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What Is Qualitative Research? | Methods & Examples

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

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

• Flexibility

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

• Natural settings

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

• Meaningful insights

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

• Generation of new ideas

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

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

• Unreliability

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

• Subjectivity

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

• Limited generalisability

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

• Labour-intensive

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

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

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

There are five common approaches to qualitative research :

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

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

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

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

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

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Qualitative Research : Definition

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

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4.2 Definitions and Characteristics of Qualitative Research

Qualitative research aims to uncover the meaning and understanding of phenomena that cannot be broken down into measurable elements. It is based on naturalistic, interpretative and humanistic notions. 5 This research method seeks to discover, explore, identify or describe subjective human experiences using non-statistical methods and develops themes from the study participants’ stories. 5 Figure 4.1 depicts major features/ characteristics of qualitative research. It utilises exploratory open-ended questions and observations to search for patterns of meaning in collected data (e.g. observation, verbal/written narrative data, photographs, etc.) and uses inductive thinking (from specific observations to more general rules) to interpret meaning. 6 Participants’ voice is evident through quotations and description of the work. 6 The context/ setting of the study and the researcher’s reflexivity (i.e. “reflection on and awareness of their bias”, the effect of the researcher’s experience on the data and interpretations) are very important and described as part of data collection. 6 Analysis of collected data is complex, often involves inductive data analysis (exploration, contrasts, specific to general) and requires multiple coding and development of themes from participant stories. 6

Reflexivity- avoiding bias/Role of the qualitative researcher

Qualitative researchers generally begin their work with the recognition that their position (or worldview) has a significant impact on the overall research process. 7 Researcher worldview shapes the way the research is conducted, i.e., how the questions are formulated, methods are chosen, data are collected and analysed, and results are reported. Therefore, it is essential for qualitative researchers to acknowledge, articulate, reflect on and clarify their own underlying biases and assumptions before embarking on any research project. 7 Reflexivity helps to ensure that the researcher’s own experiences, values, and beliefs do not unintentionally bias the data collection, analysis, and interpretation. 7 It is the gold standard for establishing trustworthiness and has been established as one of the ways qualitative researchers should ensure rigour and quality in their work. 8 The following questions in Table 4.1 may help you begin the reflective process. 9

Table 4.1: Questions to aid the reflection process

Philosophical underpinnings to qualitative research

Qualitative research uses an inductive approach and stems from interpretivism or constructivism and assumes that realities are multiple, socially constructed, and holistic. 10 According to this philosophical viewpoint, humans build reality through their interactions with the world around them. 10 As a result, qualitative research aims to comprehend how individuals make sense of their experiences and build meaning in their lives. 10 Because reality is complex/nuanced and context-bound, participants constantly construct it depending on their understanding. Thus, the interactions between the researcher and the participants are considered necessary to offer a rich description of the concept and provide an in-depth understanding of the phenomenon under investigation. 11

An Introduction to Research Methods for Undergraduate Health Profession Students Copyright © 2023 by Faith Alele and Bunmi Malau-Aduli is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

How to Write an Introduction for a Qualitative Research Study

How to Write a Lab Report Conclusion

There are two different accepted methods of conducting research in social sciences. These are quantitative and qualitative research studies. Both methods can be used to test hypotheses by carrying out investigations with groups of participants, but they achieve that in different ways. Quantitative research relies solely on numbers. For instance, the researcher may give out surveys to a large number of participants and then analyze the data from their answers by looking for patterns and correlations among different variables. In these studies, numerical data are analyzed using various statistical methods, and the researcher may not have to ever talk to any participants face-to-face.

When conducting qualitative research, the researcher often relies on a smaller group of participants, often conducts individual interviews with them and is interested in hearing their perspectives. The goal of a qualitative study isn't to find wide generalizations but to identify and analyze specific examples of a certain phenomenon and consider its possible implications. Qualitative methods often include in-depth interviews, group discussions and general participant observations by the researcher.

Why an Introduction is Important

An introduction is a crucial part of your study because it gives your readers a road map of what they can expect in reading your paper. It doesn't need to be long or elaborate, but it has to include the following elements.

State the Problem

Introduce the reader to the issue that your study addresses. Provide a concise overview of the problem and mention briefly how previous studies (if any) attempted to solve it. Don't go into details here. You'll have a chance to write a more in-depth literature review later.

Describe the Methods

Give the reader a brief overview (a couple of sentences will suffice) of the methodology you employed in your study. This is where you make it clear that your study relies on qualitative research methods. Again, don't go into as much detail as you will later in the methodology section.

State the Conclusion

That’s right. State the conclusion right in the introduction. It can be tempting to keep this part a secret until the reader gets to the end (why give everything away, you may be thinking?), but remember, you’re not writing a work of fiction. Your reader doesn't want to be surprised. They want an overview of what to expect in the conclusion and how you got there.

Address the Bigger Picture

Explain why this study is important in the bigger scheme of things. Think beyond the particular problem that your study addresses. What bigger questions will it help solve?

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• University of Southern California Libraries: Organizing Your Social Sciences Research Paper: 4. The Introduction
• Though quantitative methods are often employed as an effort of supporting the results and interpretations in a qualitative research study, they are not and should not be the focus of the report. Consequently, in your explanation and justification sections of your introduction, indicate the ways in which quantitative research played a complementary role to your qualitative analysis.

Tanya Mozias Slavin is a former academic and language teacher. She writes about education and linguistic technology, and has published articles in the Washington Post, Fast Company, CBC and other places. Find her at www.tanyamoziasslavin.com

An Introduction to Qualitative Research

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Qualitative research — when you first heard the term, your initial thought might have been, ‘What do qualitative researchers actually do?’ It may come as a surprise to you that you are already familiar with many of their activities, and you actually do them yourself — every day — as you watch and listen to what happens around you, and ask questions about what you have seen and heard.

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What is “Qualitative” in Qualitative Research? Why the Answer Does not Matter but the Question is Important

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Croker, R.A. (2009). An Introduction to Qualitative Research. In: Heigham, J., Croker, R.A. (eds) Qualitative Research in Applied Linguistics. Palgrave Macmillan, London. https://doi.org/10.1057/9780230239517_1

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Chapter 11. Interviewing

Introduction.

Interviewing people is at the heart of qualitative research. It is not merely a way to collect data but an intrinsically rewarding activity—an interaction between two people that holds the potential for greater understanding and interpersonal development. Unlike many of our daily interactions with others that are fairly shallow and mundane, sitting down with a person for an hour or two and really listening to what they have to say is a profound and deep enterprise, one that can provide not only “data” for you, the interviewer, but also self-understanding and a feeling of being heard for the interviewee. I always approach interviewing with a deep appreciation for the opportunity it gives me to understand how other people experience the world. That said, there is not one kind of interview but many, and some of these are shallower than others. This chapter will provide you with an overview of interview techniques but with a special focus on the in-depth semistructured interview guide approach, which is the approach most widely used in social science research.

An interview can be variously defined as “a conversation with a purpose” ( Lune and Berg 2018 ) and an attempt to understand the world from the point of view of the person being interviewed: “to unfold the meaning of peoples’ experiences, to uncover their lived world prior to scientific explanations” ( Kvale 2007 ). It is a form of active listening in which the interviewer steers the conversation to subjects and topics of interest to their research but also manages to leave enough space for those interviewed to say surprising things. Achieving that balance is a tricky thing, which is why most practitioners believe interviewing is both an art and a science. In my experience as a teacher, there are some students who are “natural” interviewers (often they are introverts), but anyone can learn to conduct interviews, and everyone, even those of us who have been doing this for years, can improve their interviewing skills. This might be a good time to highlight the fact that the interview is a product between interviewer and interviewee and that this product is only as good as the rapport established between the two participants. Active listening is the key to establishing this necessary rapport.

Patton ( 2002 ) makes the argument that we use interviews because there are certain things that are not observable. In particular, “we cannot observe feelings, thoughts, and intentions. We cannot observe behaviors that took place at some previous point in time. We cannot observe situations that preclude the presence of an observer. We cannot observe how people have organized the world and the meanings they attach to what goes on in the world. We have to ask people questions about those things” ( 341 ).

Types of Interviews

There are several distinct types of interviews. Imagine a continuum (figure 11.1). On one side are unstructured conversations—the kind you have with your friends. No one is in control of those conversations, and what you talk about is often random—whatever pops into your head. There is no secret, underlying purpose to your talking—if anything, the purpose is to talk to and engage with each other, and the words you use and the things you talk about are a little beside the point. An unstructured interview is a little like this informal conversation, except that one of the parties to the conversation (you, the researcher) does have an underlying purpose, and that is to understand the other person. You are not friends speaking for no purpose, but it might feel just as unstructured to the “interviewee” in this scenario. That is one side of the continuum. On the other side are fully structured and standardized survey-type questions asked face-to-face. Here it is very clear who is asking the questions and who is answering them. This doesn’t feel like a conversation at all! A lot of people new to interviewing have this ( erroneously !) in mind when they think about interviews as data collection. Somewhere in the middle of these two extreme cases is the “ semistructured” interview , in which the researcher uses an “interview guide” to gently move the conversation to certain topics and issues. This is the primary form of interviewing for qualitative social scientists and will be what I refer to as interviewing for the rest of this chapter, unless otherwise specified.

Informal (unstructured conversations). This is the most “open-ended” approach to interviewing. It is particularly useful in conjunction with observational methods (see chapters 13 and 14). There are no predetermined questions. Each interview will be different. Imagine you are researching the Oregon Country Fair, an annual event in Veneta, Oregon, that includes live music, artisan craft booths, face painting, and a lot of people walking through forest paths. It’s unlikely that you will be able to get a person to sit down with you and talk intensely about a set of questions for an hour and a half. But you might be able to sidle up to several people and engage with them about their experiences at the fair. You might have a general interest in what attracts people to these events, so you could start a conversation by asking strangers why they are here or why they come back every year. That’s it. Then you have a conversation that may lead you anywhere. Maybe one person tells a long story about how their parents brought them here when they were a kid. A second person talks about how this is better than Burning Man. A third person shares their favorite traveling band. And yet another enthuses about the public library in the woods. During your conversations, you also talk about a lot of other things—the weather, the utilikilts for sale, the fact that a favorite food booth has disappeared. It’s all good. You may not be able to record these conversations. Instead, you might jot down notes on the spot and then, when you have the time, write down as much as you can remember about the conversations in long fieldnotes. Later, you will have to sit down with these fieldnotes and try to make sense of all the information (see chapters 18 and 19).

Interview guide ( semistructured interview ). This is the primary type employed by social science qualitative researchers. The researcher creates an “interview guide” in advance, which she uses in every interview. In theory, every person interviewed is asked the same questions. In practice, every person interviewed is asked mostly the same topics but not always the same questions, as the whole point of a “guide” is that it guides the direction of the conversation but does not command it. The guide is typically between five and ten questions or question areas, sometimes with suggested follow-ups or prompts . For example, one question might be “What was it like growing up in Eastern Oregon?” with prompts such as “Did you live in a rural area? What kind of high school did you attend?” to help the conversation develop. These interviews generally take place in a quiet place (not a busy walkway during a festival) and are recorded. The recordings are transcribed, and those transcriptions then become the “data” that is analyzed (see chapters 18 and 19). The conventional length of one of these types of interviews is between one hour and two hours, optimally ninety minutes. Less than one hour doesn’t allow for much development of questions and thoughts, and two hours (or more) is a lot of time to ask someone to sit still and answer questions. If you have a lot of ground to cover, and the person is willing, I highly recommend two separate interview sessions, with the second session being slightly shorter than the first (e.g., ninety minutes the first day, sixty minutes the second). There are lots of good reasons for this, but the most compelling one is that this allows you to listen to the first day’s recording and catch anything interesting you might have missed in the moment and so develop follow-up questions that can probe further. This also allows the person being interviewed to have some time to think about the issues raised in the interview and go a little deeper with their answers.

Standardized questionnaire with open responses ( structured interview ). This is the type of interview a lot of people have in mind when they hear “interview”: a researcher comes to your door with a clipboard and proceeds to ask you a series of questions. These questions are all the same whoever answers the door; they are “standardized.” Both the wording and the exact order are important, as people’s responses may vary depending on how and when a question is asked. These are qualitative only in that the questions allow for “open-ended responses”: people can say whatever they want rather than select from a predetermined menu of responses. For example, a survey I collaborated on included this open-ended response question: “How does class affect one’s career success in sociology?” Some of the answers were simply one word long (e.g., “debt”), and others were long statements with stories and personal anecdotes. It is possible to be surprised by the responses. Although it’s a stretch to call this kind of questioning a conversation, it does allow the person answering the question some degree of freedom in how they answer.

Survey questionnaire with closed responses (not an interview!). Standardized survey questions with specific answer options (e.g., closed responses) are not really interviews at all, and they do not generate qualitative data. For example, if we included five options for the question “How does class affect one’s career success in sociology?”—(1) debt, (2) social networks, (3) alienation, (4) family doesn’t understand, (5) type of grad program—we leave no room for surprises at all. Instead, we would most likely look at patterns around these responses, thinking quantitatively rather than qualitatively (e.g., using regression analysis techniques, we might find that working-class sociologists were twice as likely to bring up alienation). It can sometimes be confusing for new students because the very same survey can include both closed-ended and open-ended questions. The key is to think about how these will be analyzed and to what level surprises are possible. If your plan is to turn all responses into a number and make predictions about correlations and relationships, you are no longer conducting qualitative research. This is true even if you are conducting this survey face-to-face with a real live human. Closed-response questions are not conversations of any kind, purposeful or not.

In summary, the semistructured interview guide approach is the predominant form of interviewing for social science qualitative researchers because it allows a high degree of freedom of responses from those interviewed (thus allowing for novel discoveries) while still maintaining some connection to a research question area or topic of interest. The rest of the chapter assumes the employment of this form.

Creating an Interview Guide

Your interview guide is the instrument used to bridge your research question(s) and what the people you are interviewing want to tell you. Unlike a standardized questionnaire, the questions actually asked do not need to be exactly what you have written down in your guide. The guide is meant to create space for those you are interviewing to talk about the phenomenon of interest, but sometimes you are not even sure what that phenomenon is until you start asking questions. A priority in creating an interview guide is to ensure it offers space. One of the worst mistakes is to create questions that are so specific that the person answering them will not stray. Relatedly, questions that sound “academic” will shut down a lot of respondents. A good interview guide invites respondents to talk about what is important to them, not feel like they are performing or being evaluated by you.

Good interview questions should not sound like your “research question” at all. For example, let’s say your research question is “How do patriarchal assumptions influence men’s understanding of climate change and responses to climate change?” It would be worse than unhelpful to ask a respondent, “How do your assumptions about the role of men affect your understanding of climate change?” You need to unpack this into manageable nuggets that pull your respondent into the area of interest without leading him anywhere. You could start by asking him what he thinks about climate change in general. Or, even better, whether he has any concerns about heatwaves or increased tornadoes or polar icecaps melting. Once he starts talking about that, you can ask follow-up questions that bring in issues around gendered roles, perhaps asking if he is married (to a woman) and whether his wife shares his thoughts and, if not, how they negotiate that difference. The fact is, you won’t really know the right questions to ask until he starts talking.

There are several distinct types of questions that can be used in your interview guide, either as main questions or as follow-up probes. If you remember that the point is to leave space for the respondent, you will craft a much more effective interview guide! You will also want to think about the place of time in both the questions themselves (past, present, future orientations) and the sequencing of the questions.

Researcher Note

Suggestion : As you read the next three sections (types of questions, temporality, question sequence), have in mind a particular research question, and try to draft questions and sequence them in a way that opens space for a discussion that helps you answer your research question.

Type of Questions

Experience and behavior questions ask about what a respondent does regularly (their behavior) or has done (their experience). These are relatively easy questions for people to answer because they appear more “factual” and less subjective. This makes them good opening questions. For the study on climate change above, you might ask, “Have you ever experienced an unusual weather event? What happened?” Or “You said you work outside? What is a typical summer workday like for you? How do you protect yourself from the heat?”

Opinion and values questions , in contrast, ask questions that get inside the minds of those you are interviewing. “Do you think climate change is real? Who or what is responsible for it?” are two such questions. Note that you don’t have to literally ask, “What is your opinion of X?” but you can find a way to ask the specific question relevant to the conversation you are having. These questions are a bit trickier to ask because the answers you get may depend in part on how your respondent perceives you and whether they want to please you or not. We’ve talked a fair amount about being reflective. Here is another place where this comes into play. You need to be aware of the effect your presence might have on the answers you are receiving and adjust accordingly. If you are a woman who is perceived as liberal asking a man who identifies as conservative about climate change, there is a lot of subtext that can be going on in the interview. There is no one right way to resolve this, but you must at least be aware of it.

Feeling questions are questions that ask respondents to draw on their emotional responses. It’s pretty common for academic researchers to forget that we have bodies and emotions, but people’s understandings of the world often operate at this affective level, sometimes unconsciously or barely consciously. It is a good idea to include questions that leave space for respondents to remember, imagine, or relive emotional responses to particular phenomena. “What was it like when you heard your cousin’s house burned down in that wildfire?” doesn’t explicitly use any emotion words, but it allows your respondent to remember what was probably a pretty emotional day. And if they respond emotionally neutral, that is pretty interesting data too. Note that asking someone “How do you feel about X” is not always going to evoke an emotional response, as they might simply turn around and respond with “I think that…” It is better to craft a question that actually pushes the respondent into the affective category. This might be a specific follow-up to an experience and behavior question —for example, “You just told me about your daily routine during the summer heat. Do you worry it is going to get worse?” or “Have you ever been afraid it will be too hot to get your work accomplished?”

Knowledge questions ask respondents what they actually know about something factual. We have to be careful when we ask these types of questions so that respondents do not feel like we are evaluating them (which would shut them down), but, for example, it is helpful to know when you are having a conversation about climate change that your respondent does in fact know that unusual weather events have increased and that these have been attributed to climate change! Asking these questions can set the stage for deeper questions and can ensure that the conversation makes the same kind of sense to both participants. For example, a conversation about political polarization can be put back on track once you realize that the respondent doesn’t really have a clear understanding that there are two parties in the US. Instead of asking a series of questions about Republicans and Democrats, you might shift your questions to talk more generally about political disagreements (e.g., “people against abortion”). And sometimes what you do want to know is the level of knowledge about a particular program or event (e.g., “Are you aware you can discharge your student loans through the Public Service Loan Forgiveness program?”).

Sensory questions call on all senses of the respondent to capture deeper responses. These are particularly helpful in sparking memory. “Think back to your childhood in Eastern Oregon. Describe the smells, the sounds…” Or you could use these questions to help a person access the full experience of a setting they customarily inhabit: “When you walk through the doors to your office building, what do you see? Hear? Smell?” As with feeling questions , these questions often supplement experience and behavior questions . They are another way of allowing your respondent to report fully and deeply rather than remain on the surface.

Creative questions employ illustrative examples, suggested scenarios, or simulations to get respondents to think more deeply about an issue, topic, or experience. There are many options here. In The Trouble with Passion , Erin Cech ( 2021 ) provides a scenario in which “Joe” is trying to decide whether to stay at his decent but boring computer job or follow his passion by opening a restaurant. She asks respondents, “What should Joe do?” Their answers illuminate the attraction of “passion” in job selection. In my own work, I have used a news story about an upwardly mobile young man who no longer has time to see his mother and sisters to probe respondents’ feelings about the costs of social mobility. Jessi Streib and Betsy Leondar-Wright have used single-page cartoon “scenes” to elicit evaluations of potential racial discrimination, sexual harassment, and classism. Barbara Sutton ( 2010 ) has employed lists of words (“strong,” “mother,” “victim”) on notecards she fans out and asks her female respondents to select and discuss.

Background/Demographic Questions

You most definitely will want to know more about the person you are interviewing in terms of conventional demographic information, such as age, race, gender identity, occupation, and educational attainment. These are not questions that normally open up inquiry. [1] For this reason, my practice has been to include a separate “demographic questionnaire” sheet that I ask each respondent to fill out at the conclusion of the interview. Only include those aspects that are relevant to your study. For example, if you are not exploring religion or religious affiliation, do not include questions about a person’s religion on the demographic sheet. See the example provided at the end of this chapter.

Temporality

Any type of question can have a past, present, or future orientation. For example, if you are asking a behavior question about workplace routine, you might ask the respondent to talk about past work, present work, and ideal (future) work. Similarly, if you want to understand how people cope with natural disasters, you might ask your respondent how they felt then during the wildfire and now in retrospect and whether and to what extent they have concerns for future wildfire disasters. It’s a relatively simple suggestion—don’t forget to ask about past, present, and future—but it can have a big impact on the quality of the responses you receive.

Question Sequence

Having a list of good questions or good question areas is not enough to make a good interview guide. You will want to pay attention to the order in which you ask your questions. Even though any one respondent can derail this order (perhaps by jumping to answer a question you haven’t yet asked), a good advance plan is always helpful. When thinking about sequence, remember that your goal is to get your respondent to open up to you and to say things that might surprise you. To establish rapport, it is best to start with nonthreatening questions. Asking about the present is often the safest place to begin, followed by the past (they have to know you a little bit to get there), and lastly, the future (talking about hopes and fears requires the most rapport). To allow for surprises, it is best to move from very general questions to more particular questions only later in the interview. This ensures that respondents have the freedom to bring up the topics that are relevant to them rather than feel like they are constrained to answer you narrowly. For example, refrain from asking about particular emotions until these have come up previously—don’t lead with them. Often, your more particular questions will emerge only during the course of the interview, tailored to what is emerging in conversation.

Once you have a set of questions, read through them aloud and imagine you are being asked the same questions. Does the set of questions have a natural flow? Would you be willing to answer the very first question to a total stranger? Does your sequence establish facts and experiences before moving on to opinions and values? Did you include prefatory statements, where necessary; transitions; and other announcements? These can be as simple as “Hey, we talked a lot about your experiences as a barista while in college.… Now I am turning to something completely different: how you managed friendships in college.” That is an abrupt transition, but it has been softened by your acknowledgment of that.

Probes and Flexibility

Once you have the interview guide, you will also want to leave room for probes and follow-up questions. As in the sample probe included here, you can write out the obvious probes and follow-up questions in advance. You might not need them, as your respondent might anticipate them and include full responses to the original question. Or you might need to tailor them to how your respondent answered the question. Some common probes and follow-up questions include asking for more details (When did that happen? Who else was there?), asking for elaboration (Could you say more about that?), asking for clarification (Does that mean what I think it means or something else? I understand what you mean, but someone else reading the transcript might not), and asking for contrast or comparison (How did this experience compare with last year’s event?). “Probing is a skill that comes from knowing what to look for in the interview, listening carefully to what is being said and what is not said, and being sensitive to the feedback needs of the person being interviewed” ( Patton 2002:374 ). It takes work! And energy. I and many other interviewers I know report feeling emotionally and even physically drained after conducting an interview. You are tasked with active listening and rearranging your interview guide as needed on the fly. If you only ask the questions written down in your interview guide with no deviations, you are doing it wrong. [2]

The Final Question

Every interview guide should include a very open-ended final question that allows for the respondent to say whatever it is they have been dying to tell you but you’ve forgotten to ask. About half the time they are tired too and will tell you they have nothing else to say. But incredibly, some of the most honest and complete responses take place here, at the end of a long interview. You have to realize that the person being interviewed is often discovering things about themselves as they talk to you and that this process of discovery can lead to new insights for them. Making space at the end is therefore crucial. Be sure you convey that you actually do want them to tell you more, that the offer of “anything else?” is not read as an empty convention where the polite response is no. Here is where you can pull from that active listening and tailor the final question to the particular person. For example, “I’ve asked you a lot of questions about what it was like to live through that wildfire. I’m wondering if there is anything I’ve forgotten to ask, especially because I haven’t had that experience myself” is a much more inviting final question than “Great. Anything you want to add?” It’s also helpful to convey to the person that you have the time to listen to their full answer, even if the allotted time is at the end. After all, there are no more questions to ask, so the respondent knows exactly how much time is left. Do them the courtesy of listening to them!

Conducting the Interview

Once you have your interview guide, you are on your way to conducting your first interview. I always practice my interview guide with a friend or family member. I do this even when the questions don’t make perfect sense for them, as it still helps me realize which questions make no sense, are poorly worded (too academic), or don’t follow sequentially. I also practice the routine I will use for interviewing, which goes something like this:

• Introduce myself and reintroduce the study
• Provide consent form and ask them to sign and retain/return copy
• Ask if they have any questions about the study before we begin
• Ask if I can begin recording
• Ask questions (from interview guide)
• Turn off the recording device
• Ask if they are willing to fill out my demographic questionnaire
• Collect questionnaire and, without looking at the answers, place in same folder as signed consent form
• Thank them and depart

A note on remote interviewing: Interviews have traditionally been conducted face-to-face in a private or quiet public setting. You don’t want a lot of background noise, as this will make transcriptions difficult. During the recent global pandemic, many interviewers, myself included, learned the benefits of interviewing remotely. Although face-to-face is still preferable for many reasons, Zoom interviewing is not a bad alternative, and it does allow more interviews across great distances. Zoom also includes automatic transcription, which significantly cuts down on the time it normally takes to convert our conversations into “data” to be analyzed. These automatic transcriptions are not perfect, however, and you will still need to listen to the recording and clarify and clean up the transcription. Nor do automatic transcriptions include notations of body language or change of tone, which you may want to include. When interviewing remotely, you will want to collect the consent form before you meet: ask them to read, sign, and return it as an email attachment. I think it is better to ask for the demographic questionnaire after the interview, but because some respondents may never return it then, it is probably best to ask for this at the same time as the consent form, in advance of the interview.

What should you bring to the interview? I would recommend bringing two copies of the consent form (one for you and one for the respondent), a demographic questionnaire, a manila folder in which to place the signed consent form and filled-out demographic questionnaire, a printed copy of your interview guide (I print with three-inch right margins so I can jot down notes on the page next to relevant questions), a pen, a recording device, and water.

After the interview, you will want to secure the signed consent form in a locked filing cabinet (if in print) or a password-protected folder on your computer. Using Excel or a similar program that allows tables/spreadsheets, create an identifying number for your interview that links to the consent form without using the name of your respondent. For example, let’s say that I conduct interviews with US politicians, and the first person I meet with is George W. Bush. I will assign the transcription the number “INT#001” and add it to the signed consent form. [3] The signed consent form goes into a locked filing cabinet, and I never use the name “George W. Bush” again. I take the information from the demographic sheet, open my Excel spreadsheet, and add the relevant information in separate columns for the row INT#001: White, male, Republican. When I interview Bill Clinton as my second interview, I include a second row: INT#002: White, male, Democrat. And so on. The only link to the actual name of the respondent and this information is the fact that the consent form (unavailable to anyone but me) has stamped on it the interview number.

Many students get very nervous before their first interview. Actually, many of us are always nervous before the interview! But do not worry—this is normal, and it does pass. Chances are, you will be pleasantly surprised at how comfortable it begins to feel. These “purposeful conversations” are often a delight for both participants. This is not to say that sometimes things go wrong. I often have my students practice several “bad scenarios” (e.g., a respondent that you cannot get to open up; a respondent who is too talkative and dominates the conversation, steering it away from the topics you are interested in; emotions that completely take over; or shocking disclosures you are ill-prepared to handle), but most of the time, things go quite well. Be prepared for the unexpected, but know that the reason interviews are so popular as a technique of data collection is that they are usually richly rewarding for both participants.

One thing that I stress to my methods students and remind myself about is that interviews are still conversations between people. If there’s something you might feel uncomfortable asking someone about in a “normal” conversation, you will likely also feel a bit of discomfort asking it in an interview. Maybe more importantly, your respondent may feel uncomfortable. Social research—especially about inequality—can be uncomfortable. And it’s easy to slip into an abstract, intellectualized, or removed perspective as an interviewer. This is one reason trying out interview questions is important. Another is that sometimes the question sounds good in your head but doesn’t work as well out loud in practice. I learned this the hard way when a respondent asked me how I would answer the question I had just posed, and I realized that not only did I not really know how I would answer it, but I also wasn’t quite as sure I knew what I was asking as I had thought.

—Elizabeth M. Lee, Associate Professor of Sociology at Saint Joseph’s University, author of Class and Campus Life , and co-author of Geographies of Campus Inequality

How Many Interviews?

Your research design has included a targeted number of interviews and a recruitment plan (see chapter 5). Follow your plan, but remember that “ saturation ” is your goal. You interview as many people as you can until you reach a point at which you are no longer surprised by what they tell you. This means not that no one after your first twenty interviews will have surprising, interesting stories to tell you but rather that the picture you are forming about the phenomenon of interest to you from a research perspective has come into focus, and none of the interviews are substantially refocusing that picture. That is when you should stop collecting interviews. Note that to know when you have reached this, you will need to read your transcripts as you go. More about this in chapters 18 and 19.

Your Final Product: The Ideal Interview Transcript

A good interview transcript will demonstrate a subtly controlled conversation by the skillful interviewer. In general, you want to see replies that are about one paragraph long, not short sentences and not running on for several pages. Although it is sometimes necessary to follow respondents down tangents, it is also often necessary to pull them back to the questions that form the basis of your research study. This is not really a free conversation, although it may feel like that to the person you are interviewing.

Final Tips from an Interview Master

Annette Lareau is arguably one of the masters of the trade. In Listening to People , she provides several guidelines for good interviews and then offers a detailed example of an interview gone wrong and how it could be addressed (please see the “Further Readings” at the end of this chapter). Here is an abbreviated version of her set of guidelines: (1) interview respondents who are experts on the subjects of most interest to you (as a corollary, don’t ask people about things they don’t know); (2) listen carefully and talk as little as possible; (3) keep in mind what you want to know and why you want to know it; (4) be a proactive interviewer (subtly guide the conversation); (5) assure respondents that there aren’t any right or wrong answers; (6) use the respondent’s own words to probe further (this both allows you to accurately identify what you heard and pushes the respondent to explain further); (7) reuse effective probes (don’t reinvent the wheel as you go—if repeating the words back works, do it again and again); (8) focus on learning the subjective meanings that events or experiences have for a respondent; (9) don’t be afraid to ask a question that draws on your own knowledge (unlike trial lawyers who are trained never to ask a question for which they don’t already know the answer, sometimes it’s worth it to ask risky questions based on your hypotheses or just plain hunches); (10) keep thinking while you are listening (so difficult…and important); (11) return to a theme raised by a respondent if you want further information; (12) be mindful of power inequalities (and never ever coerce a respondent to continue the interview if they want out); (13) take control with overly talkative respondents; (14) expect overly succinct responses, and develop strategies for probing further; (15) balance digging deep and moving on; (16) develop a plan to deflect questions (e.g., let them know you are happy to answer any questions at the end of the interview, but you don’t want to take time away from them now); and at the end, (17) check to see whether you have asked all your questions. You don’t always have to ask everyone the same set of questions, but if there is a big area you have forgotten to cover, now is the time to recover ( Lareau 2021:93–103 ).

Sample: Demographic Questionnaire

ASA Taskforce on First-Generation and Working-Class Persons in Sociology – Class Effects on Career Success

Supplementary Demographic Questionnaire

Thank you for your participation in this interview project. We would like to collect a few pieces of key demographic information from you to supplement our analyses. Your answers to these questions will be kept confidential and stored by ID number. All of your responses here are entirely voluntary!

What best captures your race/ethnicity? (please check any/all that apply)

• White (Non Hispanic/Latina/o/x)
• Black or African American
• Hispanic, Latino/a/x of Spanish
• Asian or Asian American
• American Indian or Alaska Native
• Middle Eastern or North African
• Native Hawaiian or Pacific Islander
• Other : (Please write in: ________________)

What is your current position?

• Grad Student
• Full Professor

Please check any and all of the following that apply to you:

• I identify as a working-class academic
• I was the first in my family to graduate from college
• I grew up poor

What best reflects your gender?

• Transgender female/Transgender woman
• Transgender male/Transgender man
• Gender queer/ Gender nonconforming

Anything else you would like us to know about you?

Example: Interview Guide

In this example, follow-up prompts are italicized.  Note the sequence of questions.  That second question often elicits an entire life history , answering several later questions in advance.

Introduction Script/Question

Thank you for participating in our survey of ASA members who identify as first-generation or working-class.  As you may have heard, ASA has sponsored a taskforce on first-generation and working-class persons in sociology and we are interested in hearing from those who so identify.  Your participation in this interview will help advance our knowledge in this area.

• The first thing we would like to as you is why you have volunteered to be part of this study? What does it mean to you be first-gen or working class?  Why were you willing to be interviewed?
• How did you decide to become a sociologist?
• Can you tell me a little bit about where you grew up? ( prompts: what did your parent(s) do for a living?  What kind of high school did you attend?)
• Has this identity been salient to your experience? (how? How much?)
• How welcoming was your grad program? Your first academic employer?
• Why did you decide to pursue sociology at the graduate level?
• Did you experience culture shock in college? In graduate school?
• Has your FGWC status shaped how you’ve thought about where you went to school? debt? etc?
• Were you mentored? How did this work (not work)?  How might it?
• What did you consider when deciding where to go to grad school? Where to apply for your first position?
• What, to you, is a mark of career success? Have you achieved that success?  What has helped or hindered your pursuit of success?
• Do you think sociology, as a field, cares about prestige?
• Let’s talk a little bit about intersectionality. How does being first-gen/working class work alongside other identities that are important to you?
• What do your friends and family think about your career? Have you had any difficulty relating to family members or past friends since becoming highly educated?
• Do you have any debt from college/grad school? Are you concerned about this?  Could you explain more about how you paid for college/grad school?  (here, include assistance from family, fellowships, scholarships, etc.)
• (You’ve mentioned issues or obstacles you had because of your background.) What could have helped?  Or, who or what did? Can you think of fortuitous moments in your career?
• Do you have any regrets about the path you took?
• Is there anything else you would like to add? Anything that the Taskforce should take note of, that we did not ask you about here?

Further Readings

Britten, Nicky. 1995. “Qualitative Interviews in Medical Research.” BMJ: British Medical Journal 31(6999):251–253. A good basic overview of interviewing particularly useful for students of public health and medical research generally.

Corbin, Juliet, and Janice M. Morse. 2003. “The Unstructured Interactive Interview: Issues of Reciprocity and Risks When Dealing with Sensitive Topics.” Qualitative Inquiry 9(3):335–354. Weighs the potential benefits and harms of conducting interviews on topics that may cause emotional distress. Argues that the researcher’s skills and code of ethics should ensure that the interviewing process provides more of a benefit to both participant and researcher than a harm to the former.

Gerson, Kathleen, and Sarah Damaske. 2020. The Science and Art of Interviewing . New York: Oxford University Press. A useful guidebook/textbook for both undergraduates and graduate students, written by sociologists.

Kvale, Steiner. 2007. Doing Interviews . London: SAGE. An easy-to-follow guide to conducting and analyzing interviews by psychologists.

Lamont, Michèle, and Ann Swidler. 2014. “Methodological Pluralism and the Possibilities and Limits of Interviewing.” Qualitative Sociology 37(2):153–171. Written as a response to various debates surrounding the relative value of interview-based studies and ethnographic studies defending the particular strengths of interviewing. This is a must-read article for anyone seriously engaging in qualitative research!

Pugh, Allison J. 2013. “What Good Are Interviews for Thinking about Culture? Demystifying Interpretive Analysis.” American Journal of Cultural Sociology 1(1):42–68. Another defense of interviewing written against those who champion ethnographic methods as superior, particularly in the area of studying culture. A classic.

Rapley, Timothy John. 2001. “The ‘Artfulness’ of Open-Ended Interviewing: Some considerations in analyzing interviews.” Qualitative Research 1(3):303–323. Argues for the importance of “local context” of data production (the relationship built between interviewer and interviewee, for example) in properly analyzing interview data.

Weiss, Robert S. 1995. Learning from Strangers: The Art and Method of Qualitative Interview Studies . New York: Simon and Schuster. A classic and well-regarded textbook on interviewing. Because Weiss has extensive experience conducting surveys, he contrasts the qualitative interview with the survey questionnaire well; particularly useful for those trained in the latter.

• I say “normally” because how people understand their various identities can itself be an expansive topic of inquiry. Here, I am merely talking about collecting otherwise unexamined demographic data, similar to how we ask people to check boxes on surveys. ↵
• Again, this applies to “semistructured in-depth interviewing.” When conducting standardized questionnaires, you will want to ask each question exactly as written, without deviations! ↵
• I always include “INT” in the number because I sometimes have other kinds of data with their own numbering: FG#001 would mean the first focus group, for example. I also always include three-digit spaces, as this allows for up to 999 interviews (or, more realistically, allows for me to interview up to one hundred persons without having to reset my numbering system). ↵

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

A document listing key questions and question areas for use during an interview.  It is used most often for semi-structured interviews.  A good interview guide may have no more than ten primary questions for two hours of interviewing, but these ten questions will be supplemented by probes and relevant follow-ups throughout the interview.  Most IRBs require the inclusion of the interview guide in applications for review.  See also interview and  semi-structured interview .

A data-collection method that relies on casual, conversational, and informal interviewing.  Despite its apparent conversational nature, the researcher usually has a set of particular questions or question areas in mind but allows the interview to unfold spontaneously.  This is a common data-collection technique among ethnographers.  Compare to the semi-structured or in-depth interview .

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

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

Follow-up questions used in a semi-structured interview  to elicit further elaboration.  Suggested prompts can be included in the interview guide  to be used/deployed depending on how the initial question was answered or if the topic of the prompt does not emerge spontaneously.

A form of interview that follows a strict set of questions, asked in a particular order, for all interview subjects.  The questions are also the kind that elicits short answers, and the data is more “informative” than probing.  This is often used in mixed-methods studies, accompanying a survey instrument.  Because there is no room for nuance or the exploration of meaning in structured interviews, qualitative researchers tend to employ semi-structured interviews instead.  See also interview.

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

An interview variant in which a person’s life story is elicited in a narrative form.  Turning points and key themes are established by the researcher and used as data points for further analysis.

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

Qualitative vs Quantitative Research Methods & Data Analysis

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

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

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

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

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

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

On This Page:

What Is Qualitative Research?

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

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

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

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

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

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

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

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

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

Qualitative Methods

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

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

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

Here are some examples of qualitative data:

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

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

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

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

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

Qualitative Data Analysis

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

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

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

Key Features

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

Limitations of Qualitative Research

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

Advantages of Qualitative Research

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

What Is Quantitative Research?

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

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

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

Quantitative Methods

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

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

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

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

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

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

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

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

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

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

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

Quantitative Data Analysis

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

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

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

Limitations of Quantitative Research

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

Advantages of Quantitative Research

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

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

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

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

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

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

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

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

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

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

Further Information

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

• Politics & Social Sciences
• Social Sciences

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Introduction to Qualitative Research Methods: The Search for Meaning Subsequent Edition

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• Language English
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• Publisher ‏ : ‎ Wiley-Interscience; Subsequent edition (October 1, 1984)
• Language ‏ : ‎ English
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Robert Bogdan grew up in the Bronx and attended the University of Maine in Orono. After serving as a Peace Corps volunteer in Nigeria (1964-1966) he went to graduate school in sociology. He joined the faculty at Syracuse University in 1971. He has won many awards for his writing and teaching including an honorary doctorate degree from Stockholm University. Bogdan is a Distinguished Professor Emeritus of Social Science and Education at Syracuse University. After teaching for 35 years at Syracuse he retired to rural Vermont where he writes about real photo postcards, photography, disability and research methods.

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• Research paper

Writing a Research Paper Introduction | Step-by-Step Guide

Published on September 24, 2022 by Jack Caulfield . Revised on September 5, 2024.

The introduction to a research paper is where you set up your topic and approach for the reader. It has several key goals:

• Present your topic and get the reader interested
• Provide background or summarize existing research
• Position your own approach
• Detail your specific research problem and problem statement
• Give an overview of the paper’s structure

The introduction looks slightly different depending on whether your paper presents the results of original empirical research or constructs an argument by engaging with a variety of sources.

The five steps in this article will help you put together an effective introduction for either type of research paper.

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Table of contents

Step 1: introduce your topic, step 2: describe the background, step 3: establish your research problem, step 4: specify your objective(s), step 5: map out your paper, research paper introduction examples, frequently asked questions about the research paper introduction.

The first job of the introduction is to tell the reader what your topic is and why it’s interesting or important. This is generally accomplished with a strong opening hook.

The hook is a striking opening sentence that clearly conveys the relevance of your topic. Think of an interesting fact or statistic, a strong statement, a question, or a brief anecdote that will get the reader wondering about your topic.

For example, the following could be an effective hook for an argumentative paper about the environmental impact of cattle farming:

A more empirical paper investigating the relationship of Instagram use with body image issues in adolescent girls might use the following hook:

Don’t feel that your hook necessarily has to be deeply impressive or creative. Clarity and relevance are still more important than catchiness. The key thing is to guide the reader into your topic and situate your ideas.

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This part of the introduction differs depending on what approach your paper is taking.

In a more argumentative paper, you’ll explore some general background here. In a more empirical paper, this is the place to review previous research and establish how yours fits in.

Argumentative paper: Background information

After you’ve caught your reader’s attention, specify a bit more, providing context and narrowing down your topic.

Provide only the most relevant background information. The introduction isn’t the place to get too in-depth; if more background is essential to your paper, it can appear in the body .

Empirical paper: Describing previous research

For a paper describing original research, you’ll instead provide an overview of the most relevant research that has already been conducted. This is a sort of miniature literature review —a sketch of the current state of research into your topic, boiled down to a few sentences.

This should be informed by genuine engagement with the literature. Your search can be less extensive than in a full literature review, but a clear sense of the relevant research is crucial to inform your own work.

Begin by establishing the kinds of research that have been done, and end with limitations or gaps in the research that you intend to respond to.

The next step is to clarify how your own research fits in and what problem it addresses.

Argumentative paper: Emphasize importance

In an argumentative research paper, you can simply state the problem you intend to discuss, and what is original or important about your argument.

Empirical paper: Relate to the literature

In an empirical research paper, try to lead into the problem on the basis of your discussion of the literature. Think in terms of these questions:

• What research gap is your work intended to fill?
• What limitations in previous work does it address?
• What contribution to knowledge does it make?

You can make the connection between your problem and the existing research using phrases like the following.

Now you’ll get into the specifics of what you intend to find out or express in your research paper.

The way you frame your research objectives varies. An argumentative paper presents a thesis statement, while an empirical paper generally poses a research question (sometimes with a hypothesis as to the answer).

Argumentative paper: Thesis statement

The thesis statement expresses the position that the rest of the paper will present evidence and arguments for. It can be presented in one or two sentences, and should state your position clearly and directly, without providing specific arguments for it at this point.

Empirical paper: Research question and hypothesis

The research question is the question you want to answer in an empirical research paper.

Present your research question clearly and directly, with a minimum of discussion at this point. The rest of the paper will be taken up with discussing and investigating this question; here you just need to express it.

A research question can be framed either directly or indirectly.

• This study set out to answer the following question: What effects does daily use of Instagram have on the prevalence of body image issues among adolescent girls?
• We investigated the effects of daily Instagram use on the prevalence of body image issues among adolescent girls.

If your research involved testing hypotheses , these should be stated along with your research question. They are usually presented in the past tense, since the hypothesis will already have been tested by the time you are writing up your paper.

For example, the following hypothesis might respond to the research question above:

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The final part of the introduction is often dedicated to a brief overview of the rest of the paper.

In a paper structured using the standard scientific “introduction, methods, results, discussion” format, this isn’t always necessary. But if your paper is structured in a less predictable way, it’s important to describe the shape of it for the reader.

If included, the overview should be concise, direct, and written in the present tense.

• This paper will first discuss several examples of survey-based research into adolescent social media use, then will go on to …
• This paper first discusses several examples of survey-based research into adolescent social media use, then goes on to …

Scribbr’s paraphrasing tool can help you rephrase sentences to give a clear overview of your arguments.

Full examples of research paper introductions are shown in the tabs below: one for an argumentative paper, the other for an empirical paper.

• Argumentative paper
• Empirical paper

Are cows responsible for climate change? A recent study (RIVM, 2019) shows that cattle farmers account for two thirds of agricultural nitrogen emissions in the Netherlands. These emissions result from nitrogen in manure, which can degrade into ammonia and enter the atmosphere. The study’s calculations show that agriculture is the main source of nitrogen pollution, accounting for 46% of the country’s total emissions. By comparison, road traffic and households are responsible for 6.1% each, the industrial sector for 1%. While efforts are being made to mitigate these emissions, policymakers are reluctant to reckon with the scale of the problem. The approach presented here is a radical one, but commensurate with the issue. This paper argues that the Dutch government must stimulate and subsidize livestock farmers, especially cattle farmers, to transition to sustainable vegetable farming. It first establishes the inadequacy of current mitigation measures, then discusses the various advantages of the results proposed, and finally addresses potential objections to the plan on economic grounds.

The rise of social media has been accompanied by a sharp increase in the prevalence of body image issues among women and girls. This correlation has received significant academic attention: Various empirical studies have been conducted into Facebook usage among adolescent girls (Tiggermann & Slater, 2013; Meier & Gray, 2014). These studies have consistently found that the visual and interactive aspects of the platform have the greatest influence on body image issues. Despite this, highly visual social media (HVSM) such as Instagram have yet to be robustly researched. This paper sets out to address this research gap. We investigated the effects of daily Instagram use on the prevalence of body image issues among adolescent girls. It was hypothesized that daily Instagram use would be associated with an increase in body image concerns and a decrease in self-esteem ratings.

The introduction of a research paper includes several key elements:

• A hook to catch the reader’s interest
• Relevant background on the topic
• Details of your research problem

and your problem statement

• A thesis statement or research question
• Sometimes an overview of the paper

Don’t feel that you have to write the introduction first. The introduction is often one of the last parts of the research paper you’ll write, along with the conclusion.

This is because it can be easier to introduce your paper once you’ve already written the body ; you may not have the clearest idea of your arguments until you’ve written them, and things can change during the writing process .

The way you present your research problem in your introduction varies depending on the nature of your research paper . A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement .

A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis —a prediction that will be confirmed or disproved by your research.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Caulfield, J. (2024, September 05). Writing a Research Paper Introduction | Step-by-Step Guide. Scribbr. Retrieved September 26, 2024, from https://www.scribbr.com/research-paper/research-paper-introduction/

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An Introduction to Qualitative Inquiry

Catherine r. butler.

1 Division of Nephrology and Kidney Research InstituteUniversity of WashingtonSeattle, Washington

2 Veterans Affairs Health Services Research & Development Center of Innovation for Veteran-Centered and Value-Driven CareVA Puget Sound Health Care SystemSeattle, Washington

Ann M. O’Hare

Bryan r. kestenbaum, george g. sayre, susan p.y. wong.

Many aspects of care for people with kidney disease cannot be meaningfully understood in numerical terms, and benefit from a qualitative approach to inquiry. Qualitative methodologies were originally developed in the social sciences, but are increasingly used in medical research to address questions related to people's lived experiences of illness and care, the meanings they attribute to these experiences, and how health care processes and systems function. 1 In the nephrology literature, qualitative work has helped to identify those health outcomes that matter most to people with kidney disease and their families, 2 which has informed the design and testing of clinical interventions. Other studies have shed light on complex health care processes, such as kidney transplant donation 3 and medical decision making, 4 helping to identify targets for process improvement. Qualitative work may also offer a view into the lives of people with kidney disease, 5 which supports clinicians in better understanding, communicating with, and caring for this group.

Qualitative methods can be quite distinct from the quantitative methodologic approaches that are more familiar to many clinicians and members of the kidney research community. To help readers better understand and critically appraise qualitative work, we describe the key features of this approach and compare these with methodologic techniques and concepts in quantitative research ( Table 1 ).

Key concepts and terms in quantitative and qualitative methods

Qualitative research uses non-numeric naturalistic data ( e.g. , interviews, field notes, images, and documents) to construct rich description and/or explanatory frameworks that can deepen our understanding of complex phenomena. 1 To support this in-depth inquiry, subject recruitment, data collection, and interpretation typically occur simultaneously. Study subjects are selected according to the likelihood they will provide useful information on the phenomenon of interest (known as purposive sampling). 6 As data are collected, analysis begins with a process of coding in which the researcher identifies and names the concepts that appear in the data. 7 Preliminary analysis of data gathered from early subjects informs recruitment and data collection for later subjects with whom emerging concepts are probed more fully. Concepts are examined for inter-relationships and assembled into a theoretical framework that advances understanding of the phenomenon.

Where Is the Hypothesis?

Under a deductive approach to scientific inquiry, researchers begin with a theoretical understanding of a phenomenon, then design a hypothesis-based experiment that can support or oppose this theory. However, what can be learned from these kinds of studies is inherently constrained by this predetermined theory. This feature can be a major limitation when investigating complex or poorly described phenomena. In these situations, framing the study around a narrow question of uncertain relevance to the phenomenon of interest can result in a superficial, incomplete, or distorted understanding of the data.

Qualitative inquiry supports discovery or new perspectives on phenomena when existing theory describing these phenomena is inadequate or absent. To this end, qualitative work tends to be inductive, that is, research questions are intentionally open ended to allow the researcher to collect information even when its relevance to understanding the phenomenon of interest may have been unforseen. 8 Rather than investigate a predetermined theory through hypothesis testing, inductive inquiry aims to build a conceptual understanding of the phenomenon as this emerges directly from review of the data. A range of qualitative approaches are available to address research questions that are more or less open ended versus narrowly targeted.

In quantitative research, key elements of study design, such as the recruitment and analytic plan, are typically specified in advance. This approach is needed to avoid ad hoc changes to these parameters that may violate statistical assumptions.

Researchers conducting inductive qualitative work assume that at the beginning of the study, they do not know enough about the phenomenon of interest to be able to specify what data may be salient. Qualitative methodology is thus designed to support an iterative approach to recruitment and analysis in which formative steps inform later steps. 7 , 8 Subjects are intentionally chosen on the basis of characteristics ( e.g. , age, race, diagnosis, relationships, and roles) that make it likely that their experiences and perspectives will enhance the researchers’ understanding of the phenomenon of interest. As this understanding grows, subsequent purposive sampling and analysis is tailored to fill conceptual gaps or clarify aspects of an emerging conceptual framework.

The amount of information represented in a qualitative study tends to be driven by the density of concepts in the data, rather than by the number of subjects per se . Data collection is considered complete when the analysis reaches thematic saturation, that is, the point at which further sampling yields little new information about the phenomenon. 8 A relatively small number of subjects may be sufficient to construct a detailed and coherent description or explanatory framework. Although the number and types of subjects needed to reach saturation cannot be known in advance, for study planning purposes ( e.g. , institutional review board proposals, grant applications), researchers may estimate these parameters on the basis of experience with similar studies.

In many quantitative studies, inferential tests are used to judge the likelihood that study findings apply to the source population from which the sample was selected and inclusion of large numbers of participants generally support this possibility. Study findings may be considered more broadly generalizable if the study population is sufficiently representative of other groups or persons experiencing the condition under investigation.

It is not uncommon for qualitative studies to be conducted among a small group of subjects in a narrowly defined context. However, these features, which could limit the generalizability of quantitative study results, are not typically what determines the external relevance or value of qualitative study findings. A conceptual framework may be useful for understanding related phenomena among a different or broader group (a property known as transferability 6 ) if the studied and external settings share core features that contribute to this conceptual framework.

For example, in her ethnographic work to understand decision making among 27 terminally ill patients in San Francisco, the anthropologist Sharon Kaufman describes how the hospital system itself “organizes and constrains choice making.” 4 This conceptual framework has broad relevance beyond the specific population, context, and even phenomenon studied, not because the study sample is representative of these, but because the concept of hospital processes and culture shaping patients’ decision making may be relevant to understanding other instances of decision making in clinical contexts.

However, it is also important to recognize that the primary purpose of most qualitative work is to generate theory and/or provide rich contextual description, not to test the validity of study findings in other populations or contexts. 8 Rather, it is expected that the theoretical understanding of a phenomenon resulting from qualitative study will be expanded, deepened, and/or modified when applied to other contexts. Well-developed theoretical models can also provide a strong foundation for hypothesis formulation and quantitative testing.

Regardless of the methodology, researchers must strive to employ strategies in study design, data collection, and analysis to guard against their own biases. Approaches to support objectivity in quantitative research focus on limiting the ways in which the researcher is allowed to interact with the data ( e.g. , prespecified analytic plan), segregating the researcher from the data ( e.g. , double blinding), and ensuring study results are replicable.

Constructing theory and identifying meaning in qualitative analyses necessitate close interaction with the data, and it is understood that results will be a product of the researcher’s own interpretation. Instead of attempting to extract themselves from the analytic process, researchers engaged in qualitative work are trained to explicitly recognize, consider, and acknowledge their own perspectives and how these might shape their interpretation of the data. The backgrounds and relevant experiences of the researchers are typically reported in the methods sections of qualitative studies so that readers can take these factors into consideration as they review the study. 9 Results of different qualitative analyses of the same data may vary depending on who is conducting the research, and are thus not expected to be replicable. This subjectivity reflects the reality that complex phenomena can be understood in different ways, all of which may be conceptually valuable.

Multiple methodologic approaches have been developed to ensure that the findings of qualitative analyses reflect the authentic perspectives of study subjects or features of the source data. 6 Researchers introspectively monitor for how their perspectives may shape emerging themes and intentionally challenge assumptions that may have arisen from their own experience. During analysis, emerging themes are repeatedly checked against the original data to ensure findings are grounded in these data. 10 Multiple members of the research team may participate in data collection and coding to support the likelihood that results are not the product of any one researcher’s expectations, biases, or perspectives. Techniques such as member checking, in which preliminary results are returned to study participants to confirm that the findings resonate with their experiences, may provide further reassurance that study findings accurately capture their perspectives. The trustworthiness of these findings is also increased when similar or related conclusions arise from work conducted in other populations or settings, by different researchers, and/or using alternative methodologies (known as triangulation). 1

Although quantitative and qualitative approaches to scientific inquiry evolved to support the analysis of different kinds of data, these approaches can be highly complementary and mutually reinforcing. The diversity and complexity of scientific questions in health care calls for a range of methodologic tools, and learning how to integrate the results of qualitative research into our evidence base will help to advance knowledge and improve the care of people with kidney disease.

Disclosures

A. O'Hare having reports consultancy agreements with the Pathways Project (supported by a grant from the Moore foundation to the Coalition for the Supportive Care of Kidney Patients); reports receiving research funding from the Centers for Disease Control and Prevention, National Institutes of Health, and Veterans Affairs Health Services Research & Development; reports receiving honoraria from Chugai Pharmaceutical Co. Ltd., the Coalition for the Supportive Care of Kidney Patients, Dialysis Clinics Inc., Fresenius Medical Care, Fondation Devenir, Hammersmith Hospital, the Japanese Society of Dialysis Therapy, Kaiser Permanente Southern California, University of California San Francisco, University of Pennsylvania, and UpToDate; reports being a scientific advisor or member as the Associate Editor for American Journal of Kidney Diseases, on the Editorial Board of Advances in Kidney Disease and the Editorial Board for Journal of the American Medical Association Internal Medicine, on the external advisory panel to the National Institute of Diabetes and Digestive and Kidney Diseases for the Chronic Renal Insufficiency Cohort (CRIC) study, as Technical Expert Panel, Member of the Coalition for the Supportive Care of Kidney Patients, and Member of the United States Renal Data System Steering Committee. S. Wong reports receiving honoraria from the CRIC study Opportunity Pool Program; reports being a scientific advisor or member of the Editorial Board of Journal of the American Geriatrics Society and the Editorial Board of Clinical Journal of the American Society of Nephrology. All remaining authors have nothing to disclose.

Acknowledgments

C. Butler, A. O’Hare, B. Kestenbaum, G. Sayre, and S. Wong conceptualized the study and reviewed and edited the manuscript; C. Butler was responsible for project administration and wrote the original draft; and A. O’Hare and S. Wong provided supervision.

Published online ahead of print. Publication date available at www.jasn.org .

Patients’ experiences with ‘sludge’ (administrative burden) in the cancer screening process and its relationship with screening completion, experience and health system distrust

Author affiliations

Brianna Chang 3

Vivian Zagarese 4

Jamie K Turner 5 6

Ally Southworth 5

YingXing Wu 7

Paul Yeaton 8

Jeffrey S Stein 10

Sarah H Parker 4

John W Epling 1 2

Objective ‘Sludge’ refers to administrative burdens or frictions that preclude people from getting what they want or need (eg, duplicative forms, complicated instructions, long waiting times). This mixed methods study evaluated patients’ perceptions of sludge in the colorectal cancer (CRC) screening process and some impacts of this sludge.

Design We employed an exploratory sequential mixed methods study design that comprised patient interviews and a patient survey. The interviews informed final survey revisions and captured contextual data about patients’ experiences with sludge. Interview transcripts were inductively and deductively analysed to identify overarching themes. The survey quantified sludge, delayed or forgone screenings, screening experience (Net Promoter Score) and health system distrust (Health System Distrust Scale). We used χ 2 or t-tests for univariable comparisons and logistic or linear regressions to evaluate the association between cumulative sludge score and delayed or forgone screenings, screening experience and health system distrust. Results were integrated for interpretation.

Setting Southeastern United States.

Participants Patients who were 45–75 years of age, at average risk for CRC and had either completed or been referred for CRC screening (colonoscopy or stool-based test) within the previous 12 months.

Results 22 interview participants and 255 survey participants completed the study. 38 (15%) survey participants rated their screening experience as poor (Net Promoter Score=0–7 out of 10). The mean (SD) Health System Distrust Scale score was 22.4 (6.3) out of 45 possible points (higher score=greater distrust). Perceptions of sludge in the CRC screening process varied, with long waiting times and burdensome communication being the most common sources (58% and 35% of participants, respectively). Sludge was positively associated with delayed or forgone screenings (OR=1.42, 95% CI 1.28, 1.57, p<0.001), poor screening experience (OR=1.15, 95% CI 1.04, 1.28, p=0.009) and health system distrust (β=0.47, p<0.001). Qualitative findings add descriptive detail about sludge encountered, context to impacts experienced, and illustrate the heavy emotional impact of sludge: ‘ it just isn’t worth it’ .

Conclusion Efforts to reduce sludge in the CRC screening process may improve timely completion of CRC screening, enhance patient experience and restore trust in the health system.

What is already known on this topic

Administrative burden is ubiquitous in healthcare. The administrative burden that precludes or delays healthcare delivery can be described as ‘sludge’. Although there are numerous calls to reduce the sludge that clinicians and patients experience in healthcare processes, patients’ experiences with healthcare sludge have not been well described.

What this study adds

This study illuminates patients’ self-reported experience with sludge encountered in the colorectal cancer (CRC) screening process in the Southeastern United States. Sludge was associated with delayed or forgone screenings, poor experience and health system distrust. Participants with socioeconomic disadvantage experienced disproportionate sludge.

How this study might affect research, practice or policy

Study findings highlight numerous opportunities to improve CRC screening rates and enhance patient experience through clinical, operational and policy-level efforts to reduce sludge and streamline the care transitions associated with CRC screening.

• Introduction

With more than 2 million new cases diagnosed annually, colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. 1 Screening can play an important role in the prevention and early detection of CRC, but a significant number of individuals fail to receive timely screening. For example, in the USA, over 55 million individuals are eligible for CRC screening but have not received it. 2 Further efforts are needed to identify approaches for improving access to and completion of CRC screening.

Previous research suggests that ‘sludge’ is an underexplored barrier to the completion of CRC screening. 3 4 A behavioural economics term popularised by Harvard Law professor and author, Cass Sunstein, sludge describes administrative burdens or frictions that prevent people from achieving their goals. 5 Examples of sludge include redundant paperwork, complicated or inconsistent instructions, cumbersome communication and long waiting times. 6 As a complex, multistep pathway involving several screening test options (eg, colonoscopy, stool-based tests, flexible sigmoidoscopy), variable testing intervals and multiple care transitions (eg, primary care to gastroenterology to screening facility), the CRC screening process may be particularly prone to sludge. Although the impact of sludge on patients is not well recognised in the literature, there is evidence that patients may delay or forgo recommended care as a result of sludge, especially when they are in poor health. 4 7 8 In addition, sludge can contribute to psychological distress, confusion and anger and there is some evidence that sludge decreases trust. 9 10 Importantly, sludge may disproportionately impact disadvantaged patients, which can widen health and healthcare disparities. 10–12

There are multiple calls to reduce sludge in healthcare, 13–19 including the National Health Service Bureaucracy Busting Concordat 20 and the American Medical Association’s campaign for Getting Rid of Stupid Stuff . 21 Improved understanding of patients’ experiences with sludge is needed to respond to such calls through clinical, operational and policy-level efforts to improve the CRC screening process and enhance screening rates. Thus, the purpose of this mixed methods study was to evaluate patients’ experiences with sludge in the CRC screening process and to explore some impacts of this sludge. We hypothesised that sludge in the CRC screening process is: (a) common; (b) related to delayed or forgone screenings, poor screening experience and health system distrust; and (c) differentially experienced by patients living in rural areas and with socioeconomic disadvantage.

Using an exploratory sequential mixed methods study design, 22 we conducted a qualitative interview of patients who had recently engaged in the CRC screening process, followed by a quantitative survey of a second group of patients who had recently engaged in the CRC process. The semistructured interviews informed refinements to the patient survey and offered contextual insight into patients’ experiences with sludge in the CRC screening process. The survey quantified patient-reported sludge in the CRC screening process and evaluated the relationship between this sludge and delayed or forgone screenings, screening experience and health system distrust.

Informed consent was provided by participants before beginning the study. The Strengthening the Reporting of Observational Studies in Epidemiology for cross-sectional studies, 23 the Consolidated Criteria for Reporting Qualitative Research 24 and Advancing the Reporting of Mixed Methods Studies 22 checklists guided our research and the development of this report. The following abbreviations are used in the results: primary care provider (PCP), faecal immunochemical test (FIT), FIT-DNA test (Cologuard).

Participants and setting

This study was conducted in southwest and south-central Virginia where the CRC screening rate is the lowest and CRC incidence is the highest in the state. 25 26 Interview and survey participants were mutually exclusive groups of patients who were 45–75 years of age, had either completed or been referred for CRC screening (colonoscopy or stool-based test) at a health system, centre or practice in southwest or south-central Virginia within the previous 12 months, and had no history of gastrointestinal cancer or inflammatory bowel disease (at any point) or gastrointestinal pain or rectal bleeding within the past 12 months. Participants were compensated via gift cards.

Study procedures are shown in figure 1 .

Overview of exploratory sequential mixed methods study design.

Prospective participants, identified via health system records or recruited via targeted regional social media posts, were invited to screen for eligibility to participate in a semistructured interview focused on their experience with CRC screening by completing a brief online screening instrument administered via REDCap. 27 Eligible participants were enrolled, consented and engaged in one approximately 60 min interview session with a researcher (BC) via video chat or in person in a private office space. The interview guide is included in online supplemental file 1 . Additional information for the qualitative procedures is included in online supplemental file 2 .

During Part 1 of the interview, participants completed a pilot version of the survey, pausing at designated points to provide feedback on the structure, format and clarity of survey questions and instructions. Participants then responded to the researcher’s open-ended questions during Part 2 of the interview, beginning with a request to share a detailed account of their recent experience with the CRC screening process and followed by prompts to elicit further details about sludge in the screening process, and if applicable, their response to any sludge experienced. The researcher kept field notes during both parts of the interviews and continued interviews until thematic saturation was achieved. Interviews were audio recorded and later transcribed for analysis. Transcript feedback was not elicited from participants.

Using the same eligibility criteria described in the previous section, patients were invited to participate in a survey about their experience with the CRC screening process ( online supplemental file 3 ). Developed by the research team and iteratively refined through collaborative work sessions, community engagement studios, 28 internal pilot testing and participant feedback during interview Part 1, the survey consisted of original and previously validated questions focused on sludge, screening experience and health system distrust. A summary of the survey development and evaluation process is included in online supplemental file 4 .

To evaluate sludge, participants were asked about their experience with administrative burdens that felt excessive or unnecessary during their CRC screening process (defined as beginning when a healthcare provider recommended screening and ending when the provider and the patient both receive results). Participants who had not completed the screening were asked to respond based on whatever portion of the process they had completed. Informed by previous work, 3 7 8 we specifically asked participants to quantify (on a 0–100 sliding scale) the amount of paperwork, communication, technology and waiting that felt excessive or unnecessary during the CRC screening process, with several examples provided for each ( online supplemental file 3 ). Two categories were assigned for waiting based on participant feedback offered throughout the survey refinement process (including interview Part 1). ‘Waiting–passive’ represented a delay or period of time during which the patient was waiting for a step in the CRC screening process to occur, but during which their time was not occupied (eg, waiting to be called to schedule a colonoscopy appointment, waiting for the appointment to occur, waiting to receive results), whereas ‘waiting–active’ represented the time, typically on-site in a healthcare facility, when patients were waiting for something to occur and during which they were not available to do something else (eg, in a waiting room). We calculated a cumulative sludge score by summing the sliding scale ratings for each sludge type for a potential score of 500. Participants were also asked in which phase(s) of the screening process (referral, scheduling, preparing, the test itself, acquiring results) they experienced each type of sludge.

To evaluate the impact of sludge on patients, we assessed three outcomes: delayed or forgone screenings, screening experience and health system distrust. Informed by the work of Kyle and Frakt, 8 we assessed delayed or forgone screenings via two questions: Was your colorectal cancer screening test delayed due to excessive or unnecessary administrative burden? and Did you skip your colorectal cancer screening test due to excessive or unnecessary administrative burden? We used the single-item Net Promoter Score (NPS) 29 ( How likely would you be to recommend this screening process to a close friend or family member? ), with 0 indicating not at all likely and 10 indicating extremely likely to assess ratings of screening experience and the Healthcare System Distrust Scale (HSDS) 30 to assess overall health system distrust.

General demographics and CRC screening characteristics (eg, type of screening test) were also collected. We used the US Department of Agriculture Rural-Urban Commuting Area codes to determine rurality. 31 Based on a priori power analysis showing that a sample size of 234 participants was needed to show a moderate effect size at the 0.05 level, we aimed to recruit 250 participants in anticipation of incomplete surveys.

Data analysis

Interview analysis.

For interview Part 1, one researcher (MR) listened to audio recordings of interviews, summarising potential survey modifications that emerged from participants’ feedback. This summary was combined with the interviewer’s field notes and reviewed with the senior author (JWE) to inform minor survey edits. For interview Part 2, interviews were auto transcribed using Microsoft Teams, with two researchers (JT and MR) manually verifying accuracy. Transcripts were uploaded to NVivo (QSR International, Melbourne, Australia) for analysis.

The qualitative analysis team used reflexive thematic analysis to identify and interpret themes that emerged from the data. 32 To obtain a codebook that included different perspectives, four researchers analysed transcripts, with VZ and AS using an inductive approach (emerging themes) and JT and EO using a deductive approach informed by themes identified in community engagement studios and our prior work. 3 Through an iterative, multiphase process, the codebooks were consolidated and refined to focus on participants’ experiences with sludge in the CRC screening process and their response to this sludge. We used Cohen’s kappa to assess coder agreement, with the average agreement among all four coders being 0.69 (moderate agreement). 33 The final output was a table of interview themes and exemplary quotations in online supplemental file 5 .

Survey analysis

Continuous variables were summarised using either the mean with SD or the median with IQR, while categorical variables were presented as percentages. Strata for cumulative sludge scores (≤25 and >25) and NPS (0–7 and 8–10) were determined via visual inspection of data distributions. We conducted univariable comparisons using t-tests (or Wilcoxon two-sample tests) and analysis of variance (or Kruskal-Wallis tests) for continuous variables and χ 2 tests (or Fisher’s exact tests) for categorical variables. The association between the cumulative sludge score and primary outcome variables (delayed or forgone screenings, screening experience, distrust) was evaluated using linear and logistic regressions with the following candidate variables included in the regressions: cumulative sludge score, age group, gender, race, rurality, insurer, screening status and screening type. Ethnicity was not included in the analysis due to the limited number of Hispanic/Latino participants. To assess the contribution of each sludge type, we ran additional exploratory regressions with individual sludge-type subscores retained without variable selection. Statistical analyses were performed using R V.4.2 ( https://cran.r-project.org/ ).

Integrated data analysis

To complement the research team’s interpretation of interview and survey results, we invited 16 professionals with expertise in CRC screening, behavioural economics, health equity, healthcare operations, health policy and/or patient advocacy to serve on an external expert panel. Panellists independently reviewed summaries of interview themes and survey results and responded to a structured online survey ( online supplemental file 6 ). Research team members were presented with interview and survey results and expert panel responses. The senior author (JWE) guided collaborative discussions to identify areas of convergence, complementarity or dissonance in the data and to come to consensus on key findings.

A total of 22 participants (mean (SD) age: 55.4 (9.2) years, 64% women) engaged in interviews, while 262 participants completed surveys (67% response rate) ( table 1 ). Seven survey responses were omitted since they were less than 80% complete, leaving a final sample of 255 (mean (SD) age: 58.2 (8.4) years, 65% women). 34 Demographic characteristics of the interview and survey cohorts are representative of the southwest and south-central Virginia regions. Below, we weave survey results with key themes and exemplary quotes from open-ended survey responses and the thematic analysis of interviews. 24

Sludge in the CRC screening process

Most survey participants (n=178, 70%) experienced excessive or unnecessary administrative burdens or frictions during the CRC screening process (sludge score >25). Cumulative sludge scores ranged from 0 to 355 out of 500 possible points, with mean (SD) of 95.1 (89.2) and median (IQR) of 68 (16, 157). Waiting–passive was the most common type of sludge experienced, followed by waiting–active, communication, paperwork and technology ( table 2 ).

Cumulative sludge score varied by screening completion status (completed—median (IQR): 51 (12, 129) vs not completed—154 (70, 215), p<0.001); interview participants described feeling relieved or ‘ better about all the hassle ’ after the test was over. Sludge was reported in all phases of the CRC screening process but varied by screening phase and screening type ( figure 2 ). Survey participants who had completed screening reported sludge in 0 (43%), 1 (24%), 2 (18%), 3 (11%) or ≥4 (4%) phases, with scheduling the screening test as the most common (41%). Interview participants described missed calls, voicemails and ‘ a never-ending game of phone tag ’ during scheduling.

Types of sludge reported in each phase of the colorectal cancer screening process (colonoscopy and stool-based tests). The cumulative sludge score was higher for colonoscopy (median 76 (IQR 25,166)) than stool-based tests (median 48 (IQR 9, 150)) (p<0.05). IT, information technology.

Participants who had stool-based tests described confusion, ranging from ‘ not clear’ to ‘ utter chaos’ around multiple phases of the process. They found that instructions were inconsistent or incomplete, difficult to understand and that there were forms they needed but did not have. Some described challenges with scheduling a time to pick up their test kit. Others reported that they never received results and, in some cases, that their ordering clinician did not receive results either.

You have to go to some other place to pick up the special testing kit or else your insurance won’t cover it. I don’t have time to mess with going to yet another place. …I didn’t understand what to do so I just threw it in the trash. I did not understand the directions for Cologuard. It says it is easy but there were like 10 steps, and I had no clue what to do. They literally lost my poop card in the mail. WTF?

Cumulative sludge score was significantly higher for participants with Medicaid or dual Medicare-Medicaid (median (IQR): 79 (36, 169)) versus other payers (median (IQR): 60 (23, 126)) (p=0.048), but did not differ by other demographics ( online supplemental file 7 ). Reports of sludge related to financial processes were common.

…can’t figure out how to use my insurance website to know if this will be covered without my daughter’s help. I keep worrying about all those forms you have to turn in because if I do it wrong, they are going to mess up and charge me—that always happens—and I don’t have time to deal with it and I can’t pay for it. …getting all the billing stuff straightened out every single time…well, it just isn’t worth it.

Some participants perceived inequality in the waiting time for colonoscopy, stating that ‘ it’s all about who you know’ and ‘ whether or not your doctor is part of their system’ that determines waiting time. Others perceived profit-motivated drivers of sludge in the screening process.

They take anyone with the best insurance first, so they make more money. …no way that someone poor like me is going to make it to the top of the wait list no matter what my risk is because they say that Medicaid and Medicare don’t pay them good.

There were a few examples of participants misunderstanding the concept of administrative burden or sludge. Some misattributed the high cost of care, having to complete the colonoscopy prep, and concern about anaesthesia to sludge.

Impact of sludge in the CRC screening process on patients

Delayed or forgone screenings, poor experience and health system distrust.

81 (37%) of survey participants indicated that their CRC screening test was delayed or forgone due to excessive or unnecessary paperwork, communication, technology or waiting. 38 (15%) survey participants rated their experience as poor (NPS of 0–7 out of 10). The mean (SD) for HSDS was 22.4 (6.3) out of 45 possible points (higher score=greater distrust). Variation in outcomes by demographic and screening characteristics is included in online supplemental file 7 .

Compared with survey participants who reported sludge in the CRC screening process, those who reported no sludge or very minimal sludge (cumulative sludge score ≤25) had a lower proportion of delayed or forgone screenings, fewer poor experience ratings and lower distrust scores ( figure 3 ). In our regression analysis using variable selection ( table 3 ), there was a positive relationship between cumulative sludge score and delayed or forgone screening, poor screening experience and health system distrust. In a separate regression run without variable selection to explore prediction of the outcomes with each type of sludge, there was a positive relationship between cumulative sludge score and delayed or forgone screening, poor screening experience and health system distrust ( table 4 ). Sludge in technology and both waiting variables was associated with delayed or forgone screenings, sludge in communication was associated with poor screening experience and sludge in communication and waiting–passive was associated with health system distrust.

Delayed or forgone screenings (A), poor screening experience (B) and health system distrust (C) in patients who experience no or very minimal sludge versus sludge. Cumulative sludge score ≤25 (n=77), cumulative sludge score >25 (n=178). Overall health system distrust: Healthcare System Distrust Scale (HSDS); the vertical axis shows the maximum possible score. *Mean.

…after a while, you just say forget it. It’s not worth it. I’m not really likely to recommend this process… it’s hard…especially when you work full time…

Participants expressed a general expectation that accessing healthcare is associated with ‘ jumping through multiple hoops’ , ‘ scheduling really far out’ , ‘ being your own advocate’ and resigning to ‘ the broken system’ .

Some participants described factors that mitigated the impact of sludge. For example, family history of CRC, social support and previous experience with CRC screening helped participants persist through sludge. Relationship with a PCP also facilitated the process: ‘ if Dr. [name omitted] wants me to do it, I’m going to do it no matter what’ . In contrast, perceptions of personal risk, mistrust in the health system, previous negative experiences with healthcare and unfamiliarity with the screening process exacerbated the impacts of sludge.

Sludge describes the administrative burdens or bureaucratic ‘red tape’ that patients may face in the process of acquiring healthcare. 6 Understanding patients’ experiences with sludge is crucial to responding to calls for reducing sludge and its harmful sequelae. In this mixed methods study, we found that most participants experienced some degree of sludge in the CRC screening process, with socioeconomically disadvantaged patients experiencing greater sludge. Those who experienced more sludge were more likely to delay or forgo screening, describe their screening experience as poor and report greater distrust in the health system. Given that delaying or forgoing screening increases CRC risk, efforts to reduce sludge may improve CRC screening rates and reduce the morbidity and mortality associated with CRC. Additionally, patient experience is an important component of healthcare quality, 35 and the eroding distrust in the health system is a widespread concern. 36 37 As such, reducing the sludge associated with the CRC screening process represents an opportunity to enhance healthcare quality and take important steps towards restoring trust in the health system.

Our findings align with others’ who have shown that individuals with socioeconomic disadvantage experience more administrative burden and greater negative impacts associated with this burden. 12 38–40 The concept of scarcity has been related to the experience of sludge. 41  Patients with limited resources (eg, finances, time, understanding) and overloaded with stressors may have less capacity to persist through sludge. Thus, reducing sludge may play an important role in reducing socioeconomic disparities in CRC screening and outcomes.

The scale-based outcomes in this study require some additional interpretation. The effect sizes observed for experience and distrust were generally small to moderate, but the qualitative data illustrate the depth of feeling associated with the outcomes. We chose a cut-off for the NPS (experience) that is felt to represent true dissatisfaction, rather than passivity, so even small magnitude findings of a poor experience in this study are meaningful. 29 We also consider any elevation in patients’ distrust of the health system to be important, even if incremental. In addition, we noted a relationship between completion of screening and improved experience and distrust scores, which may be attributable to a form of recall or recency bias affecting respondents’ answers. Since most CRC screening results are reassuring (negative findings), respondents who have completed screening will have had a ‘good’ final outcome and remember the experience as overall less traumatic. Further work in this area could ascertain screening results as additional information to aid analysis.

Subsequent efforts to uncover patients’ experiences with sludge encountered in cancer screening processes and to reduce this sludge may call on existing frameworks 11 42 and sludge reduction efforts in non-healthcare fields 5 43 44 to focus on the following:

Characterising additional impacts of sludge beyond delayed or forgone screenings, poor experience and distrust.

Evaluating the intersection between sludge and other well-recognised barriers to cancer screening (eg, low perception of risk, fear, embarrassment). 45–47

Exploring sludge tolerance (ie, what makes some people resilient throughout sludge-heavy processes while others are more vulnerable?). Our qualitative results suggest several factors that mitigated or intensified sludge.

Refocusing resources dedicated to improving the rate of delivery of preventive services to reducing health system and insurance-related sludge.

Streamlining the coordination of care between primary care and others involved in the cancer screening process.

Tailoring interventions to reduce sludge based on the associations identified in this study. For example, to enhance the patient experience, focusing on innovative communication efforts can keep patients engaged in the screening process as well as minimising perception of inequity or favouritism.

Evaluating messaging and communication methods preferred by patients when waiting times (passive or active) are inevitable.

Evaluating the impact and cost-effectiveness of patient navigator programmes to improve screening rates versus policy and process efforts to reduce sludge. 48 49

Incorporating quality metrics and incentives that promote administrative simplification and sludge reduction.

In the USA, most public and private insurers are required to cover the costs of clinical preventive services graded A or B by the US Preventive Services Task Force, with zero associated out-of-pocket cost to patients, as described in Section 2713 of the Affordable Care Act. 50 However, administration of this requirement is nuanced, can be sludge-laden, may require interaction with insurance companies and sometimes results in patient charges. Based on the burden of healthcare costs to many Americans and the concerns expressed by participants in the present study, assuring that patients are not responsible for out-of-pocket charges for cancer screenings, that there are no additional fees, that insurance-related paperwork and correspondence are minimised and simplified and that the number of uninsured patients is reduced is essential to improving CRC screening adherence, experience and outcomes.

Limitations

Our study had some limitations. Although our participant cohorts were representative of the region and included participants affiliated with multiple health systems, centres and providers, the lack of diversity of our cohort (eg, racial, ethnic, language) and single region studied may limit the generalisability of results. Additionally, we report on the impact of sludge on only three outcome variables based on previous work by our team and others, 3 7 12 although we recognise that sludge likely impacts patients in numerous and potentially overlapping ways. Finally, the NPS, used to evaluate participants’ experience with the CRC screening process, is limited to a single question assessment that may not capture the complexity of decision-making around CRC screening.

There are numerous national calls to reduce the harmful administrative burden—sludge—encountered by patients as they seek recommended healthcare services. In this patient-focused, mixed methods study, sludge in the CRC screening process was positively associated with delayed or forgone screenings, poor screening experience and health system distrust. Participants with socioeconomic disadvantage experienced more sludge and greater impacts of sludge compared with those without socioeconomic disadvantage. Clinical, operational and policy-level efforts to reduce sludge may improve CRC screening rates, reduce disparities, enhance experience and reduce health system distrust.

• Supplementary files
• Publication history
• Rapid Responses