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4 Gathering and Analyzing Qualitative Data

Gathering and analyzing qualitative data.

As the role of clinician researchers expands beyond the bedside, it is important to consider the possibilities of inquiry beyond the quantitative approach. In contrast to the quantitative approach, qualitative methodology is highly inductive and relies on the background and interpretation of the researcher to derive meaning from the gathering and analytic processes central to qualitative inquiry.

Chapter 4: Learning Objectives

As you explore the research opportunities central to your interests to consider whether qualitative component would enrich your work, you’ll be able to:

• Define what qualitative research is
• Compare qualitative and quantitative approaches
• Describe the process of creating themes from recurring ideas gleaned from narrative interviews

What Is Qualitative Research?

Quantitative researchers typically start with a focused research question or hypothesis, collect a small amount of numerical data from a large number of individuals, describe the resulting data using statistical techniques, and draw general conclusions about some large population. Although this method is by far the most common approach to conducting empirical research in fields such as respiratory care and other clinical fields, there is an important alternative called qualitative research. Qualitative research originated in the disciplines of anthropology and sociology but is now used to study psychological topics as well. Qualitative researchers generally begin with a less focused research question, collect large amounts of relatively “unfiltered” data from a relatively small number of individuals, and describe their data using nonstatistical techniques, such as grounded theory, thematic analysis, critical discourse analysis, or interpretative phenomenological analysis. They are usually less concerned with drawing general conclusions about human behavior than with understanding in detail the experience of their research participants.

Consider, for example, a study by researcher Per Lindqvist and his colleagues, who wanted to learn how the families of teenage suicide victims cope with their loss (Lindqvist, Johansson, & Karlsson, 2008). They did not have a specific research question or hypothesis, such as, What percentage of family members join suicide support groups? Instead, they wanted to understand the variety of reactions that families had, with a focus on what it is like from their perspectives. To address this question, they interviewed the families of 10 teenage suicide victims in their homes in rural Sweden. The interviews were relatively unstructured, beginning with a general request for the families to talk about the victim and ending with an invitation to talk about anything else that they wanted to tell the interviewer. One of the most important themes that emerged from these interviews was that even as life returned to “normal,” the families continued to struggle with the question of why their loved one committed suicide. This struggle appeared to be especially difficult for families in which the suicide was most unexpected.

The Purpose of Qualitative Research

The strength of quantitative research is its ability to provide precise answers to specific research questions and to draw general conclusions about human behavior. This method is how we know that people have a strong tendency to obey authority figures, for example, and that female undergraduate students are not substantially more talkative than male undergraduate students. But while quantitative research is good at providing precise answers to specific research questions, it is not nearly as good at generating novel and interesting research questions. Likewise, while quantitative research is good at drawing general conclusions about human behavior, it is not nearly as good at providing detailed descriptions of the behavior of particular groups in particular situations. And quantitative research is not very good at communicating what it is actually like to be a member of a particular group in a particular situation.

But the relative weaknesses of quantitative research are the relative strengths of qualitative research. Qualitative research can help researchers to generate new and interesting research questions and hypotheses. The research of Lindqvist and colleagues, for example, suggests that there may be a general relationship between how unexpected a suicide is and how consumed the family is with trying to understand why the teen committed suicide. This relationship can now be explored using quantitative research. But it is unclear whether this question would have arisen at all without the researchers sitting down with the families and listening to what they themselves wanted to say about their experience. Qualitative research can also provide rich and detailed descriptions of human behavior in the real-world contexts in which it occurs. Among qualitative researchers, this depth is often referred to as “thick description” (Geertz, 1973) .

Similarly, qualitative research can convey a sense of what it is actually like to be a member of a particular group or in a particular situation—what qualitative researchers often refer to as the “lived experience” of the research participants. Lindqvist and colleagues, for example, describe how all the families spontaneously offered to show the interviewer the victim’s bedroom or the place where the suicide occurred—revealing the importance of these physical locations to the families. It seems unlikely that a quantitative study would have discovered this detail. The table below lists some contrasts between qualitative and quantitative research

Data Collection and Analysis in Qualitative Research

Data collection approaches in qualitative research are quite varied and can involve naturalistic observation, participant observation, archival data, artwork, and many other things. But one of the most common approaches, especially for psychological research, is to conduct interviews. Interviews in qualitative research can be unstructured—consisting of a small number of general questions or prompts that allow participants to talk about what is of interest to them—or structured, where there is a strict script that the interviewer does not deviate from. Most interviews are in between the two and are called semi-structured interviews, where the researcher has a few consistent questions and can follow up by asking more detailed questions about the topics that come up. Such interviews can be lengthy and detailed, but they are usually conducted with a relatively small sample. The unstructured interview was the approach used by Lindqvist and colleagues in their research on the families of suicide victims because the researchers were aware that how much was disclosed about such a sensitive topic should be led by the families, not by the researchers.

Another approach used in qualitative research involves small groups of people who participate together in interviews focused on a particular topic or issue, known as focus groups. The interaction among participants in a focus group can sometimes bring out more information than can be learned in a one- on-one interview. The use of focus groups has become a standard technique in business and industry among those who want to understand consumer tastes and preferences. The content of all focus group interviews is usually recorded and transcribed to facilitate later analyses. However, we know from social psychology that group dynamics are often at play in any group, including focus groups, and it is useful to be aware of those possibilities. For example, the desire to be liked by others can lead participants to provide inaccurate answers that they believe will be perceived favorably by the other participants. The same may be said for personality characteristics. For example, highly extraverted participants can sometimes dominate discussions within focus groups.

Data Analysis in Qualitative Research

Although quantitative and qualitative research generally differ along several important dimensions (e.g., the specificity of the research question, the type of data collected), it is the method of data analysis that distinguishes them more clearly than anything else. To illustrate this idea, imagine a team of researchers that conducts a series of unstructured interviews with people recovering from alcohol use disorder to learn about the role of their religious faith in their recovery. Although this project sounds like qualitative research, imagine further that once they collect the data, they code the data in terms of how often each participant mentions God (or a “higher power”), and they then use descriptive and inferential statistics to find out whether those who mention God more often are more successful in abstaining from alcohol. Now it sounds like quantitative research. In other words, the quantitative-qualitative distinction depends more on what researchers do with the data they have collected than with why or how they collected the data.

But what does qualitative data analysis look like? Just as there are many ways to collect data in qualitative research, there are many ways to analyze data. Here we focus on one general approach called grounded theory (Glaser & Strauss, 1967) . This approach was developed within the field of sociology in the 1960s and has gradually gained popularity in psychology. Remember that in quantitative research, it is typical for the researcher to start with a theory, derive a hypothesis from that theory, and then collect data to test that specific hypothesis. In qualitative research using grounded theory, researchers start with the data and develop a theory or an interpretation that is “grounded in” those data. They do this analysis in stages. First, they identify ideas that are repeated throughout the data. Then they organize these ideas into a smaller number of broader themes. Finally, they write a theoretical narrative—an interpretation of the data in terms of the themes that they have identified. This theoretical narrative focuses on the subjective experience of the participants and is usually supported by many direct quotations from the participants themselves.

As an example, consider a study by researchers Laura Abrams and Laura Curran, who used the grounded theory approach to study the experience of postpartum depression symptoms among low-income mothers (Abrams & Curran, 2009) . Their data were the result of unstructured interviews with 19 participants. The table below hows the five broad themes the researchers identified and the more specific repeating ideas that made up each of those themes. In their research report, they provide numerous quotations from their participants, such as this one from “Destiny:”

“Well, just recently my apartment was broken into and the fact that his Medicaid for some reason was cancelled so a lot of things was happening within the last two weeks all at one time. So that in itself I don’t want to say almost drove me mad but it put me in a funk….Like I really was depressed. (p. 357)”

Their theoretical narrative focused on the participants’ experience of their symptoms, not as an abstract “affective disorder” but as closely tied to the daily struggle of raising children alone under often difficult circumstances. The table below illustrates the process of creating themes from repeating ideas in the qualitative research gathering and analysis process.

Given their differences, it may come as no surprise that quantitative and qualitative research do not coexist in complete harmony. Some quantitative researchers criticize qualitative methods on the grounds that they lack objectivity, are difficult to evaluate in terms of reliability and validity, and do not allow generalization to people or situations other than those actually studied. At the same time, some qualitative researchers criticize quantitative methods on the grounds that they overlook the richness of human behavior and experience and instead answer simple questions about easily quantifiable variables.

In general, however, qualitative researchers are well aware of the issues of objectivity, reliability, validity, and generalizability. In fact, they have developed a number of frameworks for addressing these issues (which are beyond the scope of our discussion). And in general, quantitative researchers are well aware of the issue of oversimplification. They do not believe that all human behavior and experience can be adequately described in terms of a small number of variables and the statistical relationships among them. Instead, they use simplification as a strategy for uncovering general principles of human behavior.

Many researchers from both the quantitative and qualitative camps now agree that the two approaches can and should be combined into what has come to be called mixed-methods research (Todd, Nerlich, McKeown, & Clarke, 2004). In fact, the studies by Lindqvist and colleagues and by Abrams and Curran both combined quantitative and qualitative approaches. One approach to combining quantitative and qualitative research is to use qualitative research for hypothesis generation and quantitative research for hypothesis testing. Again, while a qualitative study might suggest that families who experience an unexpected suicide have more difficulty resolving the question of why, a well-designed quantitative study could test a hypothesis by measuring these specific variables in a large sample. A second approach to combining quantitative and qualitative research is referred to as triangulation. The idea is to use both quantitative and qualitative methods simultaneously to study the same general questions and to compare the results. If the results of the quantitative and qualitative methods converge on the same general conclusion, they reinforce and enrich each other. If the results diverge, then they suggest an interesting new question: Why do the results diverge and how can they be reconciled?

Using qualitative research can often help clarify quantitative results via triangulation. Trenor, Yu, Waight, Zerda, and Sha (2008) investigated the experience of female engineering students at a university. In the first phase, female engineering students were asked to complete a survey, where they rated a number of their perceptions, including their sense of belonging. Their results were compared across the student ethnicities, and statistically, the various ethnic groups showed no differences in their ratings of their sense of belonging.

One might look at that result and conclude that ethnicity does not have anything to do with one’s sense of belonging. However, in the second phase, the authors also conducted interviews with the students, and in those interviews, many minority students reported how the diversity of cultures at the university enhanced their sense of belonging. Without the qualitative component, we might have drawn the wrong conclusion about the quantitative results.

This example shows how qualitative and quantitative research work together to help us understand human behavior. Some researchers have characterized qualitative research as best for identifying behaviors or the phenomenon whereas quantitative research is best for understanding meaning or identifying the mechanism. However, Bryman (2012) argues for breaking down the divide between these arbitrarily different ways of investigating the same questions.

Key Takeaways

• The qualitative approach is centered on an inductive method of reasoning
• The qualitative approach focuses on understanding phenomenon through the perspective of those experiencing it
• Researchers search for recurring topics and group themes to build upon theory to explain findings
• A mixed methods approach uses both quantitative and qualitative methods to explain different aspects of a phenomenon, processes, or practice
• This chapter can be attributed to Research Methods in Psychology by Rajiv S. Jhangiani, I-Chant A. Chiang, Carrie Cuttler, & Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted. This adaptation constitutes the fourth edition of this textbook, and builds upon the second Canadian edition by Rajiv S. Jhangiani (Kwantlen Polytechnic University) and I-Chant A. Chiang (Quest University Canada), the second American edition by Dana C. Leighton (Texas A&M University-Texarkana), and the third American edition by Carrie Cuttler (Washington State University) and feedback from several peer reviewers coordinated by the Rebus Community. This edition is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. ↵

Gathering and Analyzing Qualitative Data Copyright © by megankoster is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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How to write qualitative research questions.

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

What is qualitative research?

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

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

What are research questions?

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

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

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

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

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

Discover the fundamentals of qualitative research

Quantitative vs. qualitative research questions

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

Quantitative research questions

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

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

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

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

• What is the connection?

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

For example:

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

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

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

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

Qualitative research questions

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

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

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

A few example qualitative research questions:

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

Qualitative research question types

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

• Exploratory questions

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

• Explanatory questions

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

• Descriptive questions

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

• Predictive questions

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

Why are good qualitative research questions important?

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

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

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

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

Developing good qualitative research questions

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

1. Keep it specific

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

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

Weak example: Do people feel different about gender now?

2. Be original

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

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

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

3. Make it research-worthy

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

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

Weak example: What languages are spoken in India?

4. Focus your question

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

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

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

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

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

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

Weak example: How can hate crimes be prevented?

5. Ask something researchable

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

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

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

Related resources

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

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Qualitative Research Design: Start

Qualitative Research Design

What is Qualitative research design?

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. Instead of collecting numerical data points or intervening or introducing treatments just like in quantitative research, qualitative research helps generate hypotheses as well as 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 stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data.

Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research. Qualitative research is the opposite of quantitative research, which involves collecting and analyzing numerical data for statistical analysis. Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.

While qualitative and quantitative approaches are different, they are not necessarily opposites, and they are 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 that there is 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 together.

Research Paradigms 

• Positivist versus Post-Positivist
• Social Constructivist (this paradigm/ideology mostly birth qualitative studies)

Events Relating to the Qualitative Research and Community Engagement Workshops @ CMU Libraries

CMU Libraries is committed to helping members of our community become data experts. To that end, CMU is offering public facing workshops that discuss Qualitative Research, Coding, and Community Engagement best practices.

The following workshops are a part of a broader series on using data. Please follow the links to register for the events. 

Qualitative Coding

Using Community Data to improve Outcome (Grant Writing)

Survey Design  

Upcoming Event: March 21st, 2024 (12:00pm -1:00 pm)

Community Engagement and Collaboration Event 

Join us for an event to improve, build on and expand the connections between Carnegie Mellon University resources and the Pittsburgh community. CMU resources such as the Libraries and Sustainability Initiative can be leveraged by users not affiliated with the university, but barriers can prevent them from fully engaging.

The conversation features representatives from CMU departments and local organizations about the community engagement efforts currently underway at CMU and opportunities to improve upon them. Speakers will highlight current and ongoing projects and share resources to support future collaboration.

Event Moderators:

Taiwo Lasisi, CLIR Postdoctoral Fellow in Community Data Literacy,  Carnegie Mellon University Libraries

Emma Slayton, Data Curation, Visualization, & GIS Specialist,  Carnegie Mellon University Libraries

Nicky Agate , Associate Dean for Academic Engagement, Carnegie Mellon University Libraries

Chelsea Cohen , The University’s Executive fellow for community engagement, Carnegie Mellon University

Sarah Ceurvorst , Academic Pathways Manager, Program Director, LEAP (Leadership, Excellence, Access, Persistence) Carnegie Mellon University

Julia Poeppibg , Associate Director of Partnership Development, Information Systems, Carnegie Mellon University 

Scott Wolovich , Director of New Sun Rising, Pittsburgh 

Additional workshops and events will be forthcoming. Watch this space for updates. 

Workshop Organizer

Qualitative Research Methods

What are Qualitative Research methods?

Qualitative research adopts numerous methods or techniques including interviews, focus groups, and observation. 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 is 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-participant or detached observers.

What constitutes a good research question? Does the question drive research design choices?

According to Doody and Bailey (2014);

 We can only develop a good research question by consulting relevant literature, colleagues, and supervisors experienced in the area of research. (inductive interactions).

Helps to have a directed research aim and objective.

Researchers should not be “ research trendy” and have enough evidence. This is why research objectives are important. It helps to take time, and resources into consideration.

Research questions can be developed from theoretical knowledge, previous research or experience, or a practical need at work (Parahoo 2014). They have numerous roles, such as identifying the importance of the research and providing clarity of purpose for the research, in terms of what the research intends to achieve in the end.

Qualitative Research Questions

What constitutes a good Qualitative research question?

A good qualitative question answers the hows and whys instead of how many or how much. It could be structured as a stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data. Qualitative research gathers participants' experiences, perceptions and behavior.

Examples of good Qualitative Research Questions:

What are people's thoughts on the new library? 

How does it feel to be a first-generation student attending college?

Difference example (between Qualitative and Quantitative research questions):

How many college students signed up for the new semester? (Quan) 

How do college students feel about the new semester? What are their experiences so far? (Qual)

• Qualitative Research Design Workshop Powerpoint

Foley G, Timonen V. Using Grounded Theory Method to Capture and Analyze Health Care Experiences. Health Serv Res. 2015 Aug;50(4):1195-210. [ PMC free article: PMC4545354 ] [ PubMed: 25523315 ]

Devers KJ. How will we know "good" qualitative research when we see it? Beginning the dialogue in health services research. Health Serv Res. 1999 Dec;34(5 Pt 2):1153-88. [ PMC free article: PMC1089058 ] [ PubMed: 10591278 ]

Huston P, Rowan M. Qualitative studies. Their role in medical research. Can Fam Physician. 1998 Nov;44:2453-8. [ PMC free article: PMC2277956 ] [ PubMed: 9839063 ]

Corner EJ, Murray EJ, Brett SJ. Qualitative, grounded theory exploration of patients' experience of early mobilisation, rehabilitation and recovery after critical illness. BMJ Open. 2019 Feb 24;9(2):e026348. [ PMC free article: PMC6443050 ] [ PubMed: 30804034 ]

Moser A, Korstjens I. Series: Practical guidance to qualitative research. Part 3: Sampling, data collection and analysis. Eur J Gen Pract. 2018 Dec;24(1):9-18. [ PMC free article: PMC5774281 ] [ PubMed: 29199486 ]

Houghton C, Murphy K, Meehan B, Thomas J, Brooker D, Casey D. From screening to synthesis: using nvivo to enhance transparency in qualitative evidence synthesis. J Clin Nurs. 2017 Mar;26(5-6):873-881. [ PubMed: 27324875 ]

Soratto J, Pires DEP, Friese S. Thematic content analysis using ATLAS.ti software: Potentialities for researchs in health. Rev Bras Enferm. 2020;73(3):e20190250. [ PubMed: 32321144 ]

Zamawe FC. The Implication of Using NVivo Software in Qualitative Data Analysis: Evidence-Based Reflections. Malawi Med J. 2015 Mar;27(1):13-5. [ PMC free article: PMC4478399 ] [ PubMed: 26137192 ]

Korstjens I, Moser A. Series: Practical guidance to qualitative research. Part 4: Trustworthiness and publishing. Eur J Gen Pract. 2018 Dec;24(1):120-124. [ PMC free article: PMC8816392 ] [ PubMed: 29202616 ]

Saldaña, J. (2021). The coding manual for qualitative researchers. The coding manual for qualitative researchers, 1-440.

O'Brien BC, Harris IB, Beckman TJ, Reed DA, Cook DA. Standards for reporting qualitative research: a synthesis of recommendations. Acad Med. 2014 Sep;89(9):1245-51. [ PubMed: 24979285 ]

Palermo C, King O, Brock T, Brown T, Crampton P, Hall H, Macaulay J, Morphet J, Mundy M, Oliaro L, Paynter S, Williams B, Wright C, E Rees C. Setting priorities for health education research: A mixed methods study. Med Teach. 2019 Sep;41(9):1029-1038. [ PubMed: 31141390 ]

• Last Updated: Feb 14, 2024 4:25 PM
• URL: https://guides.library.cmu.edu/c.php?g=1346006

Research Writing and Analysis

• NVivo Group and Study Sessions
• SPSS This link opens in a new window
• Statistical Analysis Group sessions
• Using Qualtrics
• Dissertation and Data Analysis Group Sessions
• Defense Schedule - Commons Calendar This link opens in a new window
• Research Process Flow Chart
• Research Alignment Chapter 1 This link opens in a new window
• Step 1: Seek Out Evidence
• Step 2: Explain
• Step 3: The Big Picture
• Step 4: Own It
• Step 5: Illustrate
• Annotated Bibliography
• Literature Review This link opens in a new window
• Systematic Reviews & Meta-Analyses
• How to Synthesize and Analyze
• Synthesis and Analysis Practice
• Synthesis and Analysis Group Sessions
• Problem Statement
• Purpose Statement
• Conceptual Framework
• Theoretical Framework
• Quantitative Research Questions

Qualitative Research Questions

• Trustworthiness of Qualitative Data
• Analysis and Coding Example- Qualitative Data
• Thematic Data Analysis in Qualitative Design
• Dissertation to Journal Article This link opens in a new window
• International Journal of Online Graduate Education (IJOGE) This link opens in a new window
• Journal of Research in Innovative Teaching & Learning (JRIT&L) This link opens in a new window

What’s in a Qualitative Research Question?

Qualitative research questions are driven by the need for the study. Ideally, research questions are formulated as a result of the problem and purpose, which leads to the identification of the methodology. When a qualitative methodology is chosen, research questions should be exploratory and focused on the actual phenomenon under study.

From the Dissertation Center, Chapter 1: Research Question Overview , there are several considerations when forming a qualitative research question. Qualitative research questions should

Below is an example of a qualitative phenomenological design. Note the use of the term “lived experience” in the central research question. This aligns with phenomenological design.

RQ1: “ What are the lived experiences of followers of mid-level managers in the financial services sector regarding their well-being on the job?”

If the researcher wants to focus on aspects of the theory used to support the study or dive deeper into aspects of the central RQ, sub-questions might be used. The following sub-questions could be formulated to seek further insight:

RQ1a.   “How do followers perceive the quality and adequacy of the leader-follower exchanges between themselves and their novice leaders?”

RQ1b.  “Under what conditions do leader-member exchanges affect a follower’s own level of well-being?”

Qualitative research questions also display the desire to explore or describe phenomena. Qualitative research seeks the lived experience, the personal experiences, the understandings, the meanings, and the stories associated with the concepts present in our studies.

We want to ensure our research questions are answerable and that we are not making assumptions about our sample. View the questions below:

How do healthcare providers perceive income inequality when providing care to poor patients?

In Example A, we see that there is no specificity of location or geographic areas. This could lead to findings that are varied, and the researcher may not find a clear pattern. Additionally, the question implies the focus is on “income inequality” when the actual focus is on the provision of care. The term “poor patients” can also be offensive, and most providers will not want to seem insensitive and may perceive income inequality as a challenge (of course!).

How do primary care nurses in outreach clinics describe providing quality care to residents of low-income urban neighborhoods?

In Example B, we see that there is greater specificity in the type of care provider. There is also a shift in language so that the focus is on how the individuals describe what they think about, experience, and navigate providing quality care.

Other Qualitative Research Question Examples

Vague : What are the strategies used by healthcare personnel to assist injured patients?

Try this : What is the experience of emergency room personnel in treating patients with a self-inflicted household injury?

The first question is general and vague. While in the same topic area, the second question is more precise and gives the reader a specific target population and a focus on the phenomenon they would have experienced. This question could be in line with a phenomenological study as we are seeking their experience or a case study as the ER personnel are a bounded entity.

Unclear : How do students experience progressing to college?

Try this : How do first-generation community members describe the aspects of their culture that promote aspiration to postsecondary education?

The first question does not have a focus on what progress is or what students are the focus. The second question provides a specific target population and provides the description to be provided by the participants. This question could be in line with a descriptive study.

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• Chapter Five: Qualitative Data (Part 2)

Qualitative Data Gathering Research Designs

In their search for understanding communication phenomena, researchers have multiple qualitative methods from which to choose. Depending on a variety of factors (such as the nature of the research question, access to participants, time and resource commitments, etc.), researchers may select one or more of the following methods:

• ethnography
• in-depth field interviews
• focus group interviews
• the collection of narratives. 

Selecting the appropriate method for data collection is a vital component of the research process. Regardless of the method selected, researchers must reconcile the established traditions of the methodology with the specific requirements of the group or individuals participating in the research. We now discuss how to plan and implement your qualitative study. This section begins with topic selection and research focus and then proceeds to a discussion of each of the different qualitative methods.

• Chapter One: Introduction
• Chapter Two: Understanding the distinctions among research methods
• Chapter Three: Ethical research, writing, and creative work
• Chapter Four: Quantitative Methods (Part 1)
• Chapter Four: Quantitative Methods (Part 2 - Doing Your Study)
• Chapter Four: Quantitative Methods (Part 3 - Making Sense of Your Study)
• Chapter Five: Qualitative Methods (Part 1)
• Chapter Six: Critical / Rhetorical Methods (Part 1)
• Chapter Six: Critical / Rhetorical Methods (Part 2)
• Chapter Seven: Presenting Your Results

Identifying the Research Setting, Research Group, and Research Focus

Researchers have several choices when deciding how to proceed with a qualitative study. Some studies may begin with a specific communication concept, such as family communication. Researchers then begin to identify potential study participants. On other occasions, a researcher might be interested in a specific setting, such as a tattoo parlor. Gaining access to that setting to see what interesting communication concepts emerge would be very helpful. In both cases, research proceeds inductively, and conclusions emerge from the carefully gathered data. Regardless of how the initial inspiration strikes, the subsequent steps in the procedure follow a similar pattern. The following chart demonstrates the typical qualitative data gathering process:

Selecting a topic and narrowing the research focus.  During the earliest phases of the qualitative research process, researchers are tasked with identifying a focus for their study. Like all research, the individuals conducting the study are often drawn to those communication phenomena that are of the most interest to them. Perhaps a researcher has a friend or a family member who recently met his or her spouse through an on-line dating service and the researcher becomes interested in understanding how on-line dating develops. An initial research question might be, “What are the normative behaviors regarding on-line courtship?” From this point, it is important for the researcher to develop a rationale for the research. Sometimes, as in the case of on-line dating, the rationale is self-evident. As the number of people who participate in on-line dating continues to grow, it becomes an important and useful social activity to investigate. Regardless of whether or not the utility of the study seems self-evident, the researcher has an obligation to demonstrate the relevance of his or her study rationale through a review of the existing literature.

The literature review is an important component of any carefully designed research study. Although existing theory typically guides the more deductive approach of quantitative research, there are several differences regarding the more inductive, qualitative literature review. In qualitative research, the literature review is not completely finalized before data collection begins. In fact, in many cases, the literature review proceeds alongside the interviews or observations in which the researcher may be engaged. In the previous example regarding on-line courtship, the researcher would likely construct a literature review based on articles that examine on-line dating behaviors, as well as articles that examine off-line dating behaviors. However, if during the process of interviewing participants, several interviewees discuss the importance of having friends who accepted and encouraged their on-line dating attempts, the importance of a concept like  social support  might emerge. The qualitative researcher, well into the process of interviewing, might gather existing literature on social support and then ask questions regarding social support in future interviews. In some cases, the literature review continues to grow and develop as the data is being collected.

Another difference, though to a lesser degree, is that qualitative researchers often conduct a broad, rather than a deep, literature review—at least initially. The broad approach familiarizes the researcher with multiple topics that seem related to his or her research purpose. However, given that the specific data, rather than general theory, guides the entire qualitative process, the researcher can choose to analyze more deeply those topics that begin to emerge from the interaction with, or observation of, the participants. It is imperative that researchers are responsive to data collected over the course of the qualitative project so that they can augment or de-emphasize segments of the literature review as needed.

Choosing the appropriate methodology and accessing the setting or participants.  Although you can choose from many acceptable qualitative methods, including case study analysis, autoethnography, or qualitative content analysis, this chapter will focus on four common methods of collecting qualitative data: ethnography, interviewing, focus group interviewing, and narrative inquiry. Each of these methods, including their strengths and limitations, will be discussed in more detail later in this section. Choosing the appropriate method is based on a variety of factors including the nature and scope of your research question or questions, access to study participants, and researcher training and familiarity with potential methods, to name a few. As with any type of scholarly research, the law of the hammer need not apply. The law of the hammer states that if the only tool available is a hammer, then every problem will resemble a nail. If a researcher is trained and comfortable with conducting focus groups, but the best method of data collection for answering a specific research question is ethnographic research, then the researcher needs to take the necessary amount of time familiarizing himself or herself with the steps of an ethnography rather than forcing the question to conform to a focus group format. As always, the research purpose should guide the methodology, rather than the methodology guiding the purpose of the research.  

Access and trust are fundamental elements of successful data collection in qualitative research. A researcher must be able to access the research setting or interview participants in order to gather data. If the researcher is unable to gain access, it is possible that the study will have to be abandoned or significantly altered. In the case of Tom Hall’s research into government secrecy and its effects on democracy several years ago, he attempted to interview the members of the U.S. Senate and the House of Representatives who served on the Senate and House intelligence committees, respectively. Of the nearly thirty members serving at the time (2003-2004), he was not able to gain access to a single congressperson. In fact, only a handful responded to his numerous attempts at contact. Due to this lack of access, he had to shift his project entirely to a textual analysis of public documents, such as Executive Orders, Congressional Research Reports, and Department of Energy documents, in order to proceed with the research. This lack of interview access changed the general purpose of the research project and significantly altered the research questions he sought to answer. Needless to say, flexibility is an important attribute for a qualitative researcher.

In many cases, whether or not a group or organization provides access stems from whether or not the members of that organization trust the researcher. Imagine your suspicion if an individual appeared at your place of employment one day asking questions and writing information in a notebook. Just because a supervisor or gatekeeper has granted access to a researcher does not mean that all of the members of the organization or group are ready to trust the motivations of the researcher. Trust is person specific. The key to collecting solid data is for those individuals who are being observed or interviewed to understand why you are there and how you plan to use the data. If an interviewee does not trust your motivations, it is highly unlikely that s/he will be forthcoming in her/his responses—if s/he chooses to participate at all. While access to a group often relies on gaining the permission of a gatekeeper or other organizational leader, trust develops over time.

Examples of the early stages of qualitative research.  Sally is interested in studying a successful student organization on her campus. She realizes that PRSSA is an award-winning public relations organization on campus, so she contacts the faculty advisor and the current student leaders in the organization. Sally must gain the consent of the faculty advisor and other student leaders in order to begin her research on PRSSA. Sally decides to immerse herself as fully as possible with PRSSA—attending meetings, interviewing members, and observing committees, among other activities. Over the course of her research, all of Sally’s data collection efforts will be focused on this one organization. Although the initial approval of the faculty advisor and the student leaders of the organization are vital to gain access, it is important to remember that Sally will still need to gain consent from any other organization members who participate in her study.

Another example involves Bob who is also interested in studying reasons for participation in student organizations on his campus. Rather than focusing on a single organization, he decides to interview multiple participants in multiple organizations. Over the course of several weeks or months, Bob interviews numerous individuals and learns why they chose to involve themselves in student organizations. Bob uses a snowball or volunteer sample in order to recruit participants for his study. While there is no single faculty advisor or organization leader needed to gain access to these groups, Bob will still have to acquire individual consent from all of the participants in his study.

The early stages of a qualitative project are crucial for providing the foundations for a credible study. Developing the research purpose, examining the existing literature, selecting an appropriate method, and gaining access to and the trust of participants are all necessary steps.  

Qualitative Data Collection

In this section the authors discuss each of the more common qualitative methods, including the purpose, the steps involved in the particular method, and the strengths and limitations of the method. An extended example of each method is provided before moving on to the next method. The methods discussed include: ethnography, interviewing, focus group interviewing, and narrative interviewing.

Ethnography . This method is the total immersion of the researcher into the research setting. The roots of ethnography lie in cultural anthropology, which is when researchers attempt to fully understand the culture of a group by integrating themselves into the culture under investigation. Some communication scholars, such as Lawrence Wieder (1999), consider ethnography to be the main qualitative method. Although observation is the central practice of ethnographic research, a researcher may employ multiple other qualitative methodologies during the course of the project. Ethnography is the method of choice when a researcher decides to study the participants within their natural environment. Therefore, a study examining the communication patterns of college wrestlers would involve extensive interaction with a college wrestling team.

Traditional ethnography concerns a researcher or group of researchers studying the activities of a specific group or culture Over the last twenty years, an additional type of ethnographic research has emerged, where a person tells the story of some experience within their own life, with a scholarly purpose. This practice of autoethnography has become more popular in the past few years, and its validation as a legitimate form of knowledge development has also increased. Autoethnography places the researcher at the center of the investigation by directing the analysis towards the researcher’s role in the natural setting. By definition, an autoethnographer is a complete participant in his or her research, and is engaged in a full scale, in-depth, critical analysis on his or her life as it is being lived. A college athlete might detail his or her experiences as a member of a team—critically exploring his or her assimilation and identification with the group or chronicling the personal difficulties of competing at the highest level athletically. Whatever the specific focus of research, the data is drawn from detailed accounts of a person’s own experiences.  

The purpose of ethnographic research . Given though the individual goals vary from one ethnographic project to another, the overall purpose of the research remains the same: to accurately capture the social activities of the group or organization being studied. Frequently, the researcher does not have clearly defined research questions, preferring instead to capture, through observation and interviews, the social practices of the organization members. The purpose is to experience the participants in their natural setting and interpret those experiences accurately, in order to develop a better understanding of the interaction processes of the social group. Remember that one of the overarching goals of qualitative research is developing an understanding of an event, phenomenon, communicative practice, or cultural group. Ethnography is one of the ways that a researcher might accomplish this goal.

The steps in the ethnographic process . You should follow four distinct steps when conducting ethnographic research.

• Identify the research site. In ethnographic research, the principle investigator is often attracted to a particular group or organization. The person conducting the study may already be a member of the group (emic) he or she desires to research. An example of this would be when an individual who is a member of a book club decides to research the group in order to understand the group better. An etic approach might involve a graduate student who is interested in high school coaching selecting an athletic team to observe. Observation is a necessary component of ethnographic research. The full range of observation techniques are available to the researcher—from complete participant to complete observer.
• Gain access to the organization. Gaining access to an organization is vital to ethnography. Simply put, without access, ethnography is impossible. In order for the research to proceed, investigators must gain access to the organization or group. Gaining access relies on building trust with gatekeepers, informants, and other key organizational personnel. For example, if a researcher wanted to study the cultural climate of a Communication Studies Department, he or she might first begin by approaching the head of the department for approval. In this example, the department head might act as a gatekeeper—permitting or denying the research. However, even with the consent and trust of the department head, successful data collection and a successful research project are not assured. The researcher would likely need to approach each of the professors and staff in order to gain their consent to be observed during meetings and classes and office activities. While the consent of the department head may be enough to gain access to the data site, the success of the data collection portion of the project relies on earning the trust of as many of the organizational members as possible. 
• Collect and analyze data. During this stage, the real work begins. Researchers immerse themselves in the natural environment of the participants, collecting copious field notes and analyzing the data frequently. This is by far the most time consuming portion of the research process. At a minimum, most ethnographers spend six months engaged in this portion of the research and spending one or two years immersed in a group is not uncommon.
• Leave the field of investigation. When subsequent observations are no longer producing new data, the researcher is ready to wrap up the project and begin writing the final report. There are considerations when leaving the field. For one, the researcher may want to schedule additional meetings—focus groups or interviews—after the conclusion of the observation-based data gathering, in order to have the participants validate the findings or in order to follow up on interest areas not revealed through observation. The researcher should maintain the same high levels of trust that were so important during the initiation of the research project.

Recording observations using field notes . Field notes are a vital tool of the ethnographer. They are a written record of the researcher’s observations during his or her time in the field. Researchers would not be capable of remembering everything that they see during their observations, therefore keeping a notebook detailing the various activities of the community in which they are immersed is critical. Field notes are comprised of detailed records of observations as they occur. Over the course of compiling field notes, probative analysis also develops. Observers write down tentative and initial questions or conceptual possibilities alongside the field notes as they are collected. These are often referred to as “theoretical asides.” As observations and field notes grow in number, conceptual and theoretical elements may be combined and reflected upon in greater detail. More in-depth writing, focusing on explicit connections among and between the asides, are referred to as “observer commentaries” and represent a more sustained analytic treatment of the evidence collected. When the writer develops, in paragraph form, a rough draft explicating tentative themes, these writings are known as “in-process memos.”   

Strengths and limitations of ethnographic research . Ethnographic research has several strengths. First, ethnographic research observes the participants in their natural setting. In fact, to borrow terminology popular in quantitative social science, one would say that ethnographic research is ecologically valid. Rather than relying on a self-reported survey where someone reveals how they would act in a conflict situation in the workplace or relying on an experimental design where participants might role-play a workplace conflict in an artificial setting, ethnographers observe the participants in their natural environment. Second, ethnographic researcher stems from the thick, rich descriptions of the social actions of the group under investigation. Imagine the details collected by a researcher who is able to capture and describe group behavior as it unfolds and then follows up with informal interviews in order to gain the perspectives of the participants. This high level of detail is not something that survey data can replicate. Third, due to the extended observation periods in the natural setting and the cultural immersion that occurs with this method, ethnographers are able to gain deep understanding of the social activities of the group or cultural being observed.

Ethnographic research is not without its limitations. First, perhaps its most significant limitation stems from the fact that although one is able to develop an in-depth understanding of a group or culture, that understanding comes at the cost of generalizability. Just because a researcher can understand the social actions of one group or culture at a particular point in time does not mean that the knowledge derived from this understanding is relatable to other groups or cultures, which could then limit the applicability of the research. Second, sheer time and resource commitment required of a researcher to immerse herself and fully understand a culture is a limit. As noted previously, two years is not an exception but is, in many cases, normative. Finally, there exists the possibility that the researcher begins to over-identify with his or her research subjects. One example of this might involve a researcher deliberately leaving out accurate, but negative information about research subjects because the researcher does not want any aspect of the group to be seen in a negative light. Conversely, a researcher may deliberately exaggerate some characteristics to paint the group in a more desirable light. This over-identification is often referred to as  going native , and it seriously jeopardizes the credibility of a study.  

Sample ethnography . If one wants to fully understand the process of ethnographic research, one should identify a research environment, initiate an ethnographic study, and begin data collection and analysis. To facilitate understanding of the ethnographic process, we describe Susan Weinstein’s (2007) study to clarify the process of ethnographic research. Weinstein (2007) spent three years gathering field observations, collecting written artifacts, and conducting informal interviews while studying how “nine low-income, African-American and Latino urban youths” wrote about gender and sexuality through “poetry, prose, and rap lyrics” (p. 28). In her own words, Weinstein states,

In this single paragraph, Weinstein details many of the aspects vital to her study—the locations and settings where data was collected, the length of time spent conducting the research, information about the participants, consent gained, and efforts towards respondent validation. Respondent validation involves the researcher reviewing her tentative conclusions with the study participants in order to elicit their feedback regarding her interpretation of events. Weinstein’s research was guided by her belief that imaginative writing served as an outlet for the identity construction of urban youths. She found that gender and sexuality materialized in often contradictory ways in the writings of the youths and concluded those contradictory writings to be indicative of the complexity of the methods regarding these topics that youths receive from their social environment, such as family and friends and popular culture.

Ethnographic research is a challenging, yet rewarding, scholarly endeavor and a method to be used when one wants to develop as comprehensive and in-depth an understanding of a social environment as possible.

In-depth interviewing . In-depth interviewing is a qualitative method that fully situates the interviewee in the role of providing information to the interviewer. According to Lindlof and Taylor (2002), an interview is “an event in which one person (the interviewer) encourages others to freely articulate their interests and experiences” (p. 170). Ethnography may be a technique that is unfamiliar to many people, but interviewing is a process that most people have encountered at one time or another. A high degree of flexibility and variation characterizes the interview process. Qualitative interviewing can range from very structured formal interviewing to the loosely structured field interviewing that accompanies ethnographic research. This section begins with a discussion of the basic characteristics and goals of interviewing, followed by the steps for conducting an interview and the strengths and limitations of this method. We conclude with an exploration of a study relying on interviewing as the primary method.

Interview goals and characteristics . Qualitative research is inherently subjective. Qualitative research relies on its participants sharing their subjective understanding of certain experiences. Interviewing allows research participants to share their unique perspectives. Therefore, a primary goal of interviewing is for the research participant to answer the questions of the researcher. In essence, interviewing is the process of asking questions and receiving answers. Researchers want their interviewees to provide information about events or experiences that occur separate from the interview setting. Answers may take the form of stories or explanations. Interviews enable the researcher to understand the context and language forms of the social actors. Additionally, interviews allow the researcher to investigate events that he or she would otherwise not be able to access, such as closed meetings, past events, etc. The goal is to get the best possible data that will enable the researcher to successfully answer his or her research question or to provide an in-depth understanding of the social processes under investigation.

Regardless of the formality of the interview structure, an important characteristic of a sound interview is establishing a conversational tone during the interview process. Because trust is such a vital component of an interview, the interviewer should adopt a style that puts the interviewee at ease, and a conversational interview tone often goes a long way towards making the interviewee relaxed. According to Denscombe (2010), other important characteristics of the interview process include being cognizant of the feelings of the interviewee and the ability of the interviewer to tolerate silences. In day-to-day conversations silence is usually not tolerated very well, but when one is asking another to reflect on an issue, time is sometimes essential to allow the interviewee to think through an issue and to feel compelled to dig deeper in this analysis.

Time is another important element of the interview process. Interviews should last a reasonable amount of time. A researcher should not expect a participant to be willing to devote more than an hour of time for an interview, except in the most extreme of cases. Thirty minutes to one hour is considered a reasonable expectation for an interview. However, for some research questions, an even shorter interview may be enough.

Several ethical considerations confront a researcher during the interview process. As with all research involving human participants, gaining the consent of the participants is an obligation of the researcher. The researcher will also want to make sure that the interviewee understands how the researcher plans to use the information and how confidentiality will be ensured. It is common for the researcher to use pseudonyms for the interview subjects in order to mask their identities. A final ethical consideration is for the researcher to be aware of the potential for certain questions to lead the interviewee in a specific direction—questions posed in such a way that they elicit a particular answer from the participant. It is advantageous for the interviewer if the interviewee consents to an audio or video recording of the interview. Recording the interview can ensure the accuracy of the participant’s statements. With or without a recording, it is suggested that interviews be conducted in pairs—this way, one person can conduct and moderate the interview, while the other takes detailed notes regarding the interaction. Of course, the decision to use a second interviewer depends on the comfort level and consent of the participant.

Appropriate types of interview questions . Close-ended, yes or no, type questions are necessary from time to time during a qualitative interview, such as when gathering demographic information about your participants to write your methods section, but open-ended questions are recommended because they provide the interviewee with greater freedom in responding and offer the interviewer more data for analysis. Open-ended questions follow two common formats—non-directive questions and directive questions.

Directive questions  are specific questions designed to discover specific responses. Examples of directive questions would be, “Tell me what kind of professor Tom Hall is” or “How does Tom Hall’s teaching style differ from April Chatham-Carpenter’s teaching style.” In both cases, the interviewer is asking the participant to address a specific point. Compare and contrast questions, as well as Devil’s Advocate questions, are examples of directive questions.

Consider the following  non-directive question  examples. “Tell me about a time when you experienced conflict in the workplace” or “Tell me a little about yourself.” In these examples, the interviewee is free to take the focus of the question in the direction of his or her choosing, and while that response will clearly contain specific elements, it begins with a more general approach than the directive questions.

Also, it is important to remember that not every question must specifically address the research purpose. For example, in order to increase comfort and gain the trust of a participant in the early stages of the interview, the researcher might consider asking a general question like, “Would you please tell me about yourself?” This allows the participant to grow comfortable sharing information with the researcher.

Finally, during the interview process, it is essential that the researcher is skilled at asking probing questions when more specific information is desired, asking clarifying questions when the information provided is unclear, or asking validating questions when the researcher wants to ensure that he or she interpreted the response of the participant correctly.

Steps of conducting an interview .   Five steps will help you through the process.

• Identify the purpose of your study and design the interview guide. The researcher needs to make sure that interviews are the appropriate methodology to employ in answering his or her research focus. If interviews are the appropriate data collection format, then the researcher needs to design a guide for how the interview will proceed. (The focus here is on research where interviews will serve as the primary data collection method and therefore are more formally structured than they might be during the impromptu interviewing that occurs during ethnographic research). A guide is just that, a guide to conducting the interview. It is a means for the researcher to organize his or her thoughts in order to ensure consistent approaches are taken across all interviews. However, it is just a guide and the researcher can add to it, take from it, or restructure questions as the need arises during an individual interview or over the course of multiple interviews.
• Identify the participants of the study and arrange times to conduct the interviews. If the researcher has selected a particular place or location to conduct his or her study, then the selection of the participants is likely a straightforward process. If, however, the researcher seeks to interview people who share common characteristics, rather than a physical location, selection of participants will likely rely on volunteer, snowball, or purposive sampling techniques. For example, suppose a researcher is interested in studying people who read comic books. In the process of identifying the participants, the researcher could gain access to a local comic book store and ask patrons if they are willing to participate in interviews, or the researcher could find one or two people who read comic books, interview them, and then ask them to help identify other potential participants (i.e., snowball sampling).
• Introductions . Ask broad questions to increase the comfort level of the participants. In some cases a broad, introductory question might take the form of “Tell me about some of your communication strengths.” Questions of this type are known as biography questions and are designed to establish a conversational and comfortable tone for the remainder of the interview.
• Research focus questions . As the interview is underway, the researcher turns to those questions to which he or she specifically seeks answers. This is the main portion of the interview, and is where the researcher’s skills at asking probing and follow-up questions help him or her collect the desired information. As the interview moves from one topic to the next, it is helpful for the researcher to summarize the previous topic and solicit feedback from the interviewee before shifting to the next topic.
• Concluding the interview . It is common during this portion of the interview for the researcher to summarize main points in order to seek validation from the interviewee regarding the researcher’s interpretation of the responses. It is also common for the interviewer to ask the participant if he or she has any questions for the researcher. Also, always thank the participant for his or her time.
• Transcribe the interview. In order to accurately collect the data from the interviews, it is often necessary to transcribe the interviews. The transcription process can take as long, if not longer, than the interview process itself. It is essential that the researcher accurately portray the statements of the participants. Transcriptions also convert the data into a format that is often easier to analyze and interpret than the rough notes taken during the interview process.
• Analyze and interpret the data. The final step of the interview process involves analyzing and interpreting the data. Once the interviews have been transcribed, the researcher sorts back through the data in order to identify themes and common elements among the responses. Obviously, the researcher needs to keep the original research purpose firmly in mind when interpreting the data. The practice of analysis and interpretation is similar across the various qualitative methods, so a more lengthy discussion of analysis and interpretation will be presented in the final segment of this chapter.

Strengths and limitations of interviewing . Like so many other qualitative methods, one of the strengths of interview data is, quite simply, the depth of the information gathered by the researcher. Over the course of the interview, the researcher is able to probe, refocus, and follow-up on the various responses from the participant. Because of these characteristics, rich, detailed information is the product of qualitative interviewing. Another advantage stems from the flexibility of the interview process, and this flexibility also contributes to the depth of the information. Although you will likely follow an interview guide, the process itself is not as concrete as survey research questions. The researcher can adjust to the responses during the interview and guide the interview in the direction necessary to speak to the overall research agenda. It is also possible to augment and excise questions following interviews. For example, if the first three interviewees all talk about a specific event, it alerts the researcher to the importance of this event. In preparation for the subsequent interviews, the researcher can include a question to make sure that the previously mentioned event is addressed in future interviews. Interviews also allow for the acquisition of the participants’ subjective interpretation of the events being discussed. This is data in the actual words of the participants. The researcher does not rely on previously established categories but rather on the words and experiences of the interviewees. Finally, in many cases, interviews are the only means of discovering information about events that have already taken place. Interviews allow the researcher to uncover information that otherwise would not be available to him or her.

As far as the limitations of qualitative interviewing go, there are several that are worth mentioning. The sheer amount of time involved in setting up, conducting, transcribing, and analyzing interviews is daunting for many researchers. A one-hour interview may take three times that long to transcribe, particularly without the aid of electronic transcribing devices. In many cases, the interviewee may wander off-course during the interview process. The researcher has to balance the comfort level of the participant with the researcher’s need to gather relevant data. In some cases, brief meandering may be necessary in order to maintain a comfortable conversational flow between the interviewer and interviewee. There are, of course, other concerns. It is one thing to focus the interviewee on answering a specific question, it is quite another to deliberately lead the interviewee to a specific response desired by the researcher. Researchers must be fully aware of the impact and influence that they have on the entire interview process. As is always the case with qualitative data, the data collection instrument is the researcher; therefore, the limits of the researcher will affect the entire process.

Interview study example.

Cohen, M., & Avanzino, S. (2010). We are people first: Framing organizational assimilation  experiences of the physically disabled using co-cultural theory.  Communication Studies ,  61 (3), 272-303.

Cohen and Avanzino examined “how organizational members with disabilities experience and manage organizational assimilation in the workplace” (p. 272). They conducted interviews with 24 individuals with physical disabilities. The researchers employed snowball and purposive sampling to identify participants and “sixteen interviews were conducted face-to-face and eight took place over the telephone due to distance and time constraints” (pp. 280-281). From the twenty-four interviews, 140 pages of transcriptions were produced. From the data, Cohen and Avanzino uncovered eight concepts and two themes, and identified aspects of the difficult process of workplace assimilation, as well as various techniques employed by the study participants to successfully negotiate workplace assimilation.

All of the elements of qualitative interviewing are present here: a general research question focused on understanding rather than prediction and control; a small, purposely selected group of participants; and an in-depth analysis of the participants’ responses to develop themes and facilitate understanding of the assimilation process.

Research methods are not mutually exclusive, and although this study primarily used interviewing, the authors note that they also engaged in observer-participant activities. In fact, researchers often triangulate their methods, combining the next two methods to be discussed—focus groups and narrative interviewing—in conjunction with ethnographic research or qualitative interviewing to strengthen the quality of the study.

Focus group interviewing . The fundamental difference between interviewing and focus group interviewing is that focus group interviewing is designed to allow multiple participants to interact with one another. Regular interviewing often occurs one-on-one; focus groups often bring together 6-12 participants in order to gather data as they interact with one another. Many people are familiar with marketing or political focus groups designed to uncover people’s attitudes towards a particular product, political figure, or idea, but fewer people are familiar with scholarly focus groups. Research focus groups may be similar in number of participants and duration of the interaction (90-120 minutes) to these others types of focus groups, but their purpose is not to gauge attitudes about a brand or political figure. Much like a regular interview, a focus group interview is designed to elicit information from the participants but is arranged in such a way that the participants are able to openly engage in discussion with the other participants. This experience, while often difficult to moderate, can provide a wealth of data. This section includes a discussion of focus group characteristics, moderator concerns, steps in focus group interviewing, and strengths and limitations. It concludes with a look at research employing focus group methodology.

Characteristics of focus groups . In addition to the number of participants and the length of time required to conduct a focus group, other important characteristics distinguish focus groups. Focus groups allow the researcher to interview several people at once in a format that resembles a purposeful discussion. Focus groups allow researchers to gather information from a group of people in a single setting. Some of the characteristics shared with regular interviews include the designing of an interview guide and involving two researchers for the process (one to moderate and another to take notes). In the case of the interview guide, it should be clearly developed but will likely not be as lengthy as the guide for a one-on-one interview. Because focus groups allow the participants to interact with one another, a few questions by the moderator may be all the prompting needed to elicit discussion. Due to the collaborative nature of focus groups, the moderator may only need to initiate the discussion and then can spend the majority of his or her time managing and focusing the ensuing discussion rather than constantly interjecting new questions. In some cases, the interactions among the group may emphasize points of agreement, as several of the participants add on to a topic, idea, or event that has been introduced. On other occasions, the group interaction may result in points of contention, enabling the researcher to see where participants have very differing perspectives on the research questions and topic.  

Moderator concerns . The moderator’s job is much more difficult in a focus group than it is in a one-on-one interview. A focus group moderator has to manage multiple personalities rather than a single personality. It is still important to establish a conversational tone among the participants, but it is also necessary to pay close attention to the various personalities of the group. Is one person dominating the discussion? Are two people ganging up on another member? Are tensions running high among the group? Is one person overly shy and unwilling to open up? These are just a few of the concerns, characteristics, and mannerisms that a focus group moderator may need to address over the course of the focus group interview. Practice is the best tool for learning when to allow disagreements and when to cool discussion down before arguments develop. Remember, the express disagreement that stems from constructive conflict is very different from the hostility associated with destructive group conflict. The focus group moderator must also insure that the group remains focused and does not wander too far from the original intent of the moderator’s topic or question. The moderator should also refrain from displaying any bias over the course of the focus group.

Steps of conducting a focus group . Some of the standard steps of designing and conducting a focus group are as follows:

• Identify the purpose of your study and confirm that focus groups will be the most useful method for your study. Researchers will want to consider their overall research focus and then construct a list of questions that will provide the best opportunity to elicit relevant responses from the participants. You should have a clear purpose to the focus group questions, but you also need to have the flexibility to adapt as the situation merits.
• Recruit participants. Once the researcher has decided which participant attributes are essential to the study, he or she needs to initiate the process of recruiting participants. Once again, snowball sampling and purposive sampling are often the most useful methods of recruitment. Even though a desired number for a focus group is between 6-12, the researcher should select a number that he or she feels capable of moderating. Also, just because people say that they will show up does not mean that they will. It is better to have too many people show up for your focus group session, and have to turn a few people away, than to have too few people show up. It is acceptable to over-recruit by a person or two.
• Introduce purpose of the group, participants, and explain the expectations and ground rules for the discussion . The first segment of the focus group should begin with the researcher/moderator explaining the goals and purpose of the focus group, followed by a presentation of the ground rules and discussion expectations. This is a good time to express the desire for respectful conversation and equal sharing of information. It is also a good time to allow the participants to introduce each other if they are not familiar with one another.
• Ask questions and moderate the ensuing discussion . Questions should be open-ended and may be either directive or non-directive depending on the needs of the researcher. It is during this segment that most of the moderator’s skills will be put to the test as he or she strives to keep the group on task, sharing equally, and clarifying points of contention or agreement.
• Conclude the focus group . Similar to one-on-one interviewing, the moderator should allow time for the participants to clarify or elaborate on any of their previous statements. Participants should also have the opportunity to ask questions of the moderator. Finally, make sure to thank the participants for taking the time to be a part of the focus group.
• Transcribe the focus group data. One of the challenges of focus group research is clearly differentiating the various participants, who in some cases will talk over or interrupt one another. This is one of the reasons that it is good to have a moderator, a note taker, and multiple recording devices (to catch all the voices) throughout the focus group. Transcribing data of this sort can be a time consuming process. When it comes time to analyze and interpret the data, detailed and accurate transcriptions are a necessity.
• Analyze and interpret the data. Once the notes have been transcribed, the researcher sorts through the data in order to identify themes and common elements among the responses. Obviously, the researcher needs to keep the original research purpose firmly in mind when interpreting the data. The practice of analysis and interpretation is similar across the various qualitative methods, so a lengthy discussion of analysis and interpretation will be presented in the final segment of this chapter.

Strengths and limitations of research focus groups . Obviously, the greatest strength of focus group methodology is the interplay among the various focus group participants. The healthy give and take among the participants serves as a fruitful generator of data. In fact, the primary reason for selecting focus groups over one-on-one interviews is so that the researcher can record several people interacting regarding the same topic. Provided that all of the subjects of the focus group participate, the researcher can gather a multitude of opinions and ideas on similar topics. Another advantage is that you can collect a relatively large amount of data in a brief period of time. In the time that it might take to conduct two individual interviews, the researcher can conduct a focus group with 10-12 participants. Although the depth of the data as compared to individual interviews may suffer, the breadth of the data and the discussion of common topics are extremely beneficial.

There are limitations to focus groups, several of which have already been highlighted. A skilled moderator is a necessity or the group can quickly get off task and produce information that does not relate or address the original purpose of the research. There also is the potential that overly dominant group members will lead the discussion in ways that might not represent the feelings of the remainder of the group. Finally, group members might either go along to get along or deliberately disagree (playing Devil’s Advocate)—neither of which will lead to the most accurate data. According to Morgan (1997), there is always the possibility that the moderator has overly influenced the groups. Focus groups do not take place in the natural environment; they are artificially constructed. This, in turn, impacts the ecological validity of the research.

Focus group example .

Hundley, H. L., & Shyles, L. (2010). US teenagers’ perceptions and awareness of digital  technology: A focus group approach.  New Media & Society ,  12 (3), 417-433.

Hundley and Shyles conducted focus groups with 80 middle and high school teenagers. “The chief objective of this research was to further our understanding of what young people think about digital devices and the functions they serve in their lives” (p. 417). A total of eleven focus groups were conducted with five to nine students in each group. Hundley and Shyles utilized both formally structured and semi-structured focus group interview protocols. The formally structured segment consisted of specifically prepared questions, while the semi-structured portions “allowed students to speak freely, elaborate, ask questions and join in group discussions” (p. 419). According to the authors:

From the focus groups, Hundley and Shyles were able to identify several common themes among the 80 participants. Themes included high level of awareness regarding the various types of technology, a lack of awareness regarding amount of time actually spent using the technology (nearly all underestimated time spent), awareness that digital devices help them socialize, and the risk of having personal information available online. Hundley and Shyles found that their research was consistent with the existing literature regarding teens and technology.

Autoethnography  is a relatively new qualitative research method that is generating a great deal of interest. It is based in ethnography, meaning that it, too, is an attempt to understand and describe the insiders’ cultural perspectives—i.e., how insiders construct their world view/culture. Like ethnography, it is also holistic and naturalistic, rather than trying to isolate what is studied and control it. Finally, like ethnography, it requires some degree of participant observation, but in this case, the observer may the reader, not just the researcher.

While there is no one definition of autoethnography, it is the study of some aspect of culture from the author’s personal experience and perspective. Examples of topics where authors have shared their personal experience through this method include surviving breast cancer, an eating disorder, depression, being of multi-ethnic identities,  the process of transitioning from woman to man as a transgender, and much more. The researcher is the subject of study, the key informant. The method is similar to narrative data collection. The researcher/author tells h/his story on a topic or issue the person feels warrants others to learn about from an insider view. The author role is reversed from being a researcher first and then an author to being a story teller first. If the story is not compelling, the research effort has failed.

Unlike other qualitative research that focuses on description, the goal in autoethnography is not just to describe but to evoke feeling and deeper understanding. This takes the view of knowledge as being an embodied experience, not just observation. To do so, the researcher must make h/himself vulnerable, sharing a great deal of self-disclosure and demonstrating a great deal of self-reflexivity.

Nevertheless, autoethnographers still value systematic methods used in other research methods:

If you imagine research methods as on a continuum, quantitative laboratory research would be on one end of the spectrum, and autoethnography would be at the other end of the spectrum, followed by performance studies and other more artistic ways of knowing. Because this method requires a unique set of writing skills, we do not cover it in full here, but offer websites for those who might like to learn more.

For an overview:  http://www.qualitative-research.net/index.php/fqs/article/view/1589/3095

For a focus on analytic, rather than evocative autoethnography:  http://web.media.mit.edu/~kbrennan/mas790/02/Anderson,%20Analytic%20autoethnography.pdf   For an example of autoethnographic research as researcher ethics:  http://jrp.icaap.org/index.php/jrp/article/view/213/183

To perform autoethnography:  http://eppl604.wmwikis.net/file/view/spry.pdf

Media portrayal of what autoethnography is:  http://www.youtube.com/watch?v=pb50nPHgI04

Data Analysis: Interpreting Results

Collecting information is only the first of two parts in the research process. In qualitative research  how  one interprets the results is particularly salient. Recall that the world-view or epistemological approach of qualitative research is the assumption that multiple meanings are always possible and present and that meaning is created, it is perceptual, and influenced by context. It is not just observed, nor is it considered universal or objective. Thus, in the second part of the qualitative research process the researcher purposefully and explicitly  makes meaning  of the study by applying methods to reveal patterns in the data. As discussed in chapter one, making meaning is what people do when they interact every day. They negotiate and construct perspectives through the exchange of verbal and nonverbal cues. In research, the author makes meaning through a negotiation with the verbal and nonverbal messages or data collected. The researcher’s charge is to make every effort to make fair and insightful sense of what might currently be a large pile of data.

As this description suggests, because there is room for multiple interpretations, the researcher has a responsibility to analyze the data or information gathered in a highly  systematic  fashion, drawing from previous methodologists’ recommendations and guidelines. To be systematic means the researcher cannot simply focus on data that is the most convenient, or anecdotal and examine it in a half-hazard fashion. Ideally, the researcher must make every attempt to consider all the information even though it would be impossible and not useful for the researcher to include all the information in the final report of the study.

Common Steps in Qualitative Data Analysis

Analysis methods for qualitative research have several commonalities. Recall that in all qualitative research, the data is words and behaviors, not numbers. It may be in the form of artifacts such as newspaper clippings or diaries from the field of study, field notes you have taken, transcriptions of one-to-one interviews, focus groups, and/or participant’s more naturally occurring conversations. In the analysis phase, the researcher’s job is to select analysis tools  that seem to be a good fit for the type of data being examined and the objectives of the study and then to review all the data in a consistent fashion. From this, the researcher seeks to synthesize the material by organizing it into categories and then identifying connections among the many categories that will make visible a more narrow, manageable focus to make sense of the information. 

There is a variety of methods to conduct qualitative data analysis. Some are more complex, others more accessible, but it is helpful to remember that at their essence, the meaning making process for all of them is to look for patterns -- themes and patterns among the themes by “comparing and contrasting parts of the data” in a series of steps (Keyton, 2011, p. 62). Thus, before reviewing specific types of qualitative methods, we are able to identify basic steps common to all of the methods.

According to qualitative communication scholars, Thomas Lindlof and Bryan Taylor (2002), the overall analysis process involves three basic tasks: “data management, data reduction and conceptual development” (p. 211). In data management, tools to code and categorize data are used to help the researcher gain some control or order over what could be an endless volume of information. From there it becomes easier for the researcher to see that some data may be more central to understanding the results than other data. Data reduction is then when the researcher begins to assign prioritized value to the data, reducing the size of the focus of analysis for a closer look. This does not mean any information is to be thrown away. Remember qualitative researchers believe meaning is created in context. Although it is necessary practically to try to distinguish what is most salient to focus on, the other information may in time provide a rich context for more complex, subtle interpretations. The researcher will want to later return to this secondary data for such considerations. Conceptual development should emerge from accomplishing the prior two tasks. This is where and how the concepts and themes -- or meanings in the study emerge. They are grounded in the data from the specific social context of study as well as influenced by the researcher’s review of previous research and qualitative theory. Together the tasks of data collection, data management, data reduction and conceptual development emulate the  inductive  nature of qualitative research. The researcher studies communication in a smaller, more specific context, gathers extensive data, organizes it and reduces it even further to smaller kernels of knowledge, and then returns the kernels to the larger social and theoretical contexts for further thought about the significance of these interactions in everyday life.    

In applying Lindlof & Taylor’s three steps for qualitative analysis, we break down the process further, adding two additional steps to make the process more explicit. We add an introductory step called data immersion and a concluding step called evaluating results. While we present them as if they are discrete steps, the reader should know researchers begin to think about these steps before all the data is collected and may return to the data collection phase after conducting preliminary analyses. The reader should also be forewarned if you read other descriptions of this process the steps may be divided a bit differently or labeled differently. We tried to do what was most streamlined. In the end, the various descriptions are really about the same basic process.

Member checks add to the credibility of a study. They better assure the participants’ perspectives are respected and that the interpretations are grounded in their perspectives (Lincoln & Guba, 1985). Useful results from member checks are not just results that say, “yes, this is good,” or “you made a mistake in the spelling of my name,” but rather feedback that helps the researcher see the findings through the participants’ eyes, thus extending the depth and breadth of interpretations and resulting theory proposed. Another value added from this method is that it gives some ownership of the results back to the participants. They are empowered to edit and add their input (Lincoln & Guba, 1985).

For example, in a study of African-American women’s self-esteem, DeFrancisco and Chatham-Carpenter (2000) conducted member checks in recognition of their position as White women interpreting the stories of women of color. The meetings caused the researchers to reframe one of the primary themes taken from the study to focusing on the effects of racism on the women’s self-esteem to focusing on the demand for respect. The shift in words from the researcher’s (racism) to the participants’ (respect) may have seemed small, but the former framed the participants as powerless victims of a racist society, the latter framed them as strong women demanding fair treatment.

• Data Immersion: Get to know your entire data set closely. This includes the participants’ contributions as well as your field notes during data collection. A  close-read , includes reading and rereading the data set multiple times, line-by-line, perhaps in different orders (Lindlof & Taylor, 2002). There is nothing that can be substituted for building a close awareness of what you have gathered. You will likely gain a new insight every time you review the material. You need a view of the whole before you can begin to sort the data. As you do so, look for holes – is there anything you need to go back to the field of study to gather? Use a concept we discuss in more depth later called  reflexivity  (Ellis, 2004). Critically monitor and write down your observations, reactions and feelings as you process the information collected, they may influence the directions you take next. The instructions for taking good field notes described under data collection above will be helpful here, as well. It is a good idea to make a complete copy of your data and archive it in case the copy you work from becomes damaged or lost.

The chunk is called a  unit of analysis or unit of data.  Identifying one’s unit of analysis is necessary in qualitative as well as quantitative data. It helps to define what level or size of data the researcher is focusing on – to identify the boundaries of individual units of data being considered. The unit of analysis is the smallest level of the data from which the researcher sorts the data and thus making meaning. The goal is to have the same or similar size for each chunk of data. The size depends on the goals of the study. For example, if a researcher is studying how people use conversation to create and maintain their identities, the researcher’s unit of analysis is typically a person’s turn taken in a conversation. But in most theme/categorization analysis of qualitative data, the unit of analysis can be more flexible. It can be a word, a phrase, a complete sentence, a conceptual theme, a nonverbal expression, a communication episode or event such as episodes from reality television, full texts, such as speeches, and more. Since the size may vary, you may find recommendations from researchers Yvonna Lincoln and Egon Guba (1985) helpful for identifying your unit of analysis. They suggest the unit have two criteria: the first is noted above – that it be the smallest piece of recognizable information, meaning that it does not require other contextual information to be understood. Second, the piece of information should be heuristic, meaning it should help with understanding. It should help address the research question or objective of study.

For example, imagine you are studying how young adults perform their identity by what they choose to post on their Facebook or another social media site. Your unit of analysis will likely be each verbal or nonverbal indicator about the participants’ identity. So, if a person posted, “I’m a 21 year old woman who loves to laugh, but I am dead serious about the type of man I want in my life.” The following is how the sentence might be broken into individual units, or pieces of information about her identity: “I’m a 21 year old/ woman/ who loves to laugh,/ but I am dead serious/ about the type of man I want in my life/.” Thus, from just one sentence, the research can glean 5 units of data representing 5 different categories or themes: age, gender, personality, goal (looking for a mate), and sexual orientation (heterosexual).  

Once the unit of analysis is determined, the researcher can chunk up all the data into units and begin  coding  the data – organizing it into groups under labels. A  coding scheme , is a sort of shorthand device to label and separate the data (Landlof & Taylor, 2002). When finished, the codes will help to reveal categories of concepts or themes and codes make it possible to retrieve the data more easily for further analysis.

So, for the example of social identity in Facebook above, as you review the data collected from other participants’ sites and your interviews with them, imagine you notice a tendency in the descriptors that seem to refer to the participant’s demographics: gender/sex, sexual orientation, age, etc. These demographics may each become a category where you will compile the individual instances that demonstrate that category. A post from a person who identifies as male describing how he lifts weights and strives to attain muscle mass might be categorized under gender, and specifically masculinity. A person who posts a message about being a women who competes in a race for wheel-chair users might be categorized under physical abilities, etc.

The code or coding scheme is to look for demographics, the resulting categories or themes are gender/sex, sexual orientation, age, etc. In the study of coming-out narratives, the code is degree of agency, the categories are the specific degrees noted in the data. In the study of relational conversation, questions are the code, the specific functions of questions are the categories. Coding helps to identify whole families of categories and sub-categories. They help the researcher not only sort, but display the data in visual ways to make the meaning more apparent.

We offer two cautions regarding oversimplifying this process. First, while you may see preliminary codes and categories emerge from the data, the final ones may not be the same. It is important to keep one’s mind open to considering alternative or extended coding systems otherwise one may only see what s/he wants to see. While there are multiple ways to organize data and endless sizes or levels of latter categorization possible, there will likely be a way that makes sense to you. There is also no set number of categories required. You should have as many categories as it takes to account for all the data possible. In the end, you should feel the categories do a good job of representing the data as a whole, both in terms of its similarities and in terms of its differences (Lincoln & Guba, 1985).

Second, a warning about labels. Qualitative researcher use the terms coding schemes and categorizing to refer to the process of organizing data in qualitative analysis, but they do not always use the two terms in the same way. Some researchers use the terms interchangeably. Others claim there are important distinctions between the two terms. We follow Lindlof and Taylor (2002) who argue researchers first  code  the data into groups and then look for categories (how the groups connect in terms of concepts, themes, constructs). Codes are descriptive of the data groupings, whereas categories and themes are more interpretive – they tell what overall meaning the researcher makes of the groupings. Themes and category systems are the result of coding (Saldana, 2009). For example, a code may be chunking the data by participant demographics, which results in a categorization system of data that emerged according to race/ethnicity, social class, age, and gender/sex. A theme for the category of race/ethnicity might be “participants identify with homogeneous others” or “participants celebrate multicultural identities.” Each are conclusions or themes drawn from data within the category of race/ethnicity.

To further assist you in identifying codes and categories, two other researchers proposed a list of questions you might find useful (Lofland & Lofland, 1995).

Tips for coding and categorizing data:

• What is this? What does it represent?
• What is this an example of?
• What do I see going on here? What are people doing? What is happening? What kind of events are at issue here?
• If something exists, what are its types?
• How often does something occur?
• How big, strong, or intense is something?
• Is there a process, a cycle, or phases to the topic of study?
• Does one thing influence another?
• Do people use the interaction in specific ways?

(See also Sociologist Graham Gibbs’ lecture, “What is coding for?”  http://www.youtube.com/watch?v=5xM-9yuBhMc )

Data Reduction: If the data set is relatively small or the initial categories seem particularly salient, the researcher may not need to proceed to this step of refining the focus of analysis. However when conducting extensive ethnographic research it is particularly necessary to reduce the focus of analysis to a size and framework the researcher can better manage. Framing or  frame analysis  is selecting a focus or lens from which to analyze and present the data. When doing so, the researcher acknowledges that multiple frames are possible and that one’s unique perspective may influence how one positions and interprets data. One has to make choices and this fact should be documented and rational provided for the choices made. For example, one’s roles in society may influence the frame taken in analysis: a student, a psychology major, a sociology major, a communication scholar, a parent, a single person, etc. (Grbich, 2007). The goal is to develop in-depth quality in the final analysis, not quantity. Thus the researcher may begin to identify primary categories or themes and secondary ones that may or may not end up in the final report.

If we return to the example of studying participants’ identity construction on social media, the researcher may decide reporting people tend to describe themselves according to demographics is not very insightful or useful. Perhaps the comments suggest a particularly interesting connection among the participants’ comments about their gender, sex, and sexual orientation, and that given the researcher’s review of previous research and/or training, the researcher decides this focus would make a more useful contribution to the state of knowledge. The researcher is then framing the study around themes or categories tied to gender, sex and sexual orientation. Other demographic information such as race, ethnicity and age may be related in the participant comments and serve as a secondary level of themes or categories to be explored.

Throughout the analysis process, but certainly while conducting data reduction, the researcher should be looking for  exemplars  – examples such as quotes from the data that vividly illustrate the themes and categories proposed. The examples should emulate the boundaries or characteristics the researcher has used to distinguish the themes or categories. They should make the themes or categories come alive for the reader (Ryles, as summarized by Geertz, 1973). These are what will be presented in writing the report to represent the qualitative data reviewed.

Conceptual Development: The analysis process would not be very meaningful if the researcher stopped after creating a list of categories. The researcher now needs to determine what meaning to make of the list. In this step the researcher attempts to integrate the categories to consider what they mean when examined together. The researcher looks at how they might relate to or influence each other (Lindlof & Taylor, 2002). This phase is a  meta-analysis  – an examination of the examination of data – the creation of codes, categories and themes created in the previous steps. In grounded theory, described later, this is called  axial coding , but the process and goal is the same across methods – attempting to connect the codes, categories and/or themes.

The process used is basically to repeat the same steps but on a higher level of analysis: review all the codes, categories or themes (instead of the individual instances of each) in comparison to each other and attempt to understand how they relate to each other. It is as if the researcher is constructing a framework or umbrella in which to locate the individual codes, categories and themes. There are many ways researchers may attempt to do so. The manual methods suggested previously for color coding, creating grids or other visual depictions of the categories and themes can help make the connections visible. Researchers may see that the categories or themes fit well with an existing theory and so place them within that theoretical context, they may see that together the parts suggest a new theory or conceptualization of the issue being studied, they may see a metaphor emerge that helps to explain how the parts fit together, etc.

• Triangulation : As defined in the first part of this chapter, triangulation is approaching the study from multiple perspectives to enhance the rigor or integrity of the results of the study. It can include using multiple methods of data collection, gathering multiple sources of data, and for analysis it can include having multiple researchers or coders for the data, and/or drawing from multiple academic disciplines to frame the study. The idea is that if shared meanings emerge from multiple directions of data collection and analysis, those meanings are likely more sound. Sociologist Norman Denzin (2006) proposed this method to directly refute the criticism that because multiple interpretations are possible in qualitative research, the findings proposed from a study are unreliable or invalid. 
• Representativeness:  The researcher should be sure there are multiple exemplars – specific examples of quotes or behaviors that support each theme or conclusion formed. If the researcher cannot come up with enough strong examples, the claim is likely not strong enough to be warranted.
• Member check:  After preliminary or final analyses, the researcher shares the interpretations with participant members of the study to solicit feedback. The sharing can be in the form of face-to-face interviews, focus groups, or written data summaries. The goal is for the researcher to find out if the interpretations rendered ring true to the participants. Do they feel the results reflect their lived experiences? The researcher may want to use a detailed standard list of feedback questions or ask for a more holistic reaction to the research summary. After obtaining input, the researcher implements the information gathered to rethink the findings and/or cite as support for the claims in the study.
• Transparency:  Transparency in research is the expectation that researchers will make the entire process of their work explicit, openly sharing the process of meaning construction with the readers (Hiles, 2008; Seale, Gobo, Gurbrium & Silverman, 2004). This criterion emerged out of a need, as previous qualitative and quantitative research was often not transparent, in part due to page limits and related costs for academic journal publications. Thus research conclusions and what academia comes to call knowledge appeared as if from a vacuum, free of individual decision-making and perceptual influences that are always present in human endeavor, and prevented others from testing out the results further. Transparency is an ethical consideration. When researchers clearly document the steps taken in data collection and analysis and share these with the reader, s/he should be able to better understand and visualize how the conclusions were formed. If this clarity is not present, the value of the study and the researcher’s integrity may come into question. 
• Reflexivity:  An effort to examine how one’s own thoughts, feelings, and behaviors might intermingle with phases of the research process (Bochner & Ellis, 1992). Reflexivity is the recognition that the researcher is a part of what is being studied. The researcher’s unique cultural lens will necessarily affect the research process. Taking the time to place oneself and one’s values and possible biases under examination better assure this inevitable influence is not abused and that not only the researcher, but the participants know the nature of the researcher’s likely influence on the study. Careful field notes and keeping a diary or log during the analysis process will help the researcher examine this criterion.
• Grounded Theory –  Grounded Theory is actually one of the individual analysis methods described below. Its mention here speaks to the pervasive influence of grounded theory on the general process of all qualitative research. The key point regarding using grounded theory as a criterion to assess rigor and integrity is that the researcher should refrain from using her/his words to label themes/categories, and rely wherever possible on the words and images conveyed by the participants. The example above on studying self-esteem from African American women’s perspective illustrates why this is so important. The two White women researchers had initially inadvertently assigned their own label for a theme as racism rather than “respect” which the participants used.

These five steps represent the general process of conducting qualitative analyses. What follows is information about the specific analysis methods most commonly used: thematic analysis, grounded theory, and content analysis. We will also briefly introduce the reader to two methods that focus more specifically on  how  the verbal and nonverbal messages under study were constructed – discourse analysis and conversation analysis.

Thematic Analysis .  This is the most general, easily accessible method of data coding or categorizing. The reason this method is more accessible is that the rules for the general process of analyzing data as described above are more relaxed. This does not mean thematic analysis is unsystematic however. The researcher still defines the unit of analysis and data is coded first to organize it. From the categories the researcher looks for a theme within each category and then an umbrella theme or themes that might connect the individual themes. The concluding themes should best reflect the data as a whole.

In a comparison of grounded theory and thematic analysis, Mohammed Ibrahim Alhojailan (2012) concluded thematic analysis is a comprehensive method, just as is grounded theory, however “It provides flexibility for approaching research patterns in two ways, i.e. inductive and deductive” (p. 39). In its purist sense, grounded theory requires data to be inductive only. In thematic analysis, the themes may be based on information gathered from interviews and previous research and theory. And, the data does not have to be collected at one time. “This makes the process of thematic analysis more appropriate for analyzing the data when the researcher’s aim is to extract information to determine the relationship between variables and to compare different sets of evidence that pertain to different situations in the same study” (p. 39). 

Characteristics of Thematic Analysis:  Theme analysis is often used to study texts, both written and transcribed oral texts such as interviews or focus group discussions. The themes can come from the research questions and objectives guiding the study, from previous research or theory presented in the literature review, from the researcher’s standpoint as a certain gender and sex or ethnicity, social role, etc., from the data itself gathered in the study, or what is most common is from a combination of pre-existing influences and meanings that emerge from the data.  “This makes the process of thematic analysis more appropriate for analyzing the data when the research’s aim is to extract information to determine the relationship between variables and to compare different sets of evidence that pertain to different situations in [the] same study”   Alhojailan (2012, p. 39).  

Steps of Conducting a Thematic Analysis:  While the overall steps are as described above for qualitative data analysis, in thematic analysis steps 3, 4 and 5 take on a particular process. The researcher must answer the question: When do comments or behaviors become a theme? Literally anything could be claimed as a theme, so what makes a given researcher’s claims acceptable? While the comment or behavior needs to occur repeatedly in the data, counting repetition alone is not enough. Interpersonal Communication scholar William Owen (1984) suggests the researcher will know s/he has a theme when it meets the following criteria: recurrence, repetition, and forcefulness.

• Recurrence means that at least two parts of the data have the same meaning, although the meaning may be expressed in different words. The researcher looks for a pattern in the relational or underlying meaning of a message.
• Repetition is about frequency – that the same key words, phrases or sentences are mentioned again.
• Forcefulness refers to the degree of emphasis conveyed in the message. Does the way an idea is said or written suggest it is important to the speaker? This can be through vocal inflection, timing, volume, and/or emphasis placed on words or phrases in written or oral form.

While Owen would require that the data meet all three of these criteria, it may not always be possible to do so. What is important is that the researcher show evidence in the text to support her/his claims, and that they speak to the underlying meanings being expressed. There will always be other meanings in a message; the researcher’s job is to best assure the themes selected seem primary, rather than secondary. 

Owen offers an example from an analysis of a daily log a female college student was asked to make about her relationships. This one is about a high school friend. The short passage reveals all three criteria simultaneously:

Day One: She is an ideal friend. I haven’t really known her for very long, but it seems like we jumped into the middle of a relationship. I feel like I’ve known her forever.  Day Three: That night we burnt chocolate-chip cookies and drank white wine, and for the  first  time since Bud died (her brother), I had someone I could relate to. Day Five:  Special  is the word-of-the-day.

The thematic concept Owen claims is relational uniqueness. The references to “ideal friend,” jumped into the middle of a relationship,” “feel I’ve known her forever,” I had someone I could relate to,” “special is the word-of-the-day,” “It’s like Debbie and I share a secret,” “she is so special, we are so special!” “We have the perfect relationship,” all suggest the theme of uniqueness. Recurrence is apparent as is repetitious, with the word “special” being used three times in one entry. Forcefulness is also apparent with the italicizes used as in “for the  first  time,” and “special.” Comparing the current relationship to the comfort of her relationship with her brother who has now died is quite powerful.  (For an online lecture on the steps of theme analysis, see sociologist Graham Gibbs, University of Huddersfield, UK ).

Strengths and Limitations of Thematic Analysis . Because this method is a general and relatively simple (but not fast) process, it is the most widely used method for analyzing qualitative data. It is a good choice for novice qualitative researchers because the process is easy to understand. It mirrors the social cognition perceptual process we humans engage in every day: organizing countless types and sizes of data into categories to make sense of the world around us. Thematic analysis can be less time consuming than other methods for qualitative data analysis, although to be done well, it still requires repeated reviews of all the data and a willingness to sort and resort data according to appropriate themes. And, it can be applied to analyzing all sorts of data from looking for themes in artifacts, such as news stories about an event, to looking for themes across interviewees’ comments about a particular topic, to looking for themes in  how  individuals who share a cultural identity tend to exhibit similar communicative behaviors or categories. It also works when there is a large volume of data, which is not as easy to do with other qualitative methods. These strengths of the method also become limitations. Because it is so general, it is sometimes criticized for not being systematic enough. While not a failure of the method, some researchers using thematic analysis fail to fully account for their thinking that went into creating the themes claimed as results of the study. A limitation of the method itself is that the meanings of human behavior are interdependent, not independent of other being or the physical and social context. Thematic analysis calls for sorting data into discrete categories, whereby the same comment cannot be placed under two themes. Yet, as the example below will likely suggest to the reader, comments or behaviors often seem connected and could be placed in multiple categories. The themes are almost always interdependent, but the researcher may not acknowledge this. And so, research using thematic analysis is more easily open to criticism regarding the relevance of the themes identified and the bias or hidden agenda of the researcher’s choice in framing the data within the selected themes.       

Example of Thematic Analysis:

Pohl, Gayle, & DeFrancisco, Victoria. (2006). Teaching through crisis.  The International Journal of Diversity in Organisations, [sic]  Communities & Nations

In a study of why some college instructors addressed in their classrooms the events of the airplane bombings in the U.S. on 9/11 of 2001, their comments suggested the following themes: they felt they had no choice but to address the event; they needed to make sense of the events both for themselves and their students; and they felt the events fit their course content (Pohl & DeFrancisco, 2006). Below are sample comments that when sorted suggested the three themes.

• Because I felt I had to both for myself and for my students. The event was too large and had too many ramifications to ignore. I knew that it was going to be an issue that we would be dealing with for a long time.
• I really wrestled with the decision. It seemed that it would be impossible, if not completely inhuman, to try to ignore.
• Both the students and I seemed to need to talk about it and explore the events surrounding 9/11.
• It was a historic, painful, and socially critical event.
• A lot of people, including students, were experiencing a variety of strong emotions. I think it’s important to open discussion for those who want to talk and those who might benefit from listening to others’ ideas. Our students look to us for guidance – we should provide it.
• I teach in the state of New York. During the days and weeks that followed 9/11, a few members of my classes were mobilized as part of the National Guard. Other members were “absent” mentally or physically because they had found out, or hadn’t found out, about whether their family members and dear friends were alive. These issues were so in our faces” that I believed I had an obligation to incorporate the events in my teaching. Furthermore, when I suggested to my Comm. Theory class that we carry on with the projected daily schedule, they decided they WANTED to learn about theory in order to make sense of what was happening.
• I taught on the day of the attacks, and students needed some help in giving meaning to what happened.
• My students seemed paralyzed by the events of 9/11. We incorporated these events because no one else seemed to be talking about them. There was a tremendous need to address what was happening so students could begin to see beyond the events of the day.
• The events occurred shortly before my first class met, and as a relational scholar, I don’t feel we should ignore the things that affect our everyday lives in our teaching. I feel it is most powerful to use our lives in applying communication principles. As it was, we were about to discuss confirmation and disconfirmation and it seemed to me that these events could exemplify those concepts on a larger than interpersonal scale.
• Our college is just 70 miles from New York City. Some had family or friends in the World Trade Center area. My class met on September 12. We were all stunned. A Communication Ethics class will always address such issues as news media decisions to transmit graphic images. These questions were poignantly present, and the arguments on either side very forcefully available to us.
• I teach Epidemiology, human diseases, and environmental health. Terrorism and biological, nuclear, and chemical weapons issues are all topics that have to be dealt with in these courses. Unfortunately, now I realize that I have to make sure I teach these topics because a well-trained responder might save lives in the future. It’s sad I even have to deal with these issue.
• After teaching a course on “Minority Images in American Media” for several years, and regularly emphasizing the manner in which the media--- especially the news media – rely on stereotypes of Arabs and others from the Middle East as terrorists, it was immediately evident to me that I needed to spend more time addressing this issue. Also, I teach a course on Visual Communication and, for several years, had difficult convincing my students that visual images communicate much more powerfully and immediately and effectively than words do. September 11 made that argument much easier to convey with the four-day bombardment of images over and over again, so including issues from Sept. 11 in my lesson plan was an obvious choice.

Together, the four themes suggested a pattern or over-arching theme among the responses – the instructors felt a need to use the course experience to work through the crisis with their students. Some did this in a more formal way by applying relevant course concepts to help critically analyze the contexts surrounding the events, others more basically sought to create a safe space for them and their students to sort through their mixed emotions.  

Grounded Theory Method. The word “theory” in this method of data analysis might be a bit confusing initially. People tend to think of theory and methods as separate, but in this groundbreaking methodology first proposed by sociologists Barney Glaser and Anselm Strauss (1967) the relationship between theory and method are more overtly celebrated. The approach has been refined and is widely practiced today in qualitative research. It is not simply a method for categorizing data, it is a method for using data categorization to reveal underlying theory (and the word  theory  can be used here in its most general sense, as an attempt to explain some phenomena). The resulting theory can be in the form of themes, or other attempts to explain deeper levels of meaning for what is going on in the interactions of study, referred to as  substantive theory , or the result can be  formal theory  that will be used to advance the larger conceptual field of sociological inquiry (Glaser & Strauss, 1967). The idea is that theory can be and is most useful when it is developed from observation, rather than the other way around as done in quantitative research where the theory dictates the direction of a study. Thus Grounded Theory calls for an inductive approach to building theory from the ground up – based on research observation and analysis.

Unique characteristics.  As noted above, the most unique characteristic about grounded theory is that the meanings should emerge from the data itself – from the words and behaviors of the participants. Thus, it is an excellent extension of the ethnographic approach where researchers work to honor the words and perceptions of the participants. The researcher must work to resist letting h/his perspective overly influence the meanings derived from the data. Because of this characteristic, grounded theory has become a criterion for assessing a researcher’s ethics in qualitative research and for assessing the value of the results of the study.  Such criteria demand  a highly systematic and rigorous process of data coding and meaning development.

Steps in conducting.  Grounded Theory is also referred to as  open coding  or the  constant comparative process  of letting the meanings open-up -- emerge from the data, rather than imposing predetermined codes, from previous research, theory, and/or the research question(s). The terms open coding and constant comparative are actually what researchers do in steps 2-5 of the qualitative research process. They will be described further below, as they are the heart of what makes grounded theory a unique qualitative approach.

Step one (data immersion):  The researcher begins with an exhaustive review of the data, trying to capture as much of it as possible.

Step two (data management):    Open coding  is the initial, unrestrictive coding of data” before the researcher knows what the final categories or themes will be (Lindlof & Taylor, 2002, p. 219).  This step still requires defining the smallest unit of analysis and tracking each one closely. The researcher tries to ignore previous theory and research and let the meanings emerge through a process of  constantly comparing  or putting each piece of the data next to the previously coded data to look for similarities and/or differences, letting the meanings emerge piece by piece.

Open coding is a creative process. You can use a pencil, highlighter, post-it notes, or the computer to block quotes and other data and move them around as you begin to see patterns emerge. Each piece of data or instance is compared to the previous ones already categorized to see where the new piece of data belongs. Does it belong in a current category, or does it suggest a new category is warranted? You are looking for what makes sense regarding ways to organize the data. Through repeated reviews of the data the distinguishing characteristics of each category and the coding scheme will emerge.

In vivo coding.  This type of coding is done at the same time as open coding, it is a more specific type of open or grounded coding where the actual names of the codes come directly from what the participants say. The idea is to avoid the researcher imposing her/his work view as reflected in her/his labels for codes and themes. Instead the labels reflect the insider participant perspectives – it is using their words. Thus it is a preferred, more carefully grounded coding system, but it is not always possible to attain. For example, while the researcher may be quite sure the participants are engaging in a great deal of face-saving strategies, as in the case of inappropriate behaviors and creates a coding scheme for these, the participants may not realize or want to verbally recognize those behaviors.

Step three (data reduction):  Eventually the number of new categories will diminish and you, as the researcher can begin to consider whether you have reached the point of what is called  theoretical saturation  (Glaser & Strauss, 1967) .  When no new categories are emerging and the categories you have created seem stable, the researcher can assume no new data is needed for now, and the analyses may be sufficient. However, if the results do not seem very insightful, rendering for example new, unique interpretations, the researcher may still decide to return to the field to collect more information.

Step four (conceptual development):  When the open coding is completed (at least for now), the researcher moves to conduct what is called  axial coding , basically the same general step four described previously. Think of an axis – as identifying a common framework on which the categories or themes can be located. In this step the emergent or grounded theory becomes more overt. The researcher examines how the categories created might relate to each other by conducting a metacoding – codes that attempt to connect the categories, remembering these codes must also be grounded in the data.

A useful tool to test one’s metacoding is called  negative case analysis  (Lincoln & Guba, 1985) .  The basic idea behind negative case analysis is that if the researcher’s emergent theory from the axial coding can account for a specific case, incident, person, or comment that does not seem to fit with the other data codes or categories, then the resulting theory is stronger. Sometimes researchers will return to the field to find a negative case to test their emergent theory conclusions. In this view, the negative case is not to be feared as something that will hurt the researcher’s study, but rather a piece of information that may make the resulting theory more nuanced and reflective of the complexity of participants’ lived experiences. In many cases, the information from the negative case analysis may send the researcher back to the field or back to a previous step in data analysis. The researcher must find a way to account for the negative case, which may require at an extreme completely rejecting the prior analysis, and at a minimum, more carefully describing the categories, themes, and emergent theory.        

Step five (evaluating results):  As noted in the previous step, the process of assessing results has already begun. However, even after the researcher has conducted a negative case analysis and axial coding, the results are subjected to at least one more assessment. At this point the researcher may feel h/his interpretative abilities are exhausted and it is time to get a new perspective form other outside researchers, members of the community of study, or insider perspectives from some of the participants.  Member checking  (Lincoln & Guba, 1985) comes into play here. The researcher may choose to share the results with members of the study to see if the categories, themes, and resulting theory make sense to them. Do they represent their lived experiences? Member checking can be done very informally as in conversations with individuals, or the researcher may choose to circulate a summary of the findings with survey responses, or conduct a focus group discussion with members. It is not necessary, nor usually possible, to solicit feedback from everyone in the study.  The goal is to determine if the researcher’s conclusions ring true to the participants’ actual experiences and perceptions. It is an ethical tool to add value and credibility to the final report of the study.

(For a lecture on this topic, see sociologist Graham Gibbs, University of Huddersfield, UK, “Grounded Theory: Core Elements,”  http://www.youtube.com/watch?v=4SZDTp3_New )

Discourse Analysis and Conversation Analysis

There are two other interdisciplinary methods for studying spoken and written texts or discourse, including the multiple paralinguistic ways in which the speaker delivers the words. Discourse Analysis focuses on speech (or texts) as communicative acts and examines how people use language to construct meaning. The focus of analysis is on the content of what is said and the metamessages the content conveys, perhaps about identities, relationships, positions on a social issue, etc. Conversation Analysis focuses on how the speakers communicate – the patterns of using conversational turn-taking tools such as questions, pauses, volume, and more, to negotiate identities, relationships, etc. Both methods examine the text or discourse in a line-by-line fashion with detailed transcriptions. Conversation Analysis requires the added transcription devices to indicate the amount of time between turns at talk, the paralinguistic qualities of the voice, etc. (see Gail Jefferson’s transcription system, in Sacks, Schegloff & Jefferson, 1974). As you might guess, the meanings derived from both methods are deeply embedded in the unique cultural understanding. Discourse Analysis is often used in rhetorical studies, which is reviewed in another section of this textbook. It is also used heavily in the communication sub-field of performance studies (see for example, Carlin & Park-Fuller, 2012; Palczewski, 2001). In both of these areas the researcher is attempting to make meaning of words and often nonverbal messages to provide new insights and/or greater understanding. Conversation analysis is used in some ethnography if the focus is on studying the structure of interaction in language use/conversation (see for example, Hall, 2009).

Data Write-Up

When one reaches this phase of the research process it is easy to think the creative, critical thinking work is done, but particularly in qualitative research, it is not. Writing the results is part of the meaning making process. Writing itself, is often viewed as an analysis method (Richardson, 2003). It is an opportunity for the researcher to synthesize what was learned and once again review the meanings rendered, but this time in the larger context of previous research summarized in the literature review. Often returning to this larger body of knowledge will push the researcher to make deeper and/or more complex connections among their own themes and meanings rendered.   

Not all qualitative research reports follow the traditional social science organization, but if you are not writing an autoethnography or narrative study, we recommend the social science organization for clarity. It contains four basic parts. The first is the introduction and literature review, second is a description of the research methods selected for collection and analysis, third is a description of the results or meanings formed from the data, and fourth is a discussion of the study.

A metaphor that might be helpful for visualizing how your paper will look is an old-fashioned hourglass. The introduction and literature review begins broadly and then the paper narrows to a focus on the specific study’s design. The paper ends more broadly again where the author places h/his specific results back into the context of previous research and the larger field of study to consider how the study contributed to the larger field.

There are some basic criteria for the whole report to keep in mind. They are the same criteria proposed in the data analysis process. And, by the way, these are good criteria to look for as you assess other’s reports, as well.

• Transparency in writing about the process is key. Transparency refers to the need to be open, clear and explicit in describing the research procedures used to design the study, conduct data collection and data analysis (Seale, Gobo, Gurbrium & Silverman, 2004).The reader should be able to trace your steps and follow how you came to the conclusions you did. If the reader cannot do so, the author is hiding what may be useful information to help others understand how s/he came to the conclusions formed. 
• Representativeness requires the researcher to be sure the results are grounded in the words and experiences of the participants and not overly controlled by the researcher’s voice. Participant quotes are your data, the narrative in the report is your voice weaving these quotes together to make meaning. Thus much of the write up will include description – the participants' actual words and behaviors to support your claims (themes or conclusions). The reader should not feel the patterns, themes, or other conclusions were drawn out of thin air. The reader should be able to see 2-3 exemplars for each claim made about the results of the study.
• Reflexivity is related to transparency. It is an effort to be open with the reader and acknowledge that you as the researcher are a part of what is being researched. You are not an objective observer uninfluenced by the study or detached from its results. The reflexive author is careful to separate h/his own feelings and comments from what the participants said, and careful to note when such a clear separation is not possible. Reflexive writing is being critical of one’s own work. This does not mean always being negative, pointing out limitations, just that one recognizes h/his potential role in the process.

Introduction and Literature Review

The introduction and literature review are combined in this step. It is useful to think of them as a coherent rationale for the study you conducted or propose to conduct. The Rationale is drawn from life experiences, review of news reports, popular press, secondary sources (as in websites, textbooks or published reviews of literature and most importantly, previous original scholarship on the topic. As in quantitative research, research questions that guide original qualitative research are generally expected to be based on previous research. Some ethnographers and autoethnographers prefer not to review the literature prior to collecting original research so that their views are not tainted. In this case, the literature view portion of the final report would go in the discussion of the results of the study, rather than as a part of the rationale of the study.

The rationale is built by answering the following questions in the paper, usually in this order:    

• A statement of the problem that needs to be studied (this can be a social problem, an academic theory that needs to be developed, a lack of experience needed, etc.) The definition of problem is meant to be broadly defined here. This is the attention-getter of the paper. It should compel the reader to want to know more. (Usual length is from a paragraph to two pages, double-spaced.)
• Embedded in the statement of the problem and why it needs to be addressed, the researcher introduces for the first time any key terms that will be used repeatedly in the study. These should be briefly defined for the reader with a citation of the source. For example, if you were doing a study on how people build an intercultural relationship with someone from a different race or ethnicity, What key terms would you be using? Mostly likely you would need to define culture, race/ethnicity, prejudice, intercultural relationships and relational development. While there may be other concepts, only the most central ones need to be introduced here.
• A preview of the type of research warranted from the review of the problem.
• There are multiple ways to organize a review of the literature. You will want to select what helped you organize the information and understand it best. Topical organization is most popular, but it might be useful to organize the review in a chronological fashion. The organization of sub-headings should help lead the reader to understand why you have decided on the design of the study you selected.
• The question that is commonly asked is, “how much do I need to include from each study?” There is no specific answer – thank goodness. There is room for your thoughts. Basically include what is most relevant to the present study you will or did do and not more. Thus, if you adopted methods from a study then describe the study’s methods, but if you are only citing the study as evidence that your topic is important, then just cite the study, as in parentheses at the end of a statement you make as in: (Ellis, 2004). 
• A review of literature is not just a cut and pasting of a series of research abstracts. Your voice synthesizing the previous research should be central in the review.
• The review of previous research literature usually concludes with the proposal of one to three overall research questions the author will attempt to answer with the specific study proposed. (Length varies a great deal depending on the instructor’s assignment and/or publishers’ page limits. A rule of thumb is that it be almost as long as the reporting of results from your study, from five to sixteen pages).

Research Methods

As in quantitative research, there are two sub-headings to this: data collection and data analysis.

Data Collection.  Here the researcher describes the general research design proposed to answer the research questions stated at the end of the literature review. The criterion of transparency is key to follow here. This section may range from two to approximately six pages. This section includes the following, usually in this order:

• Participants – method used for soliciting participants, ethical guidelines followed in soliciting them and in terms of promises of confidentiality, or other concerns to not ask more of them than is necessary. Forms of consent are referenced and included in the appendices of the paper. Lastly, in qualitative research, if there are not too many participants, the researcher might include their first name or pseudonym and a brief description of each person’s demographics collected as relevant to the study.
• Data Collection – a detailed description of the methods chosen (e.g. interviews, ethnographic observation, …), how they were conducted, and why these choices are relevant for the general research questions asked. Actual interview questions are usually put in the appendices.

Data Analysis.  Here the researcher explains which analysis tools (e.g. content analysis, theme analysis) were selected and why they are a good fit for the general research questions asked and the specific data collection methods employed. This section includes:

• Description of how data immersion was accomplished (e.g. length of time taken, number of readings, etc.)
• Definition of the unit of analysis used with a few examples
• How the data was coded and what emerged as the coding scheme
• How the researcher managed the data and reduced it to a focus that was attainable and relevant

This is where the author describes what was constructed in step four and five of the general data analysis process: the conceptual development and evaluation of results or meta-analysis. The author describes what meanings were taken from the data based on the analysis process. A suggested outline:

• A list of the categories or themes and exemplar texts for each to demonstrate them
• If negative case analysis was conducted, how it changed the resulting interpretations.
• Results from the meta-analysis of themes or categories. What did the researcher find about how these might be related? What is the deeper and broader level of meaning attained from the analysis process?

This is where a criterion used in autoethnography might be useful (Ellis, 2004). The author is expected to use  evocative writing  -- writing that calls up emotional responses from readers. It compels readers to engage with the material beyond a cognitive level. By calling for writing that is compelling, we are not suggesting the author try to manipulate the readers’ emotions. It is just that in autoethnography the quality of a study is measured so to speak by how much it compels the readers, draws them into the reality being described, and helps them see the experience from an inside view. We think this is a good criterion for most qualitative research on human experience.

If you imagine the introduction and conclusion of your research report as covers on a book that are mirror opposites, the conclusion should respond to and connect with the introduction. The goal is that when the reader finishes s/he will feel like the book just snapped shut. The author connects the findings from the present study to the larger social problem being addressed and the larger body of research in the literature review. When the covers snap shut, the author has done a good job of answering the basic question of, “so what?”  “Why these research questions, why these participants, why this research design, why these interpretations of meaning, why do the results matter?” The following outline is offered to help assure you answer the question of “so what?”

• Preview of the sub-headings in the conclusion
• Summary of the key findings (themes, theory development and sub-categories supporting them  (less quotes are needed here).
• Contributions of the study – both practically (e.g. for practitioners working with students, patients, for people to apply in their daily life, etc.) and academically (e.g. contributions to theory, methods, topic of study – the larger field of literature on the subject). Note this is especially where the author returns to the literature review and selects specific sources that the results of the study might speak to.
• Limitations of the study (e.g. in participant selection, data collection and analysis methods applied.
• Suggestions for future research (often based on the limitations of the present study).

Other Aspects of the Paper

For a more detailed description of the writing process and format, also see Chapter 7 of this book: “ Conclusion: Presenting Your Results ".

There are other parts of the academic paper you should include in your final write-up. We have provided useful resources for you to consider when including these aspects as part of your paper.

For an example paper that uses the required APA format for a research paper write-up, see the following source:  http://owl.english.purdue.edu/media/pdf/20090212013008_560.pdf .  However, this example uses quantitative data, so be aware the results section will not look like your qualitative study results. Qualitative reports tend to be longer.

Abstract & Titles.

http://writing.wisc.edu/Handbook/presentations_abstracts.html   http://owl.english.purdue.edu/owl/resource/560/1/

Tables, References, & Other Materials.

http://owl.english.purdue.edu/owl/resource/560/19/   http://owl.english.purdue.edu/owl/resource/560/05/

Data Presentation

Instructors will often ask you to present an oral version of your study in addition to the written report. This is a great way to help you gain more full comprehension of what you did in your study. If you can explain it well to others, you likely understand more deeply what you accomplished. The oral presentation is also a great way to prepare you for academic or other professional conference presentations that will help add to your resume. Prior to submitting original research to be considered for publication in journals or edited books, researchers share their studies orally to gain feedback and revise the written version of a study for submission to publication.

Two of the most common venues are oral presentations as a part of a panel of speakers and poster presentations. You might also be called upon to write an executive summary of the results of your study that makes it more accessible for people to review quickly. There are good resources for doing all of these online, so we have provided these here.

Oral Presentations

http://writing.wisc.edu/Handbook/presentations_oral.html   http://writing.wisc.edu/Handbook/presentations_delivery.html

Poster Presentations

http://writing.wisc.edu/Handbook/presentations_poster.html

Executive Summary

http://www.csun.edu/~vcecn006/summary.html http://www.stanford.edu/group/gender/ResearchPrograms/DualCareer/DualCareerFinalExecSum.pdf  (an example of an executive summary for university policy makers, from a research study on dual career academic couples) http://www.kff.org/entmedia/upload/7618ES.pdf  (another example of an executive summary from a study of food advertising to children on television)

Alhojailan, M.I. (2012). Thematic analysis: A critical review of its process and evaluation.  West East Journal of Social Sciences, 1 (1), 39-47. [access at  http://www.westeastinstitute.com/journals/wp-content/uploads/2013/02/4-Mohammed-Ibrahim-Alhojailan-Full-Paper-Thematic-Analysis-A-Critical-Review-Of-Its-Process-And-Evaluation.pdf ]

Blumer, H. (1986).  Symbolic interactionism: Perspective and method. Berkeley: University of California Press.

Bochner, A., & Ellis, C. (1992). Personal narrative as a social approach to interpersonal communication.  Communication Theory, 2,  65-72.

Carlin, P. S., & Park-Fuller, L. M. (2012). Disaster narrative emergent/cies: Performing loss, identity and resistance.  Text and Performance Quarterly, 32 (1), 20-37.

Cohen, M., & Avanzino, S. (2010). We are people first: Framing organizational assimilation experiences of the physically disabled using co-cultural theory.  Communication Studies ,  61 (3), 272-303.

DeFrancisco, V., and Chatham-Carpenter, A.  (2000). Self in community: African American women’s views of self-esteem.  Howard Journal of Communication, 11  (2), 73-92.

Denscombe, M. (2010).  The good research guide for small-scale social research projects  (4th ed.). Maidenhead, England: Open University Press.

Denzin, N. K. (2006).  Sociological Methods: A Sourcebook.  Piscataway, NJ: Transaction.

Dilthey, W. (2010).  Selected works, volume II: Understanding the human world . R. A. Makkreel & Frithjof, R. (Eds.). Princeton, NJ: Princeton University Press.

Ellis, C. (2004).  The ethnographic I: A methodological novel about autoethnography.  Walnut Creek, CA: AltaMira Press

Ellis, C., & Bochner, A. (2000). Autoethnography, personal narrative, reflexivity: Research as subject. In N. Denzin & Y. Lincoln (Eds.),  Handbook of qualitative research  (2nd ed., pp. 733-768). Thousand Oaks, CA: Sage.

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Qualitative Study

Affiliations.

• 1 University of Nebraska Medical Center
• 2 GDB Research and Statistical Consulting
• 3 GDB Research and Statistical Consulting/McLaren Macomb Hospital
• PMID: 29262162
• Bookshelf ID: NBK470395

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. Instead of collecting numerical data points or intervene or introduce treatments just like in quantitative research, qualitative research helps generate hypotheses as well as 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 stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and application of qualitative research.

Qualitative research at its core, ask open-ended questions whose answers are not easily put into numbers such as ‘how’ and ‘why’. Due to the open-ended nature of the research questions at hand, qualitative research design is often not linear in the same way quantitative design is. One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. Phenomena such as experiences, attitudes, and behaviors can be difficult to accurately capture quantitatively, whereas a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a certain 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 important 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, qualitative and quantitative work are not necessarily opposites nor are they incompatible. While qualitative and quantitative approaches are different, they are not necessarily opposites, and they are 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 that there is 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 together.

Examples of Qualitative Research Approaches

Ethnography

Ethnography as a research design has its origins in social and cultural anthropology, and involves the researcher being directly immersed in the participant’s environment. Through this immersion, the ethnographer can use a variety of data collection techniques with the aim of being able to produce a comprehensive account of the social phenomena that occurred during the research period. 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.” As opposed to quantitative research which is deductive and tests or verifies an existing theory, grounded theory research is inductive and therefore lends itself to research that is aiming to study social interactions or experiences. In essence, Grounded Theory’s goal is to explain for example 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 defined as the “study of the meaning of phenomena or the study of the particular”. At first glance, it might seem that Grounded Theory and Phenomenology are quite similar, but upon careful examination, the differences can be seen. At its core, phenomenology looks to investigate experiences from the perspective of the individual. 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 whereas Phenomenology focuses on describing and explaining an event or phenomena 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 ‘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, in the hopes of creating a cohesive story, or narrative. 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”.

Research Paradigm

Research paradigms are the assumptions, norms, and standards that underpin different approaches to research. Essentially, research paradigms are the ‘worldview’ that inform research. It is valuable for researchers, both qualitative and quantitative, 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 ontology 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 the work researchers do. It is important to understand the ontological and epistemological foundations of the research paradigm researchers are working within to allow for a full understanding of the approach being used and the assumptions that underpin the approach as a whole. Further, it is crucial that researchers 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 vs Postpositivist

To further understand qualitative research, we need to discuss positivist and postpositivist frameworks. Positivism is a philosophy that the scientific method can and should be applied to social as well as natural sciences. Essentially, positivist thinking insists that the social sciences should use natural science methods in its research which stems from positivist ontology that there is an objective reality that exists that is fully 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 it could be approximated. 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. 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 constructivist as well, meaning they think there is no objective external reality that exists but rather 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”. Essentially, Constructivist thought focuses on how ‘reality’ is not a fixed certainty and experiences, interactions, and backgrounds give people a unique view of the world. Constructivism contends, unlike in positivist views, that there is not necessarily an ‘objective’ reality we all experience. This is the ‘relativist’ ontological view that reality and the world we live in are dynamic and socially constructed. Therefore, qualitative scientific knowledge can be inductive as well as deductive.”

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 and can even change the role of the researcher themselves. For example, is the researcher an ‘objective’ observer such as in positivist quantitative work? Or is the researcher an active participant in the research itself, as in postpositivist qualitative work? Understanding the philosophical base of the research undertaken allows researchers to fully understand the implications of their work and their role within the research, as well as reflect on their own 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 at play. The following are examples of participant sampling and selection:

Purposive sampling- selection based on the researcher’s rationale in terms of 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 is 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 a participant-observer to share the experiences of the subject or a non-participant or detached observer.

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or in the environment of the participants, 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 with the use of Computer Assisted Qualitative Data Analysis Software or CAQDAS such as ATLAS.ti or NVivo.

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. Results also could be in the form of themes and theory or model development.

Dissemination

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

Examples of Application

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 for a better understanding of what the numbers truly mean and their implications. The qualitative methods can then help clarify the quantitative data and also help refine the hypothesis for future research. Furthermore, with qualitative research researchers can explore subjects that are poorly studied with quantitative methods. These include opinions, individual's actions, and social science research.

A good 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 there are no omissions of part of the target population. A proper collection method should be selected which will help obtain the desired information without overly limiting the collected data because many times, the information sought is not well compartmentalized 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 both why teens start to smoke as well as 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 non-smokers). This survey provides specific numbers (ranked importance of each factor) and is thus a quantitative research tool.

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

The researcher can conduct interviews and/or focus groups (qualitative research) about what types and forms of peer pressure are commonly encountered, where the peer pressure comes from, and where smoking first starts. The researcher hypothetically finds that peer pressure often occurs after school at the local teen hangouts, mostly 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 of smoking. The researcher finds a local park where many local teenagers hang out and see that a shady, overgrown area of the park is where the smokers tend to hang out. The researcher notes the 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 of the park, 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 the 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 population their perceptions of the changes, what factors are still at play, as well as quantitative research that includes teen smoking rates in the community, the incidence of new teen smokers, among others.

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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.

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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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83 Qualitative Research Questions & Examples

Qualitative research questions help you understand consumer sentiment. They’re strategically designed to show organizations how and why people feel the way they do about a brand, product, or service. It looks beyond the numbers and is one of the most telling types of market research a company can do.

The UK Data Service describes this perfectly, saying, “The value of qualitative research is that it gives a voice to the lived experience .”

Read on to see seven use cases and 83 qualitative research questions, with the added bonus of examples that show how to get similar insights faster with Similarweb Research Intelligence.

What is a qualitative research question?

A qualitative research question explores a topic in-depth, aiming to better understand the subject through interviews, observations, and other non-numerical data. Qualitative research questions are open-ended, helping to uncover a target audience’s opinions, beliefs, and motivations.

How to choose qualitative research questions?

Choosing the right qualitative research questions can be incremental to the success of your research and the findings you uncover. Here’s my six-step process for choosing the best qualitative research questions.

• Start by understanding the purpose of your research. What do you want to learn? What outcome are you hoping to achieve?
• Consider who you are researching. What are their experiences, attitudes, and beliefs? How can you best capture these in your research questions ?
• Keep your questions open-ended . Qualitative research questions should not be too narrow or too broad. Aim to ask specific questions to provide meaningful answers but broad enough to allow for exploration.
• Balance your research questions. You don’t want all of your questions to be the same type. Aim to mix up your questions to get a variety of answers.
• Ensure your research questions are ethical and free from bias. Always have a second (and third) person check for unconscious bias.
• Consider the language you use. Your questions should be written in a way that is clear and easy to understand. Avoid using jargon , acronyms, or overly technical language.

Types of qualitative research questions

For a question to be considered qualitative, it usually needs to be open-ended. However, as I’ll explain, there can sometimes be a slight cross-over between quantitative and qualitative research questions.

Open-ended questions

These allow for a wide range of responses and can be formatted with multiple-choice answers or a free-text box to collect additional details. The next two types of qualitative questions are considered open questions, but each has its own style and purpose.

• Probing questions are used to delve deeper into a respondent’s thoughts, such as “Can you tell me more about why you feel that way?”
• Comparative questions ask people to compare two or more items, such as “Which product do you prefer and why?” These qualitative questions are highly useful for understanding brand awareness , competitive analysis , and more.

Closed-ended questions

These ask respondents to choose from a predetermined set of responses, such as “On a scale of 1-5, how satisfied are you with the new product?” While they’re traditionally quantitative, adding a free text box that asks for extra comments into why a specific rating was chosen will provide qualitative insights alongside their respective quantitative research question responses.

• Ranking questions get people to rank items in order of preference, such as “Please rank these products in terms of quality.” They’re advantageous in many scenarios, like product development, competitive analysis, and brand awareness.
• Likert scale questions ask people to rate items on a scale, such as “On a scale of 1-5, how satisfied are you with the new product?” Ideal for placement on websites and emails to gather quick, snappy feedback.

Qualitative research question examples

There are many applications of qualitative research and lots of ways you can put your findings to work for the success of your business. Here’s a summary of the most common use cases for qualitative questions and examples to ask.

Qualitative questions for identifying customer needs and motivations

These types of questions help you find out why customers choose products or services and what they are looking for when making a purchase.

• What factors do you consider when deciding to buy a product?
• What would make you choose one product or service over another?
• What are the most important elements of a product that you would buy?
• What features do you look for when purchasing a product?
• What qualities do you look for in a company’s products?
• Do you prefer localized or global brands when making a purchase?
• How do you determine the value of a product?
• What do you think is the most important factor when choosing a product?
• How do you decide if a product or service is worth the money?
• Do you have any specific expectations when purchasing a product?
• Do you prefer to purchase products or services online or in person?
• What kind of customer service do you expect when buying a product?
• How do you decide when it is time to switch to a different product?
• Where do you research products before you decide to buy?
• What do you think is the most important customer value when making a purchase?

Qualitative research questions to enhance customer experience

Use these questions to reveal insights into how customers interact with a company’s products or services and how those experiences can be improved.

• What aspects of our product or service do customers find most valuable?
• How do customers perceive our customer service?
• What factors are most important to customers when purchasing?
• What do customers think of our brand?
• What do customers think of our current marketing efforts?
• How do customers feel about the features and benefits of our product?
• How do customers feel about the price of our product or service?
• How could we improve the customer experience?
• What do customers think of our website or app?
• What do customers think of our customer support?
• What could we do to make our product or service easier to use?
• What do customers think of our competitors?
• What is your preferred way to access our site?
• How do customers feel about our delivery/shipping times?
• What do customers think of our loyalty programs?

Qualitative research question example for customer experience

• ‍♀️ Question: What is your preferred way to access our site?
• Insight sought: How mobile-dominant are consumers? Should you invest more in mobile optimization or mobile marketing?
• Challenges with traditional qualitative research methods: While using this type of question is ideal if you have a large database to survey when placed on a site or sent to a limited customer list, it only gives you a point-in-time perspective from a limited group of people.
• A new approach: You can get better, broader insights quicker with Similarweb Digital Research Intelligence. To fully inform your research, you need to know preferences at the industry or market level.
• ⏰ Time to insight: 30 seconds
• ✅ How it’s done: Similarweb offers multiple ways to answer this question without going through a lengthy qualitative research process. 

First, I’m going to do a website market analysis of the banking credit and lending market in the finance sector to get a clearer picture of industry benchmarks.

Here, I can view device preferences across any industry or market instantly. It shows me the device distribution for any country across any period. This clearly answers the question of how mobile dominate my target audience is , with 59.79% opting to access site via a desktop vs. 40.21% via mobile

I then use the trends section to show me the exact split between mobile and web traffic for each key player in my space. Let’s say I’m about to embark on a competitive campaign that targets customers of Chase and Bank of America ; I can see both their audiences are highly desktop dominant compared with others in their space .

Qualitative question examples for developing new products or services

Research questions like this can help you understand customer pain points and give you insights to develop products that meet those needs.

• What is the primary reason you would choose to purchase a product from our company?
• How do you currently use products or services that are similar to ours?
• Is there anything that could be improved with products currently on the market?
• What features would you like to see added to our products?
• How do you prefer to contact a customer service team?
• What do you think sets our company apart from our competitors?
• What other product or service offerings would like to see us offer?
• What type of information would help you make decisions about buying a product?
• What type of advertising methods are most effective in getting your attention?
• What is the biggest deterrent to purchasing products from us?

Qualitative research question example for service development

• ‍♀️ Question: What type of advertising methods are most effective in getting your attention?
• Insight sought: The marketing channels and/or content that performs best with a target audience .
• Challenges with traditional qualitative research methods: When using qualitative research surveys to answer questions like this, the sample size is limited, and bias could be at play.
• A better approach: The most authentic insights come from viewing real actions and results that take place in the digital world. No questions or answers are needed to uncover this intel, and the information you seek is readily available in less than a minute.
• ⏰ Time to insight: 5 minutes
• ✅ How it’s done: There are a few ways to approach this. You can either take an industry-wide perspective or hone in on specific competitors to unpack their individual successes. Here, I’ll quickly show a snapshot with a whole market perspective.

Using the market analysis element of Similarweb Digital Intelligence, I select my industry or market, which I’ve kept as banking and credit. A quick click into marketing channels shows me which channels drive the highest traffic in my market. Taking direct traffic out of the equation, for now, I can see that referrals and organic traffic are the two highest-performing channels in this market.

Similarweb allows me to view the specific referral partners and pages across these channels. 

Looking closely at referrals in this market, I’ve chosen chase.com and its five closest rivals . I select referrals in the channel traffic element of marketing channels. I see that Capital One is a clear winner, gaining almost 25 million visits due to referral partnerships.

Next, I get to see exactly who is referring traffic to Capital One and the total traffic share for each referrer. I can see the growth as a percentage and how that has changed, along with an engagement score that rates the average engagement level of that audience segment. This is particularly useful when deciding on which new referral partnerships to pursue.  

Once I’ve identified the channels and campaigns that yield the best results, I can then use Similarweb to dive into the various ad creatives and content that have the greatest impact.

These ads are just a few of those listed in the creatives section from my competitive website analysis of Capital One. You can filter this list by the specific campaign, publishers, and ad networks to view those that matter to you most. You can also discover video ad creatives in the same place too.

In just five minutes ⏰ 

• I’ve captured audience loyalty statistics across my market
• Spotted the most competitive players
• Identified the marketing channels my audience is most responsive to
• I know which content and campaigns are driving the highest traffic volume
• I’ve created a target list for new referral partners and have been able to prioritize this based on results and engagement figures from my rivals
• I can see the types of creatives that my target audience is responding to, giving me ideas for ways to generate effective copy for future campaigns

Qualitative questions to determine pricing strategies

Companies need to make sure pricing stays relevant and competitive. Use these questions to determine customer perceptions on pricing and develop pricing strategies to maximize profits and reduce churn.

• How do you feel about our pricing structure?
• How does our pricing compare to other similar products?
• What value do you feel you get from our pricing?
• How could we make our pricing more attractive?
• What would be an ideal price for our product?
• Which features of our product that you would like to see priced differently?
• What discounts or deals would you like to see us offer?
• How do you feel about the amount you have to pay for our product?

Get Faster Answers to Qualitative Research Questions with Similarweb Today

Qualitative research question example for determining pricing strategies.

• ‍♀️ Question: What discounts or deals would you like to see us offer?
• Insight sought: The promotions or campaigns that resonate with your target audience.
• Challenges with traditional qualitative research methods: Consumers don’t always recall the types of ads or campaigns they respond to. Over time, their needs and habits change. Your sample size is limited to those you ask, leaving a huge pool of unknowns at play.
• A better approach: While qualitative insights are good to know, you get the most accurate picture of the highest-performing promotion and campaigns by looking at data collected directly from the web. These analytics are real-world, real-time, and based on the collective actions of many, instead of the limited survey group you approach. By getting a complete picture across an entire market, your decisions are better informed and more aligned with current market trends and behaviors.
• ✅ How it’s done: Similarweb’s Popular Pages feature shows the content, products, campaigns, and pages with the highest growth for any website. So, if you’re trying to unpack the successes of others in your space and find out what content resonates with a target audience, there’s a far quicker way to get answers to these questions with Similarweb.

Here, I’m using Capital One as an example site. I can see trending pages on their site showing the largest increase in page views. Other filters include campaign, best-performing, and new–each of which shows you page URLs, share of traffic, and growth as a percentage. This page is particularly useful for staying on top of trending topics , campaigns, and new content being pushed out in a market by key competitors.

Qualitative research questions for product development teams

It’s vital to stay in touch with changing consumer needs. These questions can also be used for new product or service development, but this time, it’s from the perspective of a product manager or development team. 

• What are customers’ primary needs and wants for this product?
• What do customers think of our current product offerings?
• What is the most important feature or benefit of our product?
• How can we improve our product to meet customers’ needs better?
• What do customers like or dislike about our competitors’ products?
• What do customers look for when deciding between our product and a competitor’s?
• How have customer needs and wants for this product changed over time?
• What motivates customers to purchase this product?
• What is the most important thing customers want from this product?
• What features or benefits are most important when selecting a product?
• What do customers perceive to be our product’s pros and cons?
• What would make customers switch from a competitor’s product to ours?
• How do customers perceive our product in comparison to similar products?
• What do customers think of our pricing and value proposition?
• What do customers think of our product’s design, usability, and aesthetics?

Qualitative questions examples to understand customer segments

Market segmentation seeks to create groups of consumers with shared characteristics. Use these questions to learn more about different customer segments and how to target them with tailored messaging.

• What motivates customers to make a purchase?
• How do customers perceive our brand in comparison to our competitors?
• How do customers feel about our product quality?
• How do customers define quality in our products?
• What factors influence customers’ purchasing decisions ?
• What are the most important aspects of customer service?
• What do customers think of our customer service?
• What do customers think of our pricing?
• How do customers rate our product offerings?
• How do customers prefer to make purchases (online, in-store, etc.)?

Qualitative research question example for understanding customer segments

• ‍♀️ Question: Which social media channels are you most active on?
• Insight sought: Formulate a social media strategy . Specifically, the social media channels most likely to succeed with a target audience.
• Challenges with traditional qualitative research methods: Qualitative research question responses are limited to those you ask, giving you a limited sample size. Questions like this are usually at risk of some bias, and this may not be reflective of real-world actions.
• A better approach: Get a complete picture of social media preferences for an entire market or specific audience belonging to rival firms. Insights are available in real-time, and are based on the actions of many, not a select group of participants. Data is readily available, easy to understand, and expandable at a moment’s notice.
• ✅ How it’s done: Using Similarweb’s website analysis feature, you can get a clear breakdown of social media stats for your audience using the marketing channels element. It shows the percentage of visits from each channel to your site, respective growth, and specific referral pages by each platform. All data is expandable, meaning you can select any platform, period, and region to drill down and get more accurate intel, instantly.

This example shows me Bank of America’s social media distribution, with YouTube , Linkedin , and Facebook taking the top three spots, and accounting for almost 80% of traffic being driven from social media.

When doing any type of market research, it’s important to benchmark performance against industry averages and perform a social media competitive analysis to verify rival performance across the same channels.

Qualitative questions to inform competitive analysis

Organizations must assess market sentiment toward other players to compete and beat rival firms. Whether you want to increase market share , challenge industry leaders , or reduce churn, understanding how people view you vs. the competition is key.

• What is the overall perception of our competitors’ product offerings in the market?
• What attributes do our competitors prioritize in their customer experience?
• What strategies do our competitors use to differentiate their products from ours?
• How do our competitors position their products in relation to ours?
• How do our competitors’ pricing models compare to ours?
• What do consumers think of our competitors’ product quality?
• What do consumers think of our competitors’ customer service?
• What are the key drivers of purchase decisions in our market?
• What is the impact of our competitors’ marketing campaigns on our market share ? 10. How do our competitors leverage social media to promote their products?

Qualitative research question example for competitive analysis

• ‍♀️ Question: What other companies do you shop with for x?
• Insight sought: W ho are your competitors? Which of your rival’s sites do your customers visit? How loyal are consumers in your market?
• Challenges with traditional qualitative research methods:  Sample size is limited, and customers could be unwilling to reveal which competitors they shop with, or how often they around. Where finances are involved, people can act with reluctance or bias, and be unwilling to reveal other suppliers they do business with.
• A better approach: Get a complete picture of your audience’s loyalty, see who else they shop with, and how many other sites they visit in your competitive group. Find out the size of the untapped opportunity and which players are doing a better job at attracting unique visitors – without having to ask people to reveal their preferences.
• ✅ How it’s done: Similarweb website analysis shows you the competitive sites your audience visits, giving you access to data that shows cross-visitation habits, audience loyalty, and untapped potential in a matter of minutes.

Using the audience interests element of Similarweb website analysis, you can view the cross-browsing behaviors of a website’s audience instantly. You can see a matrix that shows the percentage of visitors on a target site and any rival site they may have visited.

With the Similarweb audience overlap feature, view the cross-visitation habits of an audience across specific websites. In this example, I chose chase.com and its four closest competitors to review. For each intersection, you see the number of unique visitors and the overall proportion of each site’s audience it represents. It also shows the volume of unreached potential visitors.

Here, you can see a direct comparison of the audience loyalty represented in a bar graph. It shows a breakdown of each site’s audience based on how many other sites they have visited. Those sites with the highest loyalty show fewer additional sites visited.

From the perspective of chase.com, I can see 47% of their visitors do not visit rival sites. 33% of their audience visited 1 or more sites in this group, 14% visited 2 or more sites, 4% visited 3 or more sites, and just 0.8% viewed all sites in this comparison. 

How to answer qualitative research questions with Similarweb

Similarweb Research Intelligence drastically improves market research efficiency and time to insight. Both of these can impact the bottom line and the pace at which organizations can adapt and flex when markets shift, and rivals change tactics.

Outdated practices, while still useful, take time . And with a quicker, more efficient way to garner similar insights, opting for the fast lane puts you at a competitive advantage.

With a birds-eye view of the actions and behaviors of companies and consumers across a market , you can answer certain research questions without the need to plan, do, and review extensive qualitative market research .

Wrapping up

Qualitative research methods have been around for centuries. From designing the questions to finding the best distribution channels, collecting and analyzing findings takes time to get the insights you need. Similarweb Digital Research Intelligence drastically improves efficiency and time to insight. Both of which impact the bottom line and the pace at which organizations can adapt and flex when markets shift.

Similarweb’s suite of digital intelligence solutions offers unbiased, accurate, honest insights you can trust for analyzing any industry, market, or audience.

• Methodologies used for data collection are robust, transparent, and trustworthy.
• Clear presentation of data via an easy-to-use, intuitive platform.
• It updates dynamically–giving you the freshest data about an industry or market.
• Data is available via an API – so you can plug into platforms like Tableau or PowerBI to streamline your analyses.
• Filter and refine results according to your needs.

Are quantitative or qualitative research questions best?

Both have their place and purpose in market research. Qualitative research questions seek to provide details, whereas quantitative market research gives you numerical statistics that are easier and quicker to analyze. You get more flexibility with qualitative questions, and they’re non-directional.

What are the advantages of qualitative research?

Qualitative research is advantageous because it allows researchers to better understand their subject matter by exploring people’s attitudes, behaviors, and motivations in a particular context. It also allows researchers to uncover new insights that may not have been discovered with quantitative research methods.

What are some of the challenges of qualitative research?

Qualitative research can be time-consuming and costly, typically involving in-depth interviews and focus groups. Additionally, there are challenges associated with the reliability and validity of the collected data, as there is no universal standard for interpreting the results.

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Chapter 12. Focus Groups

Introduction.

Focus groups are a particular and special form of interviewing in which the interview asks focused questions of a group of persons, optimally between five and eight. This group can be close friends, family members, or complete strangers. They can have a lot in common or nothing in common. Unlike one-on-one interviews, which can probe deeply, focus group questions are narrowly tailored (“focused”) to a particular topic and issue and, with notable exceptions, operate at the shallow end of inquiry. For example, market researchers use focus groups to find out why groups of people choose one brand of product over another. Because focus groups are often used for commercial purposes, they sometimes have a bit of a stigma among researchers. This is unfortunate, as the focus group is a helpful addition to the qualitative researcher’s toolkit. Focus groups explicitly use group interaction to assist in the data collection. They are particularly useful as supplements to one-on-one interviews or in data triangulation. They are sometimes used to initiate areas of inquiry for later data collection methods. This chapter describes the main forms of focus groups, lays out some key differences among those forms, and provides guidance on how to manage focus group interviews.

Focus Groups: What Are They and When to Use Them

As interviews, focus groups can be helpfully distinguished from one-on-one interviews. The purpose of conducting a focus group is not to expand the number of people one interviews: the focus group is a different entity entirely. The focus is on the group and its interactions and evaluations rather than on the individuals in that group. If you want to know how individuals understand their lives and their individual experiences, it is best to ask them individually. If you want to find out how a group forms a collective opinion about something (whether a product or an event or an experience), then conducting a focus group is preferable. The power of focus groups resides in their being both focused and oriented to the group . They are best used when you are interested in the shared meanings of a group or how people discuss a topic publicly or when you want to observe the social formation of evaluations. The interaction of the group members is an asset in this method of data collection. If your questions would not benefit from group interaction, this is a good indicator that you should probably use individual interviews (chapter 11). Avoid using focus groups when you are interested in personal information or strive to uncover deeply buried beliefs or personal narratives. In general, you want to avoid using focus groups when the subject matter is polarizing, as people are less likely to be honest in a group setting. There are a few exceptions, such as when you are conducting focus groups with people who are not strangers and/or you are attempting to probe deeply into group beliefs and evaluations. But caution is warranted in these cases. [1]

As with interviewing in general, there are many forms of focus groups. Focus groups are widely used by nonresearchers, so it is important to distinguish these uses from the research focus group. Businesses routinely employ marketing focus groups to test out products or campaigns. Jury consultants employ “mock” jury focus groups, testing out legal case strategies in advance of actual trials. Organizations of various kinds use focus group interviews for program evaluation (e.g., to gauge the effectiveness of a diversity training workshop). The research focus group has many similarities with all these uses but is specifically tailored to a research (rather than applied) interest. The line between application and research use can be blurry, however. To take the case of evaluating the effectiveness of a diversity training workshop, the same interviewer may be conducting focus group interviews both to provide specific actionable feedback for the workshop leaders (this is the application aspect) and to learn more about how people respond to diversity training (an interesting research question with theoretically generalizable results).

When forming a focus group, there are two different strategies for inclusion. Diversity focus groups include people with diverse perspectives and experiences. This helps the researcher identify commonalities across this diversity and/or note interactions across differences. What kind of diversity to capture depends on the research question, but care should be taken to ensure that those participating are not set up for attack from other participants. This is why many warn against diversity focus groups, especially around politically sensitive topics. The other strategy is to build a convergence focus group , which includes people with similar perspectives and experiences. These are particularly helpful for identifying shared patterns and group consensus. The important thing is to closely consider who will be invited to participate and what the composition of the group will be in advance. Some review of sampling techniques (see chapter 5) may be helpful here.

Moderating a focus group can be a challenge (more on this below). For this reason, confining your group to no more than eight participants is recommended. You probably want at least four persons to capture group interaction. Fewer than four participants can also make it more difficult for participants to remain (relatively) anonymous—there is less of a group in which to hide. There are exceptions to these recommendations. You might want to conduct a focus group with a naturally occurring group, as in the case of a family of three, a social club of ten, or a program of fifteen. When the persons know one another, the problems of too few for anonymity don’t apply, and although ten to fifteen can be unwieldy to manage, there are strategies to make this possible. If you really are interested in this group’s dynamic (not just a set of random strangers’ dynamic), then you will want to include all its members or as many as are willing and able to participate.

There are many benefits to conducting focus groups, the first of which is their interactivity. Participants can make comparisons, can elaborate on what has been voiced by another, and can even check one another, leading to real-time reevaluations. This last benefit is one reason they are sometimes employed specifically for consciousness raising or building group cohesion. This form of data collection has an activist application when done carefully and appropriately. It can be fun, especially for the participants. Additionally, what does not come up in a focus group, especially when expected by the researcher, can be very illuminating.

Many of these benefits do incur costs, however. The multiplicity of voices in a good focus group interview can be overwhelming both to moderate and later to transcribe. Because of the focused nature, deep probing is not possible (or desirable). You might only get superficial thinking or what people are willing to put out there publicly. If that is what you are interested in, good. If you want deeper insight, you probably will not get that here. Relatedly, extreme views are often suppressed, and marginal viewpoints are unspoken or, if spoken, derided. You will get the majority group consensus and very little of minority viewpoints. Because people will be engaged with one another, there is the possibility of cut-off sentences, making it even more likely to hear broad brush themes and not detailed specifics. There really is very little opportunity for specific follow-up questions to individuals. Reading over a transcript, you may be frustrated by avenues of inquiry that were foreclosed early.

Some people expect that conducting focus groups is an efficient form of data collection. After all, you get to hear from eight people instead of just one in the same amount of time! But this is a serious misunderstanding. What you hear in a focus group is one single group interview or discussion. It is not the same thing at all as conducting eight single one-hour interviews. Each focus group counts as “one.” Most likely, you will need to conduct several focus groups, and you can design these as comparisons to one another. For example, the American Sociological Association (ASA) Task Force on First-Generation and Working-Class Persons in Sociology began its study of the impact of class in sociology by conducting five separate focus groups with different groups of sociologists: graduate students, faculty (in general), community college faculty, faculty of color, and a racially diverse group of students and faculty. Even though the total number of participants was close to forty, the “number” of cases was five. It is highly recommended that when employing focus groups, you plan on composing more than one and at least three. This allows you to take note of and potentially discount findings from a group with idiosyncratic dynamics, such as where a particularly dominant personality silences all other voices. In other words, putting all your eggs into a single focus group basket is not a good idea.

How to Conduct a Focus Group Interview/Discussion

Advance preparations.

Once you have selected your focus groups and set a date and time, there are a few things you will want to plan out before meeting.

As with interviews, you begin by creating an interview (or discussion) guide. Where a good one-on-one interview guide should include ten to twelve main topics with possible prompts and follow-ups (see the example provided in chapter 11), the focus group guide should be more narrowly tailored to a single focus or topic area. For example, a focus might be “How students coped with online learning during the pandemic,” and a series of possible questions would be drafted that would help prod participants to think about and discuss this topic. These questions or discussion prompts can be creative and may include stimulus materials (watching a video or hearing a story) or posing hypotheticals. For example, Cech ( 2021 ) has a great hypothetical, asking what a fictional character should do: keep his boring job in computers or follow his passion and open a restaurant. You can ask a focus group this question and see what results—how the group comes to define a “good job,” what questions they ask about the hypothetical (How boring is his job really? Does he hate getting up in the morning, or is it more of an everyday tedium? What kind of financial support will he have if he quits? Does he even know how to run a restaurant?), and how they reach a consensus or create clear patterns of disagreement are all interesting findings that can be generated through this technique.

As with the above example (“What should Joe do?”), it is best to keep the questions you ask simple and easily understood by everyone. Thinking about the sequence of the questions/prompts is important, just as it is in conducting any interviews.

Avoid embarrassing questions. Always leave an out for the “I have a friend who X” response rather than pushing people to divulge personal information. Asking “How do you think students coped?” is better than “How did you cope?” Chances are, some participants will begin talking about themselves without you directly asking them to do so, but allowing impersonal responses here is good. The group itself will determine how deep and how personal it wants to go. This is not the time or place to push anyone out of their comfort zone!

Of course, people have different levels of comfort talking publicly about certain topics. You will have provided detailed information to your focus group participants beforehand and secured consent. But even so, the conversation may take a turn that makes someone uncomfortable. Be on the lookout for this, and remind everyone of their ability to opt out—to stay silent or to leave if necessary. Rather than call attention to anyone in this way, you also want to let everyone know they are free to walk around—to get up and get coffee (more on this below) or use the restroom or just step out of the room to take a call. Of course, you don’t really want anyone to do any of these things, and chances are everyone will stay seated during the hour, but you should leave this “out” for those who need it.

Have copies of consent forms and any supplemental questionnaire (e.g., demographic information) you are using prepared in advance. Ask a friend or colleague to assist you on the day of the focus group. They can be responsible for making sure the recording equipment is functioning and may even take some notes on body language while you are moderating the discussion. Order food (coffee or snacks) for the group. This is important! Having refreshments will be appreciated by your participants and really damps down the anxiety level. Bring name tags and pens. Find a quiet welcoming space to convene. Often this is a classroom where you move chairs into a circle, but public libraries often have meeting rooms that are ideal places for community members to meet. Be sure that the space allows for food.

Researcher Note

When I was designing my research plan for studying activist groups, I consulted one of the best qualitative researchers I knew, my late friend Raphael Ezekiel, author of The Racist Mind . He looked at my plan to hand people demographic surveys at the end of the meetings I planned to observe and said, “This methodology is missing one crucial thing.” “What?” I asked breathlessly, anticipating some technical insider tip. “Chocolate!” he answered. “They’ll be tired, ready to leave when you ask them to fill something out. Offer an incentive, and they will stick around.” It worked! As the meetings began to wind down, I would whip some bags of chocolate candies out of my bag. Everyone would stare, and I’d say they were my thank-you gift to anyone who filled out my survey. Once I learned to include some sugar-free candies for diabetics, my typical response rate was 100 percent. (And it gave me an additional class-culture data point by noticing who chose which brand; sure enough, Lindt balls went faster at majority professional-middle-class groups, and Hershey’s minibars went faster at majority working-class groups.)

—Betsy Leondar-Wright, author of Missing Class , coauthor of The Color of Wealth , associate professor of sociology at Lasell University, and coordinator of staffing at the Mission Project for Class Action

During the Focus Group

As people arrive, greet them warmly, and make sure you get a signed consent form (if not in advance). If you are using name tags, ask them to fill one out and wear it. Let them get food and find a seat and do a little chatting, as they might wish. Once seated, many focus group moderators begin with a relevant icebreaker. This could be simple introductions that have some meaning or connection to the focus. In the case of the ASA task force focus groups discussed above, we asked people to introduce themselves and where they were working/studying (“Hi, I’m Allison, and I am a professor at Oregon State University”). You will also want to introduce yourself and the study in simple terms. They’ve already read the consent form, but you would be surprised at how many people ignore the details there or don’t remember them. Briefly talking about the study and then letting people ask any follow-up questions lays a good foundation for a successful discussion, as it reminds everyone what the point of the event is.

Focus groups should convene for between forty-five and ninety minutes. Of course, you must tell the participants the time you have chosen in advance, and you must promptly end at the time allotted. Do not make anyone nervous by extending the time. Let them know at the outset that you will adhere to this timeline. This should reduce the nervous checking of phones and watches and wall clocks as the end time draws near.

Set ground rules and expectations for the group discussion. My preference is to begin with a general question and let whoever wants to answer it do so, but other moderators expect each person to answer most questions. Explain how much cross-talk you will permit (or encourage). Again, my preference is to allow the group to pick up the ball and run with it, so I will sometimes keep my head purposefully down so that they engage with one another rather than me, but I have seen other moderators take a much more engaged position. Just be clear at the outset about what your expectations are. You may or may not want to explain how the group should deal with those who would dominate the conversation. Sometimes, simply stating at the outset that all voices should be heard is enough to create a more egalitarian discourse. Other times, you will have to actively step in to manage (moderate) the exchange to allow more voices to be heard. Finally, let people know they are free to get up to get more coffee or leave the room as they need (if you are OK with this). You may ask people to refrain from using their phones during the duration of the discussion. That is up to you too.

Either before or after the introductions (your call), begin recording the discussion with their collective permission and knowledge . If you have brought a friend or colleague to assist you (as you should), have them attend to the recording. Explain the role of your colleague to the group (e.g., they will monitor the recording and will take short notes throughout to help you when you read the transcript later; they will be a silent observer).

Once the focus group gets going, it may be difficult to keep up. You will need to make a lot of quick decisions during the discussion about whether to intervene or let it go unguided. Only you really care about the research question or topic, so only you will really know when the discussion is truly off topic. However you handle this, keep your “participation” to a minimum. According to Lune and Berg ( 2018:95 ), the moderator’s voice should show up in the transcript no more than 10 percent of the time. By the way, you should also ask your research assistant to take special note of the “intensity” of the conversation, as this may be lost in a transcript. If there are people looking overly excited or tapping their feet with impatience or nodding their heads in unison, you want some record of this for future analysis.

I’m not sure why this stuck with me, but I thought it would be interesting to share. When I was reviewing my plan for conducting focus groups with one of my committee members, he suggested that I give the participants their gift cards first. The incentive for participating in the study was a gift card of their choice, and typical processes dictate that participants must complete the study in order to receive their gift card. However, my committee member (who is Native himself) suggested I give it at the beginning. As a qualitative researcher, you build trust with the people you engage with. You are asking them to share their stories with you, their intimate moments, their vulnerabilities, their time. Not to mention that Native people are familiar with being academia’s subjects of interest with little to no benefit to be returned to them. To show my appreciation, one of the things I could do was to give their gifts at the beginning, regardless of whether or not they completed participating.

—Susanna Y. Park, PhD, mixed-methods researcher in public health and author of “How Native Women Seek Support as Survivors of Intimate Partner Violence: A Mixed-Methods Study”

After the Focus Group

Your “data” will be either fieldnotes taken during the focus group or, more desirably, transcripts of the recorded exchange. If you do not have permission to record the focus group discussion, make sure you take very clear notes during the exchange and then spend a few hours afterward filling them in as much as possible, creating a rich memo to yourself about what you saw and heard and experienced, including any notes about body language and interactions. Ideally, however, you will have recorded the discussion. It is still a good idea to spend some time immediately after the conclusion of the discussion to write a memo to yourself with all the things that may not make it into the written record (e.g., body language and interactions). This is also a good time to journal about or create a memo with your initial researcher reactions to what you saw, noting anything of particular interest that you want to come back to later on (e.g., “It was interesting that no one thought Joe should quit his job, but in the other focus group, half of the group did. I wonder if this has something to do with the fact that all the participants were first-generation college students. I should pay attention to class background here.”).

Please thank each of your participants in a follow-up email or text. Let them know you appreciated their time and invite follow-up questions or comments.

One of the difficult things about focus group transcripts is keeping speakers distinct. Eventually, you are going to be using pseudonyms for any publication, but for now, you probably want to know who said what. You can assign speaker numbers (“Speaker 1,” “Speaker 2”) and connect those identifications with particular demographic information in a separate document. Remember to clearly separate actual identifications (as with consent forms) to prevent breaches of anonymity. If you cannot identify a speaker when transcribing, you can write, “Unidentified Speaker.” Once you have your transcript(s) and memos and fieldnotes, you can begin analyzing the data (chapters 18 and 19).

Advanced: Focus Groups on Sensitive Topics

Throughout this chapter, I have recommended against raising sensitive topics in focus group discussions. As an introvert myself, I find the idea of discussing personal topics in a group disturbing, and I tend to avoid conducting these kinds of focus groups. And yet I have actually participated in focus groups that do discuss personal information and consequently have been of great value to me as a participant (and researcher) because of this. There are even some researchers who believe this is the best use of focus groups ( de Oliveira 2011 ). For example, Jordan et al. ( 2007 ) argue that focus groups should be considered most useful for illuminating locally sanctioned ways of talking about sensitive issues. So although I do not recommend the beginning qualitative researcher dive into deep waters before they can swim, this section will provide some guidelines for conducting focus groups on sensitive topics. To my mind, these are a minimum set of guidelines to follow when dealing with sensitive topics.

First, be transparent about the place of sensitive topics in your focus group. If the whole point of your focus group is to discuss something sensitive, such as how women gain support after traumatic sexual assault events, make this abundantly clear in your consent form and recruiting materials. It is never appropriate to blindside participants with sensitive or threatening topics .

Second, create a confidentiality form (figure 12.2) for each participant to sign. These forms carry no legal weight, but they do create an expectation of confidentiality for group members.

In order to respect the privacy of all participants in [insert name of study here], all parties are asked to read and sign the statement below. If you have any reason not to sign, please discuss this with [insert your name], the researcher of this study, I, ________________________, agree to maintain the confidentiality of the information discussed by all participants and researchers during the focus group discussion.

Signature: _____________________________ Date: _____________________

Researcher’s Signature:___________________ Date:______________________

Figure 12.2 Confidentiality Agreement of Focus Group Participants

Third, provide abundant space for opting out of the discussion. Participants are, of course, always permitted to refrain from answering a question or to ask for the recording to be stopped. It is important that focus group members know they have these rights during the group discussion as well. And if you see a person who is looking uncomfortable or like they want to hide, you need to step in affirmatively and remind everyone of these rights.

Finally, if things go “off the rails,” permit yourself the ability to end the focus group. Debrief with each member as necessary.

Further Readings

Barbour, Rosaline. 2018. Doing Focus Groups . 2nd ed. Thousand Oaks, CA: SAGE. Written by a medical sociologist based in the UK, this is a good how-to guide for conducting focus groups.

Gibson, Faith. 2007. “Conducting Focus Groups with Children and Young People: Strategies for Success.” Journal of Research in Nursing 12(5):473–483. As the title suggests, this article discusses both methodological and practical concerns when conducting focus groups with children and young people and offers some tips and strategies for doing so effectively.

Hopkins, Peter E. 2007. “Thinking Critically and Creatively about Focus Groups.” Area 39(4):528–535. Written from the perspective of critical/human geography, Hopkins draws on examples from his own work conducting focus groups with Muslim men. Useful for thinking about positionality.

Jordan, Joanne, Una Lynch, Marianne Moutray, Marie-Therese O’Hagan, Jean Orr, Sandra Peake, and John Power. 2007. “Using Focus Groups to Research Sensitive Issues: Insights from Group Interviews on Nursing in the Northern Ireland ‘Troubles.’” International Journal of Qualitative Methods 6(4), 1–19. A great example of using focus groups productively around emotional or sensitive topics. The authors suggest that focus groups should be considered most useful for illuminating locally sanctioned ways of talking about sensitive issues.

Merton, Robert K., Marjorie Fiske, and Patricia L. Kendall. 1956. The Focused Interview: A Manual of Problems and Procedures . New York: Free Press. This is one of the first classic texts on conducting interviews, including an entire chapter devoted to the “group interview” (chapter 6).

Morgan, David L. 1986. “Focus Groups.” Annual Review of Sociology 22:129–152. An excellent sociological review of the use of focus groups, comparing and contrasting to both surveys and interviews, with some suggestions for improving their use and developing greater rigor when utilizing them.

de Oliveira, Dorca Lucia. 2011. “The Use of Focus Groups to Investigate Sensitive Topics: An Example Taken from Research on Adolescent Girls’ Perceptions about Sexual Risks.” Cien Saude Colet 16(7):3093–3102. Another example of discussing sensitive topics in focus groups. Here, the author explores using focus groups with teenage girls to discuss AIDS, risk, and sexuality as a matter of public health interest.

Peek, Lori, and Alice Fothergill. 2009. “Using Focus Groups: Lessons from Studying Daycare Centers, 9/11, and Hurricane Katrina.” Qualitative Research 9(1):31–59. An examination of the efficacy and value of focus groups by comparing three separate projects: a study of teachers, parents, and children at two urban daycare centers; a study of the responses of second-generation Muslim Americans to the events of September 11; and a collaborative project on the experiences of children and youth following Hurricane Katrina. Throughout, the authors stress the strength of focus groups with marginalized, stigmatized, or vulnerable individuals.

Wilson, Valerie. 1997. “Focus Groups: A Useful Qualitative Method for Educational Research?” British Educational Research Journal 23(2):209–224. A basic description of how focus groups work using an example from a study intended to inform initiatives in health education and promotion in Scotland.

• Note that I have included a few examples of conducting focus groups with sensitive issues in the “ Further Readings ” section and have included an “ Advanced: Focus Groups on Sensitive Topics ” section on this area. ↵

A focus group interview is an interview with a small group of people on a specific topic.  “The power of focus groups resides in their being focused” (Patton 2002:388).  These are sometimes framed as “discussions” rather than interviews, with a discussion “moderator.”  Alternatively, the focus group is “a form of data collection whereby the researcher convenes a small group of people having similar attributes, experiences, or ‘focus’ and leads the group in a nondirective manner.  The objective is to surface the perspectives of the people in the group with as minimal influence by the researcher as possible” (Yin 2016:336).  See also diversity focus group and convergence focus group.

A form of focus group construction in which people with diverse perspectives and experiences are chosen for inclusion.  This helps the researcher identify commonalities across this diversity and/or note interactions across differences.  Contrast with a convergence focus group

A form of focus group construction in which people with similar perspectives and experiences are included.  These are particularly helpful for identifying shared patterns and group consensus.  Contrast with a diversity focus group .

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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• Data Descriptor
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• Published: 03 May 2024

A dataset for measuring the impact of research data and their curation

• Libby Hemphill   ORCID: orcid.org/0000-0002-3793-7281 1 , 2 ,
• Andrea Thomer 3 ,
• Sara Lafia 1 ,
• Lizhou Fan 2 ,
• David Bleckley   ORCID: orcid.org/0000-0001-7715-4348 1 &
• Elizabeth Moss 1  

Scientific Data volume  11 , Article number:  442 ( 2024 ) Cite this article

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• Research data
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Science funders, publishers, and data archives make decisions about how to responsibly allocate resources to maximize the reuse potential of research data. This paper introduces a dataset developed to measure the impact of archival and data curation decisions on data reuse. The dataset describes 10,605 social science research datasets, their curation histories, and reuse contexts in 94,755 publications that cover 59 years from 1963 to 2022. The dataset was constructed from study-level metadata, citing publications, and curation records available through the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan. The dataset includes information about study-level attributes (e.g., PIs, funders, subject terms); usage statistics (e.g., downloads, citations); archiving decisions (e.g., curation activities, data transformations); and bibliometric attributes (e.g., journals, authors) for citing publications. This dataset provides information on factors that contribute to long-term data reuse, which can inform the design of effective evidence-based recommendations to support high-impact research data curation decisions.

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Background & summary.

Recent policy changes in funding agencies and academic journals have increased data sharing among researchers and between researchers and the public. Data sharing advances science and provides the transparency necessary for evaluating, replicating, and verifying results. However, many data-sharing policies do not explain what constitutes an appropriate dataset for archiving or how to determine the value of datasets to secondary users 1 , 2 , 3 . Questions about how to allocate data-sharing resources efficiently and responsibly have gone unanswered 4 , 5 , 6 . For instance, data-sharing policies recognize that not all data should be curated and preserved, but they do not articulate metrics or guidelines for determining what data are most worthy of investment.

Despite the potential for innovation and advancement that data sharing holds, the best strategies to prioritize datasets for preparation and archiving are often unclear. Some datasets are likely to have more downstream potential than others, and data curation policies and workflows should prioritize high-value data instead of being one-size-fits-all. Though prior research in library and information science has shown that the “analytic potential” of a dataset is key to its reuse value 7 , work is needed to implement conceptual data reuse frameworks 8 , 9 , 10 , 11 , 12 , 13 , 14 . In addition, publishers and data archives need guidance to develop metrics and evaluation strategies to assess the impact of datasets.

Several existing resources have been compiled to study the relationship between the reuse of scholarly products, such as datasets (Table  1 ); however, none of these resources include explicit information on how curation processes are applied to data to increase their value, maximize their accessibility, and ensure their long-term preservation. The CCex (Curation Costs Exchange) provides models of curation services along with cost-related datasets shared by contributors but does not make explicit connections between them or include reuse information 15 . Analyses on platforms such as DataCite 16 have focused on metadata completeness and record usage, but have not included related curation-level information. Analyses of GenBank 17 and FigShare 18 , 19 citation networks do not include curation information. Related studies of Github repository reuse 20 and Softcite software citation 21 reveal significant factors that impact the reuse of secondary research products but do not focus on research data. RD-Switchboard 22 and DSKG 23 are scholarly knowledge graphs linking research data to articles, patents, and grants, but largely omit social science research data and do not include curation-level factors. To our knowledge, other studies of curation work in organizations similar to ICPSR – such as GESIS 24 , Dataverse 25 , and DANS 26 – have not made their underlying data available for analysis.

This paper describes a dataset 27 compiled for the MICA project (Measuring the Impact of Curation Actions) led by investigators at ICPSR, a large social science data archive at the University of Michigan. The dataset was originally developed to study the impacts of data curation and archiving on data reuse. The MICA dataset has supported several previous publications investigating the intensity of data curation actions 28 , the relationship between data curation actions and data reuse 29 , and the structures of research communities in a data citation network 30 . Collectively, these studies help explain the return on various types of curatorial investments. The dataset that we introduce in this paper, which we refer to as the MICA dataset, has the potential to address research questions in the areas of science (e.g., knowledge production), library and information science (e.g., scholarly communication), and data archiving (e.g., reproducible workflows).

We constructed the MICA dataset 27 using records available at ICPSR, a large social science data archive at the University of Michigan. Data set creation involved: collecting and enriching metadata for articles indexed in the ICPSR Bibliography of Data-related Literature against the Dimensions AI bibliometric database; gathering usage statistics for studies from ICPSR’s administrative database; processing data curation work logs from ICPSR’s project tracking platform, Jira; and linking data in social science studies and series to citing analysis papers (Fig.  1 ).

Steps to prepare MICA dataset for analysis - external sources are red, primary internal sources are blue, and internal linked sources are green.

Enrich paper metadata

The ICPSR Bibliography of Data-related Literature is a growing database of literature in which data from ICPSR studies have been used. Its creation was funded by the National Science Foundation (Award 9977984), and for the past 20 years it has been supported by ICPSR membership and multiple US federally-funded and foundation-funded topical archives at ICPSR. The Bibliography was originally launched in the year 2000 to aid in data discovery by providing a searchable database linking publications to the study data used in them. The Bibliography collects the universe of output based on the data shared in each study through, which is made available through each ICPSR study’s webpage. The Bibliography contains both peer-reviewed and grey literature, which provides evidence for measuring the impact of research data. For an item to be included in the ICPSR Bibliography, it must contain an analysis of data archived by ICPSR or contain a discussion or critique of the data collection process, study design, or methodology 31 . The Bibliography is manually curated by a team of librarians and information specialists at ICPSR who enter and validate entries. Some publications are supplied to the Bibliography by data depositors, and some citations are submitted to the Bibliography by authors who abide by ICPSR’s terms of use requiring them to submit citations to works in which they analyzed data retrieved from ICPSR. Most of the Bibliography is populated by Bibliography team members, who create custom queries for ICPSR studies performed across numerous sources, including Google Scholar, ProQuest, SSRN, and others. Each record in the Bibliography is one publication that has used one or more ICPSR studies. The version we used was captured on 2021-11-16 and included 94,755 publications.

To expand the coverage of the ICPSR Bibliography, we searched exhaustively for all ICPSR study names, unique numbers assigned to ICPSR studies, and DOIs 32 using a full-text index available through the Dimensions AI database 33 . We accessed Dimensions through a license agreement with the University of Michigan. ICPSR Bibliography librarians and information specialists manually reviewed and validated new entries that matched one or more search criteria. We then used Dimensions to gather enriched metadata and full-text links for items in the Bibliography with DOIs. We matched 43% of the items in the Bibliography to enriched Dimensions metadata including abstracts, field of research codes, concepts, and authors’ institutional information; we also obtained links to full text for 16% of Bibliography items. Based on licensing agreements, we included Dimensions identifiers and links to full text so that users with valid publisher and database access can construct an enriched publication dataset.

Gather study usage data

ICPSR maintains a relational administrative database, DBInfo, that organizes study-level metadata and information on data reuse across separate tables. Studies at ICPSR consist of one or more files collected at a single time or for a single purpose; studies in which the same variables are observed over time are grouped into series. Each study at ICPSR is assigned a DOI, and its metadata are stored in DBInfo. Study metadata follows the Data Documentation Initiative (DDI) Codebook 2.5 standard. DDI elements included in our dataset are title, ICPSR study identification number, DOI, authoring entities, description (abstract), funding agencies, subject terms assigned to the study during curation, and geographic coverage. We also created variables based on DDI elements: total variable count, the presence of survey question text in the metadata, the number of author entities, and whether an author entity was an institution. We gathered metadata for ICPSR’s 10,605 unrestricted public-use studies available as of 2021-11-16 ( https://www.icpsr.umich.edu/web/pages/membership/or/metadata/oai.html ).

To link study usage data with study-level metadata records, we joined study metadata from DBinfo on study usage information, which included total study downloads (data and documentation), individual data file downloads, and cumulative citations from the ICPSR Bibliography. We also gathered descriptive metadata for each study and its variables, which allowed us to summarize and append recoded fields onto the study-level metadata such as curation level, number and type of principle investigators, total variable count, and binary variables indicating whether the study data were made available for online analysis, whether survey question text was made searchable online, and whether the study variables were indexed for search. These characteristics describe aspects of the discoverability of the data to compare with other characteristics of the study. We used the study and series numbers included in the ICPSR Bibliography as unique identifiers to link papers to metadata and analyze the community structure of dataset co-citations in the ICPSR Bibliography 32 .

Process curation work logs

Researchers deposit data at ICPSR for curation and long-term preservation. Between 2016 and 2020, more than 3,000 research studies were deposited with ICPSR. Since 2017, ICPSR has organized curation work into a central unit that provides varied levels of curation that vary in the intensity and complexity of data enhancement that they provide. While the levels of curation are standardized as to effort (level one = less effort, level three = most effort), the specific curatorial actions undertaken for each dataset vary. The specific curation actions are captured in Jira, a work tracking program, which data curators at ICPSR use to collaborate and communicate their progress through tickets. We obtained access to a corpus of 669 completed Jira tickets corresponding to the curation of 566 unique studies between February 2017 and December 2019 28 .

To process the tickets, we focused only on their work log portions, which contained free text descriptions of work that data curators had performed on a deposited study, along with the curators’ identifiers, and timestamps. To protect the confidentiality of the data curators and the processing steps they performed, we collaborated with ICPSR’s curation unit to propose a classification scheme, which we used to train a Naive Bayes classifier and label curation actions in each work log sentence. The eight curation action labels we proposed 28 were: (1) initial review and planning, (2) data transformation, (3) metadata, (4) documentation, (5) quality checks, (6) communication, (7) other, and (8) non-curation work. We note that these categories of curation work are very specific to the curatorial processes and types of data stored at ICPSR, and may not match the curation activities at other repositories. After applying the classifier to the work log sentences, we obtained summary-level curation actions for a subset of all ICPSR studies (5%), along with the total number of hours spent on data curation for each study, and the proportion of time associated with each action during curation.

Data Records

The MICA dataset 27 connects records for each of ICPSR’s archived research studies to the research publications that use them and related curation activities available for a subset of studies (Fig.  2 ). Each of the three tables published in the dataset is available as a study archived at ICPSR. The data tables are distributed as statistical files available for use in SAS, SPSS, Stata, and R as well as delimited and ASCII text files. The dataset is organized around studies and papers as primary entities. The studies table lists ICPSR studies, their metadata attributes, and usage information; the papers table was constructed using the ICPSR Bibliography and Dimensions database; and the curation logs table summarizes the data curation steps performed on a subset of ICPSR studies.

Studies (“ICPSR_STUDIES”): 10,605 social science research datasets available through ICPSR up to 2021-11-16 with variables for ICPSR study number, digital object identifier, study name, series number, series title, authoring entities, full-text description, release date, funding agency, geographic coverage, subject terms, topical archive, curation level, single principal investigator (PI), institutional PI, the total number of PIs, total variables in data files, question text availability, study variable indexing, level of restriction, total unique users downloading study data files and codebooks, total unique users downloading data only, and total unique papers citing data through November 2021. Studies map to the papers and curation logs table through ICPSR study numbers as “STUDY”. However, not every study in this table will have records in the papers and curation logs tables.

Papers (“ICPSR_PAPERS”): 94,755 publications collected from 2000-08-11 to 2021-11-16 in the ICPSR Bibliography and enriched with metadata from the Dimensions database with variables for paper number, identifier, title, authors, publication venue, item type, publication date, input date, ICPSR series numbers used in the paper, ICPSR study numbers used in the paper, the Dimension identifier, and the Dimensions link to the publication’s full text. Papers map to the studies table through ICPSR study numbers in the “STUDY_NUMS” field. Each record represents a single publication, and because a researcher can use multiple datasets when creating a publication, each record may list multiple studies or series.

Curation logs (“ICPSR_CURATION_LOGS”): 649 curation logs for 563 ICPSR studies (although most studies in the subset had one curation log, some studies were associated with multiple logs, with a maximum of 10) curated between February 2017 and December 2019 with variables for study number, action labels assigned to work description sentences using a classifier trained on ICPSR curation logs, hours of work associated with a single log entry, and total hours of work logged for the curation ticket. Curation logs map to the study and paper tables through ICPSR study numbers as “STUDY”. Each record represents a single logged action, and future users may wish to aggregate actions to the study level before joining tables.

Entity-relation diagram.

Technical Validation

We report on the reliability of the dataset’s metadata in the following subsections. To support future reuse of the dataset, curation services provided through ICPSR improved data quality by checking for missing values, adding variable labels, and creating a codebook.

All 10,605 studies available through ICPSR have a DOI and a full-text description summarizing what the study is about, the purpose of the study, the main topics covered, and the questions the PIs attempted to answer when they conducted the study. Personal names (i.e., principal investigators) and organizational names (i.e., funding agencies) are standardized against an authority list maintained by ICPSR; geographic names and subject terms are also standardized and hierarchically indexed in the ICPSR Thesaurus 34 . Many of ICPSR’s studies (63%) are in a series and are distributed through the ICPSR General Archive (56%), a non-topical archive that accepts any social or behavioral science data. While study data have been available through ICPSR since 1962, the earliest digital release date recorded for a study was 1984-03-18, when ICPSR’s database was first employed, and the most recent date is 2021-10-28 when the dataset was collected.

Curation level information was recorded starting in 2017 and is available for 1,125 studies (11%); approximately 80% of studies with assigned curation levels received curation services, equally distributed between Levels 1 (least intensive), 2 (moderately intensive), and 3 (most intensive) (Fig.  3 ). Detailed descriptions of ICPSR’s curation levels are available online 35 . Additional metadata are available for a subset of 421 studies (4%), including information about whether the study has a single PI, an institutional PI, the total number of PIs involved, total variables recorded is available for online analysis, has searchable question text, has variables that are indexed for search, contains one or more restricted files, and whether the study is completely restricted. We provided additional metadata for this subset of ICPSR studies because they were released within the past five years and detailed curation and usage information were available for them. Usage statistics including total downloads and data file downloads are available for this subset of studies as well; citation statistics are available for 8,030 studies (76%). Most ICPSR studies have fewer than 500 users, as indicated by total downloads, or citations (Fig.  4 ).

ICPSR study curation levels.

ICPSR study usage.

A subset of 43,102 publications (45%) available in the ICPSR Bibliography had a DOI. Author metadata were entered as free text, meaning that variations may exist and require additional normalization and pre-processing prior to analysis. While author information is standardized for each publication, individual names may appear in different sort orders (e.g., “Earls, Felton J.” and “Stephen W. Raudenbush”). Most of the items in the ICPSR Bibliography as of 2021-11-16 were journal articles (59%), reports (14%), conference presentations (9%), or theses (8%) (Fig.  5 ). The number of publications collected in the Bibliography has increased each decade since the inception of ICPSR in 1962 (Fig.  6 ). Most ICPSR studies (76%) have one or more citations in a publication.

ICPSR Bibliography citation types.

ICPSR citations by decade.

Usage Notes

The dataset consists of three tables that can be joined using the “STUDY” key as shown in Fig.  2 . The “ICPSR_PAPERS” table contains one row per paper with one or more cited studies in the “STUDY_NUMS” column. We manipulated and analyzed the tables as CSV files with the Pandas library 36 in Python and the Tidyverse packages 37 in R.

The present MICA dataset can be used independently to study the relationship between curation decisions and data reuse. Evidence of reuse for specific studies is available in several forms: usage information, including downloads and citation counts; and citation contexts within papers that cite data. Analysis may also be performed on the citation network formed between datasets and papers that use them. Finally, curation actions can be associated with properties of studies and usage histories.

This dataset has several limitations of which users should be aware. First, Jira tickets can only be used to represent the intensiveness of curation for activities undertaken since 2017, when ICPSR started using both Curation Levels and Jira. Studies published before 2017 were all curated, but documentation of the extent of that curation was not standardized and therefore could not be included in these analyses. Second, the measure of publications relies upon the authors’ clarity of data citation and the ICPSR Bibliography staff’s ability to discover citations with varying formality and clarity. Thus, there is always a chance that some secondary-data-citing publications have been left out of the bibliography. Finally, there may be some cases in which a paper in the ICSPSR bibliography did not actually obtain data from ICPSR. For example, PIs have often written about or even distributed their data prior to their archival in ICSPR. Therefore, those publications would not have cited ICPSR but they are still collected in the Bibliography as being directly related to the data that were eventually deposited at ICPSR.

In summary, the MICA dataset contains relationships between two main types of entities – papers and studies – which can be mined. The tables in the MICA dataset have supported network analysis (community structure and clique detection) 30 ; natural language processing (NER for dataset reference detection) 32 ; visualizing citation networks (to search for datasets) 38 ; and regression analysis (on curation decisions and data downloads) 29 . The data are currently being used to develop research metrics and recommendation systems for research data. Given that DOIs are provided for ICPSR studies and articles in the ICPSR Bibliography, the MICA dataset can also be used with other bibliometric databases, including DataCite, Crossref, OpenAlex, and related indexes. Subscription-based services, such as Dimensions AI, are also compatible with the MICA dataset. In some cases, these services provide abstracts or full text for papers from which data citation contexts can be extracted for semantic content analysis.

Code availability

The code 27 used to produce the MICA project dataset is available on GitHub at https://github.com/ICPSR/mica-data-descriptor and through Zenodo with the identifier https://doi.org/10.5281/zenodo.8432666 . Data manipulation and pre-processing were performed in Python. Data curation for distribution was performed in SPSS.

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Acknowledgements

We thank the ICPSR Bibliography staff, the ICPSR Data Curation Unit, and the ICPSR Data Stewardship Committee for their support of this research. This material is based upon work supported by the National Science Foundation under grant 1930645. This project was made possible in part by the Institute of Museum and Library Services LG-37-19-0134-19.

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Hemphill, L., Thomer, A., Lafia, S. et al. A dataset for measuring the impact of research data and their curation. Sci Data 11 , 442 (2024). https://doi.org/10.1038/s41597-024-03303-2

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Conducting and Writing Quantitative and Qualitative Research

Edward barroga.

1 Department of Medical Education, Showa University School of Medicine, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

Atsuko Furuta

Makiko arima, shizuma tsuchiya, chikako kawahara, yusuke takamiya.

Comprehensive knowledge of quantitative and qualitative research systematizes scholarly research and enhances the quality of research output. Scientific researchers must be familiar with them and skilled to conduct their investigation within the frames of their chosen research type. When conducting quantitative research, scientific researchers should describe an existing theory, generate a hypothesis from the theory, test their hypothesis in novel research, and re-evaluate the theory. Thereafter, they should take a deductive approach in writing the testing of the established theory based on experiments. When conducting qualitative research, scientific researchers raise a question, answer the question by performing a novel study, and propose a new theory to clarify and interpret the obtained results. After which, they should take an inductive approach to writing the formulation of concepts based on collected data. When scientific researchers combine the whole spectrum of inductive and deductive research approaches using both quantitative and qualitative research methodologies, they apply mixed-method research. Familiarity and proficiency with these research aspects facilitate the construction of novel hypotheses, development of theories, or refinement of concepts.

Graphical Abstract

INTRODUCTION

Novel research studies are conceptualized by scientific researchers first by asking excellent research questions and developing hypotheses, then answering these questions by testing their hypotheses in ethical research. 1 , 2 , 3 Before they conduct novel research studies, scientific researchers must possess considerable knowledge of both quantitative and qualitative research. 2

In quantitative research, researchers describe existing theories, generate and test a hypothesis in novel research, and re-evaluate existing theories deductively based on their experimental results. 1 , 4 , 5 In qualitative research, scientific researchers raise and answer research questions by performing a novel study, then propose new theories by clarifying their results inductively. 1 , 6

RATIONALE OF THIS ARTICLE

When researchers have a limited knowledge of both research types and how to conduct them, this can result in substandard investigation. Researchers must be familiar with both types of research and skilled to conduct their investigations within the frames of their chosen type of research. Thus, meticulous care is needed when planning quantitative and qualitative research studies to avoid unethical research and poor outcomes.

Understanding the methodological and writing assumptions 7 , 8 underpinning quantitative and qualitative research, especially by non-Anglophone researchers, is essential for their successful conduct. Scientific researchers, especially in the academe, face pressure to publish in international journals 9 where English is the language of scientific communication. 10 , 11 In particular, non-Anglophone researchers face challenges related to linguistic, stylistic, and discourse differences. 11 , 12 Knowing the assumptions of the different types of research will help clarify research questions and methodologies, easing the challenge and help.

SEARCH FOR RELEVANT ARTICLES

To identify articles relevant to this topic, we adhered to the search strategy recommended by Gasparyan et al. 7 We searched through PubMed, Scopus, Directory of Open Access Journals, and Google Scholar databases using the following keywords: quantitative research, qualitative research, mixed-method research, deductive reasoning, inductive reasoning, study design, descriptive research, correlational research, experimental research, causal-comparative research, quasi-experimental research, historical research, ethnographic research, meta-analysis, narrative research, grounded theory, phenomenology, case study, and field research.

AIMS OF THIS ARTICLE

This article aims to provide a comparative appraisal of qualitative and quantitative research for scientific researchers. At present, there is still a need to define the scope of qualitative research, especially its essential elements. 13 Consensus on the critical appraisal tools to assess the methodological quality of qualitative research remains lacking. 14 Framing and testing research questions can be challenging in qualitative research. 2 In the healthcare system, it is essential that research questions address increasingly complex situations. Therefore, research has to be driven by the kinds of questions asked and the corresponding methodologies to answer these questions. 15 The mixed-method approach also needs to be clarified as this would appear to arise from different philosophical underpinnings. 16

This article also aims to discuss how particular types of research should be conducted and how they should be written in adherence to international standards. In the US, Europe, and other countries, responsible research and innovation was conceptualized and promoted with six key action points: engagement, gender equality, science education, open access, ethics and governance. 17 , 18 International ethics standards in research 19 as well as academic integrity during doctoral trainings are now integral to the research process. 20

POTENTIAL BENEFITS FROM THIS ARTICLE

This article would be beneficial for researchers in further enhancing their understanding of the theoretical, methodological, and writing aspects of qualitative and quantitative research, and their combination.

Moreover, this article reviews the basic features of both research types and overviews the rationale for their conduct. It imparts information on the most common forms of quantitative and qualitative research, and how they are carried out. These aspects would be helpful for selecting the optimal methodology to use for research based on the researcher’s objectives and topic.

This article also provides information on the strengths and weaknesses of quantitative and qualitative research. Such information would help researchers appreciate the roles and applications of both research types and how to gain from each or their combination. As different research questions require different types of research and analyses, this article is anticipated to assist researchers better recognize the questions answered by quantitative and qualitative research.

Finally, this article would help researchers to have a balanced perspective of qualitative and quantitative research without considering one as superior to the other.

TYPES OF RESEARCH

Research can be classified into two general types, quantitative and qualitative. 21 Both types of research entail writing a research question and developing a hypothesis. 22 Quantitative research involves a deductive approach to prove or disprove the hypothesis that was developed, whereas qualitative research involves an inductive approach to create a hypothesis. 23 , 24 , 25 , 26

In quantitative research, the hypothesis is stated before testing. In qualitative research, the hypothesis is developed through inductive reasoning based on the data collected. 27 , 28 For types of data and their analysis, qualitative research usually includes data in the form of words instead of numbers more commonly used in quantitative research. 29

Quantitative research usually includes descriptive, correlational, causal-comparative / quasi-experimental, and experimental research. 21 On the other hand, qualitative research usually encompasses historical, ethnographic, meta-analysis, narrative, grounded theory, phenomenology, case study, and field research. 23 , 25 , 28 , 30 A summary of the features, writing approach, and examples of published articles for each type of qualitative and quantitative research is shown in Table 1 . 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43

QUANTITATIVE RESEARCH

Deductive approach.

The deductive approach is used to prove or disprove the hypothesis in quantitative research. 21 , 25 Using this approach, researchers 1) make observations about an unclear or new phenomenon, 2) investigate the current theory surrounding the phenomenon, and 3) hypothesize an explanation for the observations. Afterwards, researchers will 4) predict outcomes based on the hypotheses, 5) formulate a plan to test the prediction, and 6) collect and process the data (or revise the hypothesis if the original hypothesis was false). Finally, researchers will then 7) verify the results, 8) make the final conclusions, and 9) present and disseminate their findings ( Fig. 1A ).

Types of quantitative research

The common types of quantitative research include (a) descriptive, (b) correlational, c) experimental research, and (d) causal-comparative/quasi-experimental. 21

Descriptive research is conducted and written by describing the status of an identified variable to provide systematic information about a phenomenon. A hypothesis is developed and tested after data collection, analysis, and synthesis. This type of research attempts to factually present comparisons and interpretations of findings based on analyses of the characteristics, progression, or relationships of a certain phenomenon by manipulating the employed variables or controlling the involved conditions. 44 Here, the researcher examines, observes, and describes a situation, sample, or variable as it occurs without investigator interference. 31 , 45 To be meaningful, the systematic collection of information requires careful selection of study units by precise measurement of individual variables 21 often expressed as ranges, means, frequencies, and/or percentages. 31 , 45 Descriptive statistical analysis using ANOVA, Student’s t -test, or the Pearson coefficient method has been used to analyze descriptive research data. 46

Correlational research is performed by determining and interpreting the extent of a relationship between two or more variables using statistical data. This involves recognizing data trends and patterns without necessarily proving their causes. The researcher studies only the data, relationships, and distributions of variables in a natural setting, but does not manipulate them. 21 , 45 Afterwards, the researcher establishes reliability and validity, provides converging evidence, describes relationship, and makes predictions. 47

Experimental research is usually referred to as true experimentation. The researcher establishes the cause-effect relationship among a group of variables making up a study using the scientific method or process. This type of research attempts to identify the causal relationships between variables through experiments by arbitrarily controlling the conditions or manipulating the variables used. 44 The scientific manuscript would include an explanation of how the independent variable was manipulated to determine its effects on the dependent variables. The write-up would also describe the random assignments of subjects to experimental treatments. 21

Causal-comparative/quasi-experimental research closely resembles true experimentation but is conducted by establishing the cause-effect relationships among variables. It may also be conducted to establish the cause or consequences of differences that already exist between, or among groups of individuals. 48 This type of research compares outcomes between the intervention groups in which participants are not randomized to their respective interventions because of ethics- or feasibility-related reasons. 49 As in true experiments, the researcher identifies and measures the effects of the independent variable on the dependent variable. However, unlike true experiments, the researchers do not manipulate the independent variable.

In quasi-experimental research, naturally formed or pre-existing groups that are not randomly assigned are used, particularly when an ethical, randomized controlled trial is not feasible or logical. 50 The researcher identifies control groups as those which have been exposed to the treatment variable, and then compares these with the unexposed groups. The causes are determined and described after data analysis, after which conclusions are made. The known and unknown variables that could still affect the outcome are also included. 7

QUALITATIVE RESEARCH

Inductive approach.

Qualitative research involves an inductive approach to develop a hypothesis. 21 , 25 Using this approach, researchers answer research questions and develop new theories, but they do not test hypotheses or previous theories. The researcher seldom examines the effectiveness of an intervention, but rather explores the perceptions, actions, and feelings of participants using interviews, content analysis, observations, or focus groups. 25 , 45 , 51

Distinctive features of qualitative research

Qualitative research seeks to elucidate about the lives of people, including their lived experiences, behaviors, attitudes, beliefs, personality characteristics, emotions, and feelings. 27 , 30 It also explores societal, organizational, and cultural issues. 30 This type of research provides a good story mimicking an adventure which results in a “thick” description that puts readers in the research setting. 52

The qualitative research questions are open-ended, evolving, and non-directional. 26 The research design is usually flexible and iterative, commonly employing purposive sampling. The sample size depends on theoretical saturation, and data is collected using in-depth interviews, focus groups, and observations. 27

In various instances, excellent qualitative research may offer insights that quantitative research cannot. Moreover, qualitative research approaches can describe the ‘lived experience’ perspectives of patients, practitioners, and the public. 53 Interestingly, recent developments have looked into the use of technology in shaping qualitative research protocol development, data collection, and analysis phases. 54

Qualitative research employs various techniques, including conversational and discourse analysis, biographies, interviews, case-studies, oral history, surveys, documentary and archival research, audiovisual analysis, and participant observations. 26

Conducting qualitative research

To conduct qualitative research, investigators 1) identify a general research question, 2) choose the main methods, sites, and subjects, and 3) determine methods of data documentation access to subjects. Researchers also 4) decide on the various aspects for collecting data (e.g., questions, behaviors to observe, issues to look for in documents, how much (number of questions, interviews, or observations), 5) clarify researchers’ roles, and 6) evaluate the study’s ethical implications in terms of confidentiality and sensitivity. Afterwards, researchers 7) collect data until saturation, 8) interpret data by identifying concepts and theories, and 9) revise the research question if necessary and form hypotheses. In the final stages of the research, investigators 10) collect and verify data to address revisions, 11) complete the conceptual and theoretical framework to finalize their findings, and 12) present and disseminate findings ( Fig. 1B ).

Types of qualitative research

The different types of qualitative research include (a) historical research, (b) ethnographic research, (c) meta-analysis, (d) narrative research, (e) grounded theory, (f) phenomenology, (g) case study, and (h) field research. 23 , 25 , 28 , 30

Historical research is conducted by describing past events, problems, issues, and facts. The researcher gathers data from written or oral descriptions of past events and attempts to recreate the past without interpreting the events and their influence on the present. 6 Data is collected using documents, interviews, and surveys. 55 The researcher analyzes these data by describing the development of events and writes the research based on historical reports. 2

Ethnographic research is performed by observing everyday life details as they naturally unfold. 2 It can also be conducted by developing in-depth analytical descriptions of current systems, processes, and phenomena or by understanding the shared beliefs and practices of a particular group or culture. 21 The researcher collects extensive narrative non-numerical data based on many variables over an extended period, in a natural setting within a specific context. To do this, the researcher uses interviews, observations, and active participation. These data are analyzed by describing and interpreting them and developing themes. A detailed report of the interpreted data is then provided. 2 The researcher immerses himself/herself into the study population and describes the actions, behaviors, and events from the perspective of someone involved in the population. 23 As examples of its application, ethnographic research has helped to understand a cultural model of family and community nursing during the coronavirus disease 2019 outbreak. 56 It has also been used to observe the organization of people’s environment in relation to cardiovascular disease management in order to clarify people’s real expectations during follow-up consultations, possibly contributing to the development of innovative solutions in care practices. 57

Meta-analysis is carried out by accumulating experimental and correlational results across independent studies using a statistical method. 21 The report is written by specifying the topic and meta-analysis type. In the write-up, reporting guidelines are followed, which include description of inclusion criteria and key variables, explanation of the systematic search of databases, and details of data extraction. Meta-analysis offers in-depth data gathering and analysis to achieve deeper inner reflection and phenomenon examination. 58

Narrative research is performed by collecting stories for constructing a narrative about an individual’s experiences and the meanings attributed to them by the individual. 9 It aims to hear the voice of individuals through their account or experiences. 17 The researcher usually conducts interviews and analyzes data by storytelling, content review, and theme development. The report is written as an in-depth narration of events or situations focused on the participants. 2 , 59 Narrative research weaves together sequential events from one or two individuals to create a “thick” description of a cohesive story or narrative. 23 It facilitates understanding of individuals’ lives based on their own actions and interpretations. 60

Grounded theory is conducted by engaging in an inductive ground-up or bottom-up strategy of generating a theory from data. 24 The researcher incorporates deductive reasoning when using constant comparisons. Patterns are detected in observations and then a working hypothesis is created which directs the progression of inquiry. The researcher collects data using interviews and questionnaires. These data are analyzed by coding the data, categorizing themes, and describing implications. The research is written as a theory and theoretical models. 2 In the write-up, the researcher describes the data analysis procedure (i.e., theoretical coding used) for developing hypotheses based on what the participants say. 61 As an example, a qualitative approach has been used to understand the process of skill development of a nurse preceptor in clinical teaching. 62 A researcher can also develop a theory using the grounded theory approach to explain the phenomena of interest by observing a population. 23

Phenomenology is carried out by attempting to understand the subjects’ perspectives. This approach is pertinent in social work research where empathy and perspective are keys to success. 21 Phenomenology studies an individual’s lived experience in the world. 63 The researcher collects data by interviews, observations, and surveys. 16 These data are analyzed by describing experiences, examining meanings, and developing themes. The researcher writes the report by contextualizing and reporting the subjects’ experience. This research approach describes and explains an event or phenomenon from the perspective of those who have experienced it. 23 Phenomenology understands the participants’ experiences as conditioned by their worldviews. 52 It is suitable for a deeper understanding of non-measurable aspects related to the meanings and senses attributed by individuals’ lived experiences. 60

Case study is conducted by collecting data through interviews, observations, document content examination, and physical inspections. The researcher analyzes the data through a detailed identification of themes and the development of narratives. The report is written as an in-depth study of possible lessons learned from the case. 2

Field research is performed using a group of methodologies for undertaking qualitative inquiries. The researcher goes directly to the social phenomenon being studied and observes it extensively. In the write-up, the researcher describes the phenomenon under the natural environment over time with no implantation of controls or experimental conditions. 45

DIFFERENCES BETWEEN QUANTITATIVE AND QUALITATIVE RESEARCH

Scientific researchers must be aware of the differences between quantitative and qualitative research in terms of their working mechanisms to better understand their specific applications. This knowledge will be of significant benefit to researchers, especially during the planning process, to ensure that the appropriate type of research is undertaken to fulfill the research aims.

In terms of quantitative research data evaluation, four well-established criteria are used: internal validity, external validity, reliability, and objectivity. 23 The respective correlating concepts in qualitative research data evaluation are credibility, transferability, dependability, and confirmability. 30 Regarding write-up, quantitative research papers are usually shorter than their qualitative counterparts, which allows the latter to pursue a deeper understanding and thus producing the so-called “thick” description. 29

Interestingly, a major characteristic of qualitative research is that the research process is reversible and the research methods can be modified. This is in contrast to quantitative research in which hypothesis setting and testing take place unidirectionally. This means that in qualitative research, the research topic and question may change during literature analysis, and that the theoretical and analytical methods could be altered during data collection. 44

Quantitative research focuses on natural, quantitative, and objective phenomena, whereas qualitative research focuses on social, qualitative, and subjective phenomena. 26 Quantitative research answers the questions “what?” and “when?,” whereas qualitative research answers the questions “why?,” “how?,” and “how come?.” 64

Perhaps the most important distinction between quantitative and qualitative research lies in the nature of the data being investigated and analyzed. Quantitative research focuses on statistical, numerical, and quantitative aspects of phenomena, and employ the same data collection and analysis, whereas qualitative research focuses on the humanistic, descriptive, and qualitative aspects of phenomena. 26 , 28

Structured versus unstructured processes

The aims and types of inquiries determine the difference between quantitative and qualitative research. In quantitative research, statistical data and a structured process are usually employed by the researcher. Quantitative research usually suggests quantities (i.e., numbers). 65 On the other hand, researchers typically use opinions, reasons, verbal statements, and an unstructured process in qualitative research. 63 Qualitative research is more related to quality or kind. 65

In quantitative research, the researcher employs a structured process for collecting quantifiable data. Often, a close-ended questionnaire is used wherein the response categories for each question are designed in which values can be assigned and analyzed quantitatively using a common scale. 66 Quantitative research data is processed consecutively from data management, then data analysis, and finally to data interpretation. Data should be free from errors and missing values. In data management, variables are defined and coded. In data analysis, statistics (e.g., descriptive, inferential) as well as central tendency (i.e., mean, median, mode), spread (standard deviation), and parameter estimation (confidence intervals) measures are used. 67

In qualitative research, the researcher uses an unstructured process for collecting data. These non-statistical data may be in the form of statements, stories, or long explanations. Various responses according to respondents may not be easily quantified using a common scale. 66

Composing a qualitative research paper resembles writing a quantitative research paper. Both papers consist of a title, an abstract, an introduction, objectives, methods, findings, and discussion. However, a qualitative research paper is less regimented than a quantitative research paper. 27

Quantitative research as a deductive hypothesis-testing design

Quantitative research can be considered as a hypothesis-testing design as it involves quantification, statistics, and explanations. It flows from theory to data (i.e., deductive), focuses on objective data, and applies theories to address problems. 45 , 68 It collects numerical or statistical data; answers questions such as how many, how often, how much; uses questionnaires, structured interview schedules, or surveys 55 as data collection tools; analyzes quantitative data in terms of percentages, frequencies, statistical comparisons, graphs, and tables showing statistical values; and reports the final findings in the form of statistical information. 66 It uses variable-based models from individual cases and findings are stated in quantified sentences derived by deductive reasoning. 24

In quantitative research, a phenomenon is investigated in terms of the relationship between an independent variable and a dependent variable which are numerically measurable. The research objective is to statistically test whether the hypothesized relationship is true. 68 Here, the researcher studies what others have performed, examines current theories of the phenomenon being investigated, and then tests hypotheses that emerge from those theories. 4

Quantitative hypothesis-testing research has certain limitations. These limitations include (a) problems with selection of meaningful independent and dependent variables, (b) the inability to reflect subjective experiences as variables since variables are usually defined numerically, and (c) the need to state a hypothesis before the investigation starts. 61

Qualitative research as an inductive hypothesis-generating design

Qualitative research can be considered as a hypothesis-generating design since it involves understanding and descriptions in terms of context. It flows from data to theory (i.e., inductive), focuses on observation, and examines what happens in specific situations with the aim of developing new theories based on the situation. 45 , 68 This type of research (a) collects qualitative data (e.g., ideas, statements, reasons, characteristics, qualities), (b) answers questions such as what, why, and how, (c) uses interviews, observations, or focused-group discussions as data collection tools, (d) analyzes data by discovering patterns of changes, causal relationships, or themes in the data; and (e) reports the final findings as descriptive information. 61 Qualitative research favors case-based models from individual characteristics, and findings are stated using context-dependent existential sentences that are justifiable by inductive reasoning. 24

In qualitative research, texts and interviews are analyzed and interpreted to discover meaningful patterns characteristic of a particular phenomenon. 61 Here, the researcher starts with a set of observations and then moves from particular experiences to a more general set of propositions about those experiences. 4

Qualitative hypothesis-generating research involves collecting interview data from study participants regarding a phenomenon of interest, and then using what they say to develop hypotheses. It involves the process of questioning more than obtaining measurements; it generates hypotheses using theoretical coding. 61 When using large interview teams, the key to promoting high-level qualitative research and cohesion in large team methods and successful research outcomes is the balance between autonomy and collaboration. 69

Qualitative data may also include observed behavior, participant observation, media accounts, and cultural artifacts. 61 Focus group interviews are usually conducted, audiotaped or videotaped, and transcribed. Afterwards, the transcript is analyzed by several researchers.

Qualitative research also involves scientific narratives and the analysis and interpretation of textual or numerical data (or both), mostly from conversations and discussions. Such approach uncovers meaningful patterns that describe a particular phenomenon. 2 Thus, qualitative research requires skills in grasping and contextualizing data, as well as communicating data analysis and results in a scientific manner. The reflective process of the inquiry underscores the strengths of a qualitative research approach. 2

Combination of quantitative and qualitative research

When both quantitative and qualitative research methods are used in the same research, mixed-method research is applied. 25 This combination provides a complete view of the research problem and achieves triangulation to corroborate findings, complementarity to clarify results, expansion to extend the study’s breadth, and explanation to elucidate unexpected results. 29

Moreover, quantitative and qualitative findings are integrated to address the weakness of both research methods 29 , 66 and to have a more comprehensive understanding of the phenomenon spectrum. 66

For data analysis in mixed-method research, real non-quantitized qualitative data and quantitative data must both be analyzed. 70 The data obtained from quantitative analysis can be further expanded and deepened by qualitative analysis. 23

In terms of assessment criteria, Hammersley 71 opined that qualitative and quantitative findings should be judged using the same standards of validity and value-relevance. Both approaches can be mutually supportive. 52

Quantitative and qualitative research must be carefully studied and conducted by scientific researchers to avoid unethical research and inadequate outcomes. Quantitative research involves a deductive process wherein a research question is answered with a hypothesis that describes the relationship between independent and dependent variables, and the testing of the hypothesis. This investigation can be aptly termed as hypothesis-testing research involving the analysis of hypothesis-driven experimental studies resulting in a test of significance. Qualitative research involves an inductive process wherein a research question is explored to generate a hypothesis, which then leads to the development of a theory. This investigation can be aptly termed as hypothesis-generating research. When the whole spectrum of inductive and deductive research approaches is combined using both quantitative and qualitative research methodologies, mixed-method research is applied, and this can facilitate the construction of novel hypotheses, development of theories, or refinement of concepts.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Data curation: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Formal analysis: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C.
• Investigation: Barroga E, Matanguihan GJ, Takamiya Y, Izumi M.
• Methodology: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Project administration: Barroga E, Matanguihan GJ.
• Resources: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Supervision: Barroga E.
• Validation: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Visualization: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.