5 types of qualitative research design

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• What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on September 5, 2024 by Pritha Bhandari.

A research design is a strategy for answering your   research question  using empirical data. Creating a research design means making decisions about:

• Your overall research objectives and approach
• Whether you’ll rely on primary research or secondary research
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

You might have to write up a research design as a standalone assignment, or it might be part of a larger   research proposal or other project. In either case, you should carefully consider which methods are most appropriate and feasible for answering your question.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

• Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
• Descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

• Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

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

• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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9.4 Types of qualitative research designs

Learning objectives.

• Define focus groups and outline how they differ from one-on-one interviews
• Describe how to determine the best size for focus groups
• Identify the important considerations in focus group composition
• Discuss how to moderate focus groups
• Identify the strengths and weaknesses of focus group methodology
• Describe case study research, ethnography, and phenomenology.

There are various types of approaches to qualitative research.  This chapter presents information about focus groups, which are often used in social work research.  It also introduces case studies, ethnography, and phenomenology.

Focus Groups

Focus groups resemble qualitative interviews in that a researcher may prepare a guide in advance and interact with participants by asking them questions. But anyone who has conducted both one-on-one interviews and focus groups knows that each is unique. In an interview, usually one member (the research participant) is most active while the other (the researcher) plays the role of listener, conversation guider, and question-asker. Focus groups , on the other hand, are planned discussions designed to elicit group interaction and “obtain perceptions on a defined area of interest in a permissive, nonthreatening environment” (Krueger & Casey, 2000, p. 5).  In focus groups, the researcher play a different role than in a one-on-one interview. The researcher’s aim is to get participants talking to each other,  to observe interactions among participants, and moderate the discussion.

There are numerous examples of focus group research. In their 2008 study, for example, Amy Slater and Marika Tiggemann (2010) conducted six focus groups with 49 adolescent girls between the ages of 13 and 15 to learn more about girls’ attitudes towards’ participation in sports. In order to get focus group participants to speak with one another rather than with the group facilitator, the focus group interview guide contained just two questions: “Can you tell me some of the reasons that girls stop playing sports or other physical activities?” and “Why do you think girls don’t play as much sport/physical activity as boys?” In another focus group study, Virpi Ylanne and Angie Williams (2009) held nine focus group sessions with adults of different ages to gauge their perceptions of how older characters are represented in television commercials. Among other considerations, the researchers were interested in discovering how focus group participants position themselves and others in terms of age stereotypes and identities during the group discussion. In both examples, the researchers’ core interest in group interaction could not have been assessed had interviews been conducted on a one-on-one basis, making the focus group method an ideal choice.

Who should be in your focus group?

In some ways, focus groups require more planning than other qualitative methods of data collection, such as one-on-one interviews in which a researcher may be better able to the dialogue. Researchers must take care to form focus groups with members who will want to interact with one another and to control the timing of the event so that participants are not asked nor expected to stay for a longer time than they’ve agreed to participate. The researcher should also be prepared to inform focus group participants of their responsibility to maintain the confidentiality of what is said in the group. But while the researcher can and should encourage all focus group members to maintain confidentiality, she should also clarify to participants that the unique nature of the group setting prevents her from being able to promise that confidentiality will be maintained by other participants. Once focus group members leave the research setting, researchers cannot control what they say to other people.

Group size should be determined in part by the topic of the interview and your sense of the likelihood that participants will have much to say without much prompting. If the topic is one about which you think participants feel passionately and will have much to say, a group of 3–5 could make sense. Groups larger than that, especially for heated topics, can easily become unmanageable. Some researchers say that a group of about 6–10 participants is the ideal size for focus group research (Morgan, 1997); others recommend that groups should include 3–12 participants (Adler & Clark, 2008).  The size of the focus group is ultimately the decision of the researcher. When forming groups and deciding how large or small to make them, take into consideration what you know about the topic and participants’ potential interest in, passion for, and feelings about the topic. Also consider your comfort level and experience in conducting focus groups. These factors will help you decide which size is right in your particular case.

It may seem counterintuitive, but in general, it is better to form focus groups consisting of participants who do not know one another than to create groups consisting of friends, relatives, or acquaintances (Agar & MacDonald, 1995).  The reason is that group members who know each other may not share some taken-for-granted knowledge or assumptions. In research, it is precisely the  taken-for-granted knowledge that is often of interest; thus, the focus group researcher should avoid setting up interactions where participants may be discouraged to question or raise issues that they take for granted. However, group members should not be so different from one another that participants will be unlikely to feel comfortable talking with one another.

Focus group researchers must carefully consider the composition of the groups they put together. In his text on conducting focus groups, Morgan (1997) suggests that “homogeneity in background and not homogeneity in attitudes” (p. 36) should be the goal, since participants must feel comfortable speaking up but must also have enough differences to facilitate a productive discussion.  Whatever composition a researcher designs for her focus groups, the important point to keep in mind is that focus group dynamics are shaped by multiple social contexts (Hollander, 2004). Participants’ silences as well as their speech may be shaped by gender, race, class, sexuality, age, or other background characteristics or social dynamics—all of which might be suppressed or exacerbated depending on the composition of the group. Hollander (2004) suggests that researchers must pay careful attention to group composition, must be attentive to group dynamics during the focus group discussion, and should use multiple methods of data collection in order to “untangle participants’ responses and their relationship to the social contexts of the focus group” (p. 632).

The role of the moderator

In addition to the importance of group composition, focus groups also require skillful moderation. A moderator is the researcher tasked with facilitating the conversation in the focus group. Participants may ask each other follow-up questions, agree or disagree with one another, display body language that tells us something about their feelings about the conversation, or even come up with questions not previously conceived of by the researcher. It is just these sorts of interactions and displays that are of interest to the researcher. A researcher conducting focus groups collects data on more than people’s direct responses to her question, as in interviews.

The moderator’s job is not to ask questions to each person individually, but to stimulate conversation between participants. It is important to set ground rules for focus groups at the outset of the discussion. Remind participants you’ve invited them to participate because you want to hear from all of them. Therefore, the group should aim to let just one person speak at a time and avoid letting just a couple of participants dominate the conversation. One way to do this is to begin the discussion by asking participants to briefly introduce themselves or to provide a brief response to an opening question. This will help set the tone of having all group members participate. Also, ask participants to avoid having side conversations; thoughts or reactions to what is said in the group are important and should be shared with everyone.

As the focus group gets rolling, the moderator will play a less active role as participants talk to one another. There may be times when the conversation stagnates or when you, as moderator, wish to guide the conversation in another direction. In these instances, it is important to demonstrate that you’ve been paying attention to what participants have said. Being prepared to interject statements or questions such as “I’d really like to hear more about what Sunil and Joe think about what Dominick and Jae have been saying” or “Several of you have mentioned X. What do others think about this?” will be important for keeping the conversation going. It can also help redirect the conversation, shift the focus to participants who have been less active in the group, and serve as a cue to those who may be dominating the conversation that it is time to allow others to speak. Researchers may choose to use multiple moderators to make managing these various tasks easier.

Moderators are often too busy working with participants to take diligent notes during a focus group. It is helpful to have a note-taker who can record participants’ responses (Liamputtong, 2011). The note-taker creates, in essence, the first draft of interpretation for the data in the study. They note themes in responses, nonverbal cues, and other information to be included in the analysis later on. Focus groups are analyzed in a similar way as interviews; however, the interactive dimension between participants adds another element to the analytical process. Researchers must attend to the group dynamics of each focus group, as “verbal and nonverbal expressions, the tactical use of humour, interruptions in interaction, and disagreement between participants” are all data that are vital to include in analysis (Liamputtong, 2011, p. 175). Note-takers record these elements in field notes, which allows moderators to focus on the conversation.

Strengths and weaknesses of focus groups

Focus groups share many of the strengths and weaknesses of one-on-one qualitative interviews. Both methods can yield very detailed, in-depth information; are excellent for studying social processes; and provide researchers with an opportunity not only to hear what participants say but also to observe what they do in terms of their body language. Focus groups offer the added benefit of giving researchers a chance to collect data on human interaction by observing how group participants respond and react to one another. Like one-on-one qualitative interviews, focus groups can also be quite expensive and time-consuming. However, there may be some savings with focus groups as it takes fewer group events than one-on-one interviews to gather data from the same number of people. Another potential drawback of focus groups, which is not a concern for one-on-one interviews, is that one or two participants might dominate the group, silencing other participants. Careful planning and skillful moderation on the part of the researcher are crucial for avoiding, or at least dealing with, such possibilities. The various strengths and weaknesses of focus group research are summarized in Table 91.

Grounded Theory

Grounded theory has been widely used since its development in the late 1960s (Glaser & Strauss, 1967). Largely derived from schools of sociology, grounded theory involves emersion of the researcher in the field and in the data. Researchers follow a systematic set of procedures and a simultaneous approach to data collection and analysis. Grounded theory is most often used to generate rich explanations of complex actions, processes, and transitions. The primary mode of data collection is one-on-one participant interviews. Sample sizes tend to range from 20 to 30 individuals, sampled purposively (Padgett, 2016). However, sample sizes can be larger or smaller, depending on data saturation. Data saturation is the point in the qualitative research data collection process when no new information is being discovered. Researchers use a constant comparative approach in which previously collected data are analyzed during the same time frame as new data are being collected.  This allows the researchers to determine when new information is no longer being gleaned from data collection and analysis — that data saturation has been reached — in order to conclude the data collection phase.

Rather than apply or test existing grand theories, or “Big T” theories, grounded theory focuses on “small t” theories (Padgett, 2016). Grand theories, or “Big T” theories, are systems of principles, ideas, and concepts used to predict phenomena. These theories are backed up by facts and tested hypotheses. “Small t” theories are speculative and contingent upon specific contexts. In grounded theory, these “small t” theories are grounded in events and experiences and emerge from the analysis of the data collected.

One notable application of grounded theory produced a “small t” theory of acceptance following cancer diagnoses (Jakobsson, Horvath, & Ahlberg, 2005). Using grounded theory, the researchers interviewed nine patients in western Sweden. Data collection and analysis stopped when saturation was reached. The researchers found that action and knowledge, given with respect and continuity led to confidence which led to acceptance. This “small t” theory continues to be applied and further explored in other contexts.

Case study research

Case study research is an intensive longitudinal study of a phenomenon at one or more research sites for the purpose of deriving detailed, contextualized inferences and understanding the dynamic process underlying a phenomenon of interest. Case research is a unique research design in that it can be used in an interpretive manner to build theories or in a positivist manner to test theories. The previous chapter on case research discusses both techniques in depth and provides illustrative exemplars. Furthermore, the case researcher is a neutral observer (direct observation) in the social setting rather than an active participant (participant observation). As with any other interpretive approach, drawing meaningful inferences from case research depends heavily on the observational skills and integrative abilities of the researcher.

Ethnography

The ethnographic research method, derived largely from the field of anthropology, emphasizes studying a phenomenon within the context of its culture. The researcher must be deeply immersed in the social culture over an extended period of time (usually 8 months to 2 years) and should engage, observe, and record the daily life of the studied culture and its social participants within their natural setting. The primary mode of data collection is participant observation, and data analysis involves a “sense-making” approach. In addition, the researcher must take extensive field notes, and narrate her experience in descriptive detail so that readers may experience the same culture as the researcher. In this method, the researcher has two roles: rely on her unique knowledge and engagement to generate insights (theory), and convince the scientific community of the trans-situational nature of the studied phenomenon.

The classic example of ethnographic research is Jane Goodall’s study of primate behaviors, where she lived with chimpanzees in their natural habitat at Gombe National Park in Tanzania, observed their behaviors, interacted with them, and shared their lives. During that process, she learnt and chronicled how chimpanzees seek food and shelter, how they socialize with each other, their communication patterns, their mating behaviors, and so forth. A more contemporary example of ethnographic research is Myra Bluebond-Langer’s (1996)14 study of decision making in families with children suffering from life-threatening illnesses, and the physical, psychological, environmental, ethical, legal, and cultural issues that influence such decision-making. The researcher followed the experiences of approximately 80 children with incurable illnesses and their families for a period of over two years. Data collection involved participant observation and formal/informal conversations with children, their parents and relatives, and health care providers to document their lived experience.

Phenomenology

Phenomenology is a research method that emphasizes the study of conscious experiences as a way of understanding the reality around us. Phenomenology is concerned with the systematic reflection and analysis of phenomena associated with conscious experiences, such as human judgment, perceptions, and actions, with the goal of (1) appreciating and describing social reality from the diverse subjective perspectives of the participants involved, and (2) understanding the symbolic meanings (“deep structure”) underlying these subjective experiences. Phenomenological inquiry requires that researchers eliminate any prior assumptions and personal biases, empathize with the participant’s situation, and tune into existential dimensions of that situation, so that they can fully understand the deep structures that drives the conscious thinking, feeling, and behavior of the studied participants.

Some researchers view phenomenology as a philosophy rather than as a research method. In response to this criticism, Giorgi and Giorgi (2003) developed an existential phenomenological research method to guide studies in this area. This method can be grouped into data collection and data analysis phases. In the data collection phase, participants embedded in a social phenomenon are interviewed to capture their subjective experiences and perspectives regarding the phenomenon under investigation. Examples of questions that may be asked include “can you describe a typical day” or “can you describe that particular incident in more detail?” These interviews are recorded and transcribed for further analysis. During data analysis, the researcher reads the transcripts to: (1) get a sense of the whole, and (2) establish “units of significance” that can faithfully represent participants’ subjective experiences. Examples of such units of significance are concepts such as “felt space” and “felt time,” which are then used to document participants’ psychological experiences. For instance, did participants feel safe, free, trapped, or joyous when experiencing a phenomenon (“felt-space”)? Did they feel that their experience was pressured, slow, or discontinuous (“felt-time”)? Phenomenological analysis should take into account the participants’ temporal landscape (i.e., their sense of past, present, and future), and the researcher must transpose herself in an imaginary sense in the participant’s situation (i.e., temporarily live the participant’s life). The participants’ lived experience is described in form of a narrative or using emergent themes. The analysis then delves into these themes to identify multiple layers of meaning while retaining the fragility and ambiguity of subjects’ lived experiences.

Key Takeaways

• In terms of focus group composition, homogeneity of background among participants is recommended while diverse attitudes within the group are ideal.
• The goal of a focus group is to get participants to talk with one another rather than the researcher.
• Like one-on-one qualitative interviews, focus groups can yield very detailed information, are excellent for studying social processes, and provide researchers with an opportunity to observe participants’ body language; they also allow researchers to observe social interaction.
• Focus groups can be expensive and time-consuming, as are one-on-one interviews; there is also the possibility that a few participants will dominate the group and silence others in the group.
• Other types of qualitative research include case studies, ethnography, and phenomenology.
• Data saturation – the point in the qualitative research data collection process when no new information is being discovered
• Focus groups- planned discussions designed to elicit group interaction and “obtain perceptions on a defined area of interest in a permissive, nonthreatening environment” (Krueger & Casey, 2000, p. 5)
• Moderator- the researcher tasked with facilitating the conversation in the focus group

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Foundations of Social Work Research Copyright © 2020 by Rebecca L. Mauldin is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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5 Types of Qualitative Methods

But just as with quantitative methods, there are actually many varieties of qualitative methods.

Similar to the way you can group usability testing methods , there are also a number of ways to segment qualitative methods.

A popular and helpful categorization separate qualitative methods into five groups: ethnography, narrative, phenomenological, grounded theory, and case study. John Creswell outlines these five methods in Qualitative Inquiry and Research Design .

While the five methods generally use similar data collection techniques (observation, interviews, and reviewing text), the purpose of the study differentiates them—something similar with different types of usability tests . And like classifying different usability studies, the differences between the methods can be a bit blurry. Here are the five qualitative methods in more detail.

1. Ethnography

Ethnographic research is probably the most familiar and applicable type of qualitative method to UX professionals. In ethnography, you immerse yourself in the target participants’ environment to understand the goals, cultures, challenges, motivations, and themes that emerge. Ethnography has its roots in cultural anthropology where researchers immerse themselves within a culture, often for years! Rather than relying on interviews or surveys, you experience the environment first hand, and sometimes as a “participant observer.”

For example, one way of uncovering the unmet needs of customers is to “ follow them home ” and observe them as they interact with the product. You don’t come armed with any hypotheses to necessarily test; rather, you’re looking to find out how a product is used.

2. Narrative

The narrative approach weaves together a sequence of events, usually from just one or two individuals to form a cohesive story. You conduct in-depth interviews, read documents, and look for themes; in other words, how does an individual story illustrate the larger life influences that created it. Often interviews are conducted over weeks, months, or even years, but the final narrative doesn’t need to be in chronological order. Rather it can be presented as a story (or narrative) with themes, and can reconcile conflicting stories and highlight tensions and challenges which can be opportunities for innovation.

For example, a narrative approach can be an appropriate method for building a persona . While a persona should be built using a mix of methods—including segmentation analysis from surveys—in-depth interviews with individuals in an identified persona can provide the details that help describe the culture, whether it’s a person living with Multiple Sclerosis, a prospective student applying for college, or a working mom.

3. Phenomenological

When you want to describe an event, activity, or phenomenon, the aptly named phenomenological study is an appropriate qualitative method. In a phenomenological study, you use a combination of methods, such as conducting interviews, reading documents, watching videos, or visiting places and events, to understand the meaning participants place on whatever’s being examined. You rely on the participants’ own perspectives to provide insight into their motivations.

Like other qualitative methods, you don’t start with a well-formed hypothesis. In a phenomenological study, you often conduct a lot of interviews, usually between 5 and 25 for common themes , to build a sufficient dataset to look for emerging themes and to use other participants to validate your findings.

For example, there’s been an explosion in the last 5 years in online courses and training. But how do students engage with these courses? While you can examine time spent and content accessed using log data and even assess student achievement vis-a-vis in-person courses, a phenomenological study would aim to better understand the students experience and how that may impact comprehension of the material.

4. Grounded Theory

Whereas a phenomenological study looks to describe the essence of an activity or event, grounded theory looks to provide an explanation or theory behind the events. You use primarily interviews and existing documents to build a theory based on the data. You go through a series of open and axial coding techniques to identify themes and build the theory. Sample sizes are often also larger—between 20 to 60—with these studies to better establish a theory. Grounded theory can help inform design decisions by better understanding how a community of users currently use a product or perform tasks.

For example, a grounded theory study could involve understanding how software developers use portals to communicate and write code or how small retail merchants approve or decline customers for credit.

5. Case Study

Made famous by the Harvard Business School, even mainly quantitative researchers can relate to the value of the case study in explaining an organization, entity, company, or event. A case study involves a deep understanding through multiple types of data sources. Case studies can be explanatory, exploratory, or describing an event. The annual CHI conference has a peer-reviewed track dedicated to case studies.

For example, a case study of how a large multi-national company introduced UX methods into an agile development environment would be informative to many organizations.

The table below summarizes the differences between the five qualitative methods.

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Home » Qualitative Research – Methods, Analysis Types and Guide

Qualitative Research – Methods, Analysis Types and Guide

Table of Contents

Qualitative Research

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

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

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

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

Focus Groups

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

Ethnographic Studies

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

Text Analysis

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

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

Process of Observation

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

Record Keeping

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

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

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

Qualitative Research Analysis Methods

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

Thematic Analysis

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

Content Analysis

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

Discourse Analysis

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

Grounded Theory Analysis

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

Narrative Analysis

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

Phenomenological Analysis

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

Comparative Analysis

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

Applications of Qualitative Research

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

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

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

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

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

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

Purpose of Qualitative Research

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

Qualitative research can serve multiple purposes, including:

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

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

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

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

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

Advantages of Qualitative Research

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

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

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

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

Also see Research Methods

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• > The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences
• > Qualitative Research Design

Book contents

• The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences
• Cambridge Handbooks in Psychology
• Copyright page
• Contributors
• Part I From Idea to Reality: The Basics of Research
• Part II The Building Blocks of a Study
• Part III Data Collection
• 13 Cross-Sectional Studies
• 14 Quasi-Experimental Research
• 15 Non-equivalent Control Group Pretest–Posttest Design in Social and Behavioral Research
• 16 Experimental Methods
• 17 Longitudinal Research: A World to Explore
• 18 Online Research Methods
• 19 Archival Data
• 20 Qualitative Research Design
• Part IV Statistical Approaches
• Part V Tips for a Successful Research Career

20 - Qualitative Research Design

from Part III - Data Collection

Published online by Cambridge University Press:  25 May 2023

The social world is fascinating – full of complexities, tensions, and contradictions. Social scientists have long been interested in better understanding the social world around us. Unlike quantitative research, that focuses on collecting and analyzing numerical data to make statistical inferences about the social world, qualitative research contributes to empirical and theoretical understandings of society by examining and explaining how and why people think and act as they do through the use of non-numerical data. In other words, qualitative research uncovers social processes and mechanisms undergirding human behavior. In this chapter, we will discuss how to design a qualitative research project using two of the most common qualitative research methods: in-depth interviewing and ethnographic observations (also known as ethnography or participant observation). We will begin the chapter by discussing the what , how , and why of interviewing and ethnography. We will then discuss the importance of interrogating one’s underlying ontological and epistemological assumptions regarding research (and the research process) and the steps to follow in designing a qualitative study. We conclude the chapter by reviewing the different elements to consider when developing a qualitative research project.

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• Qualitative Research Design
• By Sinikka Elliott , Kayonne Christy , Siqi Xiao
• Edited by Austin Lee Nichols , Central European University, Vienna , John Edlund , Rochester Institute of Technology, New York
• Book: The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences
• Online publication: 25 May 2023
• Chapter DOI: https://doi.org/10.1017/9781009010054.021

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Qualitative Research Design: Start

Qualitative Research Design

What is Qualitative research design?

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. Instead of collecting numerical data points or intervening or introducing treatments just like in quantitative research, qualitative research helps generate hypotheses as well as further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much . It could be structured as a stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data.

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

While qualitative and quantitative approaches are different, they are not necessarily opposites, and they are certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined that there is a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated together.

Research Paradigms 

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

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

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

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

Qualitative Coding

Using Community Data to improve Outcome (Grant Writing)

Survey Design  

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

Community Engagement and Collaboration Event 

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

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

Event Moderators:

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

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

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

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

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

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

Scott Wolovich , Director of New Sun Rising, Pittsburgh 

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

Workshop Organizer

Qualitative Research Methods

What are Qualitative Research methods?

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

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

According to Doody and Bailey (2014);

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

Helps to have a directed research aim and objective.

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

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

Qualitative Research Questions

What constitutes a good Qualitative research question?

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

Examples of good Qualitative Research Questions:

What are people's thoughts on the new library? 

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

Difference example (between Qualitative and Quantitative research questions):

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

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

• Qualitative Research Design Workshop Powerpoint

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

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

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

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

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

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

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

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

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

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

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

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

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

Qualitative Research: Characteristics, Design, Methods & Examples

Lauren McCall

MSc Health Psychology Graduate

MSc, Health Psychology, University of Nottingham

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

Learn about our Editorial Process

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.

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

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

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

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

Qualitative research can be used to:

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

Examples of qualitative research questions include: 

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

Characteristics 

Naturalistic setting.

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

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

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

Reality is socially constructed

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

The primacy of subject matter 

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

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

Variables are complex, interwoven, and difficult to measure

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

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

Emic (insider’s point of view)

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

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

Interpretive analysis

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

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

Collecting Qualitative Data

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

Observations

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

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

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

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

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

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

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

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

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

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

Focus groups 

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

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

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

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

Ethnography

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

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

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

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

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

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

Qualitative Data Analysis Methods

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

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

Grounded theory

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

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

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

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

Content analysis

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

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

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

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

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

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

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

Discourse analysis

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

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

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

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

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

Thematic analysis

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

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

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

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

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

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

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

Phases of Thematic Analysis

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

Template analysis

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

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

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

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

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

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

Frame analysis

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

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

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

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

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

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

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

Preventing Bias in Qualitative Research

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

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

Co-coding 

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

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

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

Member checking

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

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

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

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

Reflexivity in qualitative research

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

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

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

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

Reflexivity Example

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

Establishing Trustworthiness in Qualitative Research

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

1. Credibility in Qualitative Research

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

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

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

2. Transferability in Qualitative Research

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

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

3. Dependability in Qualitative Research

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

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

4. Confirmability in Qualitative Research

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

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

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

Audit Trails in Qualitative Research

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

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

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

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

Discovery of unexpected data

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

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

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

Flexibility

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

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

Naturalistic settings

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

Limitations

Time-consuming .

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

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

Subjectivity 

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

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

Limited generalizability

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

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

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

While individual qualitative studies are often limited in their generalizability due to factors such as sample size and context, metasynthesis enables researchers to synthesize findings from multiple studies, potentially leading to more generalizable conclusions.

By integrating findings from studies conducted in diverse settings and with different populations, metasynthesis can provide broader insights into the phenomenon of interest.

Extraneous variables

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

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

What sample size should qualitative research be?

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

Are surveys qualitative or quantitative?

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

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

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

What are the ethical considerations of qualitative research?

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

What is triangulation in qualitative research?

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

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

Why is qualitative research important?

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

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

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

What is coding data in qualitative research?

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

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

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

What is the difference between qualitative and quantitative research?

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

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

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

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

What is trustworthiness in qualitative research?

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

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

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

What is data saturation in qualitative research?

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

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

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

Why is sampling in qualitative research important?

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

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

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

What is narrative analysis?

Narrative analysis is a qualitative research method used to understand how individuals create stories from their personal experiences.

There is an emphasis on understanding the context in which a narrative is constructed, recognizing the influence of historical, cultural, and social factors on storytelling.

Researchers can use different methods together to explore a research question.

Some narrative researchers focus on the content of what is said, using thematic narrative analysis, while others focus on the structure, such as holistic-form or categorical-form structural narrative analysis. Others focus on how the narrative is produced and performed.

Boeije, H. (2014). Analysis in qualitative research. Sage.

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative research in psychology , 3 (2), 77-101. https://doi.org/10.1191/1478088706qp063oa

Brooks, J., McCluskey, S., Turley, E., & King, N. (2014). The utility of template analysis in qualitative psychology research. Qualitative Research in Psychology , 12 (2), 202–222. https://doi.org/10.1080/14780887.2014.955224

Busetto, L., Wick, W., & Gumbinger, C. (2020). How to use and assess qualitative research methods. Neurological research and practice , 2 (1), 14-14. https://doi.org/10.1186/s42466-020-00059-z 

Carter, N., Bryant-Lukosius, D., DiCenso, A., Blythe, J., & Neville, A. J. (2014). The use of triangulation in qualitative research. Oncology nursing forum , 41 (5), 545–547. https://doi.org/10.1188/14.ONF.545-547

Critical Appraisal Skills Programme. (2018). CASP Checklist: 10 questions to help you make sense of a Qualitative research. https://casp-uk.net/images/checklist/documents/CASP-Qualitative-Studies-Checklist/CASP-Qualitative-Checklist-2018_fillable_form.pdf Accessed: March 15 2023

Clarke, V., & Braun, V. (2013). Successful qualitative research: A practical guide for beginners. Successful Qualitative Research , 1-400.

Denny, E., & Weckesser, A. (2022). How to do qualitative research?: Qualitative research methods. BJOG : an international journal of obstetrics and gynaecology , 129 (7), 1166-1167. https://doi.org/10.1111/1471-0528.17150 

Glaser, B. G., & Strauss, A. L. (2017). The discovery of grounded theory. The Discovery of Grounded Theory , 1–18. https://doi.org/10.4324/9780203793206-1

Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field Methods, 18 (1), 59-82. doi:10.1177/1525822X05279903

Halpren, E. S. (1983). Auditing naturalistic inquiries: The development and application of a model (Unpublished doctoral dissertation). Indiana University, Bloomington.

Hammarberg, K., Kirkman, M., & de Lacey, S. (2016). Qualitative research methods: When to use them and how to judge them. Human Reproduction , 31 (3), 498–501. https://doi.org/10.1093/humrep/dev334

Koch, T. (1994). Establishing rigour in qualitative research: The decision trail. Journal of Advanced Nursing, 19, 976–986. doi:10.1111/ j.1365-2648.1994.tb01177.x

Lincoln, Y., & Guba, E. G. (1985). Naturalistic inquiry. Newbury Park, CA: Sage.

Mays, N., & Pope, C. (2000). Assessing quality in qualitative research. BMJ, 320(7226), 50–52.

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

Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic Analysis: Striving to Meet the Trustworthiness Criteria. International Journal of Qualitative Methods, 16 (1). https://doi.org/10.1177/1609406917733847

Petty, N. J., Thomson, O. P., & Stew, G. (2012). Ready for a paradigm shift? part 2: Introducing qualitative research methodologies and methods. Manual Therapy , 17 (5), 378–384. https://doi.org/10.1016/j.math.2012.03.004

Punch, K. F. (2013). Introduction to social research: Quantitative and qualitative approaches. London: Sage

Reeves, S., Kuper, A., & Hodges, B. D. (2008). Qualitative research methodologies: Ethnography. BMJ , 337 (aug07 3). https://doi.org/10.1136/bmj.a1020

Russell, C. K., & Gregory, D. M. (2003). Evaluation of qualitative research studies. Evidence Based Nursing, 6 (2), 36–40.

Saunders, B., Sim, J., Kingstone, T., Baker, S., Waterfield, J., Bartlam, B., Burroughs, H., & Jinks, C. (2018). Saturation in qualitative research: exploring its conceptualization and operationalization. Quality & quantity , 52 (4), 1893–1907. https://doi.org/10.1007/s11135-017-0574-8

Scarduzio, J. A. (2017). Emic approach to qualitative research. The International Encyclopedia of Communication Research Methods, 1–2 . https://doi.org/10.1002/9781118901731.iecrm0082

Schreier, M. (2012). Qualitative content analysis in practice / Margrit Schreier.

Shenton, A. K. (2004). Strategies for ensuring trustworthiness in qualitative research projects. Education for Information, 22 , 63–75.

Starks, H., & Trinidad, S. B. (2007). Choose your method: a comparison of phenomenology, discourse analysis, and grounded theory. Qualitative health research , 17 (10), 1372–1380. https://doi.org/10.1177/1049732307307031

Tenny, S., Brannan, J. M., & Brannan, G. D. (2022). Qualitative Study. In StatPearls. StatPearls Publishing.

Tobin, G. A., & Begley, C. M. (2004). Methodological rigour within a qualitative framework. Journal of Advanced Nursing, 48, 388–396. doi:10.1111/j.1365-2648.2004.03207.x

Vaismoradi, M., Turunen, H., & Bondas, T. (2013). Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study. Nursing & health sciences , 15 (3), 398-405. https://doi.org/10.1111/nhs.12048

Wood L. A., Kroger R. O. (2000). Doing discourse analysis: Methods for studying action in talk and text. Sage.

Yilmaz, K. (2013). Comparison of Quantitative and Qualitative Research Traditions: epistemological, theoretical, and methodological differences. European journal of education , 48 (2), 311-325. https://doi.org/10.1111/ejed.12014

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How to Write a Research Methodology for a Research Paper

Are you overwhelmed by the multitude of qualitative research methods available? It's no secret that choosing the right approach can leave you stuck at the starting line of your research.

Selecting an unsuitable method can lead to wasted time, resources, and potentially skewed results. But with so many options to consider, it's easy to feel lost in the complexities of qualitative research.

In this comprehensive guide, we will explain the types of qualitative research, their unique characteristics, advantages, and best use cases for each method.

Let's dive in!

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• 1. What is Qualitative Research?
• 2. Types of Qualitative Research Methods
• 3. Types of Data Analysis in Qualitative Research 

What is Qualitative Research?

Qualitative research is a robust and flexible methodology used to explore and understand complex phenomena in-depth. 

Unlike quantitative research , qualitative research dives into the rich and complex aspects of human experiences, behaviors, and perceptions.

At its core, this type of research question seeks to answer for:

• Why do people think or behave a certain way?
• What are the underlying motivations and meanings behind actions?
• How do individuals perceive and interpret the world around them?

This approach values context, diversity, and the unique perspectives of participants. 

Rather than seeking generalizable findings applicable to a broad population, qualitative research aims for detailed insights, patterns, and themes that come from the people being studied.

Characteristics of Qualitative Research 

Qualitative research possesses the following characteristics: 

• Subjective Perspective: Qualitative research explores subjective experiences, emphasizing the uniqueness of human behavior and opinions.
• In-Depth Exploration: It involves deep investigation, allowing a comprehensive understanding of specific phenomena.
• Open-Ended Questions: Qualitative research uses open-ended questions to encourage detailed, descriptive responses.
• Contextual Understanding: It emphasizes the importance of understanding the research context and setting.
• Rich Descriptions: Qualitative research produces rich, descriptive findings that contribute to a nuanced understanding of the topic.

Types of Qualitative Research Methods

Researchers collect data on the targeted population, place, or event by using different types of qualitative research analysis.

Each qualitative research method offers a distinct perspective, enabling researchers to reveal concealed meanings, patterns, and valuable insights.

Below are the most commonly used qualitative research types for writing a paper.

Ethnographic Research Method 

Ethnography, a subfield of anthropology, provides a scientific approach to examining human societies and cultures. It ranks among the most widely employed qualitative research techniques.

In ethnographic field notes, researchers actively engage with the environment and live alongside the focus group. 

This immersive interaction allows researchers to gain insights into the objectives, motivations, challenges, and distinctive cultural attributes of the individuals under study.

Key cultural characteristics that ethnography helps to illustrate encompass:

• Geographical Location
• Religious Practices
• Tribal Systems
• Shared Experiences

Unlike traditional survey and interview-based research methods, ethnographers don't rely on structured questioning. 

Instead, they become observers within the community, emphasizing participant observation over an extended period. However, it may also be appropriate to complement observations with interviews of individuals who possess knowledge of the culture.

Ethnographic research can present challenges if the researcher is unfamiliar with the social norms and language of the group being studied. 

Furthermore, interpretations made by outsiders may lead to misinterpretations or confusion. Therefore, thorough validation of data is essential before presenting findings.

Narrative Method 

The narrative research design unfolds over an extended period to compile data, much like crafting a cohesive story. Similar to a narrative structure, it begins with a starting point and progresses through various life situations.

In this method, researchers engage in in-depth interviews and review relevant documents. They explore events that have had a significant impact on an individual's personality and life journey. Interviews may occur over weeks, months, or even years, depending on the depth and scope of the narrative being studied.

The outcome of narrative research is the presentation of a concise story that captures essential themes, conflicts, and challenges. It provides a holistic view of the individual's experiences, both positive and negative, which have shaped their unique narrative.

Phenomenological Method 

The term "phenomenological" pertains to the study of phenomena, which can encompass events, situations, or experiences. 

This method is ideal for examining a subject from multiple perspectives and contributing to existing knowledge, with a particular focus on subjective experiences.

Researchers employing the phenomenological method use various data collection techniques, including interviews, site visits, observations, surveys, and document reviews. 

These methods help gather rich and diverse data about the phenomenon under investigation.

A central aspect of this technique is capturing how participants experience events or activities, delving into their subjective viewpoints. Ultimately, the research results in the creation of a thematic database that validates the findings and offers insights from the subject's perspective.

Grounded Theory Method

A grounded theory approach differs from a phenomenological study in that it seeks to explain, provide reasons for, or develop theories behind an event or phenomenon. 

It serves as a means to construct new theories by systematically collecting and analyzing data related to a specific phenomenon.

Researchers employing the grounded theory method utilize a variety of data collection techniques, including observation, interviews, literature review , and the analysis of relevant documents. 

The focus of content analysis is not individual behaviors but a specific phenomenon or incident.

This method typically involves various coding techniques and large sample sizes to identify themes and develop more comprehensive theories.

Case Study Research 

The case study approach entails a comprehensive examination of a subject over an extended period, with a focus on providing detailed insights into the subject, which can be an event, person, business, or place.

Data for case studies is collected from diverse sources, including interviews, direct observation, historical records, and documentation.

Case studies find applications across various disciplines, including law, education, medicine, and the sciences. They can serve both descriptive and explanatory purposes, making them a versatile research methodology .

Researchers often turn to the case study method when they want to explore:

• 'How' and 'why' research questions
• Behaviors under observation
• Understanding a specific phenomenon
• The contextual factors influencing the phenomena

Historical Method

The historical method aims to describe and analyze past events, offering insights into present patterns and the potential to predict future scenarios. 

Researchers formulate research problems based on a hypothetical idea and then rigorously test this idea using multiple historical resources.

Key steps in the historical method include:

• Developing a research idea
• Identifying appropriate sources such as archives and libraries
• Ensuring the reliability and validity of these sources
• Creating a well-organized research outline
• Systematically collecting research data

The analysis phase involves critically assessing the collected data, accepting or rejecting it based on credibility, and identifying any conflicting evidence.

Ultimately, the outcomes of the historical method are presented in the form of a biography or a scholarly paper that provides a comprehensive account of the research findings.

Action Research 

Action research is a dynamic research approach focused on addressing practical challenges in real-world settings while simultaneously conducting research to improve the situation. 

It follows a cyclic process, starting with the identification of a specific issue or problem in a particular context.

The key steps in action research include:

• Planning and implementing actions to address the issue
• Collecting data during the action phase to understand its impact
• Reflecting on the data and analyzing it to gain insights
• Adjusting the action plan based on the analysis

This process may be iterative, with multiple cycles of action and reflection.

The outcomes of action research are practical solutions and improved practices that directly benefit the context in which the research is conducted. Additionally, it leads to a deeper and more nuanced understanding of the issue under investigation.

Focus Groups 

Focus groups are a qualitative research method used to gather in-depth insights and perspectives on a specific topic or research question. 

This approach involves assembling a small group of participants who possess relevant knowledge or experiences related to the research focus.

Key steps in the focus group method include:

• Selecting participants
• Moderating the discussion
• Structuring the conversation around open-ended questions
• Collecting data through audio or video recordings and note-taking 

The discussion is dynamic and interactive, encouraging participants to share their thoughts, experiences, and opinions.

The analysis phase involves reviewing the data collected from the focus group discussion to identify common themes, patterns, and valuable insights. Focus groups provide rich qualitative data that offer a deeper and more nuanced understanding of the research topic or question.

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Types of Data Analysis in Qualitative Research 

Qualitative research employs different data analysis methods, each suited to specific research goals:

• Thematic Analysis: Identifies recurring themes or concepts within data.
• Content Analysis: Systematically categorizes and quantifies text or media content.
• Narrative Analysis: Focuses on storytelling and narrative elements in data.
• Grounded Theory Analysis: Develops or refines theories based on data.
• Discourse Analysis: Examines language and communication patterns.
• Framework Analysis: Organizes data using predefined categories.
• Visual Analysis: Interprets visual data like photos or videos.
• Cross-case Analysis: Compares patterns across multiple cases.

The choice depends on research questions and data type, enhancing understanding and insights.

Benefits of Qualitative Research 

Qualitative research offers valuable advantages, including:

• Flexibility: Adaptable to various research questions and settings.
• Holistic Approach: Explores multiple dimensions of phenomena.
• Theory Development: Contributes to theory creation or refinement.
• Participant Engagement: Fosters active participant involvement.
• Complements Quantitative Research: Provides a comprehensive understanding.

All in all, different types of qualitative research methodology can assist in understanding the behavior and motivations of people. Similarly, it will also help in generating original ideas and formulating a better research problem.

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Types Of Qualitative Research Designs And Methods

Qualitative research design comes in many forms. Understanding what qualitative research is and the various methods that fall under its…

Qualitative research design comes in many forms. Understanding what qualitative research is and the various methods that fall under its umbrella can help determine which method or design to use. Various techniques can achieve results, depending on the subject of study.

Types of qualitative research to explore social behavior or understand interactions within specific contexts include interviews, focus groups, observations and surveys. These identify concepts and relationships that aren’t easily observed through quantitative methods. Figuring out what to explore through qualitative research is the first step in picking the right study design.

Let’s look at the most common types of qualitative methods.

What Is Qualitative Research Design?

Types of qualitative research designs, how are qualitative answers analyzed, qualitative research design in business.

There are several types of qualitative research. The term refers to in-depth, exploratory studies that discover what people think, how they behave and the reasons behind their behavior. The qualitative researcher believes that to best understand human behavior, they need to know the context in which people are acting and making decisions.

Let’s define some basic terms.

Qualitative Method

A group of techniques that allow the researcher to gather information from participants to learn about their experiences, behaviors or beliefs. The types of qualitative research methods used in a specific study should be chosen as dictated by the data being gathered. For instance, to study how employers rate the skills of the engineering students they hired, qualitative research would be appropriate.

Quantitative Method

A group of techniques that allows the researcher to gather information from participants to measure variables. The data is numerical in nature. For instance, quantitative research can be used to study how many engineering students enroll in an MBA program.

Research Design

A plan or outline of how the researcher will proceed with the proposed research project. This defines the sample, the scope of work, the goals and objectives. It may also lay out a hypothesis to be tested. Research design could also combine qualitative and quantitative techniques.

Both qualitative and quantitative research are significant. Depending on the subject and the goals of the study, researchers choose one or the other or a combination of the two. This is all part of the qualitative research design process.

Before we look at some different types of qualitative research, it’s important to note that there’s no one correct approach to qualitative research design. No matter what the type of study, it’s important to carefully consider the design to ensure the method is suitable to the research question. Here are the types of qualitative research methods to choose from:

Cluster Sampling

This technique involves selecting participants from specific locations or teams (clusters). A researcher may set out to observe, interview, or create a focus group with participants linked by location, organization or some other commonality. For example, the researcher might select the top five teams that produce an organization’s finest work. The same can be done by looking at locations (stores in a geographic region). The benefit of this design is that it’s efficient in collecting opinions from specific working groups or areas. However, this limits the sample size to only those people who work within the cluster.

Random Sampling

This design involves randomly assigning participants into groups based on a set of variables (location, gender, race, occupation). In this design, each participant is assigned an equal chance of being selected into a particular group. For example, if the researcher wants to study how students from different colleges differ from one another in terms of workplace habits and friendships, a random sample could be chosen from the student population at these colleges. The purpose of this design is to create a more even distribution of participants across all groups. The researcher will need to choose which groups to include in the study.

Focus Groups

A focus group is a small group that meets to discuss specific issues. Participants are usually recruited randomly, although sometimes they might be recruited because of personal relationships with each other or because they represent part of a certain demographic (age, location). Focus groups are one of the most popular styles of qualitative research because they allow for individual views and opinions to be shared without introducing bias. Researchers gather data through face-to-face conversation or recorded observation.

Observation

This technique involves observing the interaction patterns in a particular situation. Researchers collect data by closely watching the behaviors of others. This method can only be used in certain settings, such as in the workplace or homes.

An interview is an open-ended conversation between a researcher and a participant in which the researcher asks predetermined questions. Successful interviews require careful preparation to ensure that participants are able to give accurate answers. This method allows researchers to collect specific information about their research topic, and participants are more likely to be honest when telling their stories. However, there’s no way to control the number of unique answers, and certain participants may feel uncomfortable sharing their personal details with a stranger.

A survey is a questionnaire used to gather information from a pool of people to get a large sample of responses. This study design allows researchers to collect more data than they would with individual interviews and observations. Depending on the nature of the survey, it may also not require participants to disclose sensitive information or details. On the flip side, it’s time-consuming and may not yield the answers researchers were looking for. It’s also difficult to collect and analyze answers from larger groups.

A large study can combine several of these methods. For instance, it can involve a survey to better understand which kind of organic produce consumers are looking for. It may also include questions on the frequency of such purchases—a numerical data point—alongside their views on the legitimacy of the organic tag, which is an open-ended qualitative question.

Knowledge of the types of qualitative research designs will help you achieve the results you desire.

With quantitative research, analysis of results is fairly straightforward. But, the nature of qualitative research design is such that turning the information collected into usable data can be a challenge. To do this, researchers have to code the non-numerical data for comparison and analysis.

The researcher goes through all their notes and recordings and codes them using a predetermined scheme. Codes are created by ‘stripping out’ words or phrases that seem to answer the questions posed. The researcher will need to decide which categories to code for. Sometimes this process can be time-consuming and difficult to do during the first few passes through the data. So, it’s a good idea to start off by coding a small amount of the data and conducting a thematic analysis to get a better understanding of how to proceed.

The data collected must be organized and analyzed to answer the research questions. There are three approaches to analyzing the data: exploratory, confirmatory and descriptive.

Explanatory Data Analysis

This approach involves looking for relationships within the data to make sense of it. This design can be useful if the research question is ambiguous or open-ended. Exploratory analysis is very flexible and can be used in a number of settings. But, it generally looks at the relationship between variables while the researcher is working with the data.

Confirmatory Data Analysis

This design is used when there’s a hypothesis or theory to be tested. Confirmatory research seeks to test how well past findings apply to new observations by comparing them to statistical tests that quantify relationships between variables. It can also use prior research findings to predict new results.

Descriptive Data Analysis

In this design, the researcher will describe patterns that can be observed from the data. The researcher will take raw data and interpret it with an eye for patterns to formulate a theory that can eventually be tested with quantitative data. The qualitative design is ideal for exploring events that can’t be observed (such as people’s thoughts) or when a process is being evaluated.

With careful planning and insightful analysis, qualitative research is a versatile and useful tool in business, public policy and social studies. In the workplace, managers can use it to understand markets and consumers better or to study the health of an organization.

Businesses conduct qualitative research for many reasons. Harappa’s Thinking Critically course prepares professionals to use such data to understand their work better. Driven by experienced faculty with real-world experience, the course equips employees on a growth trajectory with frameworks and skills to use their reasoning abilities to build better arguments. It’s possible to build more effective teams. Find out how with Harappa.

Explore Harappa Diaries to learn more about topics such as What is Qualitative Research , Quantitative Vs Qualitative Research , Examples of Phenomenological Research and Tips For Studying Online to upgrade your knowledge and skills.

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Qualitative Research Methods: Types, Analysis + Examples

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

What is qualitative research?

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

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

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

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

Gather research insights

Types of qualitative research methods with examples

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

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

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

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

1. One-on-one interview

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

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

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

2. Focus groups

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

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

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

3. Ethnographic research

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

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

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

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

4. Case study research

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

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

5. Record keeping

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

6. Process of observation

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

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

Explore Insightfully Contextual Inquiry in Qualitative Research

Qualitative research: data collection and analysis

A. qualitative data collection.

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

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

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

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

B. Qualitative data analysis

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

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

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

Choosing the right software can be tough. Whether you’re a researcher, business leader, or marketer, check out the top 10  qualitative data analysis software  for analyzing qualitative data.

Characteristics of qualitative research methods

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

Qualitative research method case study

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

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

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

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

When to use qualitative research

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

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

LEARN ABOUT: Steps in Qualitative Research

Qualitative research methods vs quantitative research methods

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

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

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What are the different types of qualitative research?

Last updated

8 February 2023

Reviewed by

Jean Kaluza

Short on time? Get an AI generated summary of this article instead

Qualitative research is a crucial step in product development .  While the quantitative approach might explain where an issue lies and the number of users it affects, the qualitative method answers why the problem is happening and how it affects customers.

This type of research explains how people experience the world. Many researchers use it to understand a group’s behavior, characteristics, and motivations.

People also use qualitative research in the business sector. Qualitative research enables you to access content-rich information about user emotions and perceptions. For example, you can use it in market research to understand what a target group thinks about your company’s new ideas.

Different qualitative research types serve a particular purpose. Before we delve into the various types of qualitative research, let's begin with the basics.

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• What is qualitative research?

Qualitative research is a market research process that involves collecting and analyzing in-depth data through conversational and open-ended communication. It focuses on "what" people think and "why" they think so. Qualitative research goes beyond how many people do something to determine why they do or don't do it.

Qualitative research methods enable detailed questioning of respondents based on their responses. The researcher’s aim is to understand the participants’ feelings and motivations.

Imagine a cake company looking to get more customers at two branches on the same street. A systematic observation showed more people bought cakes from Branch A than from Branch B. One way to determine why people preferred Branch A is to interview potential customers.

Let's say the company visited both stores and interviewed customers. Upon completion, results showed that workers in Branch B lacked good customer relationships, so many people visited Branch A instead.

Another example is if marketing notices a consistent but unexplainable churn in customers. Maybe subscribers of the platform were only staying on for a month rather than a much longer expected timeline. 

Qualitative initiatives could dive into the motivations of these users. Findings may reveal that the customers achieved their goals much faster than expected. Perhaps they didn’t have the characteristics the company originally assumed they had.

Qualitative research identifies customer pain points, determines why a particular product might not yield the desired results, and tests possible solutions. It’s a helpful tool when you’re looking to develop and improve products and services. Understanding how your audience makes decisions can help you draw valuable conclusions in market research.

Learn more about qualitative research platforms

• Characteristics of qualitative research methods

Qualitative research involves collecting and evaluating non-numerical data (audio, video, and text) to deeply understand opinions, concepts, or experiences. It also includes data about lived experiences, emotions, and behavior with the meaning people add to it. 

Due to its softer manner, researchers express results more commonly in:

Video clips

Sound bites

Pull quotes

Here are the characteristics of qualitative research.

Real-time data

Qualitative research methods often collect data at the location where people encounter the product or company’s service. This ensures it’s as close to the authentic experience of its consumers as possible.

Many data sources

Qualitative researchers don't need to rely on a single source of data . They can gather different data types from sources like observations, interviews, and documents for better understanding.

Qualitative research techniques tend to break down complex problems into smaller, simpler pieces that focus on what the research intends to evaluate. The goal is to have a clear understanding of the unknown. That means you can uncover answers while leaving room for surprises and discoveries to emerge.

Raw information

Since qualitative research involves conversations, participants should be able to confide in the interviewer and give their honest opinions. Researchers should use qualitative interviewing techniques to establish trust and comfort in participants to facilitate authentic and pure reactions to products. That’s why you need to ensure the information you provide is accurate.

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• Types of qualitative research methods with examples

Qualitative research methods reveal your target audiences' behavior and perception of a particular situation. Its results are more detailed and descriptive, so you can easily draw inferences from the data.

Each qualitative research type has its purpose and might not be suitable for all projects. Before conducting a qualitative study, it's crucial to understand the various types of qualitative research methods and how they differ.

Let's look at each of the six types of qualitative research methods.

1. Phenomenological method

The phenomenological approach explores the experiences of a specific phenomenon (observable fact or event) in a person or group. These are “lived experiences.”

The method helps researchers better understand people's beliefs, attitudes, behavior, and experiences. In this method, you ask customers to describe their experiences as they perceive them. This approach recognizes there is no single objective reality; everyone experiences things differently.

Researchers usually set their assumptions aside to remove bias (bracketing) and focus on the participants’ experiences. 

While the outcome depends on the participants' points of view, researchers try to answer the following questions:

How do people experience this phenomenon?

How does it affect them?

What factors influence their experience?

This method uses information from interviews, observations, diary studies, or voice-of-customer sessions to determine a participant's feelings during a particular activity or event. During this research, it's vital to make your customers feel comfortable, so they share their honest experiences.

Your questions in phenomenological research should be free of closed-ended or leading questions. Closed-ended questions usually only require a simple one-word response and won’t tell the whole story or give you the actionable data you want to collect. 

Leading questions require your user to contradict what your question may imply. This usually results in polite and natural agreement rather than the honest response you need. In short, don’t ask them if they like a feature. Ask your user how they feel about it, either positive or negative, and let them direct the discussion from there.

You can use this method to determine your customer's purchasing behavior. For example, you can ask questions like, "Do you prefer red velvet cake or vanilla cake? Why?" The responses will depend on their experiences. The result of this research method can be useful when you want to improve your product's quality or target a different product to increase sales.

2. Ethnographic model

This model is an in-depth observation that studies your target audience in their natural environment. It involves collecting and analyzing data about people by watching them rather than interviewing them. Quite often, consumers may report using a particular product in one way, but observing could prove otherwise.

It requires researchers to adapt to the environment of their target audience. Since it could be any location, collecting data can be challenging. But this model helps you understand the challenges, cultures, settings, and motivations that occur by seeing it yourself. With well-executed ethnographic research, your company can uncover: 

Users' motivations behind using your product

How they’re using it

During what other activities are they using it

How they discovered it

And even why they stopped using it

All of these insights can help you build a more intuitive product experience that leaves consumers feeling heard and satisfied.

Companies that act on accurate ethnographic studies are often way ahead of their competitors since they have a clear idea of where their customers are and where they are going.

3. Grounded theory method

Sociologists Glaser and Strauss developed the grounded theory model in the 1960s. In this model, researchers collect, interpret, and analyze data to develop various theories regarding the research topic. Rather than establish theories before examining data, researchers develop theories after studying the data.

Researchers use this model in qualitative research to see what theories or questions arise from a given data set. They may group the drawn-out theories and analyze them further. Grounded theory needs careful content analysis since the emerging theories must be valid, else it can lead to lost insights and poor decision-making.

It is often a research method that builds on existing work. Data collection methods include interviews, observations, longitudinal studies , and diary studies.

4. Case study model

The case study model helps explain a particular element, family, person, business, or organization. It is common in fields like education and social sciences. Ways of collecting data in this model may include interviews since the research requires in-depth and real details. The researcher will ask questions to determine why a particular respondent acts the way they do.

For instance, a film streaming company might watch a family use their technology to determine their reaction to new services or products and what features could interest them.

5. Historical model

Historical studies involve identifying, locating, evaluating, and synthesizing data from the past. It doesn't only discover past events but tries to relate them to the present and future. 

For instance, you can analyze data from previous advertising campaigns and use it to conduct a new one. Or a music management company can look at the audience from a 2022 concert to plan future ones.

Historical research requires great skill. Researchers must analyze the data, look for trends or changes, or pinpoint any contradictions. You can ask questions to design your research strategy, like, "How has consumer preference changed over the years?"

Sometimes, historical data can collect irrelevant data. Let’s consider how airlines experienced so much turmoil during the pandemic. It’s possible the historical data isn’t relevant enough to gather useful data from in a post-pandemic world. 

6. Narrative model

The narrative method is one of the types of qualitative research methods that focuses on written and spoken words or visual representations by people. Here, stories become raw data.

Researchers evaluate people's lived experiences through questioning to determine issues they may face. This research method helps you understand what people think about your brand. You can use it to determine the various challenges your target audience faces on a personal narrative level.

• Qualitative research data collection

This is the process of obtaining information. Qualitative data collection involves obtaining non-numerical data. It provides researchers with detailed insights into why people make decisions. But to arrive at such conclusions, the collected data should be rich, holistic, and from participants that accurately represent your targeted audience.

Some ways to collect data in qualitative research include:

Participant observations

You collect data by watching other people's behavior closely and recording what you hear, see, or encounter. 

One-on-one interviews

This involves an open-ended conversation with your target audience. The interview can be via phone, email, or face-to-face.

In-depth surveys

This may involve distributing a questionnaire with open-ended questions.

Focus groups

Here, a moderator asks participants (usually 6–12 members) predetermined questions about your products, brand, or services. It's crucial to avoid yes-or-no questions to promote engagement.

Voice-of-customer

Here, the moderator comes up with a feature or product concept and brainstorms the idea with a customer. The customer plays an active role in shaping the concept to ensure the feature really would be a solution for them.

Card-sorting

This method involves index cards with written content about a given service or product. The moderator asks the participant to think out loud while organizing cards in ways that make sense to the user.

Diary studies

Diary studies require users to keep a journal or diary of specific experiences and their thoughts around them. These studies typically take longer to complete the data-gathering stage.

Regardless of the method you use for collecting qualitative data, it will generate a large amount of data. For example, if a researcher uses one-on-one discussions or a focus group to collect data, there will be video recordings or written notes to analyze. 

Diary study templates

• Qualitative research data analysis

Qualitative data analysis involves examining data to understand and derive meaning from it. It involves making notes, recording videos or audio, taking photos, or analyzing text documents.

Here are the steps involved in qualitative data analysis:

Prepare and organize your data: This could mean typing notes during sessions, including timestamps, or transcribing your audio.

Review and explore the data:  Check the data for repeated patterns or ideas that emerge.

Create codes for the data and assign them : Develop a set of codes to separate your data into categories and assign them.

Spot recurring themes : Link codes together into overarching, cohesive themes. 

Learn more about qualitative research data analysis software

• When to use qualitative research

Researchers use qualitative research methods to get factual data for in-depth insights. You can use qualitative research when you want to:

Develop a new product or generate an idea.

Understand the problem areas of your product or service thoroughly.

Improve your marketing strategy.

Understand your weaknesses and strengths according to your users.

Deeply explore potential consumers’ motivations, desires, and demographics to understand your company’s role within them.

Figure out how people perceive your brand, product, or services.

Stay well ahead of your competition by knowing your users better than they do.

Qualitative research helps brands understand the underlying motivations and reasons behind consumer behavior and decisions.

• Qualitative research methods vs. quantitative research methods

In a nutshell, qualitative research methods revolve around people's perspectives and their reasoning to solve the “why” and “how.” Quantitative research methods center on measurements and numbers to uncover what is happening and sometimes the timeline in which it happened. 

Together, both research methods help companies get an accurate and in-depth insight into a situation. It’s important to understand their significant differences to know when to employ each.

Here is a table to help you understand how both research methods differ.

What is the most common type of qualitative research?

A detailed interview is the most common type of qualitative research approach.

What is the most common form of qualitative interviewing?

A semi-structured interview is the most common form of qualitative interviewing. User testing is considered a qualitative interview in a one-on-one live environment.

What is the most common method used for qualitative data analysis?

Pattern matching is one of the commonest methods used for qualitative data analysis. Pattern matching involves forming a mental model to categorize all collected data into compartments to compare and evaluate.

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• Open access
• Published: 16 September 2024

A qualitative exploration of disseminating research findings among public health researchers in China

• Yiluan Hu 1 ,
• Xuejun Yin 1 , 2 ,
• Yachen Wang 1 ,
• Enying Gong 1 ,
• Xin Xin 3 ,
• Jing Liu 4 ,
• Xia Liu 4 ,
• Ruitai Shao 1 ,
• Juan Zhang 1 , 5 &
• Ross C. Brownson 6 , 7  

BMC Public Health volume  24 , Article number:  2518 ( 2024 ) Cite this article

106 Accesses

Metrics details

Research dissemination is essential to accelerate the translating of evidence into practice. Little is known about dissemination among Chinese public health researchers. This study aimed to explore the understanding and practices of disseminating research findings and to identify barriers and facilitators that influence dissemination activities to non-research audiences.

This study deployed an exploratory qualitative design with purposive and snowball sampling. One focus group with 5 participants and 12 in-depth interviews were conducted with participants working in diverse fields from universities ( n  = 10), the National Chinese Center for Disease Control and Prevention ( n  = 4), the Chinese National Cancer Center ( n  = 1), the Chinese National Center for Cardiovascular Disease ( n  = 1), and China office of a global research institute ( n  = 1) from May to December 2021 to reach saturation. Data were initially analyzed using inductive thematic analysis. The designing for dissemination (D4D) logic model was then used to organize themes and subthemes. Two coders independently coded all transcripts and discussed disparities to reach a consensus.

Out of 17 participants, 12 misunderstood the concept of dissemination; 14 had disseminated to non-research audiences: 10 to the public, 10 to practitioners, and 9 to policymakers. We identified multiple barriers to dissemination to non-research audiences across four phases of the D4D logic model, including low priority of dissemination, limited application of D4D strategies, insufficient support from the research organizations, practice settings, and health systems, and overemphasis on academic publications.

Conclusions

There was a lack of understanding and experience of dissemination, indicating a lack of emphasis on active dissemination in China. We provide implications for raising awareness, building capacity, facilitating multidisciplinary collaboration, providing incentives and infrastructure, changing climate and culture, establishing communication and executive networks, and accelerating systematic shifts in impact focus.

Peer Review reports

Introduction

The gap between research and practice is well documented [ 1 , 2 , 3 , 4 ]. Dissemination refers to the active approach of spreading evidence-based interventions to the target audience via predetermined channels using planned strategies [ 3 , 5 ] and is a prerequisite for bridging the gap between research and practice. The concept of dissemination has some overlap with other related concepts including science popularization and knowledge translation. Although both use communication techniques as useful strategies, science popularization is mainly about propagating general knowledge to the public with the aim of improving citizens’ science literacy [ 6 ], whereas dissemination involves wider audiences and aims to maximize the impact of research and promote the uptake of evidence. On the other hand, although sharing a similar goal with dissemination of bridging the research-practice gap, knowledge translation refers to the dynamic and iterative process involving synthesis, dissemination, exchange, and ethically-sound application of knowledge, which considers dissemination a component of translation [ 7 , 8 ].

Despite the importance of dissemination, dissemination is often not a priority for researchers and their organization [ 9 ] and is largely missed. For example, in a study of US public health researchers, 78% reported dissemination as important to their research, while only 27% spent over 10% of their time on dissemination [ 3 ] and 28% rated their dissemination efforts as excellent or good [ 10 ]. In addition, there are inconsistencies in preferred sources of information between researchers and non-researchers. Almost all researchers disseminated their research through academic publications [ 11 , 12 , 13 , 14 ], yet practitioners and policymakers may find them inaccessible, difficult to understand, or time-consuming [ 11 , 15 , 16 , 17 ].

To effectively disseminate the evidence, dissemination and implementation (D&I) science has thrived and designing for dissemination (D4D) has emerged as a promising direction within D&I science. The D4D perspective highlights the responsibility of researchers to actively disseminate and the need to plan from the outset to fit the adopters’ needs, assets, and time frames [ 3 ]. Useful D4D strategies include stakeholder involvement, application of D&I science theories and frameworks, incorporation of marketing, business, communication, systems approaches and professionals, and related disciplines [ 3 , 18 , 19 ]. Despite the availability of D4D, the application remains insufficient. For example, only 17% of US public health researchers used a framework or theory to plan their dissemination activities and only 34% typically involved stakeholders in the research process in 2012; 55% of US and Canadian D&I scientists typically involved stakeholders in the research process in 2018. While there is a growing body of evidence on D4D in some regions of the world, there are limited data on D4D from China.

Evidence from high-income countries has revealed individual-level barriers such as lack of capacity and reluctance to disseminate findings of a single study, and organizational-level barriers such as lack of financial resources, staff time, and academic incentives [ 14 , 20 ]. Yet, little is known about dissemination in China, where the D&I science is still in its infancy. With progresses in China’s health reform, science popularization and knowledge translation has received increasing attention, but dissemination received little attention in the field of public health. In addition, the large population, high disease burden, shortage of healthcare providers, and relatively centralized health system further exacerbate the complexity of dissemination in China [ 16 , 21 ]. A quantitative study conducted by the current team among Chinese public health researchers suggested that only 58.1% had disseminated their research findings, and that main barriers included a lack of financial resources, platforms, and collaboration mechanisms at the organizational level, as well as a lack of time, knowledge, and skills at the individual level [ 22 ].

Hence, there is urgency to explore factors underlying the dissemination in China from the perspective of researchers. We aimed to explore researchers’ understanding of the concept of dissemination and current dissemination activities, further to identify barriers and facilitators that influence dissemination to non-research audiences guided by the D4D logic model.

A qualitative study design was deployed to explore public health researchers’ perspectives on contextual factors affecting the dissemination of research findings in China. The study was reported according to the Consolidated criteria for reporting qualitative research (COREQ) guidelines (see Additional file 1) [ 23 ].

Theoretical framework

With the aim to gain insight into the barriers and facilitators for researchers to design for dissemination, this study adopted the D4D logic model as an analytical framework. The D4D logic model was published by Kwan and colleagues [ 19 ] in 2022 and included four phases: (1) the initial conceptualization phase identifying need and demand, and establishing evidence base of health issues; (2) the design phase using multiple strategies to determine the design of dissemination product as well as the packaging, messaging, and distribution plan; (3) the subsequent dissemination phase based on the push-pull-capacity model and situating the push of research, pull of practice, and capacity of health systems to support dissemination; and (4) the impact phase ensuring adoption, sustainment, and equity benefits [ 19 ].

Participants and sampling

Study participants were public health researchers working in universities, the National Chinese Center for Disease Control and Prevention (briefly as China CDC), the Chinese National Cancer Center, the Chinese National Center for Cardiovascular Disease, or China Offices of global research institutes. Universities are the most important producers of evidence in China, followed by healthcare institutions, research institutions, and companies [ 24 ].Teaching and researching are core activities for university researchers, and academic publication is one of the key tenure and promotion criteria. The China CDC is a governmental and national-level technical institution affiliated with the National Health Commission of China, and shoulders the responsibilities of focusing on the key tasks of national disease prevention and control and of instructing the provincial-, prefecture-, city-, and county-level CDC. Also under the leadership of the National Health Commission of China and shoulder responsibilities of evidence generation and implementation, the Chinese National Cancer Center and the Chinese National Center for Cardiovascular Disease are based in two big specialized hospitals in China. Given that university researchers are the biggest community for evidence generation in China, most of the participants were university researchers.

Purposive and snowball sampling methods were applied to reach less accessible target participants. First, participants were purposively selected on the basis that they had rich experience in public health research and took an active part in academia. Second, interviewees were asked to nominate other researchers who might be willing to provide information for in-depth interviews, particularly those with expertise in dissemination and implementation science. All potential participants were contacted directly by telephone by a senior member (JZ) of the research team to seek their participation. Participants were informed of the study’s purpose, process, confidentiality, and right to withdraw at any time. They were then asked to give informed oral consent to participate in the study and to be audio-recorded prior to the formal interview. In total, 18 researchers received the invitation; one declined due to unavailability during the time of this study.

Data collection

Data were collected from May 2021 to December 2021 through a focus group and in-depth interviews. Given that participants may be unfamiliar with the concept of dissemination and the experience of dissemination may be limited, we initially conducted a focus group of five participants to stimulate discussion. During the discussion, participants were actively involved and contributed a lot to the topic, so we later conducted individual interviews to gather a rich and detailed understanding of the participants’ perspectives. The focus group of five participants and the first two individual in-depth interviews were conducted face-to-face, while later ten individual in-depth interviews were conducted via Tencent Meeting (Chinese online meeting software, similar to Zoom) because of the COVID-19-related physical distancing restrictions. During the interviews, participants were alone in their office or a private space to ensure confidentiality so that they could share freely.

A multidisciplinary team of researchers and students in dissemination and implementation science, behavior science, psychology, and qualitative methods contributed to developing the interview guide. The interview guide was pilot tested and refined prior to the formal interview. As dissemination is a relatively new concept in China, participants entered interviews with a discussion about their understanding of this concept. To ensure participants have consistent understanding of dissemination, the interviewer then clarified the concept as the active approach of spreading evidence-based interventions to the target audience via predetermined channels using planned strategies [ 3 , 5 ]. Then, participants were encouraged to have a deep, detailed discussion on their dissemination experience and barriers and facilitators of dissemination to non-research audiences. Participants’ demographic information, which was pre-collected, was confirmed with participants at the end of the interview. The interview guide can be found in supplementary file 2.

All interviews were conducted in Mandarin Chinese by an interviewer experienced in qualitative research (JZ, professor, Ph.D., female) with a note-taker (YH, master’s student, female). No repeat interviews were conducted. The researchers collected participants’ demographic information, research interests, and research projects online before the formal interview to have a deep understanding of their perspectives. All interviews were audio-recorded and transcribed after obtaining oral consent from the interviewees. Transcripts were not returned to participants for comment or correction. Following qualitative research best practices [ 25 , 26 , 27 ], data collection ended when information saturation occurred and no new information was observed.

Data analysis

Data analysis occurred concurrently with data collection. Verbatim transcripts were coded using the inductive thematic analysis approach in NVivo 11 software. First, a coder (YH) reviewed transcripts to generate initial codes and aggregated them into categories to form early themes and subthemes. The D4D logic model [ 19 ] was then used to organize and map the relationships between themes and subthemes. Then, another coder (YW) independently applied codes to transcripts using the same coding framework. The codebook was constantly checked against the transcripts and was finally determined by comparison until no new information was identified. All coding results were compared and discussed between the two coders to reach a consensus. Unsolved discrepancies were resolved through discussion with a senior researcher (JZ) and at research team meetings. Data analysis was conducted in Chinese. All themes, subthemes, and typical verbatim quotes used to illustrate the main themes, were translated into English. Quotes are identified by participants’ ID to guarantee anonymity. Participants did not provide feedback on the findings.

Information saturation was reached after completing a focus group of 5 participants and 12 in-depth individual interviews with public health researchers in China. The interviews took 41.9 ± 10.9 min on average. Participants aged between 32 and 65 years, with an average of 46.5 ± 8.3 years, were primarily female (70.6%), and had a Ph.D. degree (88.2%). They worked in the universities in the field of health policy, behavioral science, global health, and implementation science ( n  = 10), the China CDC in the field of tobacco control, AIDS/STD control, tuberculosis control, and environmental health ( n  = 4), the Chinese National Cancer Center ( n  = 1), the Chinese National Center for Cardiovascular Disease ( n  = 1), and the China office of a global research institute ( n  = 1).

Theme 1: understanding of the concept of dissemination

Five out of 17 participants had no difficulty understanding the concept of dissemination as the active approach of spreading evidence-based interventions to the target audience via predetermined channels using planned strategies, while 12 participants misunderstood dissemination to some extent. Eight participants did not differentiate dissemination of research findings from science popularization of general knowledge when discussing their dissemination activities.

Dissemination means that I share some knowledge with others… I have always paid close attention to new media , and I have written and post some health science articles in Zhihu (Chinese online question-and-answer social media , similar to Quora) … Some online magazines often invite me and my colleagues to write some science articles , for example , I recently wrote an article to share some psychological and behavioral techniques for smoking cessation (Participant 01).

One participant viewed dissemination as knowledge translation, saying that dissemination referred to the process of translating and applying research, especially interventional research, into practice and policy.

I feel that dissemination in Chinese would be easily understood as science popularization , but it actually highlights the translation to the practice and policy , so translating it as ‘knowledge translation’ in Chinese may be more appropriate (participant 16).

Three participants argued that dissemination was similar to health communication, which refers to the communication and sharing of information.

The government is now promoting the awareness of knowledge translation , but I feel that knowledge translation in Chinese emphasizes the process of translating and applying our research , which is more about health technology , and sometimes there may be some commercial elements in knowledge translation. Dissemination is more similar to health communication (participant 14).

Theme 2: experience of dissemination

Subtheme 2.1: dissemination within academia.

Three participants working in the universities mainly published their research findings in peer-reviewed journals or through academic conferences for different reasons: one expressed a lack of resources in reaching non-research audiences, while two showed a lack of motivation, saying that dissemination to non-research audiences was not their priority.

I mainly published my research on peer-reviewed journals… for ordinary researchers like me , access and resources were limited (participant 07). As a researcher , I am very competent when disseminating within academia. Even if I encounter difficulties , I will face them. But for dissemination to practitioners or policymakers , the main disseminator is not me and should not be me… I am a teacher , and my priorities for the next five to ten years include publishing textbooks , participating in academic activities , working with young students , and conducting research (participant 17).

Subtheme 2.2: dissemination beyond academia

Fourteen participants described their experiences disseminating research findings to non-research audiences: 10 had disseminated to the public, 10 to practitioners, and 9 to policymakers. Participants disseminated to the public through social media and mass media. They cited social media as an accessible channel for every individual researcher. However, they felt their personal influence was limited in reaching a wide population, and they needed more resources to use mass media for dissemination. In addition, researchers were worried about possible misinformation and disinformation when disseminating on social media and mass media.

Our impact as a researcher to disseminate is so weak that our research findings posted on WeChat (Chinese social media , similar to WhatsApp and Snapchat) Moments can only be noticed by a few hundred people at most (participant 02). We are not required to add references , and sometimes the already added ones may even be deleted… and because our target audience is the public , we need to translate academic language into plain language… sometimes I am afraid of making scientific mistakes or causing misinformation (participant 01).

Dissemination to policymakers was considered impactful but with a high threshold. A participant indicated that in such cases, dissemination to practitioners was an alternative strategy to influence practice since it was more accessible. Of nine participants who have ever disseminated to policymakers, three worked in China CDC, and five engaged in health policy research.

My organization (China CDC) is a technical support organization for administrative decisions and policy-making , so a lot of our work is done for dissemination (participant 15). For researchers conducting health policy research like me , it is a must to disseminate to our government (participant 08).

Some participants felt the issuance of standards and guidelines ( n  = 4) and publication of patents ( n  = 5) as their dissemination routes. In contrast, some participants thought standards, guidelines, and patents were dissemination products that needed further disseminated, and the issuance of these products did not mean successful dissemination.

The implementation of patents is limited… now patents are mainly used by my peer researchers. Publishing patents does not mean dissemination , and patents themselves actually need to be further disseminated and implemented (participant 15).

Theme 3: facilitators and barriers of dissemination based on the D4D logic model

Factors influencing dissemination to non-research audiences emerged across four phases of the D4D logic model [ 19 ], and seven subthemes were identified: (1) motivation; (2) design processes; (3) packaging and distribution design; (4) push of research; (5) pull of practice; (6) capacity of health systems; and (7) impact of research. The subthemes are discussed in detail below and in Table  1 .

Subtheme 3.1: motivation

Most participants expressed their willingness to disseminate to non-research audiences out of a sense of social responsibility and social recognition, with the exception of two participants who did not consider dissemination to be their priority. Social climate was mentioned as another facilitator of dissemination.

The ultimate goal of scientific research is to change the public’s cognition and behavior , and the government’s decision-making process. If you do not consider dissemination , your research has no value , and it is hard to get recognition from our peers and the public (participant 12).

Subtheme 3.2: design processes

Subtheme 3.2.1: stakeholder involvement and context analysis.

Some participants indicated difficulties building relationships and reaching consensus with stakeholders (e.g., the public, media, practitioners, and policymakers) because of potential conflicts of interest between stakeholders and researchers. Involving stakeholders from the outset, building contacts based on previous relationships, and matching stakeholders’ needs were recommended by participants as helpful for stakeholder involvement. In addition, involving stakeholders from all sectors of society, not only within the health system but also outside of it (e.g., education system, non-governmental organizations, non-profit organizations, and commercial organizations), was thought to have the potential to make a greater influence.

This was based on previous collaboration between their organization and ours , and we have a long-term collaboration with them , so it was quite natural and easy to involve them… We got in touch with them when the research is being formulated. The sooner you can get in touch with stakeholders and get their support , the better… and if we can connect with people and organizations outside the health system , our dissemination efforts may have a greater impact and be more sustainable (participant 13).

Subtheme 3.2.2: application of D&I methodologies

The application of D&I methodologies was stressed as a facilitator of dissemination. However, some participants indicated that D&I science was still an emerging field in China, the limited understanding of D&I methodologies impeded the dissemination and implementation of research.

Currently , there is limited knowledge of methodologies including research design , theoretical frameworks , and qualitative methods for D&I science in China , which hinders the dissemination and implementation of research (participant 16).

Subtheme 3.2.3: marketing and business approaches

Some participants mentioned that the field of marketing was quite relevant to dissemination design and that marketing and communication approaches were promising for dissemination to non-research audiences, especially to the general public.

Take food marketing in food policy as an example , I feel that Coke’s advertising is so good that I also want to drink it; on the contrary , if you simply tell me not to eat food high in sugar and salt , then I will just not listen , let alone the ordinary consumers (participant 06).

Subtheme 3.2.4: context and situation analysis

Conducting context and situation analysis was cited as the foundation for understanding context and tailoring dissemination efforts.

Health communication always emphasizes needs assessment and audience segmentation , and it is important to understand the audiences’ needs. In many cases , what we were doing did not meet the needs of our audiences , and they did not accept (participant 04).

Subtheme 3.2.5: complexity of social, health, organizational, and political systems

Participants perceived policy resistance and low confidence in disseminating research with negative, politically or economically sensitive findings in complex social, health, organizational, and political systems. In addition, some participants noted that the COVID-19 pandemic increased the uncertainty of research findings and the vulnerability of collaboration networks.

For example , research involving the control of the tobacco industry , which is related to the economy , is very sensitive (participant 06). At first , everything went well , and they were very supportive. But because of the COVID-19 pandemic , the organization changed leadership , so we had to communicate with them again (participant 13).

Subtheme 3.3: packaging and distribution design

Subtheme 3.3.1: capability of packaging.

Participants indicated that integrating and packaging for non-research audiences was difficult and time-consuming and could be irregular and misleading, which calls for special competencies that differ from usual academic training.

It is demanding , requiring a high level of processing , summarizing , writing , and packaging skills. These are huge challenges that our daily training does not teach us (participant 12).

Subtheme 3.3.2: availability of distribution channels and platforms

The availability of channels and platforms was highlighted as an important contextual factor affecting dissemination. Those in the early stages of their careers, who had not yet established academic influence, expressed a lack of access to channels to interact with policymakers who were beyond the reach of individual researchers. Leveraging existing channels, platforms, and programs was recommended to facilitate dissemination to intended audiences.

Especially , we young researchers actually have many ideas and know a lot , but we do not have channels to share (participant 01). It is important to consider taking advantage of existing platforms or programs and hitching a ride whenever possible. Otherwise , dissemination involves a lot of financial and personnel input (participant 13).

Subtheme 3.4: push of research

Subtheme 3.4.1: incentives.

Academic publications were cited as the chief yardstick of performance evaluation, promotion requirements, and grant obligations. Some participants stated that the extent of dissemination to policymakers would also influence performance evaluation but were not given the same importance as academic publications. This was attributed by some participants to the difficulty in quantifiably evaluating dissemination activities. Although the China CDC participants expressed less pressure for academic publication than their university counterparts, they also complained about the academic incentive systems.

Dissemination to policymakers is now considered in performance evaluation , but still not as much as publishing papers on peer-reviewed journals… they may never regard dissemination as the most important criterion (participant 06). Currently , the value of science is still limited to publication and ‘Impact Factor’… Another problem is that it is difficult to define our dissemination efforts. For example , I cannot say how many people are using my APP and how much impact it burst , but I can say how many papers I have published in top journals (participant 11).

Subtheme 3.4.2: infrastructure

Seven participants reported having a dedicated person or team responsible for dissemination-related activities in their organization. These persons or teams served mainly for patent applications, communication, and publicity.

We have a Development Office dedicated for knowledge translation. They would organize seminars on dissemination like how to apply for patents (participant 14). The attitude of the communication platform in our school is very clear , and its purpose is to build prestige for our school. If we have proper research to disseminate , they will help with propaganda (participant 17).

Some participants mentioned that their organization would provide additional support, such as administrative facilitation, to help them disseminate more smoothly.

In addition to providing administrative costs , our university also provides intangible support for the development of D&I science and for the coordination of different departments (participant 16).

Subtheme 3.5: pull of practice

Participants noted a lack of climate or culture to support dissemination mainly because of the lack of priority given to some health issues themselves and the dissemination activities among leaders and practitioners.

The national government is advocating the dissemination and implementation of many innovations , but the local government may find it difficult to understand the value of (disseminating) these innovations and may not be unwilling to provide financial or personnel support (participant 10). We introduced our research and why we wanted to work with them to disseminate it , but they said that was not their focus. Then what was their focus at that time? All they wanted to do was help village doctors to pass a qualification exam and select the ‘most beautiful village doctor’. They were not interested in our dissemination of chronic diseases (participant 17).

Subtheme 3.6: capacity of health systems

Subtheme 3.6.1: communication networks.

The lack of networks between researchers and non-research audiences was cited as a barrier. Some researchers expected the health systems to build mechanisms for bidirectional communication networks between researchers and non-research audiences.

There is no mechanism to collaborate us with non-research audience… some researchers may have such relationships with non-research audiences , but that is out of their personal impact and efforts rather than the mechanisms in the health system (participant 02). There is a gap between researchers and policymakers in the academic system… maybe our organization could help bridge the gap. For example , the organization could build a system to collect our research findings regularly and disseminate to policymakers because universities have this kind of relationship with the government (participant 07).

Subtheme 3.6.2: executive networks

Executive network in the health system was considered necessary for dissemination on a large scale but difficult for ordinary university researchers to have. A participant in the China CDC pointed out that although the top-down CDC system in China, including CDCs at national, provincial, city, and county levels, could facilitate wide dissemination, their dissemination impact was still limited by the lack of human resources for public health.

Our dissemination success has benefited greatly from the solid executive network built before. For example , under the Chinese National Cancer Center , we have Cancer Prevention Offices at the provincial level. They could help us disseminate our research findings , like our evidence and apps. However , most researchers , especially university researchers , do not have such an objective support network (participant 11). The lack of human resources in public health is one of the most common problems in our country. For example , we have 40 staff working on tuberculosis at the China CDC , but only 10 at each provincial CDC , and 2 at each county CDC. In many cases , there are even half a person in counties working on tuberculosis (participant 10).

Subtheme 3.7: impact of research

Participants noted a chasm between overemphasis on academic publications and ignorance of long-term impact in the current academic system. Despite a series of national policies designed to break the undesirable orientation of “academic publications only” issued by the Chinese government, participants were pessimistic about them. They stated that the interpretation and implementation of these policies need to be further reviewed and improved.

Dissemination to non-research audiences is not expected by my organization , which does not care about these activities. However , it is the government that holds the baron , and there is nothing my organization can do about it. (participant 09). At present , national policies are developing and changing fast , but how to interpret and implement these policies needs to be gradually improved… our government is paying more and more attention to dissemination , but when it comes to the implementation level , there are still many shortcomings (participant 14).

This qualitative study explored the understanding and practices of dissemination, and further identified the barriers and facilitators of dissemination, which may be the first of this type in China. We found a lack of understanding of the concept and inadequate practices of dissemination to non-research audiences among Chinese public health researchers. We also identified barriers and facilitators in the conceptualization, design, dissemination, and impact phases of the D4D logic model [ 19 ], suggesting considerable room for improvement in the application of D4D strategies and the development of systematic resources. Our findings begin to provide a roadmap of ideas and actions to improve the active dissemination of research in China.

Dissemination was poorly understood by Chinese public health researchers, who confused it with some related concepts such as communication, science popularization, and knowledge translation, indicating a lag in the development and advocacy of dissemination in China. The lag in development and the lack of understanding of dissemination may hinder the dissemination practice and the uptake of evidence. Hence, dissemination, which highlights taking an active approach, identifying target audience, selecting predetermined channels, and using planned strategies to disseminate, should be deeply rooted in researchers’ mind to facilitate research uptake and understanding.

The public, practitioners, and policymakers were identified as three key non-research audiences for dissemination, yet most only gave a brief description when asked about their dissemination practices. While the internet and media are promising for large-scale dissemination, there is a need to strengthen the capacity of researchers to address misinformation and disinformation [ 28 , 29 ] and to facilitate collaboration between researchers and the media to achieve wide dissemination in China. Dissemination to the public and practitioners is considered as feasible and direct, while dissemination to policymakers as crucial for long-term impact. Indeed, the Chinese government holds accountability for the health of people, and proactively disseminating research findings to policymakers and government officials helps make a a greater public health impact. Nevertheless, the participants faced the dilemma of lacking personal relationships and access to channel to interact with policymakers. Although some academic associations (e.g., the Chinese Preventive Medicine Association) bring together researchers and practitioners in China, their potential to connect researchers and policymakers needs to be further strengthened to lead to dissemination success. Most of the participants with experience of dissemination in policy dissemination were those working in the China CDC or engaged in health policy research: the former stressed the mission of the China CDC to provide technical support for policy-making, and the latter stated that influencing policy was the fundamental goal of health policy research. This also suggests that organizations and researchers with stronger missions and resources to influence policy may have greater opportunities to disseminate to policymakers.

Although few in this study explicitly stated that dissemination to non-research audiences was not their priority, a lack of design capacity and distribution channels among researchers, insufficient support in organizations and the health systems, and an overemphasis on academic publications hindered dissemination to non-research audiences. First, there was a limited application of D4D strategies in the design of dissemination products, packaging and distribution plans. This is consistent with other studies suggesting that the lack of capacity was a common barrier to dissemination practice in low- and middle-income countries [ 30 ]. A good news was that Chinese researchers were actively involved diverse stakeholders at multiple stages of their research, which is consistent with the international trend of increasing emphasis on stakeholder engagement [ 31 , 32 ]. A survey of US and Canadian researchers in 2018 also revealed increases in stakeholder involvement compared to a survey of US researchers in 2012 [ 3 , 33 ]. However, there was a need to build multisectoral partnerships and improve stakeholder involvement’s depth and quality [ 32 ]. In addition, some researchers were aware of the potential for leveraging methods and frameworks from D&I science, marketing and business, communications and visual arts, and systems science to achieve dissemination success, yet the practical application needed to be improved. These disciplines (e.g., D&I science, marketing, systems science, and complexity science) originated from abroad and may not seem familiar to the Chinese public health researchers, it may require a lengthy learning and adaptation process. There are some simple tools and principles for guidance [ 34 ]. Notably, not all research finding should be disseminated to all audiences, the ability of deciding what to disseminate and to whom to disseminate should be strengthened in initial stage. Therefore, it is necessary to build capacity in the D4D principles and skills and to promote teaming across disciplines, as it may be unrealistic for public health researchers to develop all the D4D skills [ 13 ].

In addition to the need to improve researchers’ capacity and partnership across disciplines, there remained substantial room for improvement in the resources and structures that support dissemination. Specifically, there was a lack of incentives and infrastructure in research organizations (the push), a lack of climate and culture in practice or policy settings (the pull), and a lack of dissemination networks in the health system (the capacity). The persistent push–pull disconnect between researchers and practitioners was reported in other study [ 35 , 36 ]. As might have been expected, academic publications were the main criteria for performance evaluation, which may also be true in many other countries [ 10 , 14 , 33 , 37 , 38 , 39 ]. Furthermore, although some participants reported having a dedicated person or team for dissemination-related activities, the responsibilities of these dedicated persons or teams need to be further clarified and their capacity needs to be further enhanced. On the other hand, previous research points out that attention to dissemination tends to focus more on the push side than the pull and capacity sides [ 11 , 19 ]. For example, studies in the US suggested that 53% of researchers reported having a designated individual or team for dissemination [ 3 ] while only 20% of practitioners reported so [ 40 ]. Thus, changing the climate and culture in practice or policy settings to be receptive and prepared for dissemination, providing infrastructure to enhance communication between researchers and non-research audiences, and building executive networks to support wide dissemination are needed as a lack of platforms and collaboration mechanisms is also a common barrier to dissemination [ 30 ].

Problems with the lack of push, pull, and capacity for dissemination may be partly attributed to overemphasizing academic metrics rather than the long-term health and equity impacts. Several government funding agencies in developed countries have adopted policies to support or even require dissemination efforts [ 12 , 19 , 41 , 42 , 43 ]. Yet most funding agencies in China still focus on academic impact, existing fundings for dissemination in China are small in terms of its scale and are competitive to apply for. To address this issue, the Chinese government has adopted a series of national policies to reduce the overemphasis on academic publications and improve the evaluation system [ 44 , 45 , 46 , 47 ]. However, policy interpretation and grassroots implementation need to be further improved to accelerate the system shift to focus on the long-term impact of research. Frameworks such as the Research Excellence Framework (REF) [ 48 ] and the Translational Science Benefits Model (TSBM) [ 49 ] provide an outline and benchmarks by which researchers can measure the impact of scientific discoveries beyond traditional academic metrics.

This study revealed important aspects regarding research dissemination in China from the perspective of researchers with some limitations. First, 17 interview participants may not fully reflect the full spectrum in China although data saturation was reached. Given that dissemination is in its infancy in China, this study plays an initial study and future studies may need to involve more and more diversified participants to reveal dissemination of the whole research system in China. Second, some interviews were conducted online due to the COVID-19 pandemic, which limited the ability to gain information from contextual details and nonverbal expressions during the interviews. Third, the study is a qualitative exploratory study, additional large-scale quantitative studies are needed to triangulate the findings across the broader population. Indeed, the research team has run a large-scale survey to examine the attitudes and practices of Chinese public health researchers towards dissemination.

This study highlights a lack of emphasis on active dissemination in China and identifies multiple barriers to dissemination. There is a need to advance the field to promote understanding and raise awareness of dissemination—with the goal of ultimately more rapidly and equitably moving evidence to practice and policy. There is also a need to build capacity in D4D and to collaborate with experts from multiple disciplines (e.g., marketing, systems science, complexity science) to break down disciplinary silos. The findings also provide implications for promoting training programs, providing incentives and infrastructure for diverse dissemination activities, creating a climate and culture of readiness for dissemination, establishing bidirectional communication networks and efficient executive networks, and accelerating systematic shifts in policy orientation. Otherwise, dissemination is likely to sink to low priority in the already over-stretched system.

Data availability

All the data and materials of this qualitative study are available from the corresponding author on reasonable request.

Abbreviations

designing for dissemination

dissemination and implementation

National Chinese Center for Disease Control and Prevention

Balas EA, Boren SA. Managing clinical knowledge for Health Care Improvement. Yearb Med Inf. 2000;1:65–70.

Lenfant C. Shattuck lecture–clinical research to clinical practice–lost in translation? N Engl J Med. 2003;349(9):868–74. https://doi.org/10.1056/NEJMsa035507 .

Article   PubMed   Google Scholar  

Brownson RC, Jacobs JA, Tabak RG, et al. Designing for dissemination among public health researchers: findings from a national survey in the United States. Am J Public Health. 2013;103(9):1693–9. https://doi.org/10.2105/ajph.2012.301165 .

Article   PubMed   PubMed Central   Google Scholar  

Brownson RC, Eyler AA, Harris JK, et al. Getting the Word Out: New approaches for disseminating Public Health Science. J Public Health Manag Pract. 2018;24(2):102–11. https://doi.org/10.1097/PHH.0000000000000673 .

Rabin BA, Brownson RC. Terminology for dissemination and implementation research. In: Brownson RC, Colditz GA, Proctor EK, editors. Dissemination and Implementation Research in Health: translating Research to Practice. New York: Oxford University Press; 2018. p. 22.

Google Scholar  

Qiu J. Science communication in China: a critical component of the global science powerhouse. Natl Sci Rev. 2020;7(4):824–9. https://doi.org/10.1093/nsr/nwaa035 .

Canadian Institutes of Health Research. Section 1.1 Knowledge to action: what it is and what it isn’t [online]. https://cihr-irsc.gc.ca/e/41928.html (accessed 22 Feb 2023).

McCormack L, Sheridan S, Lewis M, et al. Communication and dissemination strategies to facilitate the use of health-related evidence. Evid Rep Technol Assess (Full Rep). 2013;2131–520. https://doi.org/10.23970/ahrqepcerta213 .

National Cancer Institute. Designing for Dissemination: Conference Summary Report. Washington, DC: National Cancer Institute; 2002.

Tabak RG, Stamatakis KA, Jacobs JA, et al. What predicts dissemination efforts among public health researchers in the United States? Public Health Rep. 2014;129(4):361–8. https://doi.org/10.1177/003335491412900411 .

Brownson RC, Fielding JE, Green LW. Building Capacity for evidence-based Public Health: reconciling the pulls of Practice and the push of Research. Annu Rev Public Health. 2018;39:27–53. https://doi.org/10.1146/annurev-publhealth-040617-014746 .

Wilson PM, Petticrew M, Calnan MW, et al. Does dissemination extend beyond publication: a survey of a cross section of public funded research in the UK. Implement Sci. 2010;5:61. https://doi.org/10.1186/1748-5908-5-61 .

Tabak RG, Reis RS, Wilson P, et al. Dissemination of Health-Related Research among scientists in three countries: Access to resources and Current practices. Biomed Res Int. 2015;2015:179156. https://doi.org/10.1155/2015/179156 .

McVay AB, Stamatakis KA, Jacobs JA, et al. The role of researchers in disseminating evidence to public health practice settings: a cross-sectional study. Health Res Policy Syst. 2016;14(1):42. https://doi.org/10.1186/s12961-016-0113-4 .

Harris JK, Allen P, Jacob RR, et al. Information-seeking among chronic disease prevention staff in state health departments: use of academic journals. Prev Chronic Dis. 2014;11:E138. https://doi.org/10.5888/pcd11.140201 .

Budd EL, deRuyter AJ, Wang Z, et al. A qualitative exploration of contextual factors that influence dissemination and implementation of evidence-based chronic disease prevention across four countries. BMC Health Serv Res. 2018;18(1):233. https://doi.org/10.1186/s12913-018-3054-5 .

Jin Y, Li Z, Han F, et al. Barriers and enablers for the implementation of clinical practice guidelines in China: a mixed-method study. BMJ Open. 2019;9(9):e026328. https://doi.org/10.1136/bmjopen-2018-026328 .

Ashcraft LE, Quinn DA, Brownson RC. Strategies for effective dissemination of research to United States policymakers: a systematic review. Implement Sci. 2020;15(1):89. https://doi.org/10.1186/s13012-020-01046-3 .

Kwan BM, Brownson RC, Glasgow RE, et al. Designing for Dissemination and sustainability to Promote Equitable impacts on Health. Annu Rev Public Health. 2022;43:331–53. https://doi.org/10.1146/annurev-publhealth-052220-112457 .

Long CR, Purvis RS, Flood-Grady E, et al. Health researchers’ experiences, perceptions and barriers related to sharing study results with participants. Health Res Policy Syst. 2019;17(1):25. https://doi.org/10.1186/s12961-019-0422-5 .

Zhao J, Bai W, Zhang Q, et al. Evidence-based practice implementation in healthcare in China: a living scoping review. Lancet Reg Health West Pac. 2022;20:100355. https://doi.org/10.1016/j.lanwpc.2021.100355 .

Hu Y, Yin X, Gong E et al. Are public health researchers designing for dissemination? Findings from a national survey in China [in review]. Implement Sci Commun 2023.

Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. 2007;19(6):349–57. https://doi.org/10.1093/intqhc/mzm042 .

Ministry of Science and Technology of China. Summary of academic publications of China in 2020 [online]. 2022. https://www.most.gov.cn/xxgk/xinxifenlei/fdzdgknr/kjtjbg/kjtj2022/202209/P020220920391756277580.pdf (accessed 22 Feb 2023).

Guest G, Bunce A, Johnson L. How many interviews are Enough?An experiment with data saturation and variability. Field Methods. 2006;18(1):59–82. https://doi.org/10.1177/1525822x05279903 .

Article   Google Scholar  

Saunders B, Sim J, Kingstone T, et al. Saturation in qualitative research: exploring its conceptualization and operationalization. Qual Quant. 2018;52(4):1893–907. https://doi.org/10.1007/s11135-017-0574-8 .

Vasileiou K, Barnett J, Thorpe S, et al. Characterising and justifying sample size sufficiency in interview-based studies: systematic analysis of qualitative health research over a 15-year period. BMC Med Res Methodol. 2018;18(1):148. https://doi.org/10.1186/s12874-018-0594-7 .

Green LW, Fielding JE, Brownson RC. More on fake news, disinformation, and countering these with Science. Annu Rev Public Health. 2021;42:v–vi. https://doi.org/10.1146/annurev-pu-42-012821-100001 .

Hagg E, Dahinten VS, Currie LM. The emerging use of social media for health-related purposes in low and middle-income countries: a scoping review. Int J Med Inf. 2018;115:92–105. https://doi.org/10.1016/j.ijmedinf.2018.04.010 .

Murunga VI, Oronje RN, Bates I, et al. Review of published evidence on knowledge translation capacity, practice and support among researchers and research institutions in low- and middle-income countries. Health Res Policy Syst. 2020;18(1):16. https://doi.org/10.1186/s12961-019-0524-0 .

Boaz A, Hanney S, Borst R, et al. How to engage stakeholders in research: design principles to support improvement. Health Res Policy Syst. 2018;16(1):60. https://doi.org/10.1186/s12961-018-0337-6 .

Triplett NS, Woodard GS, Johnson C, et al. Stakeholder engagement to inform evidence-based treatment implementation for children’s mental health: a scoping review. Implement Sci Commun. 2022;3(1):82. https://doi.org/10.1186/s43058-022-00327-w .

Knoepke CE, Ingle MP, Matlock DD, et al. Dissemination and stakeholder engagement practices among dissemination & implementation scientists: results from an online survey. PLoS ONE. 2019;14(11):e0216971. https://doi.org/10.1371/journal.pone.0216971 .

Article   PubMed   PubMed Central   CAS   Google Scholar  

Ross-Hellauer T, Tennant JP, Banelytė V, et al. Ten simple rules for innovative dissemination of research. PLoS Comput Biol. 2020;16(4):e1007704. https://doi.org/10.1371/journal.pcbi.1007704 .

Brownson RC. Bridging Research and Practice to Implement Strategic Public Health Science. Am J Public Health. 2021;111(8):1389–91. https://doi.org/10.2105/ajph.2021.306393 .

Bero LA, Grilli R, Grimshaw JM, et al. Closing the gap between research and practice: an overview of systematic reviews of interventions to promote the implementation of research findings. Cochrane Effective Pract Organ Care Rev Group BMJ. 1998;317(7156):465–8. https://doi.org/10.1136/bmj.317.7156.465 .

Article   CAS   Google Scholar  

Moore JB, Maddock JE, Brownson RC. The role of dissemination in Promotion and Tenure for Public Health. J Public Health Manag Pract. 2018;24(1):1–3. https://doi.org/10.1097/phh.0000000000000691 .

Tabak RG, Padek MM, Kerner JF, et al. Dissemination and implementation Science Training needs: insights from practitioners and researchers. Am J Prev Med. 2017;52(3 Suppl 3):S322–9. https://doi.org/10.1016/j.amepre.2016.10.005 .

McNeal DM, Glasgow RE, Brownson RC, et al. Perspectives of scientists on disseminating research findings to non-research audiences. J Clin Transl Sci. 2020;5(1):e61. https://doi.org/10.1017/cts.2020.563 .

Shato T, Kepper MM, McLoughlin GM, et al. Designing for dissemination among public health and clinical practitioners in the USA. J Clin Transl Sci. 2024;8(1):e8. https://doi.org/10.1017/cts.2023.695 .

Smits PA, Denis J-L. How research funding agencies support science integration into policy and practice: an international overview. Implement Sci. 2014;9:28. https://doi.org/10.1186/1748-5908-9-28 .

Glasgow RE, Vinson C, Chambers D, et al. National Institutes of Health approaches to dissemination and implementation science: current and future directions. Am J Public Health. 2012;102(7):1274–81. https://doi.org/10.2105/ajph.2012.300755 .

McLean RK, Graham ID, Bosompra K, et al. Understanding the performance and impact of public knowledge translation funding interventions: protocol for an evaluation of Canadian Institutes of Health Research knowledge translation funding programs. Implement Sci. 2012;7:57. https://doi.org/10.1186/1748-5908-7-57 .

General Office of the Communist Party of China Central Committee, the State Council of China. Opinions on deepening the reform of project evaluation, talent evaluation and institutional assessment [online]. 2018. http://www.gov.cn/zhengce/2018-07/03/content_5303251.htm (accessed 22 Feb 2023).

Ministry of Science and Technology of China. Measures to Break the Undesirable Orientation of. Academic Publications Only in Scientific and Technological Apprasials (for trial implementation) [online]. 2020. http://www.most.gov.cn/xxgk/xinxifenlei/fdzdgknr/fgzc/gfxwj/gfxwj2020/202002/t20200223_151781.html (accessed 22 Feb 2023).

General Office of the State Council of China. Guiding opinions on improving the scientific, technological achievements evaluation system [online]. 2021. http://www.gov.cn/gongbao/content/2021/content_5631817.htm (accessed 22 Feb 2023).

Ministry of Science and Technology of China. Work plan on the piloting of the evaluation reform of scientific and technological talents [online]. 2022. http://www.gov.cn/zhengce/zhengceku/2022-11/10/content_5725957.htm (accessed 22 Feb 2023).

Jensen EA, Wong P, Reed MS. How research data deliver non-academic impacts: a secondary analysis of UK Research Excellence Framework impact case studies. PLoS ONE. 2022;17(3):e0264914. https://doi.org/10.1371/journal.pone.0264914 .

Luke DA, Sarli CC, Suiter AM, et al. The translational science benefits model: a New Framework for assessing the Health and Societal benefits of clinical and Translational sciences. Clin Transl Sci. 2018;11(1):77–84. https://doi.org/10.1111/cts.12495 .

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Acknowledgements

We would like to acknowledge the support of all participants.

This work was supported in part by Disciplines Construction Project: Population Medicine (number WH10022022010) and Disciplines construction project: Multimorbidity (number WH10022022034). RCB is supported by the US National Cancer Institute (number P50CA244431), the National Institute of Diabetes and Digestive and Kidney Diseases (numbers P30DK092950, P30DK056341), and the Centers for Disease Control and Prevention (number U48DP006395), and the Foundation for Barnes-Jewish Hospital.

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JZ, RS, and RCB obtained funding. JZ, RS, RCB, and YH were responsible for the conceptualization and design of the study. JZ, RS, YH, XY, EG, and XX developed the interview guide. JZ, YH, JL, and XL collected data. YH and YW analyzed the data. YH wrote the first draft. JZ, RCB, RS, YH, and YW edited the manuscript. All authors approved the final version for submission.

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This study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Ethics Committee for Biomedical Research Projects involving Humans of the Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS&PUMC-IEC-2021-12) on March 15, 2021. Informed consent was obtained from all participants involved in the study. Consent included permission to be audio-recorded.

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Hu, Y., Yin, X., Wang, Y. et al. A qualitative exploration of disseminating research findings among public health researchers in China. BMC Public Health 24 , 2518 (2024). https://doi.org/10.1186/s12889-024-19820-z

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• Using an anti-racist research framework to design studies of oral human papillomavirus and oropharyngeal cancer in San Francisco: rationale and protocol for the Health Equity and Oral Health in People living with HIV (HEOHP) qualitative study
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• http://orcid.org/0000-0002-5869-4514 Alexandra L Hernandez 1 , 2 ,
• Elena O Lingas 3 ,
• William Juarez 1 ,
• Alessandro Villa 4 ,
• Joel Palefsky 1
• 1 Department of Medicine , University of California San Francisco , San Francisco , California , USA
• 2 Public Health Program , Touro University California College of Education and Health Sciences , Vallejo , California , USA
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• Correspondence to Dr Alexandra L Hernandez; alexandra.hernandez{at}ucsf.edu

Introduction The goal of our research programme is to develop culturally appropriate patient-specific interventions for primary and secondary prevention of human papillomavirus (HPV)-related oropharyngeal cancer (OPC) among people living with HIV (PLWH); PLWH are at a higher risk for OPC than the general population and, as with many cancers, there are disparities in OPC health outcomes by race and ethnicity. Our study incorporates an anti-racist research framework that proposes considering racism as a foundational sociocultural system that causes ill health. We expand the framework to include biases due to gender, sexual orientation, HIV status and membership in other non-dominant groups. Our research programme focuses on HPV-related OPC among people living with PLWH, and on how intersecting identities may impact an individual’s experience with oral health, obtaining regular and appropriate oral healthcare, knowledge and perceptions of oral HPV infection, risk factors for OPC and HPV vaccination.

Methods and analysis We will follow a grounded theory (GT) qualitative research methodology using focus group discussions (FGDs) to collect data. We will invite PLWH with intersecting identities to participate in one of 12–18 FGDs with 5–8 participants per group. Focus groups will be formed based on self-reported domains, including race, ethnicity, gender identity, sexual orientation and other identities that could impact oral health, such as smoking status, experience with homelessness or experience with drug use disorders. We do not know which aspects of intersecting identities are most salient to accessing oral healthcare. Using FGDs will allow us to gain this knowledge in a setting where participants can build on and reinforce shared understandings about oral healthcare. Following our GT methodology, analysis will occur concurrently with data collection, and emerging concepts or theories may result in changes to focus group guide questions. Initial focus group questions will be organised around our main objectives: (1) to identify individual, interpersonal and structural health equity factors that serve as barriers or facilitators to oral health status and care; (2) to explore knowledge and perceptions about causes, risk factors, prevention and screening for oral or OPC and (3) to elicit recommendations for improving access to regular and appropriate oral healthcare and suggestions on engaging PLWH from diverse identity groups in prevention interventions.

Ethics and dissemination All methods and procedures were approved by the University of California, San Francisco, Institutional Review Board (approval number: 23-39307) and are in accordance with the Declaration of Helsinki of 1975, as revised in 2000. Participants are required to provide informed consent. The results of this study will be presented at scholarly meetings and published in peer-reviewed journals. In addition, a lay summary of results will be created and distributed to our participants and community through our website and social media.

Trial registration number NCT06055868 .

• Health Equity
• ORAL MEDICINE
• HIV & AIDS
• HPV Infection

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2024-091474

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STRENGTHS AND LIMITATIONS OF THIS STUDY

This study is the first step in a research programme using an anti-racist research framework that considers intersecting identities as factors in the oral health experiences of people living with HIV (PLWH).

The study uses grounded theory as the qualitative research methodology, facilitating the emergence of theories from the study participants and the gathered data.

The study recruits participants from an established clinic with a diverse patient population, enabling a large number of focus groups to ensure a diversity of viewpoints and strengthen the theories generated.

The research focus on PLWH with intersecting non-dominant identities and oral health status means we may miss important information on oral health experiences unique to individuals whose identities are in the majority; further studies with PLWH who identify with dominant groups will be needed.

This study is based in the densely populated San Francisco Bay Area and the results may not be generalisable to smaller or rural communities or communities that experience different levels of discrimination, bias and stigma or that have more limited access to HIV care and other healthcare resources.

Introduction

Background and rationale, anti-racist/anti-intersectional bias research framework.

Racial injustice remains a fundamental cause of health inequities in the USA. 1 There are vast disparities in health outcomes, including physical, mental, social, emotional and oral health, by race and ethnicity. 1 The impact of race/ethnicity on health is manifested in multiple domains, including structural, interpersonal and individual experiences. 2 3 Anti-racist scholarship asks researchers to apply frameworks that consider racism as a foundational sociocultural system that can cause ill health 2–5 to completely understand the results of research on health-related outcomes. An anti-racist research agenda considers race at the beginning of a research program to shape not only the conduct and interpretation of the research study but also what research questions to pursue in the first place. 3 4 We expand this framework to include intersectionality 6 or the understanding that individuals may have multiple social identities in addition to race/ethnicity that interact and may contribute to experiences of discrimination, stigma or social isolation; for example, membership in a sexual and gender minority group (SGM) or being a person living with HIV. These complex intersectional identities may put individuals at an even greater risk of ill health than merely the sum of the individual risks alone.

The goal of our research programme is to develop culturally appropriate patient-specific interventions for primary and secondary prevention of human papillomavirus (HPV)-related oropharyngeal cancer (OPC) among people living with HIV (PLWH). We focus on PLWH because they are at the highest risk for OPC. Following our anti-racist/anti-intersectional bias research framework, we begin our program with a study to explore experiences with oral health and oral healthcare access among PLWH with intersecting identities, seeking to understand why there may be differences in oral health status and how we may begin to address these differences to achieve optimal oral health for all.

HPV-associated OPC

OPC is the most common HPV-associated cancer among men in the general population 7 and the incidence has been rising in the USA over the past three decades. 8 9 The prevalence of HPV DNA detected in OPC rose from 16.3% between 1984 and 1989 to 71.7% between 2000 and 2004. 8 Among men in the general population, the incidence of cancer of the oropharynx is now higher than the incidence of cervical cancer among women (8.9 per 100 000 men vs 7.3 per 100 000 women, respectively, data from 2013 to 2018). 7 While studies that combine HPV and non-HPV OPCs show that the increase in incidence is primarily in white men, the incidence of HPV-OPC specifically is also increasing in communities of colour. 10

PLWH are at an increased risk for all cancers associated with HPV, including cervical cancer, anal cancer and HPV-OPC. 11–14 PLWH are also at increased risk of HPV infection, the necessary causal agent for HPV-associated cancers and are more likely to have persistent HPV infection than those in the general population. 15–17 PLWH have an estimated 1.6–6.0 times increased risk of developing OPC compared with individuals in the general population. 13 18–20

There are also differences in OPC-related health outcomes by racial/ethnic group. Whites have higher incidences of OPC 21 while those with OPC categorised as African American/Black have worse survival rates. 22–25 Other disparities include a later stage of diagnosis and less frequent cancer-directed treatment among ethnic minority groups. 22 24 The hypotheses posited for these differences include manifestations of structural racism, such as the higher prevalence of smoking among African American/Black individuals, 26 lack of health insurance 27 and surgery at lower-quality hospitals. 28 29 Awareness that HPV vaccination prevents OPC among Asian, African American/Black and Hispanic groups is lower than among whites 30 and HPV vaccination rates differ by racial/ethnic group and age. 31 Few data examine the intersectionality of being a member of a racial/ethnic minority group living with HIV and OPC.

To curb this rise in OPC incidence, we need targeted interventions for those at increased risk for OPC or with poor OPC health outcomes, such as PLWH or PLWH who are also members of racial/ethnic minority groups. Prevention could include HPV vaccination, referral for vaccination, health education or screening/early detection. Prevention efforts could be coordinated through a dental clinic or through an oral healthcare provider.

Racial and ethnic disparities in oral healthcare in the general population

The USA spends more per capita on healthcare than any other country, yet has some of the poorest health outcomes. 32 While healthcare policy reforms such as the Patient Protection and Affordable Care Act (ACA) drove the number of uninsured Americans to historic lows, 33 adult dental care did not make the list of ‘essential health benefits’ included in policies offered by the ACA’s online insurance marketplace. 34 Millions of adults go without dental care every year, including people of colour, those with lower-than-average incomes and those with low educational attainment. 35 For example, African American/Black Americans and Mexican Americans are almost twice as likely to have untreated dental caries as those who identify as white. 36 Racism in dental care is being newly identified as one of the major contributors to poor dental health outcomes in non-white Americans. 37

Although differences in oral health outcomes by race/ethnicity have not been specifically studied in PLWH, it stands to reason that people of colour living with HIV will also be impacted by structural racism in oral healthcare. Although PLWH can obtain dental care through the Ryan White Care Act, 38 more than half of PLWH have unmet oral care needs, and 58%–64% do not receive regular dental care. 38 While oral health concerns have different aetiologies and treatments, the dentist’s office is often the first point of contact when problems arise.

Other discrimination and stigma faced by PLWH

PLWH face stigma and/or discrimination from living with HIV, including in the dental office. 39 Like racism, HIV stigma occurs at multiple levels, including individual, community and institutional. 39 40 Indicators of HIV stigma in a healthcare setting may include the use of excessive personal protective equipment and unnecessary referrals to specialists. 39 PLWH may have intersectionality with SGM groups, and there is additional stigma and discrimination faced by members of an SGM. 41–43

The combination of race, ethnicity and being part of a sexual or gender minority group could impact the ability of PLWH to access oral healthcare and their openness to receiving prevention interventions from oral healthcare providers. Understanding the oral healthcare experiences of PLWH with intersectional identities is the first step to developing patient-centred interventions that can improve oral health, including prevention or early detection of OPC.

Aims and objectives

This study aims to ground our future research program in an anti-racist/anti-intersectional-bias research framework by considering the impact of intersecting identities on oral health status access to oral healthcare, and knowledge and perceptions of oral HPV infection and HPV-associated cancers. This information will inform a research program and the design and implementation of interventions for primary and secondary prevention of HPV-associated OPC.

Objective 1

To identify individual, interpersonal and structural oral health equity factors that serve as barriers or facilitators to accessing regular and appropriate oral healthcare among PLWH of intersecting identities.

Objective 2

To explore knowledge and perceptions about causes, risk factors, prevention, and screening for oral and OPC and HPV vaccination and if identity group membership influences knowledge and perceptions of these issues.

Objective 3

To elicit recommendations for improving access to regular and appropriate oral healthcare and suggestions on how to engage PLWH from diverse identity groups in prevention interventions.

Methods and analysis

Patient and public involvement.

Our study design, protocol, screening script, eligibility questionnaire, focus group formation questionnaire, survey and initial focus group guide were presented to the AIDS Clinical Trials Group Community Advisory Board (CAB), a standing CAB collaborating with our clinic. Based on their feedback, modifications were made to our materials before final Institutional Review Board (IRB) approval of study materials. Future meetings will discuss findings and dissemination. This study is designed to collect information directly from patients to design future interventions and future research studies. Information collected in this study will directly inform the design and conduct of future studies.

Study design

Figure 1 presents a flow diagram of our study. We will use a qualitative study design involving focus group discussions (FGD) to address our three specific aims. We will recruit 80–144 PLWH to participate in one of 12–18 FGDs. Each FGD will have 5–8 participants. FGDs will take place over a 1-year period, and coding and analysis will be ongoing. Participants will also complete a short quantitative on-line survey so we can describe our study population and contextualise our study findings. Our study began recruitment in February of 2024, and our planned completion date is January 2025. We will recruit participants until we reach theoretical saturation in our focus groups, or January 2025, whichever comes first.

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Health Equity and Oral Health in People living with HIV Study flow diagram and research activities.

The study will take place within the University of California, San Francisco’s (UCSF) Anal Neoplasia Research and Education Center (ANCRE) Clinic. The ANCRE Clinic provides clinical care for HPV-associated diseases for people representing different racial/ethnic and SGM groups and PLWH. The clinic has 6–7 clinicians caring for approximately 80–100 patients per week.

Sample and recruitment

Inclusion and exclusion criteria.

Participants must be 18 years old or older and living with HIV, both determined through self-report. Participants must be able to speak conversational English, as the FGD facilitators are fluent in English. We will not be able to include other languages, given the dynamic discussions during FGDs. Participants must also identify as a member of one or more minority groups that places them at higher risk for poor oral health outcomes, including racial/ethnic minority groups, SGM groups or other self-reported identities that may impact their oral health, such as a person who experiences homelessness, a person who smokes, a person who suffers from a drug use disorder, a person who is disabled, etc. There are no additional exclusion criteria for this study.

Sampling methodology

We will use purposive sampling methods to recruit participants to our study. We aim to conduct FGDs with individuals sharing different identities; therefore, we will invite participation from persons sharing a particular identity until saturation is met for that identity. For example, we may reach saturation with male participants by FGD 10 and only hold FGDs with women/non-binary individuals in future FGDs.

Recruitment

We will use three main methods to recruit participants: (1) direct recruitment from the ANCRE Clinic, referrals from healthcare and service providers, and referrals from community organisations; (2) UCSF’s electronic medical records (EMR) recruitment tool and (3) modified snowball sampling. Materials will be developed to advertise and inform potential participants about the study, including flyers/posters, social media advertisements, dating application advertisements, a Facebook page and a study website.

Direct recruitment and referrals

Current and former patients of the ANCRE Clinic who meet eligibility criteria will be invited to participate in our study. Persons who have participated in ANCRE Clinic studies and have consented to be contacted for future studies will be invited to participate. Other participants will be directly referred by ANCRE clinicians during medical appointments. We will also reach out to our established networks of healthcare providers, community organisations and support groups to ask for referrals.

UCSF EMR recruitment tool

UCSF offers investigators a recruitment tool based on its electronic medical records system, which has been successfully used by previous studies at the ANCRE Clinic. A search strategy uses variables collected from standard medical care, including diagnosis, procedure, laboratory and pharmacy codes, and sociodemographic information. We will work with programmers to identify data points that could indicate eligibility. Potential participants who meet the search criteria will have an email sent to their secure email inbox informing them that they may be eligible for a study and inviting them to contact the study to learn more. Paper letters will be sent to the home address of patients not using UCSF’s secure email platform.

Modified snowball sampling

At the end of each FGD, participants will be invited to refer friends or acquaintances to our study. The referral number is capped at three to prevent an over-representation of individuals in the same social network who may share similar backgrounds. 44 Study materials with contact information will be shared with any participant interested in referring potential participants.

Enrolment phone visit

Screening for eligibility.

Once informed consent procedures are completed, participants will be screened for eligibility. We will ask participants a series of yes/no questions to determine if they meet study eligibility criteria, including (1) age over 18 years, (2) conversationally English speaking, (3) living with HIV, (4) member of a racial or ethnic minority group, (5) member of a sexual or gender minority group, (6) female/woman identity and (7) other identity important to oral health ( online supplemental material 1 has the full text of these questions). To be eligible, participants must answer ‘yes; to 1–3 and ‘yes’ to at least one of 4–7. Eligible participants will then be asked to describe their identities in their own words.

Supplemental material

Self-identifications and fgd composition.

Given our antiracist/anti-intersectional-bias framework, we do not want to rely on investigator-created categories for race/ethnicity, sexual preference, gender or any other identity. We will briefly explain the study goals to participants and the goals of focus group composition. We will then ask potential participants to describe themselves across different domains in open-text fields. Participants were asked to ‘in your own words, how would you describe’ their race, ethnicity, ancestry, country of origin, where your family comes from, gender, gender identity, sexual preference(s) and any other identities important to oral health or access to oral health ( online supplemental material 2 has the full text of these questions). We will also ask if the participant has seen a dentist in the past 12 months.

Investigators will evaluate participants’ answers to the self-identification questions and form groups based on shared identities. We anticipate that we will have groups with individuals who identify with categories like ‘Black/African American/ Caribbean’ or ‘Latinx/Hispanic/(or country of origin)’ as well as groups of different races/ethnicities that share identities like ‘gay man’, ‘trans women’ or ‘cis heterosexual female’. We will also form groups with mixed identities. Once we have assembled a group of 8–9 individuals with some shared identities, we will contact potential participants. Potential participants will be asked if they would like to participate in this group or if they would like to wait for another group.

Self-administered online quantitative survey

Participants will receive a link via email or text to a Research Electronic Data Capture (REDCap) Survey. The survey will include questions on demographic factors (ie, age, education, income and marital status), substance use history (ie, tobacco, e-cigarettes, alcohol and recreational drugs), oral health history, dental insurance experience, medical health history and questions to assess knowledge of HPV infection, cancers caused by HPV and the HPV vaccine. We will also include three validated questionnaires: (1) the Oral Health Impact Profile-14 45 46 to assess the impact of oral health problems on a participant’s life; (2) the Everyday Discrimination Scale, 47 to assess participants’ experiences with discrimination, including discrimination due to race, ethnicity, HIV status, SGM, sexual preference(s) and others and (3) the Oral Health Values Scale, 48 to assess the importance of or investment in maintaining or improving participants’ dental health. Participants who cannot complete the survey online will be offered the opportunity to complete it over the phone.

Quantitative survey analysis plan

Descriptive statistics will be used to summarise data in the quantitative survey. This includes means and standard deviations or median and quartiles for numeric variables and frequencies and percentages for categorical variables. T-tests for numeric variables and χ 2 , and Fisher’s exact test as appropriate, for categorical variables, will be used to assess imbalances between groups. Results will be presented for the overall study, and by FGD to provide context for codes, concepts and theories and to make comparisons between different identity groups.

Qualitative focus groups

Theoretical framework.

Grounded theory (GT) 49–54 is a qualitative research methodology used across many fields, including healthcare research. Differing from quantitative research which tests a priori hypotheses, GT searches data for emergent concepts. In GT, coding of data is done simultaneously with further data collection and analysis, as one informs the other, and ultimately results in the generation of theories that explain an underlying phenomenon. 51 52 GT involves a rigorous iterative process of immersion in the data (eg, focus group transcripts), multiple rounds of coding, theoretical memo-writing, generation of theory, constant comparison and refinement of theory. 55 GT provides a robust method for conducting formative research and designing interventions.

We will have reached theoretical saturation when no new ideas evolve from the FGDs. While we will hold focus groups based on participants’ self-described identities, we do not anticipate this to be an obstacle to reaching theoretical saturation as there are likely commonalities, as well as the anticipated differences, in the experiences and perspectives of the members of the different FGDs. To make sure that we have enough data to understand all dimensions of a theory as it applies to a particular identity group, we will add additional FGDs, known as ‘theoretical sampling’ in GT, as needed. The goal is to deeply understand the oral health experiences of PLWH of different intersecting identity groups, uncover the connections between them and the meanings of these experiences and to generate theories to fully describe the complex barriers and facilitators of oral healthcare.

FGD for data collection

FGDs were chosen as the data collection method as they are dynamic settings for theory generation. We do not know which aspects of intersecting identities are most salient to accessing oral healthcare and the use of FGDs will allow us to gain this knowledge in a setting where participants can build on and reinforce shared understandings about oral healthcare. The FGDs may generate both homogeneous and heterogeneous perspectives on oral healthcare depending on the participants’ identities and will allow for the gathering of a wide range of attitudes and beliefs about oral healthcare that would be difficult in a one-on-one interview setting. FGDs facilitate the likelihood of participants stimulating ideas and thoughts in other participants, moving conversations past the ideas introduced by investigators and effectively sampling several participants simultaneously. 2 50 56

Focus group guide

Following our GT theoretical framework, we will create an initial FGD guide with questions that address each objective ( online supplemental material 3 ). All questions may not be asked in all FGDs as the goal is to initiate a conversation about topics with the intention of sparking new insights directly from participants.

All FGDs will end with questions requesting ideas/thoughts/suggestions about potential interventions to increase knowledge, reduce stigma, increase comfort with oral health practitioners or to navigate resources. The guide will be reviewed after each FGD, and questions may be added/modified based on the analysis of the preceding FGD transcript and emerging theories.

FGD facilitation

FGDs will be cofacilitated by ALH and EOL, both experienced moderators. FGDs will take place in a private conference room in the UCSF building, which houses the ANCRE Clinic, or in a nearby conference room. FGDs will begin with an introduction to the study, an introduction to the facilitators, and a review of FGD procedures and norms, including respect and privacy. Participants will receive a tent card to place on the table where they can record their name or a pseudonym, and a facilitator may occasionally refer to a participant by name to ask clarification questions. Recording will begin directly before the first question is posed to the group. Introductions will not be recorded. The facilitators will also take handwritten notes.

At the end of the FGD, participants will have an opportunity to ask questions and will be asked if they would like to refer friends/acquaintances to the study. They will then be thanked, reimbursed US$100 for their time and travel and offered information on dental resources available for PLWH.

After each FGD, facilitators will individually write theoretical memos (documentation about evolving codes and concepts and their relationships 55 ), which encapsulate their major takeaways and emerging understandings of the barriers and facilitators to oral healthcare for those with intersectional identities. 55 They will amend the theoretical memos as appropriate and note changes to be made to the FGD guide. Based on the emerging data, we will also determine if there is a need for further/different FGDs.

Qualitative data analysis

We will begin our analysis with the first FGD transcript, using the discussion guide as our initial analytical tool for organising the data while remaining open to the new and unexpected. In GT, data analysis and collection occur concurrently, with each set of data gathered informing the collection of the next set. Analysis is also an iterative process in which constant comparison or repeated review of each transcript is central to the process of generating theory. The digital transcript of each focus group will be uploaded to the software MAXQDA 57 58 to aid with data analysis. FGD guide development, coding of transcripts, category identification/codebook development, revision, review and development of theories will be iterative. Ultimately, we will generate theories to describe the existence and meaning of structural, interpersonal and individual-level barriers and facilitators of oral healthcare in PLWH of different racial/ethnic identities and SGM group membership.

We will perform a similar analysis of knowledge and perceptions of OPC and HPV, as described above. For our last objective, we will collate suggestions about potential interventions or ideas on how to improve oral health and access to oral healthcare.

Researcher reflexivity

All researchers have had diversity, equity and inclusion training and will reflect and discuss the impact of their own and others’ potential biases at each project stage. Table 1 reports details of each researcher, their role, training and self-reported identities important to oral health.

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The researchers involved in this study, their training and expertise, and their self-reported identities that may impact their oral health and access to oral healthcare

Ethics and dissemination

All methods and procedures were approved by the UCSF IRB (approval number: 23-39307) and were in accordance with the Declaration of Helsinki of 1975, as revised in 2000.

Participants will complete informed consent procedures at the beginning of the screening and enrolment phone call and will provide verbal consent, which will be documented in our study database. The study goals and procedures will be explained, and questions will be answered before participants are invited to participate. Because all participants in the FGD will be PLWH, we will offer participants the opportunity to opt out of the FGD as they may not wish to have their HIV status disclosed to others through their participation. If potential participants are willing, they will provide verbal informed consent, which will be noted in our REDCap Database and initialled by the researcher conducting the phone visit.

All data collected as part of this study will be kept strictly confidential. Personal data will be collected from the eligibility form, the focus group formation questionnaire and the quantitative survey. These data will be stored in a password-protected REDCap database on a UCSF secure server that is only accessible to study researchers. Audio recordings of the FGDs and digital transcripts will also contain personal data. Audio recording and transcripts will be recorded directly to a computer, and the files will be stored on a secure UCSF BOX cloud-based password-protected file. Audio files will be destroyed after transcription and checking for accuracy during analysis. Hard copies of transcripts will be kept in locked filing cabinets in locked offices.

The results of this study will be published in peer-reviewed publications and presented at scholarly meetings. We will present the results at a CAB meeting at the end of the study. We will also prepare a newsletter for participants and community members with a lay description of our study results, which will be mailed to our participants and included on our study website.

The ultimate goal of our research program is to design and evaluate interventions for PLWH that will reduce barriers and increase facilitators to oral healthcare overall, specifically surrounding oral HPV and HPV-related OPC. These interventions would target increased awareness of risk factors for HPV-related OPC, uptake of HPV vaccines and potential screening for oral cancer and/or early diagnosis of OPC. The first step towards this goal is understanding how PLWH navigate the complexities of oral healthcare.

We need to understand why PLWH are not accessing the oral healthcare available even when they have dental insurance/benefits and/or free/low-cost options. We need to determine if the barriers are structural (location, transportation and hours of operation), reluctance to attend because of enacted stigma (oral health clinics not feeling safe and welcoming of people of different SGM groups) or other unknown reasons. Barriers and facilitators may be interconnected, overlapping and impacted by a person’s identity.

Our study design, built on an anti-racist/anti-bias intersectional framework and using GT, will allow us to connect multiple factors and generate theories that will allow us to develop multilevel interventions to address those barriers. For example, in figure 2 , we present a hypothetical theory that PLWH who are members of SGM groups feel unwelcome at dental offices, and the reasons for this feeling include structural reasons (eg, open bays in the dental office), interpersonal reasons (eg, wrong pronouns) and individual reasons (eg, self-stigma about disclosure to staff). The multilevel intervention developed in response to that theory would aim to increase comfort with oral healthcare and include changes at all three levels. The first step to developing appropriate interventions is understanding what keeps PLWH with intersectional identities out of the dental office.

Hypothetical theory explaining comfort as individual, interpersonal, and structural facilitators and barriers to accessing dental care with potential interventions that could address each level. LGBTQIA+, lesbian, gay, bisexual, transgender, queer, intersex, and asexual, plus all other identities not included.

We will use the results of this study to design a culturally appropriate, multilevel intervention to increase facilitators and address barriers to oral healthcare and, once PLWH are engaged in care, target our HPV-associated OPC prevention goals. We anticipate but cannot know until this initial step of the research is complete, that part of a future intervention will include supporting dental providers serving PLWH to become a hub for patient information on OPC risk, HPV vaccination and care referrals.

The study’s results will also be available for other researchers or public health professionals to use in designing their own studies involving oral health or access to oral healthcare. This will allow them to consider different intersecting biases as they prepare their methodologies.

Limitations

Although participants will self-identify their identities, bias may be introduced during the referral process. We will encourage referrers to refer all participants for screening regardless of race/ethnicity or SGM group membership. Another limitation is that we will not include FGDs with individuals who identify with more dominant identity groups (eg, non-Hispanic white, heterosexual, with no other identities that increase the risk for oral health issues (ie, drug use or unhoused). We seek to understand the intersectionality of living with HIV and membership in other minority identity groups but may miss important information from other PLWH.

Ethics statements

Patient consent for publication.

Not applicable.

• Bastos JL ,
• Constante HM ,
• Jamieson LM
• Fleming E ,
• Raskin SE ,
• Celeste RK , et al
• Elaine Muirhead V ,
• Freeman R , et al
• Centers for Disease Control and Prevention (CDC)
• Chaturvedi AK ,
• Engels EA ,
• Pfeiffer RM , et al
• Lechner M ,
• Masterson L , et al
• D’Souza G ,
• Westra WH ,
• Wang SJ , et al
• Biggar RJ ,
• Madeleine MM ,
• Biggar RJ , et al
• Hall HI , et al
• Nyitray AG ,
• Carvalho da Silva RJ ,
• Chang M , et al
• Silva RJC ,
• Andreoli MA , et al
• Clifford GM ,
• Polesel J ,
• Rickenbach M , et al
• Dʼsouza G ,
• William WN , et al
• Beachler DC ,
• Abraham AG ,
• Silverberg MJ , et al
• Weatherspoon DJ ,
• Chattopadhyay A ,
• Boroumand S , et al
• Megwalu UC ,
• Shavers VL ,
• Harlan LC ,
• Winn D , et al
• Zandberg DP ,
• Goloubeva O , et al
• Osazuwa-Peters N ,
• Christopher KM , et al
• Ali-Fehmi R , et al
• Sarrazin MV , et al
• Schneider EB , et al
• Wen K-Y , et al
• Markowitz LE
• ↵ Health at a glance 2021 - OECD . 2021 . Available : https://www.oecd.org/health/health-at-a-glance/ [Accessed 3 Sep 2022 ].
• Covered California
• Stein Duker LI ,
• Polido JC , et al
• ↵ Oral health surveillance report 2019 . 2021 . Available : https://www.cdc.gov/oralhealth/publications/OHSR-2019-index.html [Accessed 3 Sep 2022 ].
• Borrell LN ,
• Williams DR
• U.S. Department of Health and Human Services
• Yuvaraj A ,
• Mahendra VS ,
• Chakrapani V , et al
• Greenwood GL ,
• Bansal GP , et al
• Ching THW ,
• Finkelstein-Fox L ,
• Lee SY , et al
• Diamond LM ,
• Rosengren AL ,
• Lelutiu-Weinberger C ,
• Woodhouse EW , et al
• Magnani R ,
• Saidel T , et al
• Krieger N ,
• Naishadham D , et al
• Edwards CB ,
• Randall CL ,
• Chapman AL ,
• Hadfield M ,
• de la Espriella R ,
• Gómez Restrepo C
• Daftary A ,
• Mitnick CD , et al
• Moura CO de ,
• Silva TP da , et al
• Crabtree BF ,

Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• Data supplement 1
• Data supplement 2
• Data supplement 3

Contributors ALH designed the study, wrote the study protocol and drafted the manuscript. EOL designed the study with ALH and reviewed and edited the protocol manuscript. WJ, AV and JP participated in the study design and reviewed and edited the manuscript. ALH is the guarantor.

Funding Research reported in this publication was supported by the National Institute of Dental and Craniofacial Research of the National Institutes of Health under Award Number R03DE032972.

Disclaimer The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Competing interests AV is consultant for WSK Medical, Brain Cool, K Pharmaceuticals, Lipella Pharmaceuticals, Afyx Therapeutics, Merck K and Primary Endpoint Solutions and has funded research from Merck, MeiraGtx and Mureva. JP is a consultant or honorarium recipient from Merck, Vir Biotechnologies, Virion Therapeutics, Roche Diagnostics, Spotlight, Abbott Therapeutics, GSK, Asieris Pharmaceuticals and a stock shareholder at Virion Therapeutics. ALH, EOL and WJ have no competing of interest to disclose.

Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.

Provenance and peer review Not commissioned; peer reviewed for ethical and funding approval prior to submission.

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