding acknowledgments from raw data and unifying the names of funders with a proper typology is not a straightforward task. Such analysis comes with certain limitations that one needs to be aware of when analyzing funding acknowledgments (Aagaard et al., 2021 ; Paul-Hus et al., 2016 ; Sirtes & Riechert, 2014 ; Tang et al., 2017 ; Wang & Shapira, 2015 ). There might be a certain impact of cultural factors on what authors acknowledge in their papers (Rigby, 2011 ); funding acknowledgments may focus on external funding bodies and may tend to significantly ignore internal resources received from the researchers’ own institutions. It has been shown that authors do not always acknowledge their funders (Costas & Yegros-Yegros, 2013 ) and that acknowledgment practices vary depending on research areas (Grassano et al., 2017 ). Hence, the analysis of funding acknowledgments may offer only a partial view on the landscape of funding organizations. Last, this study is limited to scientific papers published only in journals indexed in Web of Science. Álvarez-Bornstein et al. ( 2017 ) explored the completeness and accuracy of funding acknowledgments in the Web of Science and found that some funding information was lost in 12% of the articles of their dataset. Figure  2 shows the proportion of publications with funding acknowledgments that present complete funding information (FO, FT and FG) in the current study’s dataset.

Percentage of PWFAs with complete funding information (FO, FT and FG) in MENA countries and the World (2008–2021)

About 60% of the PWFAs from MENA published between 2008 and 2021 present complete funding information, i.e., the publications contain the FO, FT and FG information in their related records. This proportion varies by country. Turkey, Qatar and Saudi Arabia lead the region with more than 70% of their PWFAs containing complete funding information. By contrast, PWFAs from Djibouti, Syria and Iran show a proportion of about 40% of records with complete funding information.

All these caveats must be kept in mind when analyzing and interpreting funding data. Also, the specific funding level or the project types supported by the funders are not considered in this study. Despite all these limitations, the funding acknowledgments available in WoS provide an important information resource to answer questions related to research funding. More specifically, this data offers some opportunities to explore the source of the funding received by researchers in terms of location and type of funder. Also, the large scale of data availability allows for country comparisons.

Proportion of PWFAs by country

Before analyzing the unified funders, the proportion of papers with funding acknowledgments (PWFAs) is examined for each country in MENA. These proportions are shown in Fig.  3 , which also includes the share of PWFAs at the MENA and World levels as benchmarks. Here a distinction is made between the international publications of a country and its domestic publications, i.e., publications without international co-authors.

When looking at the international publications, the proportion of PWFAs is 61% for the World and 49% for the MENA region. Figure  3 shows that Saudi Arabia, Qatar, Pakistan and Djibouti lead the region in terms of proportion of IPWFAs. It is worth reminding that the countries in MENA have different levels of scientific output. For example, Yemen, Palestine, Libya, Syria, Bahrain, Afghanistan and Djibouti are countries with fewer than 7,500 WoS-indexed papers published between 2008 and 2021 and with a relatively high level of international co-authorship, as shown in Table  1 . Djibouti counts the lowest output with only 256 publications during the same period and has an international co-authorship rate of 92%. These countries show a much lower proportion of PWFAs for their domestic publications than for all their international publications. This suggests that a relatively high share of funders found in PWFAs of such countries might have been acknowledged by international co-authors who collaborated with researchers from these specific countries. In contrast, some other countries such as Iran, Kuwait show small differences in terms of proportions of PWFAs when comparing their publications with and without international co-authors.

Percentage of PWFAs for international (%IPWFA) and domestic publications (%DPWFA) in MENA countries and the World (2008–2021)

The trend of the proportion of the PWFAs for each MENA country over the study period is shown in Fig.  4 , with a distinction between the international publications of a country (%IPWFA) and its domestic publications (%DPWFA). The trends for the World and the MENA region are also included as benchmarks with dotted lines. This figure provides some additional insights into the evolution of the funding of scientific publications in MENA.

Trends of the percentage of publications with funding acknowledgments for domestic and international publications in MENA countries and the World (2008–2021)

One can notice the upward trends across most countries as well as in the World and MENA. These uptrends of the proportion of PWFAs can be observed in the international publications as well as in the domestic publications of each country. It is worth noting that the MENA countries as well as the world started from a relatively low level of PWFAs in 2008 (approximately 10% on average), which might be due to low coverage of funding acknowledgments in publications in WoS in 2008. Another reason could be a lack of funding acknowledgments made by researchers in their publications in the early years of the study period. Acknowledging funders explicitly in scientific publications might have been less common in the past than it is currently.

The countries are shown in Fig.  4 from the highest average proportion of PWFAs between 2008 and 2021 (top left) to the lowest (bottom right) when considering the international publications of the country. Saudi Arabia, Qatar and Pakistan lead the region. The high growth of the proportion of PWFAs in Saudi Arabia, Qatar and the UAE may also reflect the investment in research and funding policies recently set in these countries. In the early 2000s, according to its Seventh Development Plan, Saudi Arabia increased its total amount of spending on research and development activities with the goal to reach 2% of its GDP by 2025 (Kingdom of Saudi Arabia Ministry of Economy & Planning, 2000 ). This level of investment in research brought Saudi Arabia from being the 50th largest spender in the world in 2009 to the 16th rank in 2016; one example of such spending on research in Saudi Arabia consisted of the establishment of King Abdullah University of Science and Technology (KAUST) in 2009, which currently has a 20-billion-dollar endowment (Research Professional, 2020 ). This increase is also highlighted in the recent Saudi National Transformation Program 2020 (Saudi Arabia’s Vision 2030, 2020 ). Similarly, the Ministry of Education in the UAE set a target of 1.5% of its GDP for 2021 for the expenditure on research and development. In addition to internal funding for research provided by Higher Education Institutions in the UAE, a few national sources of funding are available, such as the Abu Dhabi Department of Education and Knowledge Award, the Sheikh Hamdan Award for Medical Sciences and more recently the National Fund or Sandooq Al Watan (Al Marzouqi et al., 2019 ). In Qatar, the Qatar National Research Fund (QNRF) was established in 2006 as a national organization with the mission to fund and promote research in Qatar as well as scientific research cooperation. As a result of such development, QNRF awarded $650 million in grants in the first 7 years of its existence (Weber, 2014 ).

For most countries, the trends in the proportion of PWFAs for domestic and international publications are similar, but some countries stand out. For instance, the differences between the proportion of PWFAs in international and domestic publications is relatively small for Iran, and Kuwait throughout the study period and for Qatar in recent years. The differences between the share of PWFAs in domestic and international publications are relatively constant for several countries such as Saudi Arabia, Lebanon, Jordan, Oman, United Arab Emirates, Morocco, Algeria and Bahrain. However, these differences are increasing for Yemen, Libya, Egypt and more specifically Pakistan and Tunisia, which both show a slight decrease of the share of PWFAs in its domestic publications in recent years.

Syria, and Afghanistan show downtrends in the share of PWFAs in recent years, which might be due to the recent conflicts or unrest in these countries. Figure  4 also reveals a decrease of the share of PWFAs around 2013 for some countries, such as Tunisia, Libya, or Yemen. It is unclear what caused these decreases. One reason could be the so-called Arab Spring which impacted several countries in the region. Then, the share of PWFAs increased in these countries in the following years. Science systems are particularly vulnerable to wars, social and political unrests, which limit the availability of funding granted to scientists or may even damage the national science systems.

Major funders in MENA

The unified data allows the identification of the major funders for each MENA country. Table 3 lists the number of major agencies for each country in MENA with the distinction between the publications of the country with and without international co-authors. Major funders are defined as agencies which contribute to at least 1% of a country’s total number of publications with and without international co-authors indexed in WoS.

These results suggest that MENA countries seem to have different structures of research funding systems. Several dozen funders appear in at least 1% of the national number of international publications in countries such as Palestine, Qatar and Morocco. It appears that these countries have more diversified funding sources than countries dominated by one or two major agencies like Algeria, Tunisia, Libya, and Bahrain. Other countries such as Djibouti, Afghanistan, Saudi Arabia, or Egypt show a few funders. However, when considering only domestic publications, there is a clear decrease in the number of funders for all the countries in MENA. This decrease is particularly greater for the countries with a relatively high rate of international co-authorship. Table 3 also allows to make a distinction between countries in MENA with only one or more funders based on their contributions to domestic publications. Saudi Arabia shows the highest number of funders acknowledged in domestic publications than any other country in MENA. Then Jordan, Lebanon, Iran, Qatar and the UAE follow. Then, several countries such as Morocco, Algeria, Tunisia or Pakistan count only one major funder contributing to domestic publications.

Overall, Table  3 provides a snapshot of the number of funders in the MENA countries. It provides some useful information about the potential funding support available for each country.

To better understand the structure of research funding in MENA, when available, Table  4 lists the three main funders for each country (CU) in MENA based on the related number of domestic publications with funding acknowledgments (DPWFAs), the proportion these publications represent over the total number of domestic publications (%DP) over the study period, the country of the funder (FCU) and its type.

Unsurprisingly, Table  4 lists almost exclusively domestic funders, except for Afghanistan, Djibouti and Syria. For some countries like Algeria, Morocco, Tunisia, Bahrain, and Turkey it was not possible to find three funders because they are dominated by a single funder. Then, the countries dominated by double funders include Iran, Iraq, Libya, and Tunisia. The academic sector is the most prominent contributor across MENA with 24 universities contributing more than 1% of the total number of domestic publications in their countries. Then, the government institutions, mainly ministries of higher education and research, national research centers, foundations, or funds. Libya and Yemen are not listed in Table  5 since there is no major funder acknowledged in their domestic publications.

When available, the top three funders of international publications are listed in Table  5 along with the number of publications with funding acknowledgments (IPWFAs), the related proportion (%IP) for the corresponding country of publication (CU) over the study period, the country of the funder (FCU) and its type. This table also provides some information in terms of source of funding support received. For most countries in MENA, the funders are government organizations or organizations related to government entities. One can also see that, for some countries, the academic sector appears as the major contributing funders type since the main universities of these countries contribute to a large proportion of the national output and are acknowledged in their scientific publications. These findings also show that most important funders in Middle East countries such as Saudi Arabia, UAE, Oman, Bahrain, and Jordan are universities by contrast to North African countries. Universities in the Middle East are granted direct government funds to support research initiatives in an independent way, however research funding is regulated through national calls for research projects in North Africa as confirmed previously by Currie-Alder ( 2015 ) and Hanafi and Arvanitis ( 2015 ).

Also, the location of the funders allows to distinguish countries dominated by domestic or foreign funders. Most countries in MENA have at least one major domestic funder contributing to international publications. Afghanistan, UAE, Bahrain, Egypt, Egypt, Palestine, Syria and Yemen are the exceptions. In the case of Egypt and Yemen, King Saud University in Saudi Arabia appears as a main funder. This might be due to non-Saudi researchers who are affiliated to Saudi institutions and list them as affiliations (Bhattacharjee, 2011 ) but also as funders. The United States of America, the United Kingdom, China, Japan, South Korea. Malaysia and some European countries such as France, Germany or Spain, are the locations of the main foreign funders. This suggests some relatively strong funding ties between specific countries and the MENA region. Saudi Arabia and Iran are the only countries in MENA appearing as a foreign location of one funder: King Saud University is the main funder in the case of Egypt and Yemen. Similarly, the National Institute of Health Research of Iran appears as a main funder located in MENA for Bahrain.

Location and type of major funders

To characterize further the funding landscape in MENA, the analysis of the location of all the major funders allows us to determine the geographical source of the funding granted to research projects in which researchers in the MENA region participated. Several distinctions can be made between domestic and foreign funders, but also between MENA and non-MENA funders. The contribution of all the funders by location is shown in Fig.  5 for each country in MENA based on the share of publications where their name appears in the funding acknowledgments.

Share of PWFAs of major funders in WoS with international co-authors (top) and only domestic authors (bottom) broken down by location type for each country in MENA (2008–2021)

When considering the international publications, Fig.  5 shows that several countries in MENA, such as Palestine, Afghanistan, Iraq, Libya, Algeria, Morocco and Bahrain have a significant share of contribution of foreign funders not located in MENA (top chart in Fig.  5 ). This might be due to the presence of foreign funders acknowledged by international co-authors in the related publications. It is also possible that some foreign funders have specific funding programs focused on collaboration with researchers located in MENA.

Countries like Tunisia, Oman, Jordan, Kuwait, Saudi Arabia, Pakistan, and Yemen show a higher involvement of both domestic and foreign funders (top chart). Turkey and Iran are dominated by one domestic funder as listed previously in Table  4 .

When focusing only on domestic publications, most MENA countries show an exclusive contribution of domestic funders (bottom chart). However, researchers located in a few MENA countries such as Djibouti, Syria and Afghanistan acknowledged foreign funders in a substantial share of their publications. Also, it is worth noting that Libya and Yemen do not show any major contribution of funders in their domestic publications.

It seems the distribution of funders by location has become diverse in recent years for specific countries in MENA. However, the level of diversity in funding sources varies between MENA countries. These findings partially reveal that some differences exist between countries in MENA in terms of domestic funding capabilities and funding structures with some science systems relying more on foreign funding support than other economies especially when considering their international co-publications.

Another characteristic of funders considered in this section is their type. In Fig.  6 , the contribution of funders based on the share of publications where they are acknowledged is broken down by type for each country in MENA. As for the top 3 funders shown in Table  4 , the government agencies seem to be the most active in the region in terms of research funding. Then, the academic funders, the nonprofit funding organizations and the research councils follow. Figure  6 also shows that some countries with a relatively high number of funders such as Qatar, Palestine, and Morocco have a contribution to international publications from a diverse range of agency types (right of the top chart). The chart also highlights the strong presence of government funders in all MENA countries and academic funders in most countries.

Share of PWFAs of major funders in WoS with international co-authors (top) and only domestic authors (bottom) broken by agency type for each country in MENA (2008–2021)

However, when focusing only on the domestic publications (bottom chart), the types of the funders are less diverse than in the international publications. The government and academic sectors appear to be the major contributors in terms of publications with funding acknowledgments. In most countries in MENA, the government and/or academic sector are even the sole major source of funding acknowledged in domestic publications. However, a few countries such as Oman, Kuwait, Qatar but also Egypt and Lebanon still show other types of funders including research institutes, nonprofit and research councils being also main domestic sources of funding.

These results are aligned with statistics reported by UNESCO ( 2015 ). The bulk of Global Expenditure on Research and Development (GERD) in many countries in MENA is reported to be performed mainly by the government sector, followed by the higher education sector. At the time of the report, the UNESCO also highlights that the private sector plays a small or no role in the research activities. However, some exceptions such as Jordan, Morocco, Oman, Qatar, Tunisia and the UAE where the private sector did contribute on average 25% of GERD. But such contribution is not necessarily reflected in the funding acknowledgments found in scientific publications as per the results of this study. This may suggest that these funding contributions are directly not visible in the scientific publications as the final outputs but may support other purposes such as funding of patenting activities or commercialization efforts. Also, the funding support provided to research and development activities may also simply be reflected in the affiliations of the authors of a scientific publication.

Qualitative analyses of funding acknowledgments in international publications

To complement the previous results, several qualitative analyses of funding acknowledgments found in distinct random samples of international publications were conducted.

Based on the previous scientometric analyses, the clarity of research funding remains a challenge when acknowledged in international publications. It is not very clear who the funding recipient is. The first random sample (S1) is composed of 100 random international papers with funding acknowledgments. The purpose of analyzing this sample is to gain deeper insights into the context of the funding reported in such international publications.

Tables 4 and 5 highlight the significant presence of universities in funding acknowledgments. In many instances, universities seem to play a funder role. Notably, in domestic publications (Table  4 ), universities appear to be prominent funding contributors. The second random sample (S2) contains 25 random papers with at least one university acknowledged as a funder. The aim of the analysis of this sample is to clarify the funding structure when a university is acknowledged in the funding statement of a scientific publication.

These two random samples were extracted from the in-house version of the Web of Science T-SQL database held at the Centre for Science and Technology Studies-CWTS (Leiden University). Random sampling SQL queries with relevant clauses were run to obtain the random samples (S1: 100 IPWFAs with at least an author from MENA. S2: 25 IPWFAs with at least one university acknowledged as a funder). The MENA countries these two random samples correspond to are shown in Fig.  7 .

Number of publications by MENA country for each random sample

The funding acknowledgments found in the papers of these two random samples were analyzed manually. The data was structured based on groups of recurring themes relevant to the research questions of this study.

A qualitative analysis of funding acknowledgments in 100 random international publications

Several elements were analyzed in the first random sample. Findings are reported in Table  6 . The first element of this analysis consists of analyzing whether the funding is attributed to specific author(s). 30% of the international publications with funding acknowledgments of this random sample contain information about the attribution of the reported funding support. In most cases, authors simply juxtaposition the funders from which they receive funding and do not mention who received the funding. In about two thirds of publications with attributable funding, the funding is granted to the international co-author.

Then, the second aspect of the manual analysis concerns the acknowledgment of the authors affiliations. About half of the publications show an acknowledgment of at least one of the affiliations of the authors, i.e., the employers of the researchers, and 46% of the publications contain the grant details of the funding support received by the authors.

Next, the locations of the acknowledged funders were also analyzed from the perspective of the MENA country for which the publication is counted. It is worth reminding that the IPWFAs are fully counted against the location of each acknowledged funder that can be of mixed origin, with a distinction between domestic funding (the funder shares the same location as the MENA country for which the publication is counted) and foreign funding (the funder is located in a foreign country in MENA or Non-MENA). The full counting of IPWFAs by funder location explains why the total percentage by funder location exceeds 100%. In this first random sample, the share of foreign funders from MENA and non-MENA countries is 79% and 9% respectively. However, the proportion of domestic funders is 42%.

Similarly, funders acknowledged in publications can be of mixed type and IPWFAs are fully counted towards each type. This also explains why the total percentage of IPWFAs by funder type exceeds 100%. This first random sample shows a relatively high variety of funders in terms of types. Government funders represent the highest share (64%), followed by academic (47%) and nonprofit ones (20%).

Overall, these findings confirm the results of “Major funders in MENA” Section found with regards to the locations and types of the acknowledged funders. Additionally, a substantial share of publications contains funding acknowledgments to the authors’ employers. However, the funding is attributed to specific authors in a lesser extent. In these international publications with attributable funding, about two thirds of them show that the funding is granted to the international co-author.

A qualitative analysis of 25 random publications with at least one university acknowledged as a funder

Like Table  6 , Table  7 lists the different elements analyzed in the second random sample consisting of 25 random publications with at least one university acknowledged as a funder. In this sample, the funding is explicitly attributed to a specific author in 24% of the publications. In most cases, authors simply juxtaposition the funders from which they receive funding without explicit attribution. Nevertheless, all the publications in this sample contain an acknowledgment of the university with which at least one of the authors is affiliated.

This sample consists of publications which mention at least one university as a funder which explains the 100% value for the proportion of publications with a funder of academic type. About one third of the publications of this sample also acknowledge a government funder. Global corporates are also acknowledged but in a much lesser extent (4%).

In terms of locations of the acknowledged funders, the share of foreign funders (MENA and non-MENA) in the first and second random samples are similar. However, the proportion of domestic funders is substantially higher in the second sample than in the first one, respectively 72% and 42%. In fact, in the second random sample, all the MENA authors acknowledge their employers, i.e., the universities where they work, as their funding providers. In most cases, the acknowledgments found in that sample consist of giving credit to the authors’ employers without specific details. In such instances, the authors may simply refer to the salaries they receive from their employers to conduct research. However, other funding acknowledgments provide more details in terms of received funding support (awards of grants with grant details, purchase of equipment, travel exchange programs, special projects, etc.).

Survey of 220 corresponding authors of IPWFAs

In order to contextualize the previous results, this section presents the findings of the survey of 220 corresponding authors of 220 IPWFAs constituting the third random sample (10 publications for each country in MENA). The corresponding authors of these papers were contacted by email with a series of open and closed questions related to the funding reported in their publications. Each email was personalized, featuring title and a direct link to the related IPWFA but also the list of acknowledged funders. The primary objectives of these questions were to determine whether:

The reported funding was dedicated to a specific research project, or if the funding was internal (e.g., salaried research time),

The funding was shared among co-authors,

And whether there were any requirements regarding international collaboration with specific countries.

28 responses were received, representing a response rate of 12.7%. Response rates of surveys vary based on multiple factors such as the employed survey method, the demographics of the surveyed population, or the field (Langfeldt et al., 2023 ). However, 12.7% is higher than what is observed in a similar online email survey of researchers (Ni & Waltman, 2023 ).

The countries of affiliation of the 28 corresponding authors of the IPWFAs, at the time of publication, are listed in Table  8 . MENA countries are marked with an asterisk symbol. It is worth reminding that the corresponding authors of international publications were not necessarily from MENA at the time of publication of the IPWFAs under study and that some corresponding authors had multiple affiliations from different countries.

Quotes are reported in this section to illustrate the findings. These responses were grouped under three topics:

The distinction between funding received for a dedicated research project and the internal funding or salary received from the author’s employer to do research,

The distinction between research projects where the funding is shared among all co-authors and the juxtaposition of research funding acknowledged in publications,

And requirements in terms of international collaboration.

Dedicated funding versus salaried research time

Out of the 28 responses, 10 authors clarified that the funding support they received was dedicated to the research reported in their paper. Several answers provide insights into the distinction between research funding dedicated to specific projects and the internal funding or salary received from the authors’ employers to conduct research. The authors’ statements emphasize the source and purpose of the funding they received, clarifying the nature of financial support for their research activities.

In the first two quotes below, the funding is explicitly described as being provided for dedicated research projects. The mention of the French Ministry of Foreign Affairs and the University Grants Commission highlights the origin of these funds, which were granted for specific research initiatives. This indicates that the research was intentionally supported by external and specific entities, underlining the clear distinction between these funds and internal resources. Here, the funding is attributed through PhD programs.

The first author was a PhD student at that time and these funds were granted from the French ministry of foreign affairs.

In the second quote below, the author also mentions specific programs with the pharmaceutical industry. This may suggest a close collaboration between the author’s university and the pharmaceutical company which funds specific research projects.

Yes, it was a funded project. I was a Ph.D. student on this project. This project was granted by UGC [University Grants Commission] to my supervisor. This research was funded through pharmaceutical research programs.

The following quote illustrates how dedicated funding was provided for investigating a specific topic, in this case, waterpipe tobacco smoking. The grant was awarded by a major funder, the US National Institutes of Health, aligning the financial support directly with the research subject. This quote also emphasizes the targeted nature of funding for research purposes.

The two US National Institutes of Health grants (one from the National Institute on Drug Abuse and the other from the National Cancer Institute) that were cited in the publication were both awarded for the investigative team to study waterpipe tobacco smoking, which is the subject of the publication. So, yes, this funding was provided (in part) and "dedicated" for the purpose of studying the questions that were addressed in this publication. We were also funded to address other questions on the same topic (waterpipe tobacco smoking)

The final quote provides an example where the research did not receive dedicated funding. Instead, the authors’ institutions were contracted to provide technical support, leading to collaborative publications resulting from this collaboration. This scenario demonstrates how research outputs can arise from support work, even when the funding is not explicitly dedicated to the research at hand. The author also clearly mentions that, in some cases, scientific publications are expected to be produced from certain types of technical and research works.

We did not receive dedicated funding for the research in this paper. Johns Hopkins Bloomberg School of Public Health (JHSPH) and the Indian Institute of Health Management Research (IIHMR) were contracted by the Ministry of Public Health of Afghanistan as a third party to support monitoring and evaluation of their basic and hospital package of services. However, this work resulted in many joint publications between JHSPH and IIHMR researchers and MoPH officials. Institutions such as Hopkins pretty much expect publications to result from all technical support work.

Overall, these quotes clarify the significance of understanding the source, purpose, and intentions behind research funding. The distinction between funding dedicated to specific projects and internal resources is crucial for accurately assessing the financial landscape of scientific research.

Shared funding among co-authors or juxtaposition of research funding?

Out of 28 responses, 4 authors mentioned that the received funding was shared among the co-authors. Several answers from the corresponding authors allows to make the distinction between research projects where funding is shared among all co-authors and projects where each researcher reports their individual funding. Their answers emphasize how funding is allocated, acknowledged, and used within collaborative research efforts.

The first two quotes are instances where the funding is distributed among co-authors. In the first quote, the authors highlight that some co-authors received salaries from the reported funding, underscoring the shared nature of the financial support.

A couple of co-authors received salary from the reported funding to carry out the studies.

The second quote indicates that salaries for multiple authors were drawn from the combined funding sources, reinforcing the collaborative aspect of the project.

This paper was the result of a collaboration that was supported by a grant that I received from the Swiss National Science Foundation, as well as funding from the Leenards and Jeantet Foundations. Salaries for 7 of the authors were drawn from these fundings.

In contrast, the acknowledged funding is not shared by co-authors in most cases. The authors tend to mention and use independently the funding they receive. The subsequent quotes reveal situations where acknowledged funding is not shared among co-authors. Authors simply mention and utilize individual funding independently, indicating a non-shared funding approach.

Maziak, Rastam, Ibrahim and Ward were funded by (and salary supported by) DA024876, while Shihadeh was funded by (and salary supported by) CA120142). Eissenberg was funded by (and salary supported by) both DA024786 and CA120142.

This approach seems more frequent in cases where co-authors have distinct funding sources, as showcased in quotes where different co-authors used different funding sources based on their country of origin.

Different co-authors used different funding sources. Netherlands’ and Turkish funding was granted to the authors from The Netherlands and Turkey.

The two quotes below provide context into projects where external funding is not the primary factor behind collaboration. In one case, the research was not externally funded, and the authors leveraged their own affiliations for acknowledgment.

This was not externally funded. The study was run by a PhD student (who was externally funded by the Libyan government to do her PhD) and myself (fully funded by the University of Liverpool). We could have described it as ‘Funded by the Libyan Government’ – but they funded the student to do the PhD, not the clinical trial. So, we just used University of Liverpool as that is my university and the place of the PhD.

In another, the collaboration is driven by shared research interests rather than shared funding.

I knew Victor and Wissem much earlier than the time when we wrote the paper. The fact we share mathematical research interest is the only reason why we collaborated. There is no special shared funding relating to this article/work. The mentioned grants were used by the specified authors only.

These quotes collectively highlight the diverse approaches to acknowledging and sharing research funding among co-authors. While some collaborations involve shared financial resources, others rely on individual funding sources. This variability reflects the complexity of funding dynamics within collaborative research projects, where both shared and non-shared funding models play a role in driving scientific research activities.

International collaboration requirements

The survey of the corresponding authors also offers insights into the requirements imposed by funders for international collaborations in specific research projects. Their answers illustrate how the support provided by funders can influence the nature and extent of collaboration between researchers from different countries.

The first quote below points to a collaboration facilitated by the supervisor of a PhD student. This suggests that the collaboration was likely influenced by the co-author’s institutional connection, showcasing how affiliations with specific organizations can drive international collaboration.

The co-author was my PhD advisor who worked in Intergovernmental Authority on Development (IGAD), Djibouti

In the following quote, the mention of a postdoctoral funded by the Higher Education Commission in Pakistan and completed in Japan highlights the role of funding from a specific country in fostering international scientific mobility and collaborations for advanced research positions.

This was a Pakistan HEC post doc funding which was completed in Japan.

The third quote below reveals a certain commitment and intentions to geographical diversity and capacity building. For instance, the following quote is related to a project funded by internal budgets that emphasizes the importance of Global North–South scientific collaboration.

It [the funding] was only used for the PhD grant and the PhD student travels between the two involved countries, France and Tunisia. The reason for [my] collaboration with a colleague from Tunisia was to promote North-South scientific collaboration, training young south countries students. As a French researcher, I am particularly involved in such cooperations.

The subsequent quotes point to instances where internal budgeting and affiliations drive collaborations. In these cases, the funding sources may not be tied to external expectations for international collaboration but enable opportunities for researchers to engage across borders.

This research projected was supported by the Center’s internal budget. It was internal research funding. The colleague at the time of the research was affiliated to our institution and had assumed a position at Qatar University.

Another example specifies that temporary or visiting positions also play a critical role in funding support and funding acknowledgment:

I visited the biology department at Sultan Qaboos university [which funded the research project], there was an opportunity to collaborate on a small project.

In a different scenario described below, collaboration arises informally due to shared interests and complementary scientific disciplines. The collaboration is driven by the mutual benefits each researcher brings to the project, highlighting how rigor in research is promoted through transdisciplinary teamwork.

We are all close friends working from complementary scientific disciplines (Engineering, Epidemiology, Medicine, Psychology). We continue to work together in a collegial and transdisciplinary fashion today. We work together because each of us makes the work more rigorous, more revealing scientifically, and more fun.

In addition to specific required expertise, the facilities or equipment available in some research institutions also play a role in shaping collaborations and support acknowledged by authors. For instance, in the following quote, the author mentions that the co-author was instrumental in doing specific sample analyses that the corresponding author would not have been able to do in his own institution.

The funding was provided by the university [Izmir Institute of Technology], and it was used solely to finance the required chemicals and sample analysis. There were no conditions in terms of international collaboration. The colleague from Germany was helpful in some key sample analysis.

Finally, a corresponding author explains that the international collaboration with researchers from specific countries was a requirement from a funder supporting the research project.

Yes, this funding was dedicated to this research project. EURAPMON and Greater Los Angeles Zoo Association are the funders. And this funding was also used by co-authors. It was required from ERAPMON to collaborate with colleagues from specific countries [Djibouti, Oman] but there was no such a requirement from GLAZA.

Overall, these quotes showcase a range of international collaborations driven by various funding sources and motivations. Whether it is funders’ requirements, institutional affiliations, specific funding programs, or personal connections, funders also play a crucial role in shaping the global collaborative landscape in scientific research.

Discussion and conclusions

The aim of this study was to better understand the funding structure of scientific research in the Middle East and North Africa (MENA) region based on the funding acknowledgments found in scientific publications. An important element to consider when analyzing funding acknowledgments is the distinction between domestic publications and international publications. The recent increase of international co-authorship in scientific publications likely explains why some countries in MENA show a relatively high level of contribution of foreign funders. These foreign funders may have financially supported researchers who have co-authored scientific publications with researchers located in MENA. Also, the analysis of domestic publications reveals the contribution of the main domestic funders but also the role some foreign funders play in funding domestic research.

First, this study shows that the proportions of publications with funding acknowledgments vary greatly across MENA countries. Overall, countries in MENA have lower proportions of publications with funding acknowledgments than the World. Saudi Arabia and Qatar top the list with about half of their publications containing a funding acknowledgment. This may demonstrate the high level of funding available at a country level, but one needs to remember that some factors might impact what authors acknowledge in their publications. There are many reasons that influence the inclusion or exclusion of acknowledgments in scientific publications. For example, the presence of funding acknowledgments might be a requirement of the funder which supported financially the authors (Alvarez & Caregnato, 2018 ). In collaborations for multicentric medical research, minor contributors who do not qualify for authorship are often recognized with acknowledgments because of some journals’ editorial policies limiting the number of authors per article (Alvarez & Caregnato, 2021 ). Researchers paid by their employer such as a public university to do research, may be considered to be funded by the government but this would not necessarily be reported as a funding acknowledgment in their publications. In this case, the researcher’s affiliation may better reflect the support of their research institution as a funder.

The share of publications with funding acknowledgments follows an uptrend across all MENA countries except in countries which have witnessed conflicts or unrests in the recent years. Next, the names of the funding organizations found in the funding acknowledgments of scientific publications indexed in Web of Science (WoS) were unified. This unification process reveals a diverse funding landscape with Iran, Turkey, Saudi Arabia and Egypt having the largest number of domestic funding organizations in the region. The difference in terms of number of funders might be explained by the size of the respective country but also by the different national funding structures.

Three groups of countries in MENA can be distinguished as per their number of funders: when considering all their publications, some countries like Qatar, Palestine and Morocco are dominated by several dozen funders contributing to at least 1% of the total number of national publications; then other countries such as Saudi Arabia, the UAE, Kuwait or Pakistan rely mainly on a few funders. Finally, countries like Turkey or Iran are dominated by one or two funders. However, when analyzing only the domestic publications, then the findings reveal only a few major domestic funders for most countries in MENA.

The findings also show the contribution of domestic and foreign funders to the scientific output of each country. Some countries, like Turkey, Iran, Oman, Kuwait, Jordan and Saudi Arabia, have a relatively high level of contribution of domestic funders mentioned in their scientific papers. In contrast, other countries in MENA seem to rely more on foreign funding sources.

The main funders found in scientific publications in MENA are government and academic organizations. This is not surprising since most of the scientific research in MENA is conducted by public universities funded by the governments and more specifically by the Ministry of Higher Education and Research or equivalent national institutions. Nevertheless, this study also shows the funding contributions of other sectors or types such as nonprofit institutions, research councils or national academies. Corporations appear as funders mainly in international scientific publications, but their contribution is much less visible. Public–private partnerships, and more specifically collaboration between the public and the private sector, have gained traction in scientific research funding in recent years and help to accelerate the translation of research into practical applications.

The different qualitative analyses allow a better understanding of the funding reported by authors in funding publications. More specifically, they clarified when the funding was attributed to specific authors, whether the funding was internal or external, and if it was dedicated to a specific project. Furthermore, the responses received from the surveyed corresponding authors shed light on collaborations observed in international co-authored publications. These analyses contribute to the limited body of qualitative studies on acknowledgments in science from the perspective of researchers (Alvarez & Caregnato, 2020 ; Cronin & Overfelt, 1994 ; Roa‐Atkinson & Velho, 2005 ). They confirm the important role played by acknowledgments in the primary communication process and also contribute to the literature about the operationalization of funding (Aagaard et al., 2021 ). The attribution and the amalgamation (fusion or juxtaposition) of funding are revealed by the employed qualitative methods and provide context on the collaboration between co-authors (Alvarez & Caregnato, 2020 ).

This study also contributes to a growing literature on research funding (Gök et al., 2016 ) which concerns various stakeholders: governments, public and private funding institutions, universities, research managers, and researchers. Several MENA countries have made investments in science and technology capacity to promote research and innovation (Schmoch et al., 2016 ; Shin et al., 2012 ; Siddiqi et al., 2016 ). Policy makers also changed their research governance (Currie-Alder, 2019 ). For instance, Arab countries have set national research priorities and changed the way to access public funding. Research funds expanded over the past two decades (Currie-Alder, 2015 ) and incentives were set to collaborate with distant and scientifically proficient foreign partners to connect with global scientific networks and improve the rank or Arab research organizations in international rankings of academic quality (Currie-Alder, 2019 ; Currie-Alder et al., 2018 ).

This present study sheds light on the recent trends on the landscape of funding in scientific research conducted in MENA. While the findings are significant, the analysis of funding acknowledgments comes with limitations which may underestimate the role of institutional funding which researchers do not always mention explicitly in their acknowledgments. In fact, researchers also mention the institutional funding their received by reporting their institutional affiliations in their scientific publications. Although some limitations exist, this study provides insights into the structure of scientific funding in MENA especially in terms of funding source, type and funding trends. These insights can be used by policy makers to monitor and design their research funding programs (Alvarez-Bornstein & Montesi, 2021 ; Paul-Hus et al., 2016 ; Wang & Shapira, 2015 ). For instance, from a funding policy and research evaluation perspective, policymakers could examine whether researchers in specific countries who received funding have produced any scientific publications (Albrecht et al., 2009 ; Alvarez & Caregnato, 2018 , 2021 ; Álvarez-Bornstein et al., 2018 ; Costas & Yegros-Yegros, 2013 ; Díaz-Faes & Bordons, 2014 ; Gao et al., 2019 ; Gök et al., 2016 ). Another example may consist of determining the trends in financing a specific subject or research area has received (Dorsey et al., 2006 ). Other works using funding acknowledgments have involved the mapping of funders to specific fields (Lewison & Dawson, 1998 ; Lewison et al., 2001 ) or specific funding programs (Boyack & Börner, 2003 ). Rangnekar ( 2005 ) also conducted an analysis of the mention of the Multiple Sclerosis Society, as a funder, within multiple sclerosis-related publications to analyze its visibility, its research orientations as well as its impact.

Finally, the results of this study open doors to new research opportunities. This study also reveals that funding acknowledgments data is a valuable starting point to understand funding structures and funding mechanisms. For instance, future work could focus on transnational research funding and how different forms of funding are used and reported by researchers. More specifically, future research may seek to analyze the collaboration and co-funding networks by country at the research area level, which may provide useful insights into the structures of funding mechanisms with regards to collaboration and research fields. The recent expansion of grant data coverage through the integration of Pivot-RP data in WoS Footnote 1 means that more records in WoS will have funding information for the first time and may also open doors to more granular analyses including the funding types (e.g. research, training, awards, collaboration agreement, travel, postdoctoral award, etc.). However, this study also reveals the complexity hidden in funding acknowledgments and the importance of both quantitative and qualitative methods to reveal information not explicitly communicated in funding acknowledgments. Ideally, to use funding acknowledgments quantitatively, authors will need to be more explicit about the funding context of their research. Scientific journals, conferences, books editors and preprint servers may have an important role to play in streamlining the funding information communicated by authors. Achieving a complete standardization of funding acknowledgments may not be feasible, necessitating an enduring need for qualitative analyses. Such quantitative and qualitative analyses are expected to better inform the policy makers on the funding structure of national science systems in MENA. They are also expected to provide insights on how the national science systems can best be funded in the near future.

Data availability

The research presented in this paper uses Web of Science data made available by Clarivate. The author is not allowed to share this data. However, the list of unified funders with their type and country is available in a data repository (El-Ouahi, 2023 ).

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Acknowledgements

I would like to thank Ludo Waltman and Thomas Franssen for their insightful comments and valuable suggestions that greatly improved the quality of this paper. I extend my gratitude to two anonymous reviewers whose comments enhanced the quality of this article.

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El-Ouahi, J. Research funding in the Middle East and North Africa: analyses of acknowledgments in scientific publications indexed in the Web of Science (2008–2021). Scientometrics (2024). https://doi.org/10.1007/s11192-024-04983-8

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Received : 16 September 2023

Accepted : 28 February 2024

Published : 28 May 2024

DOI : https://doi.org/10.1007/s11192-024-04983-8

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