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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 November 20, 2023 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.

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.

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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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Chapter 2. Research Design

Getting started.

When I teach undergraduates qualitative research methods, the final product of the course is a “research proposal” that incorporates all they have learned and enlists the knowledge they have learned about qualitative research methods in an original design that addresses a particular research question. I highly recommend you think about designing your own research study as you progress through this textbook. Even if you don’t have a study in mind yet, it can be a helpful exercise as you progress through the course. But how to start? How can one design a research study before they even know what research looks like? This chapter will serve as a brief overview of the research design process to orient you to what will be coming in later chapters. Think of it as a “skeleton” of what you will read in more detail in later chapters. Ideally, you will read this chapter both now (in sequence) and later during your reading of the remainder of the text. Do not worry if you have questions the first time you read this chapter. Many things will become clearer as the text advances and as you gain a deeper understanding of all the components of good qualitative research. This is just a preliminary map to get you on the right road.

Research Design Steps

Before you even get started, you will need to have a broad topic of interest in mind. [1] . In my experience, students can confuse this broad topic with the actual research question, so it is important to clearly distinguish the two. And the place to start is the broad topic. It might be, as was the case with me, working-class college students. But what about working-class college students? What’s it like to be one? Why are there so few compared to others? How do colleges assist (or fail to assist) them? What interested me was something I could barely articulate at first and went something like this: “Why was it so difficult and lonely to be me?” And by extension, “Did others share this experience?”

Once you have a general topic, reflect on why this is important to you. Sometimes we connect with a topic and we don’t really know why. Even if you are not willing to share the real underlying reason you are interested in a topic, it is important that you know the deeper reasons that motivate you. Otherwise, it is quite possible that at some point during the research, you will find yourself turned around facing the wrong direction. I have seen it happen many times. The reason is that the research question is not the same thing as the general topic of interest, and if you don’t know the reasons for your interest, you are likely to design a study answering a research question that is beside the point—to you, at least. And this means you will be much less motivated to carry your research to completion.

Researcher Note

Why do you employ qualitative research methods in your area of study? What are the advantages of qualitative research methods for studying mentorship?

Qualitative research methods are a huge opportunity to increase access, equity, inclusion, and social justice. Qualitative research allows us to engage and examine the uniquenesses/nuances within minoritized and dominant identities and our experiences with these identities. Qualitative research allows us to explore a specific topic, and through that exploration, we can link history to experiences and look for patterns or offer up a unique phenomenon. There’s such beauty in being able to tell a particular story, and qualitative research is a great mode for that! For our work, we examined the relationships we typically use the term mentorship for but didn’t feel that was quite the right word. Qualitative research allowed us to pick apart what we did and how we engaged in our relationships, which then allowed us to more accurately describe what was unique about our mentorship relationships, which we ultimately named liberationships ( McAloney and Long 2021) . Qualitative research gave us the means to explore, process, and name our experiences; what a powerful tool!

How do you come up with ideas for what to study (and how to study it)? Where did you get the idea for studying mentorship?

Coming up with ideas for research, for me, is kind of like Googling a question I have, not finding enough information, and then deciding to dig a little deeper to get the answer. The idea to study mentorship actually came up in conversation with my mentorship triad. We were talking in one of our meetings about our relationship—kind of meta, huh? We discussed how we felt that mentorship was not quite the right term for the relationships we had built. One of us asked what was different about our relationships and mentorship. This all happened when I was taking an ethnography course. During the next session of class, we were discussing auto- and duoethnography, and it hit me—let’s explore our version of mentorship, which we later went on to name liberationships ( McAloney and Long 2021 ). The idea and questions came out of being curious and wanting to find an answer. As I continue to research, I see opportunities in questions I have about my work or during conversations that, in our search for answers, end up exposing gaps in the literature. If I can’t find the answer already out there, I can study it.

—Kim McAloney, PhD, College Student Services Administration Ecampus coordinator and instructor

When you have a better idea of why you are interested in what it is that interests you, you may be surprised to learn that the obvious approaches to the topic are not the only ones. For example, let’s say you think you are interested in preserving coastal wildlife. And as a social scientist, you are interested in policies and practices that affect the long-term viability of coastal wildlife, especially around fishing communities. It would be natural then to consider designing a research study around fishing communities and how they manage their ecosystems. But when you really think about it, you realize that what interests you the most is how people whose livelihoods depend on a particular resource act in ways that deplete that resource. Or, even deeper, you contemplate the puzzle, “How do people justify actions that damage their surroundings?” Now, there are many ways to design a study that gets at that broader question, and not all of them are about fishing communities, although that is certainly one way to go. Maybe you could design an interview-based study that includes and compares loggers, fishers, and desert golfers (those who golf in arid lands that require a great deal of wasteful irrigation). Or design a case study around one particular example where resources were completely used up by a community. Without knowing what it is you are really interested in, what motivates your interest in a surface phenomenon, you are unlikely to come up with the appropriate research design.

These first stages of research design are often the most difficult, but have patience . Taking the time to consider why you are going to go through a lot of trouble to get answers will prevent a lot of wasted energy in the future.

There are distinct reasons for pursuing particular research questions, and it is helpful to distinguish between them.  First, you may be personally motivated.  This is probably the most important and the most often overlooked.   What is it about the social world that sparks your curiosity? What bothers you? What answers do you need in order to keep living? For me, I knew I needed to get a handle on what higher education was for before I kept going at it. I needed to understand why I felt so different from my peers and whether this whole “higher education” thing was “for the likes of me” before I could complete my degree. That is the personal motivation question. Your personal motivation might also be political in nature, in that you want to change the world in a particular way. It’s all right to acknowledge this. In fact, it is better to acknowledge it than to hide it.

There are also academic and professional motivations for a particular study.  If you are an absolute beginner, these may be difficult to find. We’ll talk more about this when we discuss reviewing the literature. Simply put, you are probably not the only person in the world to have thought about this question or issue and those related to it. So how does your interest area fit into what others have studied? Perhaps there is a good study out there of fishing communities, but no one has quite asked the “justification” question. You are motivated to address this to “fill the gap” in our collective knowledge. And maybe you are really not at all sure of what interests you, but you do know that [insert your topic] interests a lot of people, so you would like to work in this area too. You want to be involved in the academic conversation. That is a professional motivation and a very important one to articulate.

Practical and strategic motivations are a third kind. Perhaps you want to encourage people to take better care of the natural resources around them. If this is also part of your motivation, you will want to design your research project in a way that might have an impact on how people behave in the future. There are many ways to do this, one of which is using qualitative research methods rather than quantitative research methods, as the findings of qualitative research are often easier to communicate to a broader audience than the results of quantitative research. You might even be able to engage the community you are studying in the collecting and analyzing of data, something taboo in quantitative research but actively embraced and encouraged by qualitative researchers. But there are other practical reasons, such as getting “done” with your research in a certain amount of time or having access (or no access) to certain information. There is nothing wrong with considering constraints and opportunities when designing your study. Or maybe one of the practical or strategic goals is about learning competence in this area so that you can demonstrate the ability to conduct interviews and focus groups with future employers. Keeping that in mind will help shape your study and prevent you from getting sidetracked using a technique that you are less invested in learning about.

STOP HERE for a moment

I recommend you write a paragraph (at least) explaining your aims and goals. Include a sentence about each of the following: personal/political goals, practical or professional/academic goals, and practical/strategic goals. Think through how all of the goals are related and can be achieved by this particular research study . If they can’t, have a rethink. Perhaps this is not the best way to go about it.

You will also want to be clear about the purpose of your study. “Wait, didn’t we just do this?” you might ask. No! Your goals are not the same as the purpose of the study, although they are related. You can think about purpose lying on a continuum from “ theory ” to “action” (figure 2.1). Sometimes you are doing research to discover new knowledge about the world, while other times you are doing a study because you want to measure an impact or make a difference in the world.

Basic research involves research that is done for the sake of “pure” knowledge—that is, knowledge that, at least at this moment in time, may not have any apparent use or application. Often, and this is very important, knowledge of this kind is later found to be extremely helpful in solving problems. So one way of thinking about basic research is that it is knowledge for which no use is yet known but will probably one day prove to be extremely useful. If you are doing basic research, you do not need to argue its usefulness, as the whole point is that we just don’t know yet what this might be.

Researchers engaged in basic research want to understand how the world operates. They are interested in investigating a phenomenon to get at the nature of reality with regard to that phenomenon. The basic researcher’s purpose is to understand and explain ( Patton 2002:215 ).

Basic research is interested in generating and testing hypotheses about how the world works. Grounded Theory is one approach to qualitative research methods that exemplifies basic research (see chapter 4). Most academic journal articles publish basic research findings. If you are working in academia (e.g., writing your dissertation), the default expectation is that you are conducting basic research.

Applied research in the social sciences is research that addresses human and social problems. Unlike basic research, the researcher has expectations that the research will help contribute to resolving a problem, if only by identifying its contours, history, or context. From my experience, most students have this as their baseline assumption about research. Why do a study if not to make things better? But this is a common mistake. Students and their committee members are often working with default assumptions here—the former thinking about applied research as their purpose, the latter thinking about basic research: “The purpose of applied research is to contribute knowledge that will help people to understand the nature of a problem in order to intervene, thereby allowing human beings to more effectively control their environment. While in basic research the source of questions is the tradition within a scholarly discipline, in applied research the source of questions is in the problems and concerns experienced by people and by policymakers” ( Patton 2002:217 ).

Applied research is less geared toward theory in two ways. First, its questions do not derive from previous literature. For this reason, applied research studies have much more limited literature reviews than those found in basic research (although they make up for this by having much more “background” about the problem). Second, it does not generate theory in the same way as basic research does. The findings of an applied research project may not be generalizable beyond the boundaries of this particular problem or context. The findings are more limited. They are useful now but may be less useful later. This is why basic research remains the default “gold standard” of academic research.

Evaluation research is research that is designed to evaluate or test the effectiveness of specific solutions and programs addressing specific social problems. We already know the problems, and someone has already come up with solutions. There might be a program, say, for first-generation college students on your campus. Does this program work? Are first-generation students who participate in the program more likely to graduate than those who do not? These are the types of questions addressed by evaluation research. There are two types of research within this broader frame; however, one more action-oriented than the next. In summative evaluation , an overall judgment about the effectiveness of a program or policy is made. Should we continue our first-gen program? Is it a good model for other campuses? Because the purpose of such summative evaluation is to measure success and to determine whether this success is scalable (capable of being generalized beyond the specific case), quantitative data is more often used than qualitative data. In our example, we might have “outcomes” data for thousands of students, and we might run various tests to determine if the better outcomes of those in the program are statistically significant so that we can generalize the findings and recommend similar programs elsewhere. Qualitative data in the form of focus groups or interviews can then be used for illustrative purposes, providing more depth to the quantitative analyses. In contrast, formative evaluation attempts to improve a program or policy (to help “form” or shape its effectiveness). Formative evaluations rely more heavily on qualitative data—case studies, interviews, focus groups. The findings are meant not to generalize beyond the particular but to improve this program. If you are a student seeking to improve your qualitative research skills and you do not care about generating basic research, formative evaluation studies might be an attractive option for you to pursue, as there are always local programs that need evaluation and suggestions for improvement. Again, be very clear about your purpose when talking through your research proposal with your committee.

Action research takes a further step beyond evaluation, even formative evaluation, to being part of the solution itself. This is about as far from basic research as one could get and definitely falls beyond the scope of “science,” as conventionally defined. The distinction between action and research is blurry, the research methods are often in constant flux, and the only “findings” are specific to the problem or case at hand and often are findings about the process of intervention itself. Rather than evaluate a program as a whole, action research often seeks to change and improve some particular aspect that may not be working—maybe there is not enough diversity in an organization or maybe women’s voices are muted during meetings and the organization wonders why and would like to change this. In a further step, participatory action research , those women would become part of the research team, attempting to amplify their voices in the organization through participation in the action research. As action research employs methods that involve people in the process, focus groups are quite common.

If you are working on a thesis or dissertation, chances are your committee will expect you to be contributing to fundamental knowledge and theory ( basic research ). If your interests lie more toward the action end of the continuum, however, it is helpful to talk to your committee about this before you get started. Knowing your purpose in advance will help avoid misunderstandings during the later stages of the research process!

The Research Question

Once you have written your paragraph and clarified your purpose and truly know that this study is the best study for you to be doing right now , you are ready to write and refine your actual research question. Know that research questions are often moving targets in qualitative research, that they can be refined up to the very end of data collection and analysis. But you do have to have a working research question at all stages. This is your “anchor” when you get lost in the data. What are you addressing? What are you looking at and why? Your research question guides you through the thicket. It is common to have a whole host of questions about a phenomenon or case, both at the outset and throughout the study, but you should be able to pare it down to no more than two or three sentences when asked. These sentences should both clarify the intent of the research and explain why this is an important question to answer. More on refining your research question can be found in chapter 4.

Chances are, you will have already done some prior reading before coming up with your interest and your questions, but you may not have conducted a systematic literature review. This is the next crucial stage to be completed before venturing further. You don’t want to start collecting data and then realize that someone has already beaten you to the punch. A review of the literature that is already out there will let you know (1) if others have already done the study you are envisioning; (2) if others have done similar studies, which can help you out; and (3) what ideas or concepts are out there that can help you frame your study and make sense of your findings. More on literature reviews can be found in chapter 9.

In addition to reviewing the literature for similar studies to what you are proposing, it can be extremely helpful to find a study that inspires you. This may have absolutely nothing to do with the topic you are interested in but is written so beautifully or organized so interestingly or otherwise speaks to you in such a way that you want to post it somewhere to remind you of what you want to be doing. You might not understand this in the early stages—why would you find a study that has nothing to do with the one you are doing helpful? But trust me, when you are deep into analysis and writing, having an inspirational model in view can help you push through. If you are motivated to do something that might change the world, you probably have read something somewhere that inspired you. Go back to that original inspiration and read it carefully and see how they managed to convey the passion that you so appreciate.

At this stage, you are still just getting started. There are a lot of things to do before setting forth to collect data! You’ll want to consider and choose a research tradition and a set of data-collection techniques that both help you answer your research question and match all your aims and goals. For example, if you really want to help migrant workers speak for themselves, you might draw on feminist theory and participatory action research models. Chapters 3 and 4 will provide you with more information on epistemologies and approaches.

Next, you have to clarify your “units of analysis.” What is the level at which you are focusing your study? Often, the unit in qualitative research methods is individual people, or “human subjects.” But your units of analysis could just as well be organizations (colleges, hospitals) or programs or even whole nations. Think about what it is you want to be saying at the end of your study—are the insights you are hoping to make about people or about organizations or about something else entirely? A unit of analysis can even be a historical period! Every unit of analysis will call for a different kind of data collection and analysis and will produce different kinds of “findings” at the conclusion of your study. [2]

Regardless of what unit of analysis you select, you will probably have to consider the “human subjects” involved in your research. [3] Who are they? What interactions will you have with them—that is, what kind of data will you be collecting? Before answering these questions, define your population of interest and your research setting. Use your research question to help guide you.

Let’s use an example from a real study. In Geographies of Campus Inequality , Benson and Lee ( 2020 ) list three related research questions: “(1) What are the different ways that first-generation students organize their social, extracurricular, and academic activities at selective and highly selective colleges? (2) how do first-generation students sort themselves and get sorted into these different types of campus lives; and (3) how do these different patterns of campus engagement prepare first-generation students for their post-college lives?” (3).

Note that we are jumping into this a bit late, after Benson and Lee have described previous studies (the literature review) and what is known about first-generation college students and what is not known. They want to know about differences within this group, and they are interested in ones attending certain kinds of colleges because those colleges will be sites where academic and extracurricular pressures compete. That is the context for their three related research questions. What is the population of interest here? First-generation college students . What is the research setting? Selective and highly selective colleges . But a host of questions remain. Which students in the real world, which colleges? What about gender, race, and other identity markers? Will the students be asked questions? Are the students still in college, or will they be asked about what college was like for them? Will they be observed? Will they be shadowed? Will they be surveyed? Will they be asked to keep diaries of their time in college? How many students? How many colleges? For how long will they be observed?

Recommendation

Take a moment and write down suggestions for Benson and Lee before continuing on to what they actually did.

Have you written down your own suggestions? Good. Now let’s compare those with what they actually did. Benson and Lee drew on two sources of data: in-depth interviews with sixty-four first-generation students and survey data from a preexisting national survey of students at twenty-eight selective colleges. Let’s ignore the survey for our purposes here and focus on those interviews. The interviews were conducted between 2014 and 2016 at a single selective college, “Hilltop” (a pseudonym ). They employed a “purposive” sampling strategy to ensure an equal number of male-identifying and female-identifying students as well as equal numbers of White, Black, and Latinx students. Each student was interviewed once. Hilltop is a selective liberal arts college in the northeast that enrolls about three thousand students.

How did your suggestions match up to those actually used by the researchers in this study? It is possible your suggestions were too ambitious? Beginning qualitative researchers can often make that mistake. You want a research design that is both effective (it matches your question and goals) and doable. You will never be able to collect data from your entire population of interest (unless your research question is really so narrow to be relevant to very few people!), so you will need to come up with a good sample. Define the criteria for this sample, as Benson and Lee did when deciding to interview an equal number of students by gender and race categories. Define the criteria for your sample setting too. Hilltop is typical for selective colleges. That was a research choice made by Benson and Lee. For more on sampling and sampling choices, see chapter 5.

Benson and Lee chose to employ interviews. If you also would like to include interviews, you have to think about what will be asked in them. Most interview-based research involves an interview guide, a set of questions or question areas that will be asked of each participant. The research question helps you create a relevant interview guide. You want to ask questions whose answers will provide insight into your research question. Again, your research question is the anchor you will continually come back to as you plan for and conduct your study. It may be that once you begin interviewing, you find that people are telling you something totally unexpected, and this makes you rethink your research question. That is fine. Then you have a new anchor. But you always have an anchor. More on interviewing can be found in chapter 11.

Let’s imagine Benson and Lee also observed college students as they went about doing the things college students do, both in the classroom and in the clubs and social activities in which they participate. They would have needed a plan for this. Would they sit in on classes? Which ones and how many? Would they attend club meetings and sports events? Which ones and how many? Would they participate themselves? How would they record their observations? More on observation techniques can be found in both chapters 13 and 14.

At this point, the design is almost complete. You know why you are doing this study, you have a clear research question to guide you, you have identified your population of interest and research setting, and you have a reasonable sample of each. You also have put together a plan for data collection, which might include drafting an interview guide or making plans for observations. And so you know exactly what you will be doing for the next several months (or years!). To put the project into action, there are a few more things necessary before actually going into the field.

First, you will need to make sure you have any necessary supplies, including recording technology. These days, many researchers use their phones to record interviews. Second, you will need to draft a few documents for your participants. These include informed consent forms and recruiting materials, such as posters or email texts, that explain what this study is in clear language. Third, you will draft a research protocol to submit to your institutional review board (IRB) ; this research protocol will include the interview guide (if you are using one), the consent form template, and all examples of recruiting material. Depending on your institution and the details of your study design, it may take weeks or even, in some unfortunate cases, months before you secure IRB approval. Make sure you plan on this time in your project timeline. While you wait, you can continue to review the literature and possibly begin drafting a section on the literature review for your eventual presentation/publication. More on IRB procedures can be found in chapter 8 and more general ethical considerations in chapter 7.

Once you have approval, you can begin!

Research Design Checklist

Before data collection begins, do the following:

• Write a paragraph explaining your aims and goals (personal/political, practical/strategic, professional/academic).
• Define your research question; write two to three sentences that clarify the intent of the research and why this is an important question to answer.
• Review the literature for similar studies that address your research question or similar research questions; think laterally about some literature that might be helpful or illuminating but is not exactly about the same topic.
• Find a written study that inspires you—it may or may not be on the research question you have chosen.
• Consider and choose a research tradition and set of data-collection techniques that (1) help answer your research question and (2) match your aims and goals.
• Define your population of interest and your research setting.
• Define the criteria for your sample (How many? Why these? How will you find them, gain access, and acquire consent?).
• If you are conducting interviews, draft an interview guide.
•  If you are making observations, create a plan for observations (sites, times, recording, access).
• Acquire any necessary technology (recording devices/software).
• Draft consent forms that clearly identify the research focus and selection process.
• Create recruiting materials (posters, email, texts).
• Apply for IRB approval (proposal plus consent form plus recruiting materials).
• Block out time for collecting data.
• At the end of the chapter, you will find a " Research Design Checklist " that summarizes the main recommendations made here ↵
• For example, if your focus is society and culture , you might collect data through observation or a case study. If your focus is individual lived experience , you are probably going to be interviewing some people. And if your focus is language and communication , you will probably be analyzing text (written or visual). ( Marshall and Rossman 2016:16 ). ↵
• You may not have any "live" human subjects. There are qualitative research methods that do not require interactions with live human beings - see chapter 16 , "Archival and Historical Sources." But for the most part, you are probably reading this textbook because you are interested in doing research with people. The rest of the chapter will assume this is the case. ↵

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

A methodological tradition of inquiry and research design that focuses on an individual case (e.g., setting, institution, or sometimes an individual) in order to explore its complexity, history, and interactive parts.  As an approach, it is particularly useful for obtaining a deep appreciation of an issue, event, or phenomenon of interest in its particular context.

The controlling force in research; can be understood as lying on a continuum from basic research (knowledge production) to action research (effecting change).

In its most basic sense, a theory is a story we tell about how the world works that can be tested with empirical evidence.  In qualitative research, we use the term in a variety of ways, many of which are different from how they are used by quantitative researchers.  Although some qualitative research can be described as “testing theory,” it is more common to “build theory” from the data using inductive reasoning , as done in Grounded Theory .  There are so-called “grand theories” that seek to integrate a whole series of findings and stories into an overarching paradigm about how the world works, and much smaller theories or concepts about particular processes and relationships.  Theory can even be used to explain particular methodological perspectives or approaches, as in Institutional Ethnography , which is both a way of doing research and a theory about how the world works.

Research that is interested in generating and testing hypotheses about how the world works.

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

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

Research that contributes knowledge that will help people to understand the nature of a problem in order to intervene, thereby allowing human beings to more effectively control their environment.

Research that is designed to evaluate or test the effectiveness of specific solutions and programs addressing specific social problems.  There are two kinds: summative and formative .

Research in which an overall judgment about the effectiveness of a program or policy is made, often for the purpose of generalizing to other cases or programs.  Generally uses qualitative research as a supplement to primary quantitative data analyses.  Contrast formative evaluation research .

Research designed to improve a program or policy (to help “form” or shape its effectiveness); relies heavily on qualitative research methods.  Contrast summative evaluation research

Research carried out at a particular organizational or community site with the intention of affecting change; often involves research subjects as participants of the study.  See also participatory action research .

Research in which both researchers and participants work together to understand a problematic situation and change it for the better.

The level of the focus of analysis (e.g., individual people, organizations, programs, neighborhoods).

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

A fictional name assigned to give anonymity to a person, group, or place.  Pseudonyms are important ways of protecting the identity of research participants while still providing a “human element” in the presentation of qualitative data.  There are ethical considerations to be made in selecting pseudonyms; some researchers allow research participants to choose their own.

A requirement for research involving human participants; the documentation of informed consent.  In some cases, oral consent or assent may be sufficient, but the default standard is a single-page easy-to-understand form that both the researcher and the participant sign and date.   Under federal guidelines, all researchers "shall seek such consent only under circumstances that provide the prospective subject or the representative sufficient opportunity to consider whether or not to participate and that minimize the possibility of coercion or undue influence. The information that is given to the subject or the representative shall be in language understandable to the subject or the representative.  No informed consent, whether oral or written, may include any exculpatory language through which the subject or the representative is made to waive or appear to waive any of the subject's rights or releases or appears to release the investigator, the sponsor, the institution, or its agents from liability for negligence" (21 CFR 50.20).  Your IRB office will be able to provide a template for use in your study .

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

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

Qualitative study design: Qualitative study design

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Introduction

The effective evaluation of research involves assessing the way a study has been designed and conducted, and whether the method used was the most appropriate for answering the aims of the study. In contrast to quantitative studies, which are about breadth, qualitative research focuses on depth. 

Whereas quantitative research aims to develop objective theories by generating quantifiable numerical data, qualitative research aims to understand meaning. This might be the meanings that people attribute to their work, their behaviours or beliefs, or their attitudes or perceptions. Qualitative research is often based on methods of observation and enquiry; qualitative research “explores the meaning of human experiences and creates the possibilities of change through raised awareness and purposeful action” ( Taylor & Francis, 2013 ). Qualitative research focuses on life experiences; they are more about the “why” and “how” rather than the “how many”, or “how often”. 

Qualitative study designs might be chosen for any number of reasons. In health, you might be interested in finding out how nurses feel or experience care in the ICU; or you might want to find out how people engaged in heavy substance use found the experience of connecting with a support agency. Qualitative study designs are beneficial for certain types of research questions such as those looking to provide unique insights into specific contexts or social situations. However, they are not as strong when wanting to find direct cause and effect links or where a statistically significant result is required ( Taylor et al., 2006 ). 

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Qualitative Study

Affiliations.

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

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

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

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore ‘compete’ against each other and the philosophical paradigms associated with each, qualitative and quantitative work are not necessarily opposites nor are they incompatible. While qualitative and quantitative approaches are different, they are not necessarily opposites, and they are certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined that there is a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated together.

Examples of Qualitative Research Approaches

Ethnography

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

Grounded Theory

Grounded Theory is the “generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior.” As opposed to quantitative research which is deductive and tests or verifies an existing theory, grounded theory research is inductive and therefore lends itself to research that is aiming to study social interactions or experiences. In essence, Grounded Theory’s goal is to explain for example how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.

Phenomenology

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

Narrative Research

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

Research Paradigm

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

Positivist vs Postpositivist

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

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

Constructivist

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

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

Data Sampling

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

Purposive sampling- selection based on the researcher’s rationale in terms of being the most informative.

Criterion sampling-selection based on pre-identified factors.

Convenience sampling- selection based on availability.

Snowball sampling- the selection is by referral from other participants or people who know potential participants.

Extreme case sampling- targeted selection of rare cases.

Typical case sampling-selection based on regular or average participants.

Data Collection and Analysis

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

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or in the environment of the participants, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed which may then be coded manually or with the use of Computer Assisted Qualitative Data Analysis Software or CAQDAS such as ATLAS.ti or NVivo.

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

Dissemination

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

Examples of Application

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

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

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

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

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

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

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

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

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

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

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What is Qualitative in Qualitative Research

Patrik aspers.

1 Department of Sociology, Uppsala University, Uppsala, Sweden

2 Seminar for Sociology, Universität St. Gallen, St. Gallen, Switzerland

3 Department of Media and Social Sciences, University of Stavanger, Stavanger, Norway

What is qualitative research? If we look for a precise definition of qualitative research, and specifically for one that addresses its distinctive feature of being “qualitative,” the literature is meager. In this article we systematically search, identify and analyze a sample of 89 sources using or attempting to define the term “qualitative.” Then, drawing on ideas we find scattered across existing work, and based on Becker’s classic study of marijuana consumption, we formulate and illustrate a definition that tries to capture its core elements. We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. This formulation is developed as a tool to help improve research designs while stressing that a qualitative dimension is present in quantitative work as well. Additionally, it can facilitate teaching, communication between researchers, diminish the gap between qualitative and quantitative researchers, help to address critiques of qualitative methods, and be used as a standard of evaluation of qualitative research.

If we assume that there is something called qualitative research, what exactly is this qualitative feature? And how could we evaluate qualitative research as good or not? Is it fundamentally different from quantitative research? In practice, most active qualitative researchers working with empirical material intuitively know what is involved in doing qualitative research, yet perhaps surprisingly, a clear definition addressing its key feature is still missing.

To address the question of what is qualitative we turn to the accounts of “qualitative research” in textbooks and also in empirical work. In his classic, explorative, interview study of deviance Howard Becker ( 1963 ) asks ‘How does one become a marijuana user?’ In contrast to pre-dispositional and psychological-individualistic theories of deviant behavior, Becker’s inherently social explanation contends that becoming a user of this substance is the result of a three-phase sequential learning process. First, potential users need to learn how to smoke it properly to produce the “correct” effects. If not, they are likely to stop experimenting with it. Second, they need to discover the effects associated with it; in other words, to get “high,” individuals not only have to experience what the drug does, but also to become aware that those sensations are related to using it. Third, they require learning to savor the feelings related to its consumption – to develop an acquired taste. Becker, who played music himself, gets close to the phenomenon by observing, taking part, and by talking to people consuming the drug: “half of the fifty interviews were conducted with musicians, the other half covered a wide range of people, including laborers, machinists, and people in the professions” (Becker 1963 :56).

Another central aspect derived through the common-to-all-research interplay between induction and deduction (Becker 2017 ), is that during the course of his research Becker adds scientifically meaningful new distinctions in the form of three phases—distinctions, or findings if you will, that strongly affect the course of his research: its focus, the material that he collects, and which eventually impact his findings. Each phase typically unfolds through social interaction, and often with input from experienced users in “a sequence of social experiences during which the person acquires a conception of the meaning of the behavior, and perceptions and judgments of objects and situations, all of which make the activity possible and desirable” (Becker 1963 :235). In this study the increased understanding of smoking dope is a result of a combination of the meaning of the actors, and the conceptual distinctions that Becker introduces based on the views expressed by his respondents. Understanding is the result of research and is due to an iterative process in which data, concepts and evidence are connected with one another (Becker 2017 ).

Indeed, there are many definitions of qualitative research, but if we look for a definition that addresses its distinctive feature of being “qualitative,” the literature across the broad field of social science is meager. The main reason behind this article lies in the paradox, which, to put it bluntly, is that researchers act as if they know what it is, but they cannot formulate a coherent definition. Sociologists and others will of course continue to conduct good studies that show the relevance and value of qualitative research addressing scientific and practical problems in society. However, our paper is grounded in the idea that providing a clear definition will help us improve the work that we do. Among researchers who practice qualitative research there is clearly much knowledge. We suggest that a definition makes this knowledge more explicit. If the first rationale for writing this paper refers to the “internal” aim of improving qualitative research, the second refers to the increased “external” pressure that especially many qualitative researchers feel; pressure that comes both from society as well as from other scientific approaches. There is a strong core in qualitative research, and leading researchers tend to agree on what it is and how it is done. Our critique is not directed at the practice of qualitative research, but we do claim that the type of systematic work we do has not yet been done, and that it is useful to improve the field and its status in relation to quantitative research.

The literature on the “internal” aim of improving, or at least clarifying qualitative research is large, and we do not claim to be the first to notice the vagueness of the term “qualitative” (Strauss and Corbin 1998 ). Also, others have noted that there is no single definition of it (Long and Godfrey 2004 :182), that there are many different views on qualitative research (Denzin and Lincoln 2003 :11; Jovanović 2011 :3), and that more generally, we need to define its meaning (Best 2004 :54). Strauss and Corbin ( 1998 ), for example, as well as Nelson et al. (1992:2 cited in Denzin and Lincoln 2003 :11), and Flick ( 2007 :ix–x), have recognized that the term is problematic: “Actually, the term ‘qualitative research’ is confusing because it can mean different things to different people” (Strauss and Corbin 1998 :10–11). Hammersley has discussed the possibility of addressing the problem, but states that “the task of providing an account of the distinctive features of qualitative research is far from straightforward” ( 2013 :2). This confusion, as he has recently further argued (Hammersley 2018 ), is also salient in relation to ethnography where different philosophical and methodological approaches lead to a lack of agreement about what it means.

Others (e.g. Hammersley 2018 ; Fine and Hancock 2017 ) have also identified the treat to qualitative research that comes from external forces, seen from the point of view of “qualitative research.” This threat can be further divided into that which comes from inside academia, such as the critique voiced by “quantitative research” and outside of academia, including, for example, New Public Management. Hammersley ( 2018 ), zooming in on one type of qualitative research, ethnography, has argued that it is under treat. Similarly to Fine ( 2003 ), and before him Gans ( 1999 ), he writes that ethnography’ has acquired a range of meanings, and comes in many different versions, these often reflecting sharply divergent epistemological orientations. And already more than twenty years ago while reviewing Denzin and Lincoln’ s Handbook of Qualitative Methods Fine argued:

While this increasing centrality [of qualitative research] might lead one to believe that consensual standards have developed, this belief would be misleading. As the methodology becomes more widely accepted, querulous challengers have raised fundamental questions that collectively have undercut the traditional models of how qualitative research is to be fashioned and presented (1995:417).

According to Hammersley, there are today “serious treats to the practice of ethnographic work, on almost any definition” ( 2018 :1). He lists five external treats: (1) that social research must be accountable and able to show its impact on society; (2) the current emphasis on “big data” and the emphasis on quantitative data and evidence; (3) the labor market pressure in academia that leaves less time for fieldwork (see also Fine and Hancock 2017 ); (4) problems of access to fields; and (5) the increased ethical scrutiny of projects, to which ethnography is particularly exposed. Hammersley discusses some more or less insufficient existing definitions of ethnography.

The current situation, as Hammersley and others note—and in relation not only to ethnography but also qualitative research in general, and as our empirical study shows—is not just unsatisfactory, it may even be harmful for the entire field of qualitative research, and does not help social science at large. We suggest that the lack of clarity of qualitative research is a real problem that must be addressed.

Towards a Definition of Qualitative Research

Seen in an historical light, what is today called qualitative, or sometimes ethnographic, interpretative research – or a number of other terms – has more or less always existed. At the time the founders of sociology – Simmel, Weber, Durkheim and, before them, Marx – were writing, and during the era of the Methodenstreit (“dispute about methods”) in which the German historical school emphasized scientific methods (cf. Swedberg 1990 ), we can at least speak of qualitative forerunners.

Perhaps the most extended discussion of what later became known as qualitative methods in a classic work is Bronisław Malinowski’s ( 1922 ) Argonauts in the Western Pacific , although even this study does not explicitly address the meaning of “qualitative.” In Weber’s ([1921–-22] 1978) work we find a tension between scientific explanations that are based on observation and quantification and interpretative research (see also Lazarsfeld and Barton 1982 ).

If we look through major sociology journals like the American Sociological Review , American Journal of Sociology , or Social Forces we will not find the term qualitative sociology before the 1970s. And certainly before then much of what we consider qualitative classics in sociology, like Becker’ study ( 1963 ), had already been produced. Indeed, the Chicago School often combined qualitative and quantitative data within the same study (Fine 1995 ). Our point being that before a disciplinary self-awareness the term quantitative preceded qualitative, and the articulation of the former was a political move to claim scientific status (Denzin and Lincoln 2005 ). In the US the World War II seem to have sparked a critique of sociological work, including “qualitative work,” that did not follow the scientific canon (Rawls 2018 ), which was underpinned by a scientifically oriented and value free philosophy of science. As a result the attempts and practice of integrating qualitative and quantitative sociology at Chicago lost ground to sociology that was more oriented to surveys and quantitative work at Columbia under Merton-Lazarsfeld. The quantitative tradition was also able to present textbooks (Lundberg 1951 ) that facilitated the use this approach and its “methods.” The practices of the qualitative tradition, by and large, remained tacit or was part of the mentoring transferred from the renowned masters to their students.

This glimpse into history leads us back to the lack of a coherent account condensed in a definition of qualitative research. Many of the attempts to define the term do not meet the requirements of a proper definition: A definition should be clear, avoid tautology, demarcate its domain in relation to the environment, and ideally only use words in its definiens that themselves are not in need of definition (Hempel 1966 ). A definition can enhance precision and thus clarity by identifying the core of the phenomenon. Preferably, a definition should be short. The typical definition we have found, however, is an ostensive definition, which indicates what qualitative research is about without informing us about what it actually is :

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

Flick claims that the label “qualitative research” is indeed used as an umbrella for a number of approaches ( 2007 :2–4; 2002 :6), and it is not difficult to identify research fitting this designation. Moreover, whatever it is, it has grown dramatically over the past five decades. In addition, courses have been developed, methods have flourished, arguments about its future have been advanced (for example, Denzin and Lincoln 1994) and criticized (for example, Snow and Morrill 1995 ), and dedicated journals and books have mushroomed. Most social scientists have a clear idea of research and how it differs from journalism, politics and other activities. But the question of what is qualitative in qualitative research is either eluded or eschewed.

We maintain that this lacuna hinders systematic knowledge production based on qualitative research. Paul Lazarsfeld noted the lack of “codification” as early as 1955 when he reviewed 100 qualitative studies in order to offer a codification of the practices (Lazarsfeld and Barton 1982 :239). Since then many texts on “qualitative research” and its methods have been published, including recent attempts (Goertz and Mahoney 2012 ) similar to Lazarsfeld’s. These studies have tried to extract what is qualitative by looking at the large number of empirical “qualitative” studies. Our novel strategy complements these endeavors by taking another approach and looking at the attempts to codify these practices in the form of a definition, as well as to a minor extent take Becker’s study as an exemplar of what qualitative researchers actually do, and what the characteristic of being ‘qualitative’ denotes and implies. We claim that qualitative researchers, if there is such a thing as “qualitative research,” should be able to codify their practices in a condensed, yet general way expressed in language.

Lingering problems of “generalizability” and “how many cases do I need” (Small 2009 ) are blocking advancement – in this line of work qualitative approaches are said to differ considerably from quantitative ones, while some of the former unsuccessfully mimic principles related to the latter (Small 2009 ). Additionally, quantitative researchers sometimes unfairly criticize the first based on their own quality criteria. Scholars like Goertz and Mahoney ( 2012 ) have successfully focused on the different norms and practices beyond what they argue are essentially two different cultures: those working with either qualitative or quantitative methods. Instead, similarly to Becker ( 2017 ) who has recently questioned the usefulness of the distinction between qualitative and quantitative research, we focus on similarities.

The current situation also impedes both students and researchers in focusing their studies and understanding each other’s work (Lazarsfeld and Barton 1982 :239). A third consequence is providing an opening for critiques by scholars operating within different traditions (Valsiner 2000 :101). A fourth issue is that the “implicit use of methods in qualitative research makes the field far less standardized than the quantitative paradigm” (Goertz and Mahoney 2012 :9). Relatedly, the National Science Foundation in the US organized two workshops in 2004 and 2005 to address the scientific foundations of qualitative research involving strategies to improve it and to develop standards of evaluation in qualitative research. However, a specific focus on its distinguishing feature of being “qualitative” while being implicitly acknowledged, was discussed only briefly (for example, Best 2004 ).

In 2014 a theme issue was published in this journal on “Methods, Materials, and Meanings: Designing Cultural Analysis,” discussing central issues in (cultural) qualitative research (Berezin 2014 ; Biernacki 2014 ; Glaeser 2014 ; Lamont and Swidler 2014 ; Spillman 2014). We agree with many of the arguments put forward, such as the risk of methodological tribalism, and that we should not waste energy on debating methods separated from research questions. Nonetheless, a clarification of the relation to what is called “quantitative research” is of outmost importance to avoid misunderstandings and misguided debates between “qualitative” and “quantitative” researchers. Our strategy means that researchers, “qualitative” or “quantitative” they may be, in their actual practice may combine qualitative work and quantitative work.

In this article we accomplish three tasks. First, we systematically survey the literature for meanings of qualitative research by looking at how researchers have defined it. Drawing upon existing knowledge we find that the different meanings and ideas of qualitative research are not yet coherently integrated into one satisfactory definition. Next, we advance our contribution by offering a definition of qualitative research and illustrate its meaning and use partially by expanding on the brief example introduced earlier related to Becker’s work ( 1963 ). We offer a systematic analysis of central themes of what researchers consider to be the core of “qualitative,” regardless of style of work. These themes – which we summarize in terms of four keywords: distinction, process, closeness, improved understanding – constitute part of our literature review, in which each one appears, sometimes with others, but never all in the same definition. They serve as the foundation of our contribution. Our categories are overlapping. Their use is primarily to organize the large amount of definitions we have identified and analyzed, and not necessarily to draw a clear distinction between them. Finally, we continue the elaboration discussed above on the advantages of a clear definition of qualitative research.

In a hermeneutic fashion we propose that there is something meaningful that deserves to be labelled “qualitative research” (Gadamer 1990 ). To approach the question “What is qualitative in qualitative research?” we have surveyed the literature. In conducting our survey we first traced the word’s etymology in dictionaries, encyclopedias, handbooks of the social sciences and of methods and textbooks, mainly in English, which is common to methodology courses. It should be noted that we have zoomed in on sociology and its literature. This discipline has been the site of the largest debate and development of methods that can be called “qualitative,” which suggests that this field should be examined in great detail.

In an ideal situation we should expect that one good definition, or at least some common ideas, would have emerged over the years. This common core of qualitative research should be so accepted that it would appear in at least some textbooks. Since this is not what we found, we decided to pursue an inductive approach to capture maximal variation in the field of qualitative research; we searched in a selection of handbooks, textbooks, book chapters, and books, to which we added the analysis of journal articles. Our sample comprises a total of 89 references.

In practice we focused on the discipline that has had a clear discussion of methods, namely sociology. We also conducted a broad search in the JSTOR database to identify scholarly sociology articles published between 1998 and 2017 in English with a focus on defining or explaining qualitative research. We specifically zoom in on this time frame because we would have expect that this more mature period would have produced clear discussions on the meaning of qualitative research. To find these articles we combined a number of keywords to search the content and/or the title: qualitative (which was always included), definition, empirical, research, methodology, studies, fieldwork, interview and observation .

As a second phase of our research we searched within nine major sociological journals ( American Journal of Sociology , Sociological Theory , American Sociological Review , Contemporary Sociology , Sociological Forum , Sociological Theory , Qualitative Research , Qualitative Sociology and Qualitative Sociology Review ) for articles also published during the past 19 years (1998–2017) that had the term “qualitative” in the title and attempted to define qualitative research.

Lastly we picked two additional journals, Qualitative Research and Qualitative Sociology , in which we could expect to find texts addressing the notion of “qualitative.” From Qualitative Research we chose Volume 14, Issue 6, December 2014, and from Qualitative Sociology we chose Volume 36, Issue 2, June 2017. Within each of these we selected the first article; then we picked the second article of three prior issues. Again we went back another three issues and investigated article number three. Finally we went back another three issues and perused article number four. This selection criteria was used to get a manageable sample for the analysis.

The coding process of the 89 references we gathered in our selected review began soon after the first round of material was gathered, and we reduced the complexity created by our maximum variation sampling (Snow and Anderson 1993 :22) to four different categories within which questions on the nature and properties of qualitative research were discussed. We call them: Qualitative and Quantitative Research, Qualitative Research, Fieldwork, and Grounded Theory. This – which may appear as an illogical grouping – merely reflects the “context” in which the matter of “qualitative” is discussed. If the selection process of the material – books and articles – was informed by pre-knowledge, we used an inductive strategy to code the material. When studying our material, we identified four central notions related to “qualitative” that appear in various combinations in the literature which indicate what is the core of qualitative research. We have labeled them: “distinctions”, “process,” “closeness,” and “improved understanding.” During the research process the categories and notions were improved, refined, changed, and reordered. The coding ended when a sense of saturation in the material arose. In the presentation below all quotations and references come from our empirical material of texts on qualitative research.

Analysis – What is Qualitative Research?

In this section we describe the four categories we identified in the coding, how they differently discuss qualitative research, as well as their overall content. Some salient quotations are selected to represent the type of text sorted under each of the four categories. What we present are examples from the literature.

Qualitative and Quantitative

This analytic category comprises quotations comparing qualitative and quantitative research, a distinction that is frequently used (Brown 2010 :231); in effect this is a conceptual pair that structures the discussion and that may be associated with opposing interests. While the general goal of quantitative and qualitative research is the same – to understand the world better – their methodologies and focus in certain respects differ substantially (Becker 1966 :55). Quantity refers to that property of something that can be determined by measurement. In a dictionary of Statistics and Methodology we find that “(a) When referring to *variables, ‘qualitative’ is another term for *categorical or *nominal. (b) When speaking of kinds of research, ‘qualitative’ refers to studies of subjects that are hard to quantify, such as art history. Qualitative research tends to be a residual category for almost any kind of non-quantitative research” (Stiles 1998:183). But it should be obvious that one could employ a quantitative approach when studying, for example, art history.

The same dictionary states that quantitative is “said of variables or research that can be handled numerically, usually (too sharply) contrasted with *qualitative variables and research” (Stiles 1998:184). From a qualitative perspective “quantitative research” is about numbers and counting, and from a quantitative perspective qualitative research is everything that is not about numbers. But this does not say much about what is “qualitative.” If we turn to encyclopedias we find that in the 1932 edition of the Encyclopedia of the Social Sciences there is no mention of “qualitative.” In the Encyclopedia from 1968 we can read:

Qualitative Analysis. For methods of obtaining, analyzing, and describing data, see [the various entries:] CONTENT ANALYSIS; COUNTED DATA; EVALUATION RESEARCH, FIELD WORK; GRAPHIC PRESENTATION; HISTORIOGRAPHY, especially the article on THE RHETORIC OF HISTORY; INTERVIEWING; OBSERVATION; PERSONALITY MEASUREMENT; PROJECTIVE METHODS; PSYCHOANALYSIS, article on EXPERIMENTAL METHODS; SURVEY ANALYSIS, TABULAR PRESENTATION; TYPOLOGIES. (Vol. 13:225)

Some, like Alford, divide researchers into methodologists or, in his words, “quantitative and qualitative specialists” (Alford 1998 :12). Qualitative research uses a variety of methods, such as intensive interviews or in-depth analysis of historical materials, and it is concerned with a comprehensive account of some event or unit (King et al. 1994 :4). Like quantitative research it can be utilized to study a variety of issues, but it tends to focus on meanings and motivations that underlie cultural symbols, personal experiences, phenomena and detailed understanding of processes in the social world. In short, qualitative research centers on understanding processes, experiences, and the meanings people assign to things (Kalof et al. 2008 :79).

Others simply say that qualitative methods are inherently unscientific (Jovanović 2011 :19). Hood, for instance, argues that words are intrinsically less precise than numbers, and that they are therefore more prone to subjective analysis, leading to biased results (Hood 2006 :219). Qualitative methodologies have raised concerns over the limitations of quantitative templates (Brady et al. 2004 :4). Scholars such as King et al. ( 1994 ), for instance, argue that non-statistical research can produce more reliable results if researchers pay attention to the rules of scientific inference commonly stated in quantitative research. Also, researchers such as Becker ( 1966 :59; 1970 :42–43) have asserted that, if conducted properly, qualitative research and in particular ethnographic field methods, can lead to more accurate results than quantitative studies, in particular, survey research and laboratory experiments.

Some researchers, such as Kalof, Dan, and Dietz ( 2008 :79) claim that the boundaries between the two approaches are becoming blurred, and Small ( 2009 ) argues that currently much qualitative research (especially in North America) tries unsuccessfully and unnecessarily to emulate quantitative standards. For others, qualitative research tends to be more humanistic and discursive (King et al. 1994 :4). Ragin ( 1994 ), and similarly also Becker, ( 1996 :53), Marchel and Owens ( 2007 :303) think that the main distinction between the two styles is overstated and does not rest on the simple dichotomy of “numbers versus words” (Ragin 1994 :xii). Some claim that quantitative data can be utilized to discover associations, but in order to unveil cause and effect a complex research design involving the use of qualitative approaches needs to be devised (Gilbert 2009 :35). Consequently, qualitative data are useful for understanding the nuances lying beyond those processes as they unfold (Gilbert 2009 :35). Others contend that qualitative research is particularly well suited both to identify causality and to uncover fine descriptive distinctions (Fine and Hallett 2014 ; Lichterman and Isaac Reed 2014 ; Katz 2015 ).

There are other ways to separate these two traditions, including normative statements about what qualitative research should be (that is, better or worse than quantitative approaches, concerned with scientific approaches to societal change or vice versa; Snow and Morrill 1995 ; Denzin and Lincoln 2005 ), or whether it should develop falsifiable statements; Best 2004 ).

We propose that quantitative research is largely concerned with pre-determined variables (Small 2008 ); the analysis concerns the relations between variables. These categories are primarily not questioned in the study, only their frequency or degree, or the correlations between them (cf. Franzosi 2016 ). If a researcher studies wage differences between women and men, he or she works with given categories: x number of men are compared with y number of women, with a certain wage attributed to each person. The idea is not to move beyond the given categories of wage, men and women; they are the starting point as well as the end point, and undergo no “qualitative change.” Qualitative research, in contrast, investigates relations between categories that are themselves subject to change in the research process. Returning to Becker’s study ( 1963 ), we see that he questioned pre-dispositional theories of deviant behavior working with pre-determined variables such as an individual’s combination of personal qualities or emotional problems. His take, in contrast, was to understand marijuana consumption by developing “variables” as part of the investigation. Thereby he presented new variables, or as we would say today, theoretical concepts, but which are grounded in the empirical material.

Qualitative Research

This category contains quotations that refer to descriptions of qualitative research without making comparisons with quantitative research. Researchers such as Denzin and Lincoln, who have written a series of influential handbooks on qualitative methods (1994; Denzin and Lincoln 2003 ; 2005 ), citing Nelson et al. (1992:4), argue that because qualitative research is “interdisciplinary, transdisciplinary, and sometimes counterdisciplinary” it is difficult to derive one single definition of it (Jovanović 2011 :3). According to them, in fact, “the field” is “many things at the same time,” involving contradictions, tensions over its focus, methods, and how to derive interpretations and findings ( 2003 : 11). Similarly, others, such as Flick ( 2007 :ix–x) contend that agreeing on an accepted definition has increasingly become problematic, and that qualitative research has possibly matured different identities. However, Best holds that “the proliferation of many sorts of activities under the label of qualitative sociology threatens to confuse our discussions” ( 2004 :54). Atkinson’s position is more definite: “the current state of qualitative research and research methods is confused” ( 2005 :3–4).

Qualitative research is about interpretation (Blumer 1969 ; Strauss and Corbin 1998 ; Denzin and Lincoln 2003 ), or Verstehen [understanding] (Frankfort-Nachmias and Nachmias 1996 ). It is “multi-method,” involving the collection and use of a variety of empirical materials (Denzin and Lincoln 1998; Silverman 2013 ) and approaches (Silverman 2005 ; Flick 2007 ). It focuses not only on the objective nature of behavior but also on its subjective meanings: individuals’ own accounts of their attitudes, motivations, behavior (McIntyre 2005 :127; Creswell 2009 ), events and situations (Bryman 1989) – what people say and do in specific places and institutions (Goodwin and Horowitz 2002 :35–36) in social and temporal contexts (Morrill and Fine 1997). For this reason, following Weber ([1921-22] 1978), it can be described as an interpretative science (McIntyre 2005 :127). But could quantitative research also be concerned with these questions? Also, as pointed out below, does all qualitative research focus on subjective meaning, as some scholars suggest?

Others also distinguish qualitative research by claiming that it collects data using a naturalistic approach (Denzin and Lincoln 2005 :2; Creswell 2009 ), focusing on the meaning actors ascribe to their actions. But again, does all qualitative research need to be collected in situ? And does qualitative research have to be inherently concerned with meaning? Flick ( 2007 ), referring to Denzin and Lincoln ( 2005 ), mentions conversation analysis as an example of qualitative research that is not concerned with the meanings people bring to a situation, but rather with the formal organization of talk. Still others, such as Ragin ( 1994 :85), note that qualitative research is often (especially early on in the project, we would add) less structured than other kinds of social research – a characteristic connected to its flexibility and that can lead both to potentially better, but also worse results. But is this not a feature of this type of research, rather than a defining description of its essence? Wouldn’t this comment also apply, albeit to varying degrees, to quantitative research?

In addition, Strauss ( 2003 ), along with others, such as Alvesson and Kärreman ( 2011 :10–76), argue that qualitative researchers struggle to capture and represent complex phenomena partially because they tend to collect a large amount of data. While his analysis is correct at some points – “It is necessary to do detailed, intensive, microscopic examination of the data in order to bring out the amazing complexity of what lies in, behind, and beyond those data” (Strauss 2003 :10) – much of his analysis concerns the supposed focus of qualitative research and its challenges, rather than exactly what it is about. But even in this instance we would make a weak case arguing that these are strictly the defining features of qualitative research. Some researchers seem to focus on the approach or the methods used, or even on the way material is analyzed. Several researchers stress the naturalistic assumption of investigating the world, suggesting that meaning and interpretation appear to be a core matter of qualitative research.

We can also see that in this category there is no consensus about specific qualitative methods nor about qualitative data. Many emphasize interpretation, but quantitative research, too, involves interpretation; the results of a regression analysis, for example, certainly have to be interpreted, and the form of meta-analysis that factor analysis provides indeed requires interpretation However, there is no interpretation of quantitative raw data, i.e., numbers in tables. One common thread is that qualitative researchers have to get to grips with their data in order to understand what is being studied in great detail, irrespective of the type of empirical material that is being analyzed. This observation is connected to the fact that qualitative researchers routinely make several adjustments of focus and research design as their studies progress, in many cases until the very end of the project (Kalof et al. 2008 ). If you, like Becker, do not start out with a detailed theory, adjustments such as the emergence and refinement of research questions will occur during the research process. We have thus found a number of useful reflections about qualitative research scattered across different sources, but none of them effectively describe the defining characteristics of this approach.

Although qualitative research does not appear to be defined in terms of a specific method, it is certainly common that fieldwork, i.e., research that entails that the researcher spends considerable time in the field that is studied and use the knowledge gained as data, is seen as emblematic of or even identical to qualitative research. But because we understand that fieldwork tends to focus primarily on the collection and analysis of qualitative data, we expected to find within it discussions on the meaning of “qualitative.” But, again, this was not the case.

Instead, we found material on the history of this approach (for example, Frankfort-Nachmias and Nachmias 1996 ; Atkinson et al. 2001), including how it has changed; for example, by adopting a more self-reflexive practice (Heyl 2001), as well as the different nomenclature that has been adopted, such as fieldwork, ethnography, qualitative research, naturalistic research, participant observation and so on (for example, Lofland et al. 2006 ; Gans 1999 ).

We retrieved definitions of ethnography, such as “the study of people acting in the natural courses of their daily lives,” involving a “resocialization of the researcher” (Emerson 1988 :1) through intense immersion in others’ social worlds (see also examples in Hammersley 2018 ). This may be accomplished by direct observation and also participation (Neuman 2007 :276), although others, such as Denzin ( 1970 :185), have long recognized other types of observation, including non-participant (“fly on the wall”). In this category we have also isolated claims and opposing views, arguing that this type of research is distinguished primarily by where it is conducted (natural settings) (Hughes 1971:496), and how it is carried out (a variety of methods are applied) or, for some most importantly, by involving an active, empathetic immersion in those being studied (Emerson 1988 :2). We also retrieved descriptions of the goals it attends in relation to how it is taught (understanding subjective meanings of the people studied, primarily develop theory, or contribute to social change) (see for example, Corte and Irwin 2017 ; Frankfort-Nachmias and Nachmias 1996 :281; Trier-Bieniek 2012 :639) by collecting the richest possible data (Lofland et al. 2006 ) to derive “thick descriptions” (Geertz 1973 ), and/or to aim at theoretical statements of general scope and applicability (for example, Emerson 1988 ; Fine 2003 ). We have identified guidelines on how to evaluate it (for example Becker 1996 ; Lamont 2004 ) and have retrieved instructions on how it should be conducted (for example, Lofland et al. 2006 ). For instance, analysis should take place while the data gathering unfolds (Emerson 1988 ; Hammersley and Atkinson 2007 ; Lofland et al. 2006 ), observations should be of long duration (Becker 1970 :54; Goffman 1989 ), and data should be of high quantity (Becker 1970 :52–53), as well as other questionable distinctions between fieldwork and other methods:

Field studies differ from other methods of research in that the researcher performs the task of selecting topics, decides what questions to ask, and forges interest in the course of the research itself . This is in sharp contrast to many ‘theory-driven’ and ‘hypothesis-testing’ methods. (Lofland and Lofland 1995 :5)

But could not, for example, a strictly interview-based study be carried out with the same amount of flexibility, such as sequential interviewing (for example, Small 2009 )? Once again, are quantitative approaches really as inflexible as some qualitative researchers think? Moreover, this category stresses the role of the actors’ meaning, which requires knowledge and close interaction with people, their practices and their lifeworld.

It is clear that field studies – which are seen by some as the “gold standard” of qualitative research – are nonetheless only one way of doing qualitative research. There are other methods, but it is not clear why some are more qualitative than others, or why they are better or worse. Fieldwork is characterized by interaction with the field (the material) and understanding of the phenomenon that is being studied. In Becker’s case, he had general experience from fields in which marihuana was used, based on which he did interviews with actual users in several fields.

Grounded Theory

Another major category we identified in our sample is Grounded Theory. We found descriptions of it most clearly in Glaser and Strauss’ ([1967] 2010 ) original articulation, Strauss and Corbin ( 1998 ) and Charmaz ( 2006 ), as well as many other accounts of what it is for: generating and testing theory (Strauss 2003 :xi). We identified explanations of how this task can be accomplished – such as through two main procedures: constant comparison and theoretical sampling (Emerson 1998:96), and how using it has helped researchers to “think differently” (for example, Strauss and Corbin 1998 :1). We also read descriptions of its main traits, what it entails and fosters – for instance, an exceptional flexibility, an inductive approach (Strauss and Corbin 1998 :31–33; 1990; Esterberg 2002 :7), an ability to step back and critically analyze situations, recognize tendencies towards bias, think abstractly and be open to criticism, enhance sensitivity towards the words and actions of respondents, and develop a sense of absorption and devotion to the research process (Strauss and Corbin 1998 :5–6). Accordingly, we identified discussions of the value of triangulating different methods (both using and not using grounded theory), including quantitative ones, and theories to achieve theoretical development (most comprehensively in Denzin 1970 ; Strauss and Corbin 1998 ; Timmermans and Tavory 2012 ). We have also located arguments about how its practice helps to systematize data collection, analysis and presentation of results (Glaser and Strauss [1967] 2010 :16).

Grounded theory offers a systematic approach which requires researchers to get close to the field; closeness is a requirement of identifying questions and developing new concepts or making further distinctions with regard to old concepts. In contrast to other qualitative approaches, grounded theory emphasizes the detailed coding process, and the numerous fine-tuned distinctions that the researcher makes during the process. Within this category, too, we could not find a satisfying discussion of the meaning of qualitative research.

Defining Qualitative Research

In sum, our analysis shows that some notions reappear in the discussion of qualitative research, such as understanding, interpretation, “getting close” and making distinctions. These notions capture aspects of what we think is “qualitative.” However, a comprehensive definition that is useful and that can further develop the field is lacking, and not even a clear picture of its essential elements appears. In other words no definition emerges from our data, and in our research process we have moved back and forth between our empirical data and the attempt to present a definition. Our concrete strategy, as stated above, is to relate qualitative and quantitative research, or more specifically, qualitative and quantitative work. We use an ideal-typical notion of quantitative research which relies on taken for granted and numbered variables. This means that the data consists of variables on different scales, such as ordinal, but frequently ratio and absolute scales, and the representation of the numbers to the variables, i.e. the justification of the assignment of numbers to object or phenomenon, are not questioned, though the validity may be questioned. In this section we return to the notion of quality and try to clarify it while presenting our contribution.

Broadly, research refers to the activity performed by people trained to obtain knowledge through systematic procedures. Notions such as “objectivity” and “reflexivity,” “systematic,” “theory,” “evidence” and “openness” are here taken for granted in any type of research. Next, building on our empirical analysis we explain the four notions that we have identified as central to qualitative work: distinctions, process, closeness, and improved understanding. In discussing them, ultimately in relation to one another, we make their meaning even more precise. Our idea, in short, is that only when these ideas that we present separately for analytic purposes are brought together can we speak of qualitative research.

Distinctions

We believe that the possibility of making new distinctions is one the defining characteristics of qualitative research. It clearly sets it apart from quantitative analysis which works with taken-for-granted variables, albeit as mentioned, meta-analyses, for example, factor analysis may result in new variables. “Quality” refers essentially to distinctions, as already pointed out by Aristotle. He discusses the term “qualitative” commenting: “By a quality I mean that in virtue of which things are said to be qualified somehow” (Aristotle 1984:14). Quality is about what something is or has, which means that the distinction from its environment is crucial. We see qualitative research as a process in which significant new distinctions are made to the scholarly community; to make distinctions is a key aspect of obtaining new knowledge; a point, as we will see, that also has implications for “quantitative research.” The notion of being “significant” is paramount. New distinctions by themselves are not enough; just adding concepts only increases complexity without furthering our knowledge. The significance of new distinctions is judged against the communal knowledge of the research community. To enable this discussion and judgements central elements of rational discussion are required (cf. Habermas [1981] 1987 ; Davidsson [ 1988 ] 2001) to identify what is new and relevant scientific knowledge. Relatedly, Ragin alludes to the idea of new and useful knowledge at a more concrete level: “Qualitative methods are appropriate for in-depth examination of cases because they aid the identification of key features of cases. Most qualitative methods enhance data” (1994:79). When Becker ( 1963 ) studied deviant behavior and investigated how people became marihuana smokers, he made distinctions between the ways in which people learned how to smoke. This is a classic example of how the strategy of “getting close” to the material, for example the text, people or pictures that are subject to analysis, may enable researchers to obtain deeper insight and new knowledge by making distinctions – in this instance on the initial notion of learning how to smoke. Others have stressed the making of distinctions in relation to coding or theorizing. Emerson et al. ( 1995 ), for example, hold that “qualitative coding is a way of opening up avenues of inquiry,” meaning that the researcher identifies and develops concepts and analytic insights through close examination of and reflection on data (Emerson et al. 1995 :151). Goodwin and Horowitz highlight making distinctions in relation to theory-building writing: “Close engagement with their cases typically requires qualitative researchers to adapt existing theories or to make new conceptual distinctions or theoretical arguments to accommodate new data” ( 2002 : 37). In the ideal-typical quantitative research only existing and so to speak, given, variables would be used. If this is the case no new distinction are made. But, would not also many “quantitative” researchers make new distinctions?

Process does not merely suggest that research takes time. It mainly implies that qualitative new knowledge results from a process that involves several phases, and above all iteration. Qualitative research is about oscillation between theory and evidence, analysis and generating material, between first- and second -order constructs (Schütz 1962 :59), between getting in contact with something, finding sources, becoming deeply familiar with a topic, and then distilling and communicating some of its essential features. The main point is that the categories that the researcher uses, and perhaps takes for granted at the beginning of the research process, usually undergo qualitative changes resulting from what is found. Becker describes how he tested hypotheses and let the jargon of the users develop into theoretical concepts. This happens over time while the study is being conducted, exemplifying what we mean by process.

In the research process, a pilot-study may be used to get a first glance of, for example, the field, how to approach it, and what methods can be used, after which the method and theory are chosen or refined before the main study begins. Thus, the empirical material is often central from the start of the project and frequently leads to adjustments by the researcher. Likewise, during the main study categories are not fixed; the empirical material is seen in light of the theory used, but it is also given the opportunity to kick back, thereby resisting attempts to apply theoretical straightjackets (Becker 1970 :43). In this process, coding and analysis are interwoven, and thus are often important steps for getting closer to the phenomenon and deciding what to focus on next. Becker began his research by interviewing musicians close to him, then asking them to refer him to other musicians, and later on doubling his original sample of about 25 to include individuals in other professions (Becker 1973:46). Additionally, he made use of some participant observation, documents, and interviews with opiate users made available to him by colleagues. As his inductive theory of deviance evolved, Becker expanded his sample in order to fine tune it, and test the accuracy and generality of his hypotheses. In addition, he introduced a negative case and discussed the null hypothesis ( 1963 :44). His phasic career model is thus based on a research design that embraces processual work. Typically, process means to move between “theory” and “material” but also to deal with negative cases, and Becker ( 1998 ) describes how discovering these negative cases impacted his research design and ultimately its findings.

Obviously, all research is process-oriented to some degree. The point is that the ideal-typical quantitative process does not imply change of the data, and iteration between data, evidence, hypotheses, empirical work, and theory. The data, quantified variables, are, in most cases fixed. Merging of data, which of course can be done in a quantitative research process, does not mean new data. New hypotheses are frequently tested, but the “raw data is often the “the same.” Obviously, over time new datasets are made available and put into use.

Another characteristic that is emphasized in our sample is that qualitative researchers – and in particular ethnographers – can, or as Goffman put it, ought to ( 1989 ), get closer to the phenomenon being studied and their data than quantitative researchers (for example, Silverman 2009 :85). Put differently, essentially because of their methods qualitative researchers get into direct close contact with those being investigated and/or the material, such as texts, being analyzed. Becker started out his interview study, as we noted, by talking to those he knew in the field of music to get closer to the phenomenon he was studying. By conducting interviews he got even closer. Had he done more observations, he would undoubtedly have got even closer to the field.

Additionally, ethnographers’ design enables researchers to follow the field over time, and the research they do is almost by definition longitudinal, though the time in the field is studied obviously differs between studies. The general characteristic of closeness over time maximizes the chances of unexpected events, new data (related, for example, to archival research as additional sources, and for ethnography for situations not necessarily previously thought of as instrumental – what Mannay and Morgan ( 2015 ) term the “waiting field”), serendipity (Merton and Barber 2004 ; Åkerström 2013 ), and possibly reactivity, as well as the opportunity to observe disrupted patterns that translate into exemplars of negative cases. Two classic examples of this are Becker’s finding of what medical students call “crocks” (Becker et al. 1961 :317), and Geertz’s ( 1973 ) study of “deep play” in Balinese society.

By getting and staying so close to their data – be it pictures, text or humans interacting (Becker was himself a musician) – for a long time, as the research progressively focuses, qualitative researchers are prompted to continually test their hunches, presuppositions and hypotheses. They test them against a reality that often (but certainly not always), and practically, as well as metaphorically, talks back, whether by validating them, or disqualifying their premises – correctly, as well as incorrectly (Fine 2003 ; Becker 1970 ). This testing nonetheless often leads to new directions for the research. Becker, for example, says that he was initially reading psychological theories, but when facing the data he develops a theory that looks at, you may say, everything but psychological dispositions to explain the use of marihuana. Especially researchers involved with ethnographic methods have a fairly unique opportunity to dig up and then test (in a circular, continuous and temporal way) new research questions and findings as the research progresses, and thereby to derive previously unimagined and uncharted distinctions by getting closer to the phenomenon under study.

Let us stress that getting close is by no means restricted to ethnography. The notion of hermeneutic circle and hermeneutics as a general way of understanding implies that we must get close to the details in order to get the big picture. This also means that qualitative researchers can literally also make use of details of pictures as evidence (cf. Harper 2002). Thus, researchers may get closer both when generating the material or when analyzing it.

Quantitative research, we maintain, in the ideal-typical representation cannot get closer to the data. The data is essentially numbers in tables making up the variables (Franzosi 2016 :138). The data may originally have been “qualitative,” but once reduced to numbers there can only be a type of “hermeneutics” about what the number may stand for. The numbers themselves, however, are non-ambiguous. Thus, in quantitative research, interpretation, if done, is not about the data itself—the numbers—but what the numbers stand for. It follows that the interpretation is essentially done in a more “speculative” mode without direct empirical evidence (cf. Becker 2017 ).

Improved Understanding

While distinction, process and getting closer refer to the qualitative work of the researcher, improved understanding refers to its conditions and outcome of this work. Understanding cuts deeper than explanation, which to some may mean a causally verified correlation between variables. The notion of explanation presupposes the notion of understanding since explanation does not include an idea of how knowledge is gained (Manicas 2006 : 15). Understanding, we argue, is the core concept of what we call the outcome of the process when research has made use of all the other elements that were integrated in the research. Understanding, then, has a special status in qualitative research since it refers both to the conditions of knowledge and the outcome of the process. Understanding can to some extent be seen as the condition of explanation and occurs in a process of interpretation, which naturally refers to meaning (Gadamer 1990 ). It is fundamentally connected to knowing, and to the knowing of how to do things (Heidegger [1927] 2001 ). Conceptually the term hermeneutics is used to account for this process. Heidegger ties hermeneutics to human being and not possible to separate from the understanding of being ( 1988 ). Here we use it in a broader sense, and more connected to method in general (cf. Seiffert 1992 ). The abovementioned aspects – for example, “objectivity” and “reflexivity” – of the approach are conditions of scientific understanding. Understanding is the result of a circular process and means that the parts are understood in light of the whole, and vice versa. Understanding presupposes pre-understanding, or in other words, some knowledge of the phenomenon studied. The pre-understanding, even in the form of prejudices, are in qualitative research process, which we see as iterative, questioned, which gradually or suddenly change due to the iteration of data, evidence and concepts. However, qualitative research generates understanding in the iterative process when the researcher gets closer to the data, e.g., by going back and forth between field and analysis in a process that generates new data that changes the evidence, and, ultimately, the findings. Questioning, to ask questions, and put what one assumes—prejudices and presumption—in question, is central to understand something (Heidegger [1927] 2001 ; Gadamer 1990 :368–384). We propose that this iterative process in which the process of understanding occurs is characteristic of qualitative research.

Improved understanding means that we obtain scientific knowledge of something that we as a scholarly community did not know before, or that we get to know something better. It means that we understand more about how parts are related to one another, and to other things we already understand (see also Fine and Hallett 2014 ). Understanding is an important condition for qualitative research. It is not enough to identify correlations, make distinctions, and work in a process in which one gets close to the field or phenomena. Understanding is accomplished when the elements are integrated in an iterative process.

It is, moreover, possible to understand many things, and researchers, just like children, may come to understand new things every day as they engage with the world. This subjective condition of understanding – namely, that a person gains a better understanding of something –is easily met. To be qualified as “scientific,” the understanding must be general and useful to many; it must be public. But even this generally accessible understanding is not enough in order to speak of “scientific understanding.” Though we as a collective can increase understanding of everything in virtually all potential directions as a result also of qualitative work, we refrain from this “objective” way of understanding, which has no means of discriminating between what we gain in understanding. Scientific understanding means that it is deemed relevant from the scientific horizon (compare Schütz 1962 : 35–38, 46, 63), and that it rests on the pre-understanding that the scientists have and must have in order to understand. In other words, the understanding gained must be deemed useful by other researchers, so that they can build on it. We thus see understanding from a pragmatic, rather than a subjective or objective perspective. Improved understanding is related to the question(s) at hand. Understanding, in order to represent an improvement, must be an improvement in relation to the existing body of knowledge of the scientific community (James [ 1907 ] 1955). Scientific understanding is, by definition, collective, as expressed in Weber’s famous note on objectivity, namely that scientific work aims at truths “which … can claim, even for a Chinese, the validity appropriate to an empirical analysis” ([1904] 1949 :59). By qualifying “improved understanding” we argue that it is a general defining characteristic of qualitative research. Becker‘s ( 1966 ) study and other research of deviant behavior increased our understanding of the social learning processes of how individuals start a behavior. And it also added new knowledge about the labeling of deviant behavior as a social process. Few studies, of course, make the same large contribution as Becker’s, but are nonetheless qualitative research.

Understanding in the phenomenological sense, which is a hallmark of qualitative research, we argue, requires meaning and this meaning is derived from the context, and above all the data being analyzed. The ideal-typical quantitative research operates with given variables with different numbers. This type of material is not enough to establish meaning at the level that truly justifies understanding. In other words, many social science explanations offer ideas about correlations or even causal relations, but this does not mean that the meaning at the level of the data analyzed, is understood. This leads us to say that there are indeed many explanations that meet the criteria of understanding, for example the explanation of how one becomes a marihuana smoker presented by Becker. However, we may also understand a phenomenon without explaining it, and we may have potential explanations, or better correlations, that are not really understood.

We may speak more generally of quantitative research and its data to clarify what we see as an important distinction. The “raw data” that quantitative research—as an idealtypical activity, refers to is not available for further analysis; the numbers, once created, are not to be questioned (Franzosi 2016 : 138). If the researcher is to do “more” or “change” something, this will be done by conjectures based on theoretical knowledge or based on the researcher’s lifeworld. Both qualitative and quantitative research is based on the lifeworld, and all researchers use prejudices and pre-understanding in the research process. This idea is present in the works of Heidegger ( 2001 ) and Heisenberg (cited in Franzosi 2010 :619). Qualitative research, as we argued, involves the interaction and questioning of concepts (theory), data, and evidence.

Ragin ( 2004 :22) points out that “a good definition of qualitative research should be inclusive and should emphasize its key strengths and features, not what it lacks (for example, the use of sophisticated quantitative techniques).” We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. Qualitative research, as defined here, is consequently a combination of two criteria: (i) how to do things –namely, generating and analyzing empirical material, in an iterative process in which one gets closer by making distinctions, and (ii) the outcome –improved understanding novel to the scholarly community. Is our definition applicable to our own study? In this study we have closely read the empirical material that we generated, and the novel distinction of the notion “qualitative research” is the outcome of an iterative process in which both deduction and induction were involved, in which we identified the categories that we analyzed. We thus claim to meet the first criteria, “how to do things.” The second criteria cannot be judged but in a partial way by us, namely that the “outcome” —in concrete form the definition-improves our understanding to others in the scientific community.

We have defined qualitative research, or qualitative scientific work, in relation to quantitative scientific work. Given this definition, qualitative research is about questioning the pre-given (taken for granted) variables, but it is thus also about making new distinctions of any type of phenomenon, for example, by coining new concepts, including the identification of new variables. This process, as we have discussed, is carried out in relation to empirical material, previous research, and thus in relation to theory. Theory and previous research cannot be escaped or bracketed. According to hermeneutic principles all scientific work is grounded in the lifeworld, and as social scientists we can thus never fully bracket our pre-understanding.

We have proposed that quantitative research, as an idealtype, is concerned with pre-determined variables (Small 2008 ). Variables are epistemically fixed, but can vary in terms of dimensions, such as frequency or number. Age is an example; as a variable it can take on different numbers. In relation to quantitative research, qualitative research does not reduce its material to number and variables. If this is done the process of comes to a halt, the researcher gets more distanced from her data, and it makes it no longer possible to make new distinctions that increase our understanding. We have above discussed the components of our definition in relation to quantitative research. Our conclusion is that in the research that is called quantitative there are frequent and necessary qualitative elements.

Further, comparative empirical research on researchers primarily working with ”quantitative” approaches and those working with ”qualitative” approaches, we propose, would perhaps show that there are many similarities in practices of these two approaches. This is not to deny dissimilarities, or the different epistemic and ontic presuppositions that may be more or less strongly associated with the two different strands (see Goertz and Mahoney 2012 ). Our point is nonetheless that prejudices and preconceptions about researchers are unproductive, and that as other researchers have argued, differences may be exaggerated (e.g., Becker 1996 : 53, 2017 ; Marchel and Owens 2007 :303; Ragin 1994 ), and that a qualitative dimension is present in both kinds of work.

Several things follow from our findings. The most important result is the relation to quantitative research. In our analysis we have separated qualitative research from quantitative research. The point is not to label individual researchers, methods, projects, or works as either “quantitative” or “qualitative.” By analyzing, i.e., taking apart, the notions of quantitative and qualitative, we hope to have shown the elements of qualitative research. Our definition captures the elements, and how they, when combined in practice, generate understanding. As many of the quotations we have used suggest, one conclusion of our study holds that qualitative approaches are not inherently connected with a specific method. Put differently, none of the methods that are frequently labelled “qualitative,” such as interviews or participant observation, are inherently “qualitative.” What matters, given our definition, is whether one works qualitatively or quantitatively in the research process, until the results are produced. Consequently, our analysis also suggests that those researchers working with what in the literature and in jargon is often called “quantitative research” are almost bound to make use of what we have identified as qualitative elements in any research project. Our findings also suggest that many” quantitative” researchers, at least to some extent, are engaged with qualitative work, such as when research questions are developed, variables are constructed and combined, and hypotheses are formulated. Furthermore, a research project may hover between “qualitative” and “quantitative” or start out as “qualitative” and later move into a “quantitative” (a distinct strategy that is not similar to “mixed methods” or just simply combining induction and deduction). More generally speaking, the categories of “qualitative” and “quantitative,” unfortunately, often cover up practices, and it may lead to “camps” of researchers opposing one another. For example, regardless of the researcher is primarily oriented to “quantitative” or “qualitative” research, the role of theory is neglected (cf. Swedberg 2017 ). Our results open up for an interaction not characterized by differences, but by different emphasis, and similarities.

Let us take two examples to briefly indicate how qualitative elements can fruitfully be combined with quantitative. Franzosi ( 2010 ) has discussed the relations between quantitative and qualitative approaches, and more specifically the relation between words and numbers. He analyzes texts and argues that scientific meaning cannot be reduced to numbers. Put differently, the meaning of the numbers is to be understood by what is taken for granted, and what is part of the lifeworld (Schütz 1962 ). Franzosi shows how one can go about using qualitative and quantitative methods and data to address scientific questions analyzing violence in Italy at the time when fascism was rising (1919–1922). Aspers ( 2006 ) studied the meaning of fashion photographers. He uses an empirical phenomenological approach, and establishes meaning at the level of actors. In a second step this meaning, and the different ideal-typical photographers constructed as a result of participant observation and interviews, are tested using quantitative data from a database; in the first phase to verify the different ideal-types, in the second phase to use these types to establish new knowledge about the types. In both of these cases—and more examples can be found—authors move from qualitative data and try to keep the meaning established when using the quantitative data.

A second main result of our study is that a definition, and we provided one, offers a way for research to clarify, and even evaluate, what is done. Hence, our definition can guide researchers and students, informing them on how to think about concrete research problems they face, and to show what it means to get closer in a process in which new distinctions are made. The definition can also be used to evaluate the results, given that it is a standard of evaluation (cf. Hammersley 2007 ), to see whether new distinctions are made and whether this improves our understanding of what is researched, in addition to the evaluation of how the research was conducted. By making what is qualitative research explicit it becomes easier to communicate findings, and it is thereby much harder to fly under the radar with substandard research since there are standards of evaluation which make it easier to separate “good” from “not so good” qualitative research.

To conclude, our analysis, which ends with a definition of qualitative research can thus both address the “internal” issues of what is qualitative research, and the “external” critiques that make it harder to do qualitative research, to which both pressure from quantitative methods and general changes in society contribute.

Acknowledgements

Financial Support for this research is given by the European Research Council, CEV (263699). The authors are grateful to Susann Krieglsteiner for assistance in collecting the data. The paper has benefitted from the many useful comments by the three reviewers and the editor, comments by members of the Uppsala Laboratory of Economic Sociology, as well as Jukka Gronow, Sebastian Kohl, Marcin Serafin, Richard Swedberg, Anders Vassenden and Turid Rødne.

Biographies

is professor of sociology at the Department of Sociology, Uppsala University and Universität St. Gallen. His main focus is economic sociology, and in particular, markets. He has published numerous articles and books, including Orderly Fashion (Princeton University Press 2010), Markets (Polity Press 2011) and Re-Imagining Economic Sociology (edited with N. Dodd, Oxford University Press 2015). His book Ethnographic Methods (in Swedish) has already gone through several editions.

is associate professor of sociology at the Department of Media and Social Sciences, University of Stavanger. His research has been published in journals such as Social Psychology Quarterly, Sociological Theory, Teaching Sociology, and Music and Arts in Action. As an ethnographer he is working on a book on he social world of big-wave surfing.

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Contributor Information

Patrik Aspers, Email: [email protected] .

Ugo Corte, Email: [email protected] .

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Research Design 101

Everything You Need To Get Started (With Examples)

By: Derek Jansen (MBA) | Reviewers: Eunice Rautenbach (DTech) & Kerryn Warren (PhD) | April 2023

Navigating the world of research can be daunting, especially if you’re a first-time researcher. One concept you’re bound to run into fairly early in your research journey is that of “ research design ”. Here, we’ll guide you through the basics using practical examples , so that you can approach your research with confidence.

Overview: Research Design 101

What is research design.

• Research design types for quantitative studies
• Video explainer : quantitative research design
• Research design types for qualitative studies
• Video explainer : qualitative research design
• How to choose a research design
• Key takeaways

Research design refers to the overall plan, structure or strategy that guides a research project , from its conception to the final data analysis. A good research design serves as the blueprint for how you, as the researcher, will collect and analyse data while ensuring consistency, reliability and validity throughout your study.

Understanding different types of research designs is essential as helps ensure that your approach is suitable  given your research aims, objectives and questions , as well as the resources you have available to you. Without a clear big-picture view of how you’ll design your research, you run the risk of potentially making misaligned choices in terms of your methodology – especially your sampling , data collection and data analysis decisions.

The problem with defining research design…

One of the reasons students struggle with a clear definition of research design is because the term is used very loosely across the internet, and even within academia.

Some sources claim that the three research design types are qualitative, quantitative and mixed methods , which isn’t quite accurate (these just refer to the type of data that you’ll collect and analyse). Other sources state that research design refers to the sum of all your design choices, suggesting it’s more like a research methodology . Others run off on other less common tangents. No wonder there’s confusion!

In this article, we’ll clear up the confusion. We’ll explain the most common research design types for both qualitative and quantitative research projects, whether that is for a full dissertation or thesis, or a smaller research paper or article.

Research Design: Quantitative Studies

Quantitative research involves collecting and analysing data in a numerical form. Broadly speaking, there are four types of quantitative research designs: descriptive , correlational , experimental , and quasi-experimental . 

Descriptive Research Design

As the name suggests, descriptive research design focuses on describing existing conditions, behaviours, or characteristics by systematically gathering information without manipulating any variables. In other words, there is no intervention on the researcher’s part – only data collection.

For example, if you’re studying smartphone addiction among adolescents in your community, you could deploy a survey to a sample of teens asking them to rate their agreement with certain statements that relate to smartphone addiction. The collected data would then provide insight regarding how widespread the issue may be – in other words, it would describe the situation.

The key defining attribute of this type of research design is that it purely describes the situation . In other words, descriptive research design does not explore potential relationships between different variables or the causes that may underlie those relationships. Therefore, descriptive research is useful for generating insight into a research problem by describing its characteristics . By doing so, it can provide valuable insights and is often used as a precursor to other research design types.

Correlational Research Design

Correlational design is a popular choice for researchers aiming to identify and measure the relationship between two or more variables without manipulating them . In other words, this type of research design is useful when you want to know whether a change in one thing tends to be accompanied by a change in another thing.

For example, if you wanted to explore the relationship between exercise frequency and overall health, you could use a correlational design to help you achieve this. In this case, you might gather data on participants’ exercise habits, as well as records of their health indicators like blood pressure, heart rate, or body mass index. Thereafter, you’d use a statistical test to assess whether there’s a relationship between the two variables (exercise frequency and health).

As you can see, correlational research design is useful when you want to explore potential relationships between variables that cannot be manipulated or controlled for ethical, practical, or logistical reasons. It is particularly helpful in terms of developing predictions , and given that it doesn’t involve the manipulation of variables, it can be implemented at a large scale more easily than experimental designs (which will look at next).

That said, it’s important to keep in mind that correlational research design has limitations – most notably that it cannot be used to establish causality . In other words, correlation does not equal causation . To establish causality, you’ll need to move into the realm of experimental design, coming up next…

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Experimental Research Design

Experimental research design is used to determine if there is a causal relationship between two or more variables . With this type of research design, you, as the researcher, manipulate one variable (the independent variable) while controlling others (dependent variables). Doing so allows you to observe the effect of the former on the latter and draw conclusions about potential causality.

For example, if you wanted to measure if/how different types of fertiliser affect plant growth, you could set up several groups of plants, with each group receiving a different type of fertiliser, as well as one with no fertiliser at all. You could then measure how much each plant group grew (on average) over time and compare the results from the different groups to see which fertiliser was most effective.

Overall, experimental research design provides researchers with a powerful way to identify and measure causal relationships (and the direction of causality) between variables. However, developing a rigorous experimental design can be challenging as it’s not always easy to control all the variables in a study. This often results in smaller sample sizes , which can reduce the statistical power and generalisability of the results.

Moreover, experimental research design requires random assignment . This means that the researcher needs to assign participants to different groups or conditions in a way that each participant has an equal chance of being assigned to any group (note that this is not the same as random sampling ). Doing so helps reduce the potential for bias and confounding variables . This need for random assignment can lead to ethics-related issues . For example, withholding a potentially beneficial medical treatment from a control group may be considered unethical in certain situations.

Quasi-Experimental Research Design

Quasi-experimental research design is used when the research aims involve identifying causal relations , but one cannot (or doesn’t want to) randomly assign participants to different groups (for practical or ethical reasons). Instead, with a quasi-experimental research design, the researcher relies on existing groups or pre-existing conditions to form groups for comparison.

For example, if you were studying the effects of a new teaching method on student achievement in a particular school district, you may be unable to randomly assign students to either group and instead have to choose classes or schools that already use different teaching methods. This way, you still achieve separate groups, without having to assign participants to specific groups yourself.

Naturally, quasi-experimental research designs have limitations when compared to experimental designs. Given that participant assignment is not random, it’s more difficult to confidently establish causality between variables, and, as a researcher, you have less control over other variables that may impact findings.

All that said, quasi-experimental designs can still be valuable in research contexts where random assignment is not possible and can often be undertaken on a much larger scale than experimental research, thus increasing the statistical power of the results. What’s important is that you, as the researcher, understand the limitations of the design and conduct your quasi-experiment as rigorously as possible, paying careful attention to any potential confounding variables .

Research Design: Qualitative Studies

There are many different research design types when it comes to qualitative studies, but here we’ll narrow our focus to explore the “Big 4”. Specifically, we’ll look at phenomenological design, grounded theory design, ethnographic design, and case study design.

Phenomenological Research Design

Phenomenological design involves exploring the meaning of lived experiences and how they are perceived by individuals. This type of research design seeks to understand people’s perspectives , emotions, and behaviours in specific situations. Here, the aim for researchers is to uncover the essence of human experience without making any assumptions or imposing preconceived ideas on their subjects.

For example, you could adopt a phenomenological design to study why cancer survivors have such varied perceptions of their lives after overcoming their disease. This could be achieved by interviewing survivors and then analysing the data using a qualitative analysis method such as thematic analysis to identify commonalities and differences.

Phenomenological research design typically involves in-depth interviews or open-ended questionnaires to collect rich, detailed data about participants’ subjective experiences. This richness is one of the key strengths of phenomenological research design but, naturally, it also has limitations. These include potential biases in data collection and interpretation and the lack of generalisability of findings to broader populations.

Grounded Theory Research Design

Grounded theory (also referred to as “GT”) aims to develop theories by continuously and iteratively analysing and comparing data collected from a relatively large number of participants in a study. It takes an inductive (bottom-up) approach, with a focus on letting the data “speak for itself”, without being influenced by preexisting theories or the researcher’s preconceptions.

As an example, let’s assume your research aims involved understanding how people cope with chronic pain from a specific medical condition, with a view to developing a theory around this. In this case, grounded theory design would allow you to explore this concept thoroughly without preconceptions about what coping mechanisms might exist. You may find that some patients prefer cognitive-behavioural therapy (CBT) while others prefer to rely on herbal remedies. Based on multiple, iterative rounds of analysis, you could then develop a theory in this regard, derived directly from the data (as opposed to other preexisting theories and models).

Grounded theory typically involves collecting data through interviews or observations and then analysing it to identify patterns and themes that emerge from the data. These emerging ideas are then validated by collecting more data until a saturation point is reached (i.e., no new information can be squeezed from the data). From that base, a theory can then be developed .

As you can see, grounded theory is ideally suited to studies where the research aims involve theory generation , especially in under-researched areas. Keep in mind though that this type of research design can be quite time-intensive , given the need for multiple rounds of data collection and analysis.

Ethnographic Research Design

Ethnographic design involves observing and studying a culture-sharing group of people in their natural setting to gain insight into their behaviours, beliefs, and values. The focus here is on observing participants in their natural environment (as opposed to a controlled environment). This typically involves the researcher spending an extended period of time with the participants in their environment, carefully observing and taking field notes .

All of this is not to say that ethnographic research design relies purely on observation. On the contrary, this design typically also involves in-depth interviews to explore participants’ views, beliefs, etc. However, unobtrusive observation is a core component of the ethnographic approach.

As an example, an ethnographer may study how different communities celebrate traditional festivals or how individuals from different generations interact with technology differently. This may involve a lengthy period of observation, combined with in-depth interviews to further explore specific areas of interest that emerge as a result of the observations that the researcher has made.

As you can probably imagine, ethnographic research design has the ability to provide rich, contextually embedded insights into the socio-cultural dynamics of human behaviour within a natural, uncontrived setting. Naturally, however, it does come with its own set of challenges, including researcher bias (since the researcher can become quite immersed in the group), participant confidentiality and, predictably, ethical complexities . All of these need to be carefully managed if you choose to adopt this type of research design.

Case Study Design

With case study research design, you, as the researcher, investigate a single individual (or a single group of individuals) to gain an in-depth understanding of their experiences, behaviours or outcomes. Unlike other research designs that are aimed at larger sample sizes, case studies offer a deep dive into the specific circumstances surrounding a person, group of people, event or phenomenon, generally within a bounded setting or context .

As an example, a case study design could be used to explore the factors influencing the success of a specific small business. This would involve diving deeply into the organisation to explore and understand what makes it tick – from marketing to HR to finance. In terms of data collection, this could include interviews with staff and management, review of policy documents and financial statements, surveying customers, etc.

While the above example is focused squarely on one organisation, it’s worth noting that case study research designs can have different variation s, including single-case, multiple-case and longitudinal designs. As you can see in the example, a single-case design involves intensely examining a single entity to understand its unique characteristics and complexities. Conversely, in a multiple-case design , multiple cases are compared and contrasted to identify patterns and commonalities. Lastly, in a longitudinal case design , a single case or multiple cases are studied over an extended period of time to understand how factors develop over time.

As you can see, a case study research design is particularly useful where a deep and contextualised understanding of a specific phenomenon or issue is desired. However, this strength is also its weakness. In other words, you can’t generalise the findings from a case study to the broader population. So, keep this in mind if you’re considering going the case study route.

How To Choose A Research Design

Having worked through all of these potential research designs, you’d be forgiven for feeling a little overwhelmed and wondering, “ But how do I decide which research design to use? ”. While we could write an entire post covering that alone, here are a few factors to consider that will help you choose a suitable research design for your study.

Data type: The first determining factor is naturally the type of data you plan to be collecting – i.e., qualitative or quantitative. This may sound obvious, but we have to be clear about this – don’t try to use a quantitative research design on qualitative data (or vice versa)!

Research aim(s) and question(s): As with all methodological decisions, your research aim and research questions will heavily influence your research design. For example, if your research aims involve developing a theory from qualitative data, grounded theory would be a strong option. Similarly, if your research aims involve identifying and measuring relationships between variables, one of the experimental designs would likely be a better option.

Time: It’s essential that you consider any time constraints you have, as this will impact the type of research design you can choose. For example, if you’ve only got a month to complete your project, a lengthy design such as ethnography wouldn’t be a good fit.

Resources: Take into account the resources realistically available to you, as these need to factor into your research design choice. For example, if you require highly specialised lab equipment to execute an experimental design, you need to be sure that you’ll have access to that before you make a decision.

Keep in mind that when it comes to research, it’s important to manage your risks and play as conservatively as possible. If your entire project relies on you achieving a huge sample, having access to niche equipment or holding interviews with very difficult-to-reach participants, you’re creating risks that could kill your project. So, be sure to think through your choices carefully and make sure that you have backup plans for any existential risks. Remember that a relatively simple methodology executed well generally will typically earn better marks than a highly-complex methodology executed poorly.

Recap: Key Takeaways

We’ve covered a lot of ground here. Let’s recap by looking at the key takeaways:

• Research design refers to the overall plan, structure or strategy that guides a research project, from its conception to the final analysis of data.
• Research designs for quantitative studies include descriptive , correlational , experimental and quasi-experimenta l designs.
• Research designs for qualitative studies include phenomenological , grounded theory , ethnographic and case study designs.
• When choosing a research design, you need to consider a variety of factors, including the type of data you’ll be working with, your research aims and questions, your time and the resources available to you.

If you need a helping hand with your research design (or any other aspect of your research), check out our private coaching services .

Psst… there’s more (for free)

This post is part of our dissertation mini-course, which covers everything you need to get started with your dissertation, thesis or research project. 

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Is there any blog article explaining more on Case study research design? Is there a Case study write-up template? Thank you.

Thanks this was quite valuable to clarify such an important concept.

Thanks for this simplified explanations. it is quite very helpful.

This was really helpful. thanks

Thank you for your explanation. I think case study research design and the use of secondary data in researches needs to be talked about more in your videos and articles because there a lot of case studies research design tailored projects out there.

Please is there any template for a case study research design whose data type is a secondary data on your repository?

This post is very clear, comprehensive and has been very helpful to me. It has cleared the confusion I had in regard to research design and methodology.

This post is helpful, easy to understand, and deconstructs what a research design is. Thanks

how to cite this page

Thank you very much for the post. It is wonderful and has cleared many worries in my mind regarding research designs. I really appreciate .

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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.

• Open access
• Published: 08 April 2024

A qualitative study to explore experiences of anti-racism teaching in medical residency programs across the United States and subsequent creation of the SPOC (Support - Pipeline - Outcomes - Community) Model to guide future curricula design

• Alida M. Gertz 1 , 2 ,
• Michele Smith 1 ,
• Davon Thomas 1 ,
• Angeline Ti 1 ,
• Cheryl Vamos 2 &
• Joe Bohn 2  

BMC Medical Education volume  24 , Article number:  382 ( 2024 ) Cite this article

Metrics details

Racism contributes to health disparities and is a serious threat to public health. Teaching physicians about racism, how to address it in medical practice, and developing high quality and sustainable curricula are essential to combating racism.

This study aimed to (1) describe the experience of racism and anti-racism teaching in residency programs, and elicit recommendations from key informants, and (2) use these data and formative research to develop recommendations for other residencies creating, implementing, and evaluating anti-racism curricula in their own programs.

From May to July 2023, 20 faculty and residents were recruited via convenience sampling for key informant interviews conducted via Microsoft Teams. Interviews were audio recorded, transcribed, and coded. An initial list of themes was developed using theoretical frameworks, and then refined using a grounded-theory approach. A brief online optional anonymous demographic survey was sent to participants in August of 2023. 

Eighty percent (20/25) of participants approached were interviewed. Seventy-five percent (15/20) answered a brief optional demographic survey. Seven themes emerged: (1) Racism in medicine is ubiquitous; (2) Anti-racism teaching in medicine varies widely; (3) Sustainability strategies should be multifaceted and include recruitment, resource allocation, and outcome measures; (4) Resources are widely available and accessible if one knows where to look; (5) Outcomes and metrics of success should include resident- faculty-, patient- community-, and system-focused outcomes; (6) Curricular strategies should be multilayered, longitudinal, and woven into the curriculum; and (7) Self-reflection and discomfort are necessary parts of the process. 

Conclusions

This study is one of the first to qualitatively examine perspectives of key stakeholders invested in anti-racism teaching for residents. The Support - Pipeline - Outcomes - Community (SPOC) Model, that was developed using information collected during this study, can be used in the future as a guide for others working to design and implement sustainable and high quality anti-racism curricula for residents.

Peer Review reports

Introduction

There is no question that racism contributes to differences in health outcomes between different populations and is, therefore, a serious threat to public health [ 1 ]. Inequities among different racial groups in the United States are well documented [ 1 , 2 , 3 ]. Teaching physicians about racism, learning how to address it within the practice of medicine, and developing sustainable and high quality curricula to do so are key.

Published literature describing anti-racism curricula in residency programs and particularly in primary care programs is growing but still lacking in many respects including data on how to ensure the sustainability and quality of such programs [ 4 , 5 ]. Curricula that have been described in the peer-reviewed literature include those describing curricular strategies such as lecture series, longitudinal experiences, increasing resident/student knowledge, improving attitudes, decreasing implicit bias, and increasing diversity of residents and staff [ 6 , 7 , 8 , 9 , 10 , 11 ].

Although health disparities teaching is now required in family medicine residency programs, it is unclear if and how anti-racism teaching, specifically, is taking place and whether it is effective [ 12 ]. Of the small number of social determinants of health post-graduate medical education curricula that exist and are described in the literature, the vast majority do not focus on sustainability or continuous quality improvement efforts [ 13 , 14 ]. Most reports focus on descriptions of the curricula, evaluation of the curricula and/or residents, and faculty perceptions of and experiences with the curriculum [ 12 ]. Similarly, there is a dearth of qualitative research exploring program directors’ and residents’ perspectives of racism and anti-racism teaching in various programs. Finally, few studies have included descriptions of patient-oriented outcomes, which is understandable given the difficulty in demonstrating causation. For example, it is difficult (but not impossible [ 15 ]) to design a study that provides evidence that medical students or residents who were included in a curriculum designed to improve empathy, actually went on to care for patients who lived longer due to their chronic diseases being better controlled because of improvements in their providers’ empathy skills [ 16 ,  17 ].

This study aimed to use qualitative data gathered via key informant interviews and formative research to explore approaches to developing a sustainable, and high quality anti-racism curriculum for residency programs in the U.S. Findings from the interviews were used to inform development of a model that programs can utilize as a roadmap or guide when creating, implementing, evaluating, and sustaining and high quality anti-racism curricula in their own programs.

Conceptual framework and model development

The Consolidated Framework for Sustainability Model [ 4 ] and Deming’s Theory of Quality Improvement [ 18 ] were used to guide the creation of the interview questions and probes . A modified grounded theory approach was used to create an initial list of themes, which was then built upon as the transcripts were coded. Using the Consolidated Framework for Implementation Research (CFIR) [ 19 , 20 ], the themes and sub-themes were then organized to develop a model for development of anti-racism curricula for physicians in training.

Instrument development

A semi-structured interview guide was developed based on the research aims and the theoretical frameworks described above. Questions were designed to elicit participants' perceptions and experiences with racism in medicine, anti-racism teaching in medicine, and curricular development for residency programs. A brief optional, anonymous demographics survey was emailed to participants to complete after the interviews. The in-depth interview guide is shown in Table 1 .

Sampling and recruitment

A convenience sampling technique was used for recruitment. Participants included faculty and prior residents from across the U.S. from multiple specialties, who had either thought about or been involved in designing, implementing, and evaluating anti-racism curricula in their own institutions. We included not only faculty but also residents and former residents who had been the recipients of such efforts or lack therof. Subjects were recruited via emails, texts, or in person conversations. Participants were chosen based on prior knowledge or pre-existing interest, experience, and/or expertise in the area of study, and the lead author’s or colleagues recommendations. Participants were invited to interview until theoretical redundancy was reached. Inclusion criteria were (1) adults age 18 years or older who (2) worked at a residency program, were current residents, or had previously been a resident in a residency program in the U.S. No incentives were provided. Participation was voluntary. Verbal informed consent was obtained from participants prior to involvement in the study. A concerted effort was made to ensure that at a minimum half of all participants were those who identified as under-represented minorities.

Data collection and analysis

The lead author with expertise in public health, clinical care, and medical education utilized the in-depth interview guide to conduct, record, and transcribe the interviews via Microsoft Teams from May to July 2023. Interviews lasted on average approximately 40 minutes (range 20 minutes to 2.5 hours). Transcriptions were de-identified and saved in Microsoft Word and then collated and coded in Microsoft Excel. A brief online optional anonymous demographic survey was sent in August of 2023 to participants who completed the interviews. Data from the in-depth interviews were analyzed using coding and thematic analysis. AMG developed the initial list of questions and themes; JB, MS, and MV reviewed and provided feedback. AMG then conducted and transcribed the interviews using the updated questions. Prompts were updated to include subthemes that arose during previous interviews. Coding was initially conducted by AMG with review and adjustment by MS and JB. Themes, sub-themes, and representative quotes were initially compiled by AMG with input and adjustment based on feedback from MS, JB, DT, and AT. AMG developed the SPOC model (described below) and refined it based on feedback from all of the other authors. The final list of themes and the model were reviewed, updated, and approved by all authors.

Of 25 potential participants approached, 20 (80%) completed in-depth interviews and 15 of those 20 (75%) completed an additional optional post interview brief demographic survey between May and August of 2023. Interview participants included faculty, current residents, and program directors. Participants included people who self-identified as persons of color, as well as those who self-identified as being part of other minority communities (e.g., religious minorities and sexual minorities). Geographic location of participants also varied but included participants from the East Coast, South, Mid-west, and Western U.S. Details of the demographics for those participants who opted to answer the brief demographic survey questions are shown below in Table  2 .

Seven major themes emerged from the interviews and within each major theme, a number of sub-themes emerged. The major themes that emerged were: (1) Racism in medicine is ubiquitous; (2) Anti-racism teaching in medicine varies widely; (3) Sustainability strategies should be multifaceted and include recruitment, resources allocation, and outcome measures; (4) Resources are widely available and accessible if one knows where to find them; (5) Outcomes and metrics of success should include resident- faculty-, patient-, community-, and system-focused outcomes; (6) Curricular strategies should be multilayered, longitudinal, and woven into the curriculum; and (7) Self-reflection and discomfort are necessary parts of the process. 

Major theme 1: experiences of racism in medicine are ubiquitous

Subthemes included in the first major theme regarding ubiquitous experiences of racism in medicine highlighted that everyone has either witnessed and/or experienced racism directed at themselves, their colleagues, and/or their patients. Some have experienced extensive racism and had little recourse. One respondent noted, “I can say that at all stages of my training I experienced racism,” while another recalled, “One of the attendings … asked me about my visa status...” (from someone who was born and raised in the US). Another noted, “I frequently got mistaken for [the one other dark-skinned person in the program]” Another subtheme was that outright racism was not uncommon and ranged from use of the “N word,” to assuming a physician was someone on staff with lesser training such as a student, environmental services staff, transport staff, nurse, or tech. One participant recalled, “One of my attendings … would always wear a suit and he was the only black attending that I can recall in the ICU ... A lot of the other attendings would wear scrubs … and when he was asked by one of my co residents... ‘why do you always wear suits, including on weekends?’, he said, ‘So that people take me seriously.’” Another subtheme was that racism exists on a spectrum ranging from micro-aggressions (in written word, spoken word, and actions and gestures) to structural and systemic racism such as policies and social/cultural “norms.” One respondent noted, “I had an attending who would joke about me being from Africa and [ask] if I swing trees or have pet lions.” Another subtheme that emerged was that racism exists in the medical system in multiple forms including but not limited to race-based medicine and calculators to expectations of outcomes based on race to misguided attempts to address racism. Highlighted here was also the point that racist policies instituted by local, state, or federal government (such as restrictions on use of the words equity and diversity) all the way down to racist clinic policies (such as allowing physicians to refuse to see patients who arrive >10 min late) exist and contribute to the problem. To illustrate this, one responded noted, “There are a lot of things [we could do to improve care for our under-represented minority patients, for example], if patients arrive late, you can accommodate [because] you know they obviously have struggles... a lot of the time [they have] transportation issues or [other barriers] we just don’t know [about].” Several people discussed discrimination based on other characteristics (e.g. sexuality, religion, etc.) and the importance of considering intersectionality in such curricula. Tokenism was also mentioned, and it was noted that often people of color are pushed into equity and anti-racism work even when they may prefer to focus on other things. When they are interested in doing this work, they are often poorly compensated. One participant recalled, “I’ve had promotions announced [and then] people comment that it was smart of my boss to [promote me] because [they could now] ‘check the diversity box.’”

Major theme 2: experience of teaching anti-racism in medicine are variable

Multiple subthemes were elucidated as part of the second major theme exploring experiences of teaching anti-racism in medicine. Multiple participants said they had little to no anti-racism teaching in their own training. Some reported they had a minimal amount, but it was named something else such as “social determinants of health” or “cultural competency.” One participant recalled: “I can remember maybe once or twice where there was some discussion within dermatology specifically about different appearances of rashes on darker skin, and that was the extent of it, though. There was absolutely no discussion of racism specifically or its impacts on health.” Another recalled, “My medical school and residency both had lectures and seminars on cultural competency, [but] I can’t remember anything... like an antiracist curriculum at any point.” One subtheme that emerged here was that the tone for anti-racism teaching is set from the top. System leaders, chairs, faculty/program directors must be an example and set the tone for anti-racism action and teaching. One respondent noted, “I really try to model my own style around those [attendings] that I came to respect very highly … to be able to confront the [racism] issues directly.” Many respondents reported at least attempting to engage in teaching anti-racism in their current practice. Some had very developed curricula; several even reported enacting other anti-racism measures focused on recruitment and retention efforts, and redesigning activities that previously perpetrated implicit bias (such as interview selection rubrics, orientation activities, and even morbidity and mortality (M&M) presentations). Representative quotes describing development of such curricular improvements to address racism included: “The ambulatory attending rounds were not infrequently centered around issues of race and implicit bias.” And “We received a grant ...to create a virtual reality application intended to teach providers about social determinants of health and Health Equity, which is to say also … about racism... I led a team that created [the] exercise ...[that] dropped the user into [an] … under-resourced neighborhood and has them follow a family through six different scenes [describes each scenario]. [Learners are then] assigned to look for help assets and health risks within the setting.” Participants reported in their current programs, having a number of activities aimed at educating residents about equity including didactics, interactive sessions, case-based learning poverty simulations, outside consultants, and support groups for underrepresented minorities (URMs). Finally, a few respondents noted that their programs really emphasized collaboration with the community and having community representation.

Major theme 3: sustainability considerations for anti-racism curricula should focus on recruitment & retention, resources, and systemic changes

Subthemes noted within the third major theme of sustainability efforts included the importance of integrating anti-racism outcome measures into credentialing, accreditation, and other metrics needed for individual or program success (such USMLE, MCAT, specialty board exam questions, ACGME core competency, and hospital equity scores tied to grant funding). Representative quotes highlighted the importance of having “measurable outcomes in the population that residents treat, [including things like] satisfaction scores.” One respondent said, “Every ACGME accredited program has specific milestones that … are connected to EIDA... I would like to see that happen on a specialty-specific basis. I would like to see that at the ACGME level, it’s happening through the clinical learning environment review. Healthcare disparities are there as part of healthcare quality but don’t really have teeth behind them. So, to make it an ACGME requirement, to really add in that language in the different core competencies, would be something that could be really powerful.” Another commented, “I think there should be anti-racist and implicit bias [criteria included in] how medical students are evaluated. … [and] when you apply to medical school, it should be part of the screening... it ought to be as important as all the other things that you screen for.” Another subtheme that emerged in the sustainability category highlighted the importance of ensuring all lecture topics covered during residency include teaching points on equity and anti-racism. One respondent said anti-racism should be “...more integrated in every topic, every talk... if we’re talking about communication, [we mention] cultural humility. If we’re talking about heart failure, [we note] healthcare disparities in this area. So it is really woven into everything that we’re doing instead of set aside as its own topic.” Ensuring dedicated staff, with protected and compensated time, are in charge of leading the effort, while also ensuring buy-in and an ownership feeling by all, was another subtheme articulated. Participants said, “[You] not only need funding, but [also] to have a strong commitment.” And that “having that ownership and pride from the people higher up is paramount.” The significance of finding and ensuring ongoing and permanent resources and support are present and sharing training opportunities across the system was also highlighted. Interviewees noted, “[Programs should capitalize on] any ways in which you can combine forces, because obviously these concepts are transdisciplinary, so there’s no need for each program to recreate the wheel and there’s power in numbers if multiple programs in the same institution can have a shared curriculum.” And “Many of our educational leaders have become trainers as well of those programs. So not only are they receiving the training, but they’re providing the training so that there’s some built-in model where we have local expertise.” Ensuring URM are recruited, supported, and promoted to leadership positions, and providing extra mentoring and support for URM, was another subtheme that emerged. One participant noted, “…it’s not just limited to finding someone who was previously not going to get in or get selected and bringing [that person into your program] … [this can’t undo] the decades or centuries of suppression … it is more likely that people from those groups are going to have struggles and those struggles need to be supported as well. So we had systems for making sure we provide [support].” Another subtheme that emerged was promoting STEM in local communities to encourage kids from URM groups to be interested in medicine. One interviewee commented, “One of the structural things that is currently being done... is to make sure that when we are looking at hiring program directors, assistant program directors, or core faculty, that we are thinking about diversity, and if we don’t have representation from groups historically underrepresented in medicine, then we’re probably not trying hard enough to sponsor and mentor faculty members to aspire to those roles.” The importance of continuous quality improvement efforts was also highlighted. Finally, it was noted that changing the mindset from “We are doing this to help URM,” to “We are doing this to make us all better,” was noted to be very important.

Major theme 4: tools for curriculum building are abundant if you know where to find them

Subthemes in the fourth major theme focused on different types of resources and strategies available to build curricula and included: books & podcasts and having residents present on a topic they learned about listening or reading, using problem and case-based learning (e.g., Cases that explain topics such as the roots of health care disparities or unfair consequences/discipline for similar actions in white residents vs. URM), using online simulations and other tools, inviting speakers, having pre-recorded lectures, having paid expert consultants who may be URM themselves, inviting speakers from the community or creating a community medicine rotation, shadowing other staff in clinic or hospital, didactics, and having colleagues share their own experiences. One respondent noted, “Having small groups [where] people just like you ... [including] leaders [can openly] discuss … experiences [during] residency, [including those involving] racism, or homophobia, [etc.,] ... getting people’s personal perspective... allow[ing] people to be comfortable, [especially for some white residents/students who] might be sheltered … it might open their eyes [or allow them to realize] colleagues … have experienced all these horrible things .... I think would be really useful because in a sense... talking about personal experiences [will help people understand] … then you won’t have those people who [say] ‘racism doesn’t exist’ or ‘it doesn’t happen anymore.’ When you hear about it firsthand from your colleagues. I think that really makes a huge statement.”

Major theme 5: outcome measures should be multilayered and include resident, faculty, patient, community, and system metrics

Subthemes in this major theme about outcomes, highlighted the importance of using varied metrics to measure curriculum success. One technique mentioned use of resident pre-post surveys/tests/interviews (to measure knowledge, attitudes, and beliefs). Use of the Kirkpatrick Model for curriculum development, was also mentioned. Respondents also commented on specific strategies used in their own programs: “[To capture] people’s perceptions of the talk itself, whether they intend to change their practice ... surveys are offered right after the talk is given, by email.” Another noted, “Residents take the implicit bias test every so often,” and another noted use of a “test or quiz … to reflect whatever knowledge was gained during that portion of the curriculum,” and yet another commented on the usefulness of “a group discussion .. making sure that they’re applying the correct knowledge and guidelines to patients.” One respondent also suggested, “Assess … residents of color. How comfortable [are] they … with the curriculum and ... how comfortable are they addressing their [program leadership] if there are issues, or if they’re being discriminated against. How confident are they about [being able to successfully] seek help [or] discuss those issues [with program staff, faculty, or leadership]?” Demographics tracking (such as the percent of URM students considered for interviews, the percent matched, the percent that go on to become faculty, and the percent that pursue fellowship) was also emphasized as an important metric. One respondent commented, “The first thing is … keeping track of … how many [URM] residents we had in our program,” and another noted the importance of “whether or not the number of URM residents and faculty had increased over the years to have ... racial concordance to match our patient population,” and yet another suggested tracking “...how many residents of color have we admitted... how many of them have [completed the] program...” One participant said, “...if your intern classes every year have a high representation of black male residents, but those residents are all not completing the program, then that’s obviously a problem.” Another suggested, “Track the number of residents who self-identify as underrepresented in medicine who applied to our programs, who interview at our programs, and who get ranked.” Another subtheme in this area included tracking patient-oriented outcomes such as use of patient surveys, and measuring patient access to care, and patient health outcomes. One participant advised looking at measures such as “[Are] patients not showing up for follow up visits? [Adhering to] medications? [Are] patients actually connected with care? [Do they] trust in the care that they’re receiving or trust the doctors that they have?... If ... not … why?” Another suggested “seeing if your community feels that we are doing everything in our power to make sure that people are treated equally and fairly,” and a third suggested, “[Look at URM patients compared to white patients. Are they] getting their screenings? [Having] improvements in their A1C?” Tracking system resources and funding allocation and hiring equity outcome experts as consultants were other subthemes that emerged.

Major theme 6: curricular strategies should be multipronged, include integration, and be longitudinal

Subthemes surrounding curricular design strategies highlighted that integration into all other parts of the curriculum should occur, that longitudinal integration was needed, and that it was important to provide evidence and data, when available, to support teaching. It was noted that there is a vast literature on the health effects of racism and it is important for educators to use it to teach residents. Incorporating personal stories of experiences of racism in the medical system faced by patients as well as medical professionals was also suggested. An anti-racism journal club was recommended by several participants. Having a safe space for discussion and also a venue to provide anonymous feedback without fear of retribution was noted as an important curricular strategy. One respondent suggested, “[Have an] anonymous comment box where people can feel free to speak up about topics without having their name associated with [their comments],” while another pointed to the importance of “developing openness in your program that allows for the residents and other team members and patients - the full community at the residency program - to be able to share perspectives.” A broad range of “what not to do” recommendations were made and comments in this subtheme included: “You can’t just hire one tokenized black person with no budget, no protected time, no equitable advancement, or promotion [potential],” and when discussing a part of residency where residents would visit a poor neighborhood adjacent to the hospital one responded noted that they “... don’t know if the word is voyeuristic, but it initially had been very problematic in the sense that it just felt more like [we were] touring this place as opposed to actually learning about the history and integrating ourselves [into the community].” And (referring to the online system-wide required ‘bias’ courses) another noted, “… at least from my experience, most people just check them off or don’t really pay that much attention.” And “…required training course that you do online that you have [to complete to get] your hospital privileges or clinic privileges, like … an EHR training, and I felt that was really useless because most of the time people just very quickly click through them…” Another commented: “We implement systems, and nobody really cares about any form of evaluation..“ Finally, it was emphasized that programs must come up with unbiased ways to deal with “concerns” raised about residents of color to ensure all concerns were dealth with fairly. Finally recognizing that URM residents might not always feel safe speaking out when they have questions, was noted as an important step in creating an effective learning environment.

Major theme 7: self-reflection, discomfort, engagement are all necessary

The final major theme around introspection and advocacy encompassed a number of subthemes including (1) a need to address and advocate for change on a social level and in society at large, not just in medicine, (2) recognizing that many of the murders that occur are traumatic for URM residents, and (3) addressing potentially unrecognized or uncomfortable issues such as white fragility, and ensuring each person engaging in this work should start by critically examining their own beliefs and biases. Another point that was noted was that strategies that work for programs based in urban academic centers, might not work for more rural programs. Likewise, programs with many IMGs might need to consider a slightly different approach from programs with mostly US medical graduates. One participant (from a program with many IMGs) said, “... I have talked about colonialism and how we also can translate that to how our black population in the US has been treated historically, but not everyone seems to have that same connection ... I have had residents tell me ‘I grew up in [X country], no one has anything. Everyone suffers. Poverty is everywhere’ .... Many of them have told me ‘When I come to the US, I assume this is the best health care system in the world ... so why isn’t this patient taking their meds?’ So much of our curriculum content is geared towards US grads - I find it doesn’t always fit what I need for my [residents].”

A full list of themes, sub-themes, and additional select representative quotes are shown in Table  3 below.

Specific resources such as books, book lists, articles, simulation websites, consultants, podcasts, and other tools were collected during the course of this study, and can be found here: https://www.medicalantiracismcurriculum.com/ .

Model development

To develop a visual guide for programs designing sustainable anti-racism curricula in the future, the Consolidated Framework for Implementation Research (CFIR) [ 19 , 20 , 21 ] was used to organize themes and sub-themes derived from key informant interviews, and guide creation of the SPOC (Support – Pipeline – Outcomes – Community) Model (see Fig.  1 ) - pronounced “spoke”. Using the CFIR domains that would influence success of such curricula, the team contextualized themes and sub-themes derived from interviews, to design the model as an actionable guide. These CFIR domains considered included: the outer setting (e.g. society as a whole, policies and laws, and the hospital system), innovation (e.g. the curriculum structure, strategies, and resources), inner setting (e.g. university or college and program including resources and available funding), individuals (e.g. the teachers, learners, champions, and those the curriculum affects such as the patients), and the implementation process (e.g. what measured outcomes will strongly influence how successful the curricula are).

The SPOC (Support – Pipeline – Outcomes – Community) Model for creating sustainable anti-racism curricula for physicians in training

Integrating the reorganized themes and subthemes into the CFIR domains, we included as the four inner spokes of the model: (1) Support, (2) Pipeline, (3) Outcomes, and (4) Community. Within the first spoke of ‘Support’, programs must ensure that resources for the curriculum are secured, that funding is present for the activities that the curriculum will include, and finally that dedicated staff are identified, and importantly, compensated for their time spent building and maintaining the curriculum. As part of the second spoke, ‘Pipeline’, programs must ensure that recruitment, retention, and promotion of traditionally under-represented minorities in medicine occurs within their program. Within the third spoke of ‘Outcomes’, it is imperative that outcomes focused on residents, the program and institution itself, and last, but likely most importantly, on patients are agreed upon, tracked, and utilized to measure program success. If these metrics are not improving over time, the curriculum must be adjusted. Finally, the last spoke, ‘Community’, involves inclusion of the community the program serves in program planning and evaluation (e.g., community action boards), integration of the program into the community (e.g. community based rotations), and participation in community activities by residents and faculty (e.g., involvement in STEM programs at local schools).

Summary of findings

This study employed in-depth interviews with key informants, formative research, and existing theoretical frameworks, to determine strategies for creating sustainable, effective, and continuously improving anti-racism curricula for medical residents. Findings highlight the need for focusing on ensuring the four key elements of (1) Support (2) Pipeline (3) Outcomes and (4) Community. The SPOC model can be used as a roadmap for future anti-racism curriculum design and implementation.

Key messages

One of the key messages of this work is that 'what gets measured gets done', and can be used to hold people accountable, which is essential if anti-racism work is to be successful. Including outcome and accountability measures tied to credentialing and accreditation is necessary to ensure long-term goals are met and continuous quality improvement occurs. Recruitment and retention of underrepresented minorities into programs and leadership positions is also necessary and, along with resource allocation and availability, is essential to long-term sustainability of anti-racism curricula. Community involvement is also key.

Limitations and strengths

Findings from this study are subject to serveral limitaitons. The formative and qualitative nature of the work potentially limits the generalizability of the findings. In addition, this work may be limited by regional or system restrictions (for example prohibition of the use of the term “diversity” in programs in Florida). Moreover, individual program sustainability will depend on individual funding and resource availability which may vary from program to program. Finally, only 15 of the 20 participants opted to answer the optional demographic survey, limiting our ability to analyze complete demographic data for our study sample.

The strength of this work is rooted in the breadth and depth of experience represented by the participants as well as the research team itself which consisted of a diverse group of clinical, psychology, and public health practitioners, faculty, and educators. Team members included those who identified as URM. Multiple members also have extensive experience in adult learning, direct patient care to populations which are vulnerable, and teaching and curriculum building for adult learners in the areas of equity, social determinants of health, gender studies, and trauma informed care. The research team also included members with expertise in use of theoretical frameworks.

This work is one of the first to qualitatively examine the experiences and perspectives of key stakeholders involved or invested in creating and advancing anti-racism curricula. It highlights the importance of considering sustainability factors when creating, implementing, and evaluating anti-racism curricula for physicians in training.

Next steps for research in this area should focus on examining measurable and meaningful outcomes of anti-racism curricula to identify what strategies and approaches are most effective in bringing about the desired downstream effects for residents, programs, health care systems, communities, and the health care system as a whole.

Policy makers and academic medical residency leaders can access and use this work to drive recommendations for future policies aimed to support and advance anti-racism teaching in physician training programs specifically: (1) Implementation of credentialing designed to promote integration of anti-racism teaching and (2) Implementation of academic hospital system outcome metrics aimed at measuring equity that are tied to accreditation. Policy makers should also recognize that some regional policies might be impeding this work in specific parts of the country, and advocacy efforts to change such policies at the local and national level will be needed to ensure this work can be done effectively.

Community participation is a key to success. Programs undertaking this work should involve the communities they serve in each step of the process. Establishing a community action board may be an effective manner in which to accomplish community involvement, but other methods can also be used.

Available tools for future work

Along with specific curriculum tools ( https://www.medicalantiracismcurriculum.com/ ), the SPOC Model can assist teachers and learners who are interested in designing, implementing, and evaluating their own anti-racism curricula. This model may support future residency programs’ efforts to ensure sustainability and continuous quality improvement components are built into curricula, and resultant downstream improvements in health outcomes and community involvement occurs.

Availability of data and materials

The datasets generated and/or analyzed during the current study are not publicly available due concern for keeping identity of participants anonymous but may be provided in part from the corresponding author on reasonable request.

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Acknowledgements

We would like to thank the residents, staff, students, and other faculty at the Wellstar Douglas Family Medicine Residency Program for their support of the anti-racism curriculum and for all of their feedback and efforts to continuously improve the education provided to the residents and the care given to our patients. Thank you also to Dr. Helena Spector for her editing assistance.

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Gertz, A.M., Smith, M., Thomas, D. et al. A qualitative study to explore experiences of anti-racism teaching in medical residency programs across the United States and subsequent creation of the SPOC (Support - Pipeline - Outcomes - Community) Model to guide future curricula design. BMC Med Educ 24 , 382 (2024). https://doi.org/10.1186/s12909-024-05305-5

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Women’s experiences of attempted suicide in the perinatal period (ASPEN-study) – a qualitative study

• Kaat De Backer   ORCID: orcid.org/0000-0001-5202-2808 1 ,
• Alexandra Pali   ORCID: orcid.org/0009-0009-5817-156X 1 , 2 ,
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Suicide is a leading cause of maternal death during pregnancy and the year after birth (the perinatal period). While maternal suicide is a relatively rare event with a prevalence of 3.84 per 100,000 live births in the UK [ 1 ], the impact of maternal suicide is profound and long-lasting. Many more women will attempt suicide during the perinatal period, with a worldwide estimated prevalence of 680 per 100,000 in pregnancy and 210 per 100,000 in the year after birth [ 2 ]. Qualitative research into perinatal suicide attempts is crucial to understand the experiences, motives and the circumstances surrounding these events, but this has largely been unexplored.

Our study aimed to explore the experiences of women and birthing people who had a perinatal suicide attempt and to understand the context and contributing factors surrounding their perinatal suicide attempt.

Through iterative feedback from a group of women with lived experience of perinatal mental illness and relevant stakeholders, a qualitative study design was developed. We recruited women and birthing people ( N  = 11) in the UK who self-reported as having undertaken a suicide attempt. Interviews were conducted virtually, recorded and transcribed. Using NVivo software, a critical realist approach to Thematic Analysis was followed, and themes were developed.

Three key themes were identified that contributed to the perinatal suicide attempt. The first theme ‘Trauma and Adversities’ captures the traumatic events and life adversities with which participants started their pregnancy journeys. The second theme, ‘Disillusionment with Motherhood’ brings together a range of sub-themes highlighting various challenges related to pregnancy, birth and motherhood resulting in a decline in women’s mental health. The third theme, ‘Entrapment and Despair’, presents a range of factors that leads to a significant deterioration of women’s mental health, marked by feelings of failure, hopelessness and losing control.

Conclusions

Feelings of entrapment and despair in women who are struggling with motherhood, alongside a background of traumatic events and life adversities may indicate warning signs of a perinatal suicide. Meaningful enquiry around these factors could lead to timely detection, thus improving care and potentially prevent future maternal suicides.

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Pregnancy, childbirth, and the postnatal period are a positive and empowering experience for many women and birthing people Footnote 1 . Yet it is widely accepted that the perinatal period is also a time of significant stress, with one in four women experiencing mental health difficulties during this time [ 3 ]. Evidence on the impact of perinatal mental ill-health on the mother [ 4 ], her children [ 5 ], the wider family [ 6 ] and society [ 7 ] has grown in the last decade and worldwide, maternal suicide has been identified as a global public health issue [ 8 ]. In European countries with enhanced surveillance systems for maternal mortality maternal suicide has been identified as one of the leading causes of maternal death [ 9 ]. In the UK, the Confidential Enquiries into Maternal Deaths (MBRRACE-UK) have repeatedly highlighted similar findings, leading to the development and expansion of specialist perinatal mental health services in the UK [ 10 ]. Despite this, there has been no sign of a reduction in suicide rates [ 11 , 12 , 13 , 14 ]. The UK Government has therefore identified pregnant women and new mothers for the first time as a priority group in the recent Suicide Prevention Strategy [ 15 ].

While maternal suicide is a relatively rare event with a prevalence of 3.84 per 100,000 live births (95% CI 2.55–5.55) in the UK [ 1 ], many more women will attempt suicide during pregnancy and the year after birth. Worldwide, the pooled prevalence of perinatal suicide attempts has been estimated to be 680 per 100,000 (95% CI 0.10–4.69%) during pregnancy and 210 per 100,000 (95% CI 0.01–3.21%) during the first-year postpartum [ 2 ]. As well as distressing in their own right, perinatal suicide attempts are known to increase the risk of future fatal acts [ 16 ]. Antenatal [ 17 ] and postnatal suicide attempts [ 18 ] are also associated with increased maternal and neonatal morbidity, adverse birth outcomes, and further suicide attempts.

It is important to note that terminology in suicide research has been a contentious issue and a wide range of definitions have been used in various contexts. The US National Center for Injury and Control issued guidance on uniform definitions in the context of self-directed violence’ [ 19 ], which has informed our study definition of ‘suicide attempt’: “a non-fatal, self-directed, potentially injurious behaviour with intent to die as a result of the behaviour. A suicide attempt might not result in injury”. This definition contains three components worth highlighting, i.e. (1) suicidal ideation, (2) suicidal intent and (3) suicidal behaviour. ‘Suicidal ideation’, also known as ‘suicidality’ (i.e. thoughts of engaging in suicide-related behaviour) [ 19 ] is a known risk factor for suicide [ 20 ] but does not necessarily lead to suicidal behaviours (e.g., behaviour that is self-directed and deliberately results in injury or the potential for injury to oneself, with implicit or explicit evidence of suicidal intent’) [ 19 ]. ‘Suicide attempt’ must also be distinguished from ‘near-fatal deliberate self-harm’, which was defined by Douglas et al (2004) as ‘an act of self-harm using a method that would usually lead to death, or self-injury to a “vital” body area, or self-poisoning that requires admission to an intensive care unit or is judged to be potentially lethal [ 21 ]’. This definition does not contain an element of ‘suicidal intent’, ie. explicit or implicit evidence that at the time of injury the individual intended to kill self or wished to die, and that the individual understood the probable consequences of his or her actions [ 19 ].

To date, perinatal suicide research has predominately been based on case note reviews [ 1 ], retrospective cohort studies [ 22 ], or qualitative studies focussing on suicidal ideation [ 23 ]. Research into suicide attempts in the perinatal period is therefore acutely needed, to gain a better understanding of the circumstances surrounding maternal suicide, the support available to perinatal women and how future deaths can be avoided. To our knowledge, no studies in the UK have used qualitative methods to explore the experiences of women who undertook a suicide attempt in pregnancy or during the postnatal period, yet survived. A better understanding of these events could help refine support and early interventions for women and birthing people at risk.

Aim of the study

The aim of this study was to explore the experiences of women and birthing people who had undertaken one or more suicide attempts during the perinatal period.

Study design

The ASPEN-study (Attempted Suicide during the PEriNatal period) utilised a qualitative design, using semi-structured interviews, to allow for an in-depth understanding of the contextual factors of perinatal suicide attempts, and to demystify the taboos and misunderstanding that are enshrouding this phenomenon [ 24 ]. Qualitative methods are particularly helpful to study sensitive topics [ 25 ] and can facilitate a deeper understanding of suicide attempts, beyond merely explaining [ 26 ]. We adopted a critical realist ontology, meaning participants’ accounts were seen as ‘truths’, even when their reported recall might have been impacted by serious mental illness and/or distress at the time of events [ 27 ]. We also adopted an objectivist epistemological stance meaning our belief system of how we acquire knowledge is one of reality existing and not being constructed, thus enabling an approach to participants’ narratives with no preconceived notions of how the participants may experience the phenomenon of interest [ 28 ]. Drawing on our epistemological and ontological positions, a critical realist approach to Thematic Analysis was best aligned with our philosophical underpinnings. Critical realist TA is an alternative approach to Thematic Analysis, that differs from codebook TA with its positivistic assumptions [ 29 ], or reflexive TA that is grounded in philosophical constructivism [ 30 , 31 ]. Critical realist TA is an explanatory approach that aims to produce causal knowledge through qualitative research on phenomena in the world around us [ 32 , 33 ]. We wanted to go beyond merely ‘exploring’ the phenomenon of perinatal suicide attempt, but aimed to understand what women had experienced during this time, such as any significant life course events they identified as relevant to their perinatal suicide attempt, the specific circumstances in the lead-up to the suicide attempt, their views of motherhood and how this impacted their mental health and any key elements or milestones that made a substantial difference on their journey to recovery. As such, this approach informed our development and structure of the interview schedule and analysis of the data to ensure that this was captured.

Participants and recruitment

The study was advertised through social media and third sector organisations in the field of perinatal mental health and suicide prevention (see Acknowledgements). Interested participants were included if they: (1) were 18 years of age or older; (2) had one or more suicide attempts during the perinatal period (i.e. from pregnancy up to the first year after giving birth), including when the attempt was prevented by self, a loved one or a member of the public; (3) and this happened less than 10 years ago; (4) were residing in the UK; and (5) were not receiving inpatient psychiatric care or experiencing an acute episode of a psychiatric disorder at the time of recruitment. The latter exclusion criterium was adopted in line with our safety protocol, to prevent delays in recovery by addressing such a difficult event outside a therapeutic environment. We used both convenience sampling and purposive sampling techniques: we interviewed anyone who responded to our recruitment materials, met the inclusion criteria and wanted to participate in the study after reading the participant information sheet (convenience sampling). Simultaneously, we also made concerted efforts through intense collaboration with community leaders and third sector organisations to recruit a diverse sample of women and birthing people from different ethnic, cultural, socio-economic and religious backgrounds (purposive sampling). A total of twelve women and birthing people contacted the research team with an interest in the study. Eligibility for the study was explored in a sensitive way, against the overall inclusion criteria and the three components of the study’s definition of ‘suicide attempt’ (suicidal ideation, intent and behaviour). Where in doubt, eligibility was discussed with the wider supervision team. In total, eleven interviews were conducted. A twelfth interested participant did not attend the (online) interview and did not respond to any follow-up emails. Recruitment was finalised when no new themes were being generated from data analysis of the last two interviews [ 34 ]. Participants received reimbursement of £50 for their time to complete the interview and a short demographic survey.

Data collection and analysis

Semi-structured interviews lasted between 38 and 115 min ( MTime  = 65 min) and were conducted via video-conference software (Microsoft Teams) by one researcher (KDB) between October 2022 and April 2023. Interviews were audio-recorded, transcribed and de-identified by a professional transcription company. Field notes were taken during the interview. Transcriptions were checked for accuracy by two researchers (KDB, AP). The interview schedule, which was co-designed with a panel of women with lived experience of perinatal mental illness, aimed to explore experiences of mental health difficulties prior to and during the perinatal period, the circumstances in the lead-up to the suicide attempt, and those following the suicide attempt. The interview schedule was used flexibly and did not prevent participants from sharing their story in the order they preferred, but instead, was used as an aid to prompt where required. Interview data was so rich that a secondary analysis focusing on social support prior and after women’s suicide attempts was undertaken, to be published separately.

Thematic Analysis (TA) [ 30 , 31 , 33 ] of the interview data was conducted using NVivo software while adopting a critical realist approach to Thematic Analysis [ 30 , 31 , 33 ]. The process of data analysis is rarely a linear event, and guided by Fryer’s previous work on critical realist TA [ 33 ], our approach to data analysis is presented in Fig.  1 and can best be described as follows:

Display of critical realist approach to thematic analysis

Public and patient involvement and engagement (PPIE)

An established advisory panel of women with lived experience of perinatal mental illness was consulted during different phases of the study with additional feedback sought from key stakeholders in the field of perinatal mental illness (see Acknowledgements). The process of PPIE during the study design and data collection phase of this study has been documented elsewhere [ 35 ]. A draft manuscript was shared with research participants to sense-check findings and comment on the manuscript. Participants were also given the opportunity to select a pseudonym of their choice. A total of 8 participants reviewed the draft manuscript and their feedback was incorporated in the final version of this paper.

The study team and reflexivity

The research team are a multidisciplinary team of researchers and clinical academics, with backgrounds in psychology (FLC, AE, RH, SAS, AP), psychiatry (LMH), and midwifery (KDB, JS), and several had clinical experience of supporting women who attempted suicide during the perinatal period (KDB, FLC, LMH). Within the research team, there was a balance between those who were parents and those who did not have children and researchers were at different stages of their life, spanning nearly three generations. The phenomenon of suicidality in the perinatal period was familiar to most of the research team, through extensive clinical experience and/or previous research in the field of perinatal mental health. Our positionality is therefore best described as ‘hybrid’, concordant with our critical realist ontology, as we aimed to align our existing knowledge and understanding (i.e. being embedded in the data) with the uniqueness and unfamiliarity of each individual story that was shared with us as a ‘truth’ (i.e. being an objective onlooker), in order to analyse the data in a coherent and sensitive matter [ 36 ]. Data were collected by one researcher (KDB) who was trained in advanced qualitative research techniques as well as having clinical experience as a perinatal mental health midwife. Analysis was conducted by the same researcher and a MSc Student with a background in clinical psychology (AP). Regular team meetings were held throughout the data collection and analysis phase to discuss and sense-check the developing themes and sub-themes.

Participant safety and researcher wellbeing

The safety and emotional wellbeing of all participants was key throughout the study. Thus, we adopted key elements of trauma-informed care into our study design [ 37 ]. A robust safety protocol, with clear pathways for escalation if required, was developed with the input of the PPIE advisory panel [ 38 ]. The study team undertook bespoke training in trauma-informed interviewing and the interview schedule was developed with this in mind. A safety check prior and after the interview was carried out by the same researcher (KDB), either via email or by phone and all participants were offered a confidential de-brief session with an independent clinical psychologist. The psychological safety of the researchers was also considered [ 25 ] and supported by access to regular reflective supervision sessions provided by a clinical psychologist and regular debrief sessions with supervisors to process any difficult emotions arising from conducting the interviews [ 39 ]. We were acutely aware of the potentially triggering content of the audio files and raised this with the transcription company [ 40 ]. When sending audio recordings for transcription, a summary of triggering content was provided to ensure the transcription would be appropriately allocated.

The majority of our sample ( N  = 11) were White British women ( n  = 10), with one woman from a mixed ethnic background. Participants were predominantly married ( n  = 8) and had higher education qualifications ( n  = 7). All but one participant had received a mental health diagnosis by a doctor or other healthcare professional in the past although the demographic survey did not allow to ascertain when this diagnosis had been given. More than half of the participants in our sample were given multiple diagnoses, indicating a high level of complexity in mental health presentation. In most cases, pregnancies had been planned ( n  = 9). All but two women were multiparous, with half of the sample having two children ( n  = 6), and three participants having three or more children. Two women were first-time mothers at the time of the attempt. Four women undertook their suicide attempt during pregnancy, with a fifth woman being pregnant whilst her older child was still under the age of one. The remaining six women undertook a suicide attempt within the year after giving birth. Four participants had a stay in an inpatient psychiatric Mother and Baby Unit (MBU), and for three of them the admission was preceded by their suicide attempt. For one participant, the admission in the Mother and Baby Unit was subsequently followed by an admission in a general psychiatric hospital, where she undertook the actual suicide attempt. A full table of demographic and clinical information can be found in Table  1 .

Qualitative analysis resulted in the identification of three key themes that played a significant role in the deterioration of women’s mental health during the perinatal period, ultimately culminating into a suicide attempt. Saturation for all themes and sub-themes was achieved after nine interviews when no new themes or subthemes were generated. Data from the remaining two interviews confirmed our analysis and provided additional depth and detail [ 34 ]. The three overarching themes are presented in Fig.  2 : Theme 1 ‘Trauma and Adversities’ , consisting of family history of perinatal mental illness and psycho-social adversities, including grief and trauma; Theme 2 ‘Disillusionment with Motherhood’ , marked by a variety of challenges that arose during pregnancy or the postnatal period; and Theme 3 ‘Entrapment and Despair’ , where multiple stressors piled up with no respite or support available, leading to a severe deterioration of mental ill-health, and ultimately, the suicide attempt.

Display of themes and sub-themes

Qualitative data is presented below, with the most representative quotations in text and an additional table of supplementary of quotations included in Supplementary Material 1 .

Theme 1: trauma and adversities

All respondents in our sample started their pregnancy journeys with a range of vulnerabilities, such as previous mental health difficulties, loss, trauma, or social risk factors including domestic abuse and substance misuse. Nevertheless, participants were not always aware of the profound impact these would have on their mental health later in pregnancy and in the postnatal period. Subthemes contributing to this were:

Psycho-social adversities

Many women had experienced mental health difficulties at some point in their life, and most were fully aware of their potentially devastating impact. Some had experienced poor mental health during adolescence and young adulthood and anticipated mental health problems during the perinatal period.

“I’ve had some terrible things happen in my life about failed marriage and fertility problems. Big, big things that I’ve sort of managed with a strength of mine that I perhaps didn’t have in my late teens or early 20s to overcome. So I guess it was always on my radar knowing the stats around you are more likely to have perinatal mental health problems if you’ve had bouts of depression in the past.” – Rosy .

In contrast, others had dealt with traumatic experiences in their life, but could not see how this would be relevant to their mental health during pregnancy and the postnatal period. They started their pregnancy unaware of any potential risks to their mental health.

“I lost my brother when he was 18. […] And I didn’t get a lot of time off work, I was kind of straight back into work. I’m a [professional role in mental health], so I was working in acute psychiatry. Back to work, dealing with other people’s trauma and I don’t think I really dealt with my own particularly well. And it was kind of I think eight months later I had an episode of depression, just very low mood, apathy, poor motivation, poor concentration, was treated briefly with antidepressants and then just kind of did okay after that. So there had been nothing.” – Simone .

Previous trauma was reported by almost all respondents, whether it being through a bereavement, or traumatic life experiences, such as miscarriage and infertility, domestic abuse, fractured relationships, or suicide of a loved one. Two women reported having experienced domestic abuse. One of them reported the abuse, which she described as a ‘punishment’, only started after informing her partner of the pregnancy.

“It was a punishment actually that I dared to be pregnant even though he knew I wasn’t on any contraception or anything. And it really shocked me because he had never ever been like that before.” – Lauren .

For the other respondent, the domestic abuse had been long-lasting and led her to seek coping strategies to deal with the trauma and pain. Being in an abusive relationship created the worst possible start for pregnancy, with no support available.

“Well, it was my first pregnancy. I was 24 so I still hadn’t grown up properly, and I was in a really bad domestic violence relationship so there was a lot going on around that. I was getting no support [for] my pregnancy. I was also using as well which I regret profoundly, but I was drinking, like I drank occasionally because of my mental health, and my mental health was just all over the place; I was really, really unwell.” – Selina .

For some, their previous mental health difficulties were related to an earlier pregnancy or birth experience:

“I had huge amounts of birth trauma from my first, which I had a debrief for from the hospital, which was incredibly unhelpful. And it ended in emergency caesarean [section], after nine days of labour, and being in hospital, as a very naïve 19-year-old, having her first baby; looking back on it, feeling quite coerced by doctors, but not realising at the time that that’s what was happening. And that has impacted me for the rest of my life.” – Sam .

The severity of previous perinatal mental health problems was varied, with one woman having experienced postpartum psychosis after the birth of her first child. Going into the second pregnancy, the risk of relapse was hanging over her like a dark cloud:

“I remember sort of going to the 12-week scan with [second pregnancy] and getting the picture and thinking like shit, it’s really real now and it could all happen again. So I was really scared about that. Because the reccurrence rates are quite high for psychosis, so it’s quite likely that I was going to become unwell. So I was worried, yes, I was really concerned.” – Marie .

This feeling of worry was also reported by women with mild to moderate mental health difficulties and was compounded by a fear of being dismissed and not being able to access support if they would require it.

“I think there was something about the anxiousness of doing it all again, because I think I had some prenatal depression with my first, that wasn’t picked up, and then postnatal anxiety through the roof, that was also never picked up, and was told that was normal.” – Sam .

Family history of perinatal mental illness

Several respondents had a family history of perinatal mental illness and were vigilant that they might experience something similar. To mitigate this risk, they actively sought perinatal mental health support at the earliest opportunity.

“My mum had severe perinatal mental illness, she was hospitalised after my older brother for a year without him […]. At the time they didn’t really have Mother and Baby Units. Then I came [a few] years later and she was hospitalised again but with me for six months, and she passed away […] So my dad said she was saying the same things as each time she’d been sectioned; she would present with very religious ideation and stuff like this, so it was exactly the same stuff, and she died by suicide. So because of that collective history, when we were trying to get pregnant we thought “We need to let someone know we’re trying to get pregnant,” and so I was referred then to a Perinatal Psychiatrist before we got pregnant” - Sarah .

For others, this family history was not something which was spoken about prior to their own experiences of perinatal mental illness. One respondent mentioned she had never been aware of her mother’s history of postnatal depression until she herself started to experience postnatal depression.

“I didn’t know that my mum had postnatal depression. That’s not anything that she’d shared until… I knew that my brother cried a lot and I think he had a cows’ milk protein intolerance, but I didn’t know that my mum…” – Rosy .

Theme 2: disillusionment with motherhood

While previous mental health challenges or trauma were present in the background, all women were profoundly disillusioned with motherhood which contributed to a deterioration in their mental health. This theme of ‘Disillusionment with Motherhood’ captures three sub-themes that reflect a discrepancy between what women thought or hoped motherhood would be like, and the crushing reality they found themselves in. Together, these sub-themes compounded each other and became a catalyst for worsening mental health. The following sub-themes address the various areas of disillusionment that women in our sample reported: in their bodies, in their identity and in the bond with their baby.

The physical and mental struggle of pregnancy and birth

All participants held hopes and expectations of what their pregnancy, birth or the postnatal period would be like. For some first-time mothers, it soon became clear that the societal rosy-hued image of pregnancy was very far removed from their own experience of pregnancy. As they came to grips with how pregnancy was unfolding, the harsh contrast between expectation and reality was so high that many struggled to adjust to this:

“There’s all this thing about pregnancy you’re supposed to be glowing and it’s all marvellous and you’ve got these wonderful hormones, but I was just beached on the sofa feeling hot and sweaty thinking when is this baby going to come out, when’s it going to come out?” – Simone .

For those who had been pregnant before, the reality of another pregnancy, knowing full well what was in store, started to dawn on them:

“I don’t know, it hit me like a ton of bricks. Like oh shit, I’m doing this again. I’m pregnant again.” – Liv .

In addition to these psychological adjustments to reality, respondents mentioned how the physical toll of pregnancy and childbirth played a significant role in the deterioration of their mental health. This close correlation between physical issues and mental health decline was abundantly clear across the sample.

“I was horribly, horribly sick [hyperemesis]; that got worse each pregnancy. I don’t know if that’s normal; I’d heard it is. But horribly sick, which makes you absolutely miserable anyway.” – Sam . “I just sort of couldn’t wait for it [the pregnancy] to end. Yes, I just wanted to give birth. So when they said that they were going to induce me at 40 weeks I thought thank goodness, because my sickness started again quite late on. Again, I don’t know if it was because of the pre-eclampsia. But yes, I was just very ready, very ready to have little one.” – Hannah .

In the most extreme cases, pregnancy was not viewed as something to be enjoyed, but something that left women feeling repulsive.

“So since the pregnancy, just my life fell apart really, I was unemployed, and I just felt the whole way through not just sick and ill, absolutely physically repulsive, like I just felt like an absolute filthy animal. I can’t describe the disgust I felt for myself and the bigger my bump grew, the more disgusting I felt. And I don’t know, it’s just everything was awful, every day was awful.” – Lauren .

For other women physical injuries as a result of childbirth left them unable to function and to enjoy the things they were looking forward to as a new mother.

“I had some tearing and I’d had an episiotomy and they hadn’t healed, so my episiotomy had opened up and there were lots of A&E [Accidents and Emergency] visits and an operation eventually, but I think that really didn’t help my mental health because obviously if you’re in pain all the time then, it just drags you down, doesn’t it? So I wasn’t able to do my normal stuff, I wasn’t able to just carry on with life because I was in pain, I couldn’t sit and I felt like I couldn’t do mummy things.” – Mel .

Apart from the physical repercussions of pregnancy and childbirth, it was the trauma of giving birth and its psychological sequalae which triggered a marked deterioration in the mental health of several women in our sample.

“It was just sort of like you couldn’t expect it to happen, it was like a poor pregnancy and sort of felt like, you know, the birth went wrong as well.” – Hannah . “I had a premature baby. And I went on, I don’t know, like trauma response. Like totally numb. I suppose the adrenalin, the shock, everything…” – Liv .

Invalidation of identity and self-sacrifice

Almost all respondents encountered negative experiences with healthcare professionals at some point during pregnancy or the postnatal period and felt invalidated and dismissed by these. Women reported they were not seen as a person, with a complete identity, but reduced to a vessel for their baby, with little consideration given to their own feelings. This led to a profound loss of identity, exacerbating feelings of being invisible, inadequate and unimportant.

“It was never about me. And I know it’s not all about me, but when I’m wanting to commit suicide, it is very much about me and not one person asked me if I was alright, they were more concerned if the baby was alright, which I was as well, but they just completely bypassed that there was any reason I would do it.“ – Selina .

There seemed to be a lack of professional inquisitiveness to understand why a mother(-to-be) would consider suicide. Instead, all attention was directed towards the well-being of the baby, leading to multiple missed opportunities for timely care and support. In some cases, women reached out but their calls for help were simply ignored while their mood was rapidly deteriorating. These experiences would have devastating consequences on their further help-seeking behaviour.

“What really killed me, what was like the punch in the face that I needed was when I had my midwife appointment at, I don’t know, eight, ten weeks, something like that, and I told her ‘you know what, I’m not feeling right. There’s something bubbling inside me that is not alright, is not correct. I feel more anxious than normal, I can’t sleep, it’s all very weird’. And she just said ‘okay, I’m going to pin that down here to talk about in your next appointment. But we’re not going to do anything right now’. I never saw her again, by the way.” – Liv .

Invalidating encounters like the one described above would have a profound impact on how women viewed healthcare professionals as a source of support and whether they would reach out to them and share the extent of their mental health problems.

“I just felt like nobody was listening at all, just not heard one bit.” – Anna .

For some, the invalidating experience would almost become a motivator to succeed in their suicide plans, as they felt the severity of their mental health problems was brushed under the carpet. One participant sought help after a first suicide attempt through a medication overdose and shared the following:

“So then I think a few more weeks went by and I went back to the doctor’s. I said to the doctor, ’I want to kill myself’. My medication and stuff, I was honest with him, I said the medications and stuff that he was put… I think he tried me on Zopiclone as well with not sleeping and he said, ‘Well if you wanted to kill yourself, you would have done it by now’. I was just… I sort of felt then I’ve got something to prove.” – Hannah .

The loss of identity made respondents feel invisible to healthcare professionals and went hand in hand with exhausting themselves to be the best possible mother for their baby. Women described feelings of total self-sacrifice to meet this perceived standard of ‘the perfect mother’.

“I think I sort of went into supermum mode when I came home, like I had something to prove, and again, it’s that background of failure. I think I’m quite hard on myself anyway and I’m quite… If something goes wrong, I’m probably harder on myself in my head than somebody else would be and I maybe got a bit of a perfectionist trait, so I really didn’t want to rely on anybody, I didn’t ask for help with anything regarding my little boy, and I had a really, really strong bond with him which was really positive, but I think I was sort of going like overkill with not asking for help.” – Hannah .

However, as women started to experience the hard reality of caring for a newborn, they felt unable to meet this impossible standard. The perceived pressure to achieve (unrealistic) goals as well as their feelings of failure to do so started to take a significant strain on their mental health.

“No one had ever told me that before. No one had ever said that you don’t just have to drop everything and run to your child. Because I thought that that was what a secure bond was; and obviously now I’ve learnt about attachment theory and things. I thought that, for her to be securely bonded with me, I had to give every last drop of myself to be her mum.” – Sam .

‘It wasn’t like starry-eyed love’

Closely linked with the previous sub-theme, was the realisation for many women that they did not feel an instant rush of love for their baby. Several women reported feeling unsettled and flawed as a mother when they felt distant and detached from their baby. Women tried their very best to ‘act as a mother’ and do whatever their baby required, but this did not mean they also ‘felt like a mother’.

“So, at the beginning it was very strange. It, because like I said, I was determined to do anything in my power to get that baby out of NICU [Neonatal Intensive Care Unit]. Like whatever it takes, whatever the cost. So it never felt like oh, it’s my baby. I would have jumped in front of a train for him but it was not like a starry-eyed love. And that kept going.” – Liv . “In terms of motherhood, yes, I don’t know whether I just felt I was failing at it or… [pause] I don’t know, I felt very not connected to the baby. I had felt very, very bonded and very connected, and then I wasn’t at all.” – Sarah .

Sadly, for some, this lack of bonding with their baby persisted for a long time, with enduring consequences on their mental health and family happiness, leading to feelings of guilt and shame with which they still are coming to terms with.

“I had no attachment to him probably for about five years, nothing at all, just this ongoing sense of regret and I remember thinking daily I’ve made such a massive mistake in my life and almost this like realisation you are never going to get back what you had before, so just this real hopelessness actually at life.” – Lauren . “I just couldn’t, I couldn’t bond with, I couldn’t. Even still now I love her to pieces but we’re not like mother and daughter, we’re not.” – Anna .

Theme 3: entrapment and despair

In the final phase leading up to the suicide attempt, women experienced an accumulation of stressors, unleashing an overwhelming feeling of hopelessness and entrapment, with seemingly no way out of the situation they found themselves in. The sub-themes identified under this theme of ‘Entrapment and Despair’ left women no breathing space or respite. A perfect storm was brewing, for which women only started to see one way out, and that was by taking their own life.

Feeling like a failure

All respondents expressed a pervasive feeling of utter failure, intersecting their different identifies as a woman, mother and partner. Their perceived inability to meet expectations, whether this related to giving birth, feeding their baby, or functioning as a mother and partner stood in sharp contrast with how they viewed other mothers, who seemed to be effortlessly successful in doing so.

“You sort of just blame yourself. So I can just remember looking at him when he was asleep thinking like, ’Oh you’ve failed, I can’t do this, I’ve already failed at being a mum, but I can’t do this’, and I can just remember just thinking that, looking at him. So I think even though I know it wasn’t my fault, you really felt like a failure and I felt like it was me, like there was something wrong with me, because a lot of women around me, like even family, they never really had experiences like that, they would have like a good pregnancy, like a vaginal birth, a normal birth, so I really felt like I had failed and I really blamed myself for that.” – Hannah .

This feeling of being a total failure created a sense of dread, leaving them fearful every day that their inability and incompetence as a mother would be further exposed.

“I remember seeing the light coming in through the curtains in the morning and just thinking “Oh my god, no, I can’t, I can’t do another day,” like my heart would go, and it was that dread, that whole dread would come over me and I’d think “I can’t do another day today, I just can’t do it. I can’t do it.” It was like a… Yes, it was really hard. I just felt like I don’t know, it felt like I just wasn’t good enough for her, I wasn’t good enough. […] It just felt like I wasn’t good enough to be her mum.” – Mel .

This overwhelming sense of incompetence erased feelings of love, enjoyment or hope and instilled a feeling that their baby and loved ones would be better off without them.

“So it just escalated. This what was going on in my head about, you know, me not being good enough, a failure, just escalated even more, that now I was thinking they are going to take him away, everyone will know how rubbish I am. So it was later that week where I still wasn’t sleeping and I just thought, do you know what, the both of them would be better off without me, because I’ve just failed, I’m just a failure. They will be better off without me.” – Simone . “…That just made me feel so, so low that I think that spiral of internalised feelings and negativity compounded with this sort of isolation and lack of sleep just led me to think they’d be better off without me around, they’d have a parent maybe or a family that would be able to meet their needs.” – Rosy .

Intense intrusive thoughts and abnormal experiences

More than half of the women in our sample reported intrusive ideas or unsettling experiences in the period preceding their suicide attempt. For many, this came as a total surprise as they were unaware this could happen and they felt unable to express the extent of their intrusive thoughts to anyone.

“I remember getting up and going to the bathroom to brush my teeth and then started hearing voices. So this voice, I didn’t recognise it, was just chanting, ‘stinky [name of baby], stinky [name of baby]’, which is my baby’s name and I was like why’s that happening? I don’t understand. Where’s that coming from? And then later that day I remember looking at my husband and thinking you’re the father of this baby, but I’m not its mother. It was a really odd thought, because I was like I know I’ve been pregnant and I know I’ve just been through all that labour, but I look at this baby and it’s not mine, but I know you are the dad. It was really odd.”- Simone . “They [the intrusive thoughts] were really, really scary. And totally uncontrollable as well. They were so vivid and they used to make me feel really upset because they happened quite early on, probably when she was only a few weeks old and I remembering googling them and reading loads of things about it didn’t mean that you were not coping, it didn’t meant that you were going to hurt your baby, it didn’t mean that you were depressed, but I think maybe I should have perhaps seen that as a bit of a sign that I needed to get some help because it was weeks and weeks later that I finally did. But yes, they did upset me and I only told my mum, I didn’t tell anybody else because I just felt as though are people going to think that I’m going to hurt her? Am I going to hurt her if I talk about it more? Yes, they were really scary.” – Rosy .

For some, these ideas were extremely horrific and a symptom of their psychotic illness at the time. Unfortunately, this was left undiagnosed and untreated, leaving them totally desperate and isolated while these unsettling thoughts became their lived reality.

“[…] I started to think ‘oh I’ve committed all these awful crimes in my life’ and I was kind of struggling to process what they were and I was thinking have I killed people and maybe buried them and I don’t know where they are or have I kind of done a big theft or something but not been able to quite work out where I’d stolen the money from. But I was kind of panicking that I’d either buried these bodies or hidden this money and I couldn’t remember where they were, so I was panicking someone else is going to find them and then I’m going to be put in prison. So I had this kind of I want to die because I’m scared I’m going to go to prison because I’ve done all these awful things. And I just felt absolutely desperate.” – Lauren .

Alone in this world

While these distressing experiences of failure and intrusive thoughts invaded women’s mindset, women felt profoundly alone and isolated. Social isolation was reported as a catalyst for their suicide attempt by every woman in the sample. For some, it was a continuation of the situation they had already been in, but during this stage everything felt more desperate, more alone.

“I think by that point I wasn’t talking to anybody at all, not family, certainly not the kids’ dad. The kids’ dad… […] I just totally blocked his number and I wasn’t seeing anybody else. And actually, in some ways, I don’t think anybody wanted to see me because they were just like, “Why have you had another kid?” So the only people that I saw were my own kids, maybe the odd school teacher at pickup but that was it. No one from work. No friends really.” – Lauren .

For others, it was the absence of their partner, who had to return to work after paternity leave, that served as a lever for an acute deterioration of their mental health.

“Everything was fine until about three weeks after the birth and we were back at home, and my husband went back to work; it was him going back to work and I just, yes, fell apart.” – Sarah .

Some respondents had their baby during one of the COVID-19 pandemic lockdowns, when social restrictions meant they were unable to meet with friends or family or seek peer support from other mothers. Instead, they felt cooped up inside their house, alone and isolated, with their suicidal thoughts.

“Completely isolated. Not being able to, like I could have been going to, I don’t know, prenatal yoga. Or breastfeeding groups or toddler groups. Anything else that would take me out of that loop. So I think obviously that made it a lot worse. I don’t think that it would have been… – I don’t know.” – Liv . “So she was three or four months old when Covid hit and it was the whole lockdown and yes, everything just got ten times worse because I couldn’t do anything then; I couldn’t go and talk to my mum, I couldn’t go out, I couldn’t even have doctor’s appointments, I couldn’t have hospital appointments which made me worry even more, and my husband’s a key worker so I was just on my own all the time. Yes, and I think that’s when it got to the point where I just felt like I couldn’t cope anymore.” – Mel .

Several respondents recalled how this feeling of loneliness instilled a determination in them to retreat into isolation further. This meant they no longer wanted to speak to or be around others, even when they had a supportive network in place. An unstoppable cycle of isolation and socially avoidant behaviour was set in motion.

“I just stopped talking to people. That’s when I stopped talking to anybody and I got really ill with my mental health because of it, but I thought “Well, why am I going to talk to people when they don’t listen to me anyway?”- Selina . “I knew exactly what I was doing. I knew how I was going to do it. I just wanted it done. So I thought I have to tell him. I have to tell him. But I couldn’t tell him that I was off to kill myself.” – Simone .

‘Tired’ and ‘wired’

All but two respondents mentioned sleep deprivation as a major contributing factor to the accumulation of despair in the days or weeks before the suicide attempt. The sheer exhaustion they felt prevented them from thinking clearly or having the energy to face their circumstances and get better.

“My little boy slept really well from, gosh, about three weeks, maybe less than that, he would sleep through the night which was really, really lucky, but I couldn’t sleep and I think, yes, the problems of not sleeping had a snowball effect.” – Hannah .

This level of hypervigilance and restlessness was for many women the reason why they were unable to sleep. While women reported to feel exhausted on one hand, they also reported to experience an unhealthy level of drive, anger or arousal, leaving them ‘tired and wired’.

“I stopped sleeping entirely; I was so angry all the time – it’s all the textbook depression symptoms, but I was so angry all the time. I was so tired all the time, but just wired, couldn’t sleep.”- Sam . “I remember thinking I’m just so tired, I just want to go to sleep. I just want to be asleep and not be disturbed. But my mind was just so busy.” – Simone .

Some displayed agitated and manic behaviour to such an extent that they struggled to understand how this went unnoticed.

“I live three miles from the hospital and after they sent me home the next day, I walked back to the hospital with [the] kids and I was mowing the lawn five days after he was born and cleaning the house from top to bottom and driving all over the city after a [caesarean] section and you kind of just think like why did nobody notice? How can you think that that’s normal behaviour? Because I just felt this constant need, like I’ve got to be constantly doing things, constantly cleaning things, constantly walking places or doing things, alongside this absolute anger.” – Lauren .

The irreversibility of motherhood

A majority of respondents described they came to a very agonising realisation that they were unable to get out of being a mother and that they found themselves in an irreversible situation, with no going back. The feeling of being ‘stuck’ was so pervasive, that many expressed they wanted either the pregnancy to end, or to not wake up. The irreversibility of motherhood was surrounded by feelings of deep regret and an admission that this had been their own fault and responsibility.

“I remember actually hoping he would be stillborn towards the end, I think after the bridge. I just really wanted for him to be stillborn because if he was then it would all be over but it wouldn’t be my fault, and then I couldn’t go back. I think there was this constant sense of wanting to go back before any of it had happened and I just have my [older] children and I was working and I was happy and I kept seeking these ways just to go back and there weren’t any and I just got more and more desperate as time went on.” – Lauren .

Many respondents shared their conflicting emotions towards their baby, who they viewed as the cause of their distress on the one hand, and as the reason to stay alive on the other.

“[…] I simply could not do it anymore. Help, or don’t help. Whatever. I’m just not going to be around. And it’s almost like this feeling of, you want someone to take the baby off you, so that the baby’s not around, or that’s how I felt. The baby is your reason to stay alive, but the baby’s also the thing that’s causing you so much anguish. And that conflict is just so hard.” – Sam .

Women were desperate to get a grip on the situation, yet it all felt in vain, with no improvement in sight. An overwhelming feeling of hopelessness took over, leaving women with no light at the end of the tunnel and only one option: taking their own life.

“I don’t know how to explain it. I was feeling like all the things that I had to do were like water in my hands. I could see it. I could feel it. I could hold it. But it was coming through my fingers and I couldn’t do anything about it.” – Liv .

Our study identified three overarching themes, marking different phases during which women’s mental health gradually deteriorated. Whilst not all sub-themes under these themes were necessarily reported by every respondent, they paint a comprehensive picture of the distressing feelings and contributing factors that women experienced in the days and weeks prior to their suicide attempt. Nearly half of our sample undertook a suicide attempt during pregnancy. This is in line with evidence suggesting antepartum suicide attempts are an important complication of pregnancy [ 2 ] and act as a strong predictor for postnatal suicidal behaviour, including completed suicide [ 41 ]. In addition, participants in our sample whose suicide attempt occurred during the postnatal period reported suicidal ideation had started during pregnancy, making the antenatal period a critical period for both antenatal and postnatal suicide prevention.

Our first theme, ‘Trauma and adversities’, captures vulnerabilities prior to conception and during pregnancy and has two key elements: (1) psycho-social adversities, including grief and trauma and (2) having a family history of perinatal mental health difficulties. Women with previous mental health difficulties, in particular those with a history of depression and mood disorders, are known to have an increased risk of fatal and non-fatal perinatal suicide attempts [ 3 , 42 , 43 ]. In addition, previous adverse life events and abuse, especially when these occurred during childhood, [ 44 , 45 ], perinatal bereavement and infertility [ 46 ], comorbid substance use disorders and intimate partner violence [ 47 ], have also been associated with an increased risk of perinatal suicidal thoughts and suicidal behaviour. While the need for trauma-informed maternity services has become a public health priority [ 37 ], it is not always matched by a general awareness of the importance to raise these issues during pregnancy or the postnatal period [ 48 ]. This is reflected in our findings, where several of the respondents had experienced significant trauma and adverse life events prior to becoming pregnant but did not feel this was particularly relevant. Similarly, for some respondents a significant family history of perinatal mental health problems was unbeknown to them until their own mental health deteriorated. In contrast, those respondents who started pregnancy with an alertness of the risk of perinatal mental health problems in light of their own previous mental health difficulties or those of close relatives, reported to have prophylactic support measures in place, for instance by accessing a community perinatal mental health service during pregnancy. While this did not prevent their mental health from deteriorating, it did shorten the referral and escalation times when they reached a point of crisis. Having meaningful conversations about the prevalence of perinatal mental ill-health early on in pregnancy and undertaking a thorough assessment of mental health-related risk factors, such as previous mental health history, domestic abuse, substance misuse, previous trauma, among others, at every contact with maternity services is therefore essential to mitigate these pre-existing vulnerabilities [ 49 ].

In our second theme, ‘Disillusionment with Motherhood’, we identified a range of triggering factors that caused women’s mental health to decline. A first and often overlooked sub-theme that we identified was the impact of a physically and mentally challenging pregnancy and birth and their role in a subsequent mental health deterioration. This was often exacerbated when women received unkind, disrespectful care, which made them feel invisible. Whilst there are no studies to our knowledge that directly associate birth trauma with an increased risk of perinatal suicide, the association between birth trauma and postpartum post-traumatic stress disorder (PTSD) is well established [ 50 , 51 , 52 , 53 ]. Postpartum PTSD in turn is associated with poor coping and stress and highly co-morbid with depression [ 50 ]. Less evidence is available on the association between pregnancy and birth complications and perinatal suicide risk. One study found no association between maternal complications in pregnancy and during birth with hospitalisation for a suicide attempt [ 54 ]. Yet, as illustrated by our study sample, not all suicide attempts will result in an admission to a general hospital for medical treatment. Thus, further evidence is needed to understand the role of physical health complications, both during pregnancy, childbirth and the postnatal period, and their role in mood deterioration.

The subsequent sub-themes of ‘Invalidation of identify and self-sacrifice’ and ‘It wasn’t like starry-eyed love’ are closely intertwined and bring the complexity of women’s conflicting emotions towards motherhood to light [ 55 ]. The desire to be a good mother as a newly found identify often came to the detriment of their own personal self, with many women reporting situations of total self-sacrifice [ 56 ]. These daily struggles, of trying to be the perfect mother on the one hand, while trying to bond with their baby on the other hand, was in many cases fertile soil to start feeling obsolete as a person and feeling disillusioned in motherhood. Our findings build on previous work from Reid et al. (2022), who identified key factors in the context of a perinatal suicide attempt, such as a strained mother-infant bond, lack of social support, loneliness and hopelessness [ 44 ]. This resonates with our sub-themes of “Feeling like a failure”, “Alone in this world” and “Irreversibility of motherhood”. Our final theme “Entrapment and Despair” is in line with Reid et al. (2022)’s final phase, called ‘Darkness Descends’ [ 23 ] and is marked by pervasive feelings of hopelessness and failed motherhood. Under this theme, a turbulent accumulation of negative factors resulting in a fast deterioration of their mental health was reported by all respondents. These feelings of hopelessness and being totally entrapped were so all-encompassing, that participants felt no other way out than by attempting to take their own life. However, in this third stage, women did not just feel disillusioned, they felt totally incompetent as a mother, to a point they believed their baby and family would be better off without them. The finality of motherhood, with no way to turn back time or to escape their fate (‘Irreversibility of Motherhood’), drove them further to despair [ 55 ]. The MBRRACE-UK reports have repeatedly raised such feelings of incompetence as a mother and estrangement of the infant as a ‘red flag’ which should be taken seriously to prevent future maternal deaths by suicide [ 1 , 13 , 57 ].

Another factor we identified in this phase was the occurrence of intrusive thoughts and unsettling (psychotic) experiences, brought together in the subtheme ‘Intense intrusive thoughts and abnormal experiences’. The majority of our respondents reported abnormal experiences that were very unsettling to them. For some, these could be described as intrusive thoughts in the context of Obsessive Compulsive Disorder. Although intrusive thoughts are common among new parents, such experiences are often misunderstood, surrounded by stigma, and sometimes being misdiagnosed or over-normalised and dismissed, preventing timely and effective intervention [ 58 ]. For others in our sample, these experiences may have been delusions or hallucinations as part of a psychotic presentation. For all respondents who had them, the experiences were intense, frightening and difficult to understand at the time. Practitioner knowledge, sensitive risk assessment and careful diagnostic consideration about the nature and type of internal experiences is fundamental to appropriately treat women experiencing these upsetting experiences [ 59 ]. Yet equally important is increased public awareness on the occurrence and impact of such experiences, so women can seek timely support when they experience these frightening thoughts or delusions.

A third common factor we identified was sleep deprivation during pregnancy and the postnatal period and its profound impact on women’s mental health. Sleep disturbance is very common in relation to mental illness, and was highlighted in the most recent MBRRACE-UK report as marked and persistent in those women who died by suicide, even when treated with hypnotic medication [ 1 ]. A recent systematic review by Palagini et al. (2023) showed insomnia and poor sleep quality increased the odds of suicidal risk in pregnant and postpartum women by more than threefold, independently from psychiatric comorbidity [ 60 ]. Especially in a context of onset of psychotic illness, such as bipolar disorder, insomnia often precipitates other psychotic symptoms such as restlessness, irritability and rapid mood changes [ 61 ]. Unfortunately, as sleep loss is generally accepted as a common ‘side effect’ of pregnancy and having a newborn baby, its severity and potential devastating consequences are poorly understood and often minimised. Overall, the theme of ‘Entrapment and Despair’ captures the sheer hopelessness and inability to gain control over a rapidly escalating situation, in line with Klonsky and May’s Three-Step-Theory of suicide [ 62 ]. This theoretical model of suicide considers three steps to suicide. Being in pain and hopelessness leads to suicidal ideation (Step 1), which can be exacerbated by isolation or countered by connectedness (Step 2). The final step is marked by one’s capability of attempting suicide (Step 3). The pervasive feeling of hopelessness and lack of control gradually paved the way for a solid belief it would be better to no longer be here. Participants in our sample shared how they accepted this belief and waited for an opportunity to carry out their suicide plan. This combination of hopelessness and rejection of motherhood, a belief that death would be preferred and an opportunity to act on these thoughts has been previously theorised as a culmination of factors for perinatal suicide [ 23 ]. In line with findings from previous MBRRACE-UK reports, the vast majority of respondents in our sample turned to violent methods for suicide, such as jumping, hanging, suffocation, using sharp objects or stepping in front of traffic, reflecting the high level of distress women found themselves in and the determination with which they wanted to carry out their plan.

Strengths and limitation

Our study is the first to our knowledge to focus on suicide attempts during the perinatal period and offers a rich understanding of women’s experiences surrounding these highly distressing events. A strength of this study is the recruitment of participants across the UK, rather than one geographical area, with diversity in the sample regarding age, parity, psychiatric morbidity, social support, educational attainment and socio-economic status. Significant efforts were made to recruit women from diverse ethnic, cultural, and religious backgrounds, through invitations and meetings with community leaders and designated support groups. Despite our efforts, we did not achieve diversity regarding ethnic and cultural background, one of the limitations of this study. Ethnicity data from the latest MBRRCACE-UK report showed that women who died by suicide were predominately white (86%), with no further ethnicity details on the remaining 14% [ 1 ]. As a result, although this was never our intention, we are aware our study findings are focusing on the experiences of White women in the UK and not transferrable to an ethnically and culturally more diverse sample, or to other countries across the globe. In addition, our sample consisted predominantly of participants with higher educational qualification, in positions of employment. Therefore, our analysis was unable to explore the impact of poverty on women’s suicidality, which is known to be an important driver of poor (perinatal) mental health [ 63 , 64 ]. We are aware a more ethnically, culturally, religiously and socio-economically heterogenous sample is likely to represent a diversity of perspectives, highlighting these issues. Another limitation was the design of the demographic survey, which did not specifically differentiate between mental health diagnosis given during the life course or specifically at the time of the suicide attempt. Suicide research, especially in a perinatal context, is notorious for its recruitment challenges. Saturation for all themes and sub-themes was achieved well within the available sample and is one of the strengths of this study. Another strength of our study is the sensitivity and rigour of patient and public involvement throughout the various phases of the study. This was crucial to do justice to the courage which participants had shown by sharing their stories and to keep respondents safe throughout their research participation.

Implications for clinical practice and care and future research

Our study highlights the importance of routine inquiry of previous mental health difficulties and family history of perinatal mental health problems at the first encounter during pregnancy. Yet, such an assessment needs to be more comprehensive than a tick-box exercise and should be accompanied by a personalised conversation about prevalence of perinatal mental health problems and potential triggers, including trauma and grief. Professionals should be given adequate time during antenatal encounters to explore this in depth and, where required, receive additional training in perinatal mental health to build confidence in doing so. The perinatal period is often described as a ‘window of opportunity’, but this goes both ways: While every encounter creates opportunity for screening, detection and support, it also has the potential for invoking or deepening trauma. Our study revealed the devastating and long-lasting impact of unkind, careless and dismissive remarks by healthcare professionals on women’s mental health, thus instilling a feeling of failure by throw-away comments that would ripple on weeks and months after they were uttered. Perinatal healthcare professionals need to understand the weight of their words, how they can provide hope when women are struggling, but equally how they can push women further into isolation and despair. Culturally aware and trauma-informed clinical practice is essential to achieve this, whilst also recognising the impact of burn-out and carer’s fatigue in an overstretched and under-resourced healthcare service. Healthcare professionals need to be cautious about the difference between normalising and dismissing distressing feelings. In addition, professionals need to fully understand the profound impact of physical, social and psychological risk factors as identified by our study. The physical and mental challenge of pregnancy and childbirth, often in combination with a traumatic birth experience should not be underestimated. An impaired mother-infant dyad, feelings of resentment of motherhood, and the discrepancy between women’s expectations and their lived reality are all key triggers that should be discussed, identified and addressed at the earliest opportunity, in a non-judgemental and sensitive way to avoid further escalation. Women need to be validated and reassured by professionals when disclosing these feelings, and be informed that support is available to help them transition into motherhood. Continuity of care throughout the perinatal period, if done with sensitivity and person-centredness, can foster trusting relationship so women feel safe and supported to disclose distressing feelings. Similarly, insomnia and sleep disturbance, albeit in combination with restlessness and irritability, intrusive thoughts and feelings of lack of control and failure are red flags for severe and rapid mental health deterioration that required prompt and effective action. More than anything, women need to feel safe and listened to, so they can share their feelings with healthcare professionals without fear of judgement, shame and stigma. Our study showed that women will often retreat into silence prior to a suicide attempt and in that moment more than ever rely on attentive, educated and compassionate support networks to avoid a suicide attempt.

Future research into perinatal suicide attempt should focus on developing effective preventative interventions and public health strategies, both in an antenatal and postnatal context, with their distinct healthcare professionals’ involvement and resource challenges. By using implementation science methods, these interventions should be tested and evaluated on their efficacy and effectiveness, in order to reduce future maternal suicides.

This study is the first UK-based qualitative study looking at suicide attempts during the perinatal period. Our findings identified three themes with several contributing factors which led women to undertake a suicide attempt. It is important to understand the impact of previous trauma and life adversity when going through pregnancy and the postnatal period. Feelings of disillusionment with motherhood and feeling entrapped in a hopeless situation were key phases women experienced in the lead-up to their suicide attempt. Our study findings have important implications for clinical practice and healthcare professionals should be aware of warning signs, to improve timely detection and facilitate meaningful inquiry, in order to improve care and prevent future maternal suicide deaths.

Data availability

The datasets generated and analysed during the current study are not publicly available due to the privacy of the participants in the study and the sensitive nature of the data. Further inquiries can be directed to the corresponding author ([email protected]).

We acknowledge not all people who give birth and go through the perinatal period identity as women, female or mothers. While this paper utilises predominantly the terms women and mothers, we aim to include also those who identify as transgender, non-binary or any other gender identity.

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Acknowledgements

We would like to thank all the women and birthing people who took part in this study, for their time, their bravery and the honesty with which they shared their story. Their commitment to improve care for others who find themselves in a similar position was a privilege to witness. We thank Dr Clare Dolman, the Patient Advisory Group at the Section for Women’s Mental Health at King’s College London, the South London Applied Research Collaboration Maternity and Perinatal Mental Health theme Patient and Public Involvement and Engagement group for their suggestions and feedback throughout the different stages of this study. We also like to thank the third sector partners that were closely involved in the study journey, such as Maternal Mental Health Alliance, Mothers for Mothers, the Institute of Health Visiting, the Motherhood Group, REFORM, National Childbirth Trust (NCT), and Maternity Action.

This work was supported by the National Institute for Health and Care Research (NIHR) South London Applied Research Collaboration (NIHR200152). Patient and public involvement engagement activities undertaken for this study were funded through a King’s Engaged Research Network (KERN) Public Engagement Small Grant Award. Kaat De Backer, Sergio A. Silverio, Professor Jane Sandall and Dr Abigail Easter are supported by the NIHR Applied Research Collaboration South London (NIHR ARC South London) at King’s College Hospital NHS Foundation Trust. Kaat De Backer (King’s College London) is also in receipt of an NIHR Doctoral Research Fellowship (NIHR302565). Sergio A. Silverio (King’s College London) is currently in receipt of a Personal Doctoral Fellowship from the NIHR ARC South London Capacity Building Theme [NIHR-INF-2170]. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

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Alexandra Pali

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AE, LMH, JS, RH, KDB conceived the work and designed the study. SAS and MN contributed to the development of the design. MN led the Public and Patient Involvement and Engagement. KDB, AP, AE, FLC contributed to data acquisition. KDB, AP, AE, FLC interpreted the data. KDB drafted the manuscript and incorporated revisions from all other authors. All authors read and approved the final manuscript.

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Ethical approvals were sought and granted by the King’s College London Health Faculties Research Ethics Committee, in January 2021 (reference HR-20/21-20092), with a further amendment in June 2022, after further feedback from the advisory panel and stakeholder meeting (reference MOD-21/22-20092). The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.

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De Backer, K., Pali, A., Challacombe, F.L. et al. Women’s experiences of attempted suicide in the perinatal period (ASPEN-study) – a qualitative study. BMC Psychiatry 24 , 255 (2024). https://doi.org/10.1186/s12888-024-05686-3

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Correction: Improving the Engagement of Underrepresented People in Health Research Through Equity-Centered Design Thinking: Qualitative Study and Process Evaluation for the Development of the Grounding Health Research in Design Toolkit

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• Alessandra N Bazzano 1 , MPH, PhD   ; 
• Lesley-Ann Noel 2 , PhD   ; 
• Tejal Patel 1 , MA   ; 
• C Chantel Dominique 3 , AA   ; 
• Catherine Haywood 4 , BSW   ; 
• Shenitta Moore 5 , MD   ; 
• Andrea Mantsios 6 , PhD   ; 
• Patricia A Davis 1 , BSc  

1 Department of Social, Behavioral, and Population Sciences, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States

2 College of Design, North Carolina State University, Raleigh, NC, United States

3 Global Impact Board, New Orleans, LA, United States

4 Louisiana Community Health Outreach Network, New Orleans, LA, United States

5 Louisiana State University Health Sciences Center, New Orleans, LA, United States

6 Public Health Innovation & Action, New York, NY, United States

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In “Improving the Engagement of Underrepresented People in Health Research Through Equity-Centered Design Thinking: Qualitative Study and Process Evaluation for the Development of the Grounding Health Research in Design Toolkit” (JMIR Form Res 2023;7:e43101) the authors noted one error.

In Reference 28, the URL:

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This is a non–peer-reviewed article. submitted 14.03.24; accepted 14.03.24; published 04.04.24.

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• http://orcid.org/0000-0002-8761-2055 Rodwell Gundo ,
• Mavis Fhumulani Mulaudzi
• Department of Nursing Science , University of Pretoria , Pretoria , South Africa
• Correspondence to Dr Rodwell Gundo; rodwell.gundo{at}up.ac.za

Introduction Nurses are essential for implementing evidence-based practices to improve patient outcomes. Unfortunately, nurses lack knowledge about research and do not always understand research terminology. This study aims to develop an in-service training programme for health research for nurses and midwives in the Tshwane district of South Africa.

Methods and analysis This protocol outlines a codesign study guided by the five stages of design thinking proposed by the Hasso-Plattner Institute of Design at Stanford University. The participants will include nurses and midwives at two hospitals in the Tshwane district, Gauteng Province. The five stages will be implemented in three phases: Phase 1: Stage 1—empathise and Stage 2—define. Exploratory sequential mixed methods including focus group discussions with nurses and midwives (n=40), face-to-face interviews (n=6), and surveys (n=330), will be used in this phase. Phase 2: Stage 3—ideate and Stage 4—prototype. A team of research experts (n=5), nurses and midwives (n=20) will develop the training programme based on the identified learning needs. Phase 3: Stage 5—test. The programme will be delivered to clinical nurses and midwives (n=41). The training programme will be evaluated through pretraining and post-training surveys and face-to-face interviews (n=4) following training. SPSS V.29 will be used for quantitative analysis, and content analysis will be used to analyse qualitative data.

Ethics and dissemination The protocol was approved by the Faculty of Health Sciences Research Ethics Committee of the University of Pretoria (reference number 123/2023). The protocol is also registered with the National Health Research Database in South Africa (reference number GP_202305_032). The study findings will be disseminated through conference presentations and publications in peer-reviewed journals.

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STRENGTHS AND LIMITATIONS OF THIS STUDY

This study will be strengthened through the use of quantitative and qualitative methods to understand the research problem.

The inclusion of two hospitals and the participation of different nurses and midwives will ensure the credibility of the findings.

Local research experts, nurses and midwives will collaborate to develop a training programme appropriate to the context of the setting.

The findings will be limited to two hospitals; therefore, the findings may not be generalisable to other hospitals.

Introduction

Evidence-based practice (EBP) has gained prominence in health services internationally over the past three decades. 1 EBP integrates individual clinical expertise with clinical evidence generated from systematic research. 2 EBP aims to deliver appropriate, efficient patient care. 3 Consequently, generating evidence that informs care delivery has become increasingly important for improving patient-centred care, patient safety, patient outcomes and the healthcare system. 1 3 In healthcare, nurses are well positioned to implement EBP because they constitute the largest proportion of the health workforce. 1 4 Nurses thus have to be proactive in acquiring, synthesising and using research knowledge and the best evidence to inform their practice and decision-making. 3 4

Recognising the need for EBP, many nursing organisations worldwide have developed best practice guidelines for patient-care decision-making. 4 In South Africa, the roadmap for strengthening nursing and midwifery acknowledges that nurses are vital for providing safe and effective patient care. Strategically, investing in nurse-led research will help develop nurse-led models of care. 5 Similarly, the South African Nursing Council expects nurses to actively participate in research activities, including academic writing, reading and reviewing, as part of continuing professional development. 6 Training nurses and midwives can enhance their research capacity and enable them to use available resources for research, ultimately leading to changes in EBP in clinical settings.

Nurses need to gain research knowledge and become comfortable with research terminology. 7 8 Although undergraduate nursing training includes a research component, this training does not always translate into a strong understanding of research. 7 As such, there needs to be more nurse-led patient-centred research. A recent review of nursing research from 2000 to 2019 showed that most nursing research is conducted by nurses working at higher education institutions. Research output and collaboration are also disproportionately more prominent in high-income countries across North America, Europe, and Oceania than in low-income and middle-income countries. 9 The other challenges that affect health research include limited time, lack of research facilities, research culture, mentors, access to mentors, and workforce capacity. 10

Little is known about the research literacy of nurses and midwives and research training programmes for practicing nurses and midwives in South Africa. Therefore, we developed a protocol to develop a research training programme for nurses and midwives in the Tshwane district of South Africa. This protocol is guided by the following research questions: (a) what are the levels of nurses’ and midwives’ knowledge, attitudes and involvement in research?; (b) what are the learning needs of nurses and midwives regarding research design and implementation?; (c) what content should be included in a research training programme for nurses and midwives?; (d) how does the developed training programme impact nurses’ knowledge about research?

Theoretical framework

The principles of constructivism learning theory will guide this study. This theory is rooted in the work of Piaget and Vygotsky. 11 This paradigm explains how people might acquire and retain knowledge. 12 Through the lens of constructivism learning theory, adult educators acknowledge learners’ previous experiences, appreciate multiple perspectives and embed learning in social contexts. The instructor is a mentor who helps learners understand new information. Constructivism learning theory has three dimensions, namely, individual constructivism, social constructivism and contextualism. In individual constructivism, learners are self-directed and construct knowledge via personal experience. Social constructivism assumes that learning is socially mediated, and that knowledge is constructed through social interaction. In contextualism, learning should be tied to real-life contexts. 13 Some benefits of constructivism theory are that learners enjoy learning because they are actively engaged and have ownership over what they learn. 12 The theory was considered appropriate because the study will be conducted at two research-intensive hospitals. Therefore, nurses and midwives are familiar with the research process.

Methods and analysis

Research design.

We will use a codesign approach guided by the stages of design thinking proposed by the Hasso-Plattner Institute of Design at Stanford University. 14 15 The design originated from participatory research and involves active engagement of the participants to identify needs and collaboratively propose solutions. 14 16 The approach is considered appropriate because it ensures meaningful involvement of end-users, thereby creating meaningful benefits. 17 A codesign approach ensures fewer challenges when implementing the initiative because stakeholders are fully engaged throughout the process. 14 Underpinned by the African philosophy of Ubuntu, the process will promote the culture of working together and collective solidarity. 18

The study will be guided by the five stages of design thinking: empathise, define, ideate, prototype and test. Empathise aims to understand the deeper issues, needs and challenges needed to solve the problem. Define involves data analysis and prioritising the needs of the end users of the training programme. Ideate includes brainstorming for innovative solutions to address the identified needs. In the prototype stage, the idea or innovation is shown to the end users and other stakeholders. Finally, testing involves checking what works in a real-world setting. 14 15

Study setting

The study will be conducted at two public hospitals in the Tshwane district of Gauteng Province in South Africa. The province has the highest population density, the most hospitals and the greatest number of nurses and midwives. 19 According to a 2016 community survey, Gauteng has a population of 13.4 million people. 20 Tshwane is one of the five districts in the province and the third most populous district, accounting for 24% of the population in the province. 21 There are three district hospitals, namely, Tshwane, Pretoria West, Jubilee and ODI; one regional hospital, Mamelodi; and three tertiary hospitals, namely, Steve Biko Academic Hospital, Dr George Mukhari Hospital and Khalafong Hospital. The two hospitals were selected due to their proximity to the University of Pretoria. One of the hospitals is a tertiary hospital with 800 beds. The second hospital is a 240-bed district hospital linked to the University of Pretoria’s Faculty of Health Sciences. 22

Target population

The population will comprise nurses and midwives working at the two hospitals. In South Africa, there are six categories of nurses and midwives based on qualifications as follows: registered auxiliary nurse (higher certificate), registered general nurse (diploma in nursing), registered midwife (advanced diploma), registered professional nurse and midwife (bachelor’s degree), nurse specialist or midwife specialist (postgraduate diploma), advanced specialist nurse (master’s degree) and those with doctorate degrees. 5 Nurses working at academic hospitals are expected to engage in research activities, including academic writing, reading and reviewing, as part of continuing professional development. 6 A preliminary audit revealed 1900 nurses and midwives working at the two hospitals.

Inclusion and exclusion criteria

Participation will be limited to registered auxiliary nurses, registered general nurses, registered midwives, registered professional nurses and midwives older than 18 years, those registered with the South African Nursing Council, and those with more than 3 months of experience. All people older than 18 years are mandated to give legal consent in South Africa. Nurses with less than 3 months of experience or undergoing orientation will be excluded from the study.

As illustrated in table 1 , the study will be implemented in three phases and five stages to address the four objectives. Stage 1 is currently underway. The collection of the qualitative data started in December 2023 at one of the two hospitals. This will proceed at the second hospital until April 2024. The whole study is expected to be completed by September 2024.

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Illustration of the research process guided by the stages of design thinking

In this phase, we aim to understand the nurses’ and midwives’ perceived knowledge, attitudes and involvement in research and their learning needs. We will base our investigation on empathising and defining. An exploratory sequential mixed methods design will be used. This design begins with collecting and analysing qualitative data. The qualitative findings are used to develop quantitative measures or instruments to test the identified variables. 23 In this study, the qualitative findings will be used to revise a questionnaire for the subsequent quantitative strand.

Strand 1—qualitative study

Qualitative methods are appropriate for investigating the who, what and where of events or experiences of informants of a poorly understood phenomenon. 24 25

Sample size and sampling

Forty-six participants (n=46) will be selected from nurses and midwives working at the two hospitals. The sample size was pragmatically determined according to the mode of data collection and the volume of data to be collected. However, the final sample size will be determined by data saturation.

We will purposively sample nurses and midwives from the following cadres: registered auxiliary nurses, registered general nurses, registered midwives, and registered professional nurses and midwives. As presented in table 2 , two focus group discussions (FGDs) will be held at each hospital and will involve 10 participants each. Due to power differences that can cause a halo effect among the participants, 26 one FGD will include senior professional nurses and midwives. In contrast, the other FDG will include junior nurses and midwives with either diplomas or certificates. For the individual interviews, three participants (one registered auxiliary nurse, one registered general nurse with a diploma and one professional nurse (with either a bachelor’s or postgraduate qualification)) will be invited to participate. The participants will be expected to share their knowledge of the competencies needed for conducting health research.

Sampling plan for the qualitative strand

Data collection

The study information will be communicated through nursing and midwifery managers. Participation will be voluntary. Nurses and midwives willing to participate will be invited for either FGDs or individual interviews. The participants will be given the details of the study and a consent form. The interviews will be conducted in English in hospitals in private settings at times and places that are most convenient for participants. The participants will be requested to use pseudonyms during interviews. A semistructured interview guide will be used for the interviews (refer to online supplemental file 1 ). The interviews will be audiotaped and later transcribed verbatim in English.

Supplemental material

Data analysis.

The data will be analysed manually using conventional content analysis as described by Hsieh and Shannon. 27 The steps of the analysis will be as follows: (a) repeatedly reading the data to achieve immersion and a sense of the whole; (b) deriving and labelling codes by highlighting the words that capture critical thoughts and concepts; (c) sorting the related codes into categories; (d) organising numerous subcategories into fewer categories; (e) defining each category; and (f) identifying the relationship of the categories in terms of their concurrence, antecedents or consequences. To ensure the reliability of the qualitative coding, tHead2he two researchers will code the first transcript independently. The online Coding Analysis Toolkits 28 will be used to calculate intercoder reliability. The two researchers will discuss differences and agree on the coding before proceeding to the next transcript.

Methodological rigour

Trustworthiness will be achieved through credibility, transferability, dependability and confirmability. 24 29 Credibility will be achieved through spatial and personal triangulation. Spatial triangulation refers to collecting data on the same phenomenon from multiple sites, while personal triangulation refers to collecting data from different types and levels of people. 29 This study will collect data from different cadres of nurses and midwives at two hospitals. Transferability will be enhanced by providing sufficient study details. Dependability and confirmability will be achieved by establishing an audit trail describing the procedures and processes. Additionally, reflexivity will be used to ensure the transparency and quality of the study. 29 30 Reflexivity is where researchers critique, appraise and evaluate the influence of subjectivity and context on the research process. 30 In some branches of qualitative inquiries, researchers use reflexive bracketing to prevent subjective influences. However, Olmos-Vega et al 30 observed that this approach is no longer favoured in modern qualitative research because setting aside certain aspects of subjectivity is problematic. In this study, reflexivity will be ensured by keeping memos and field notes to document interpersonal dynamics and critical decisions made throughout the study.

Strand 2—quantitative study

A cross-sectional survey will be used to assess nurses’ and midwives’ perceived knowledge, attitudes and involvement in research.

The sample size was calculated using Yamane’s formula 31 as follows: n=N/(1+N(e2), where n is the sample, N is the population size, and e is the level of precision. Assuming a 95% CI and the estimated proportion of an attribute p=0.5, the calculated sample size for a population N=1900 with ±5% precision is 330. In this study, a convenience sampling technique will be used to select participants.

The researchers will brief nurse managers about the study. Furthermore, posters inviting nurses and midwives to participate in the study will be placed in each department. The poster will include details of the study and relevant contact details. The nurses and midwives willing to participate will be given an information sheet, consent form and questionnaire. They will be requested to leave the completed questionnaire in a designated box in the unit manager’s office.

Data collection instrument

The data will be collected using the Edmonton Research Orientation Survey (EROS). The EROS was developed in Canada and is a valid and reliable self-reported instrument for measuring perceived knowledge, attitudes and involvement in research. The tool has four subscales with 43 items. The four subscales are the value of research, value of innovation, research involvement and research utilisation (EBP). Valuing research is a positive attitude towards research; the value of innovation refers to being on the leading edge or keeping up to date with information; research involvement relates to active participation in research; and research utilisation (EBP) pertains to whether respondents use research to guide their day-to-day practice. Additionally, there is a category for the barriers and support for research. 32–34

The EROS items are measured using a 5-point Likert scale ranging from 1—strongly disagree to 5—strongly agree. The maximum score is 215. Higher overall scores indicate a stronger research orientation. The scores will be categorised into high (between 143 and 215 points), medium (73–142 points) or low (0–72 points). 32 33 The tool has been extensively used to assess the research orientation of health professionals, including physiotherapists, 35 midwives, 36 occupational therapists, 33 academics 32 and undergraduate students. 34 Previous studies reported high internal reliability with Cronbach’s alpha coefficients of 0.95 37 and 0.92. 34

Although the tool has been previously used among South African occupational therapists, 33 the copyright author observed that the tool had been developed at a time when there was no access to information via the internet, hence the need to find ways of incorporating such issues. This study will use qualitative findings to identify items not included in the tool but relevant to the South African context.

The quantitative data will be entered into Microsoft Excel and imported to IBM SPSS statistics V.29. Descriptive statistics will be used to summarise demographic characteristics and questionnaire scores. Mean scores and SD will be calculated for individual items, subgroup scores and overall scores. Independent sample t-tests, Mann-Whitney U tests, and multiple regression will be used to compare the scores of different groups of nurses and midwives. The assumptions for each test will be assessed before analysis. The level of significance will be set at 0.05.

During this phase, we will develop the training programme based on the learning needs identified in Phase 1. Research experts (n=5) will participate in a one-design studio workshop to brainstorm the content to be included in the training programme. Although there is limited literature on the definition and characteristics of an expert, Bruce et al 38 defined an expert as a person who is knowledgeable or informed in a particular discipline. Bruce et al 38 further observed that maximum variation or heterogeneity in sampling experts yields rich information. This study will select experts based on the criteria proposed by Davis 39 and Rubio et al . 40 The characteristics include clinical experience in the setting, professional certification in a related area, research experience, work experience, conference presentation and publication in the topic area.

A design studio workshop is a process in which participants create, and critique proposed interventions. 16 The researcher will share the findings of Phase 1 and explain the workshop’s goal to the participants. Participants will be provided with pens, sticky notes and flip-chart paper. The researcher will facilitate discussion and capture feedback. At the end of the workshop, the researcher will consolidate the ideas, create a more detailed programme design and communicate with the participants.

Next, we will develop a prototype to be discussed in a consultative meeting and validation meeting. An iterative process will be used to validate the developed training programme. The consultative meeting will be held with research experts (n=5). A validation exercise will also be conducted with nurses and midwives (n=20), the programme’s end-users. The nurses and midwives will be identified in consultation with nurse managers at the two hospitals to avoid disruption of services. During the validation exercise, the participants will be grouped into smaller idea groups to review and discuss the developed programme. Each group will be requested to identify a representative to report on behalf of the group. The feedback from the consultative and validation meeting will help to improve the developed programme.

The purpose of this phase is to assess the impact of the developed training programme. The developed training will be delivered to 41 nurses and midwives in the Tshwane district. The sample is based on similar studies that have implemented interventions for health professionals. For example, a study by Gundo et al 41 used G-Power software 42 to calculate the sample size based on a conservative effect size of d=0.5, a power of 80% and an alpha=0.05. The calculated sample size was 34, but 41 participants were invited to participate in training to allow for a dropout rate of at most 20%. The identification and invitation of the participants will be negotiated with nurse managers at the two hospitals to avoid service disruptions. The selection process will ensure the representation of the different cadres of nurses and midwives. We will invite a team of research experts to facilitate the training. The impact of the training will be assessed by comparing pre-survey and post-survey EROS scores, FGDs with participants, and evaluations at the end of the training. A paired-sample t-test will be used to compare the pretest and post-test scores.

This protocol aims to develop a research training programme for nurses and midwives in the Tshwane district of South Africa. Initially, we will investigate the learning needs of nurses and midwives. The learning needs will inform a training programme to improve research capacity. As observed by Hines et al , 7 implementing a training programme will improve nurses’ research knowledge, critical appraisal ability and research efficacy. Building capacity for health research in Africa will enhance the ownership of research activities that target relevant topics.

Furthermore, findings relevant to local populations will be communicated in a culturally acceptable manner. Research recommendations may also resonate better and have a better uptake among African policymakers than research produced by internationally led teams. 43–45 This research training programme could be used in other hospitals with similar contexts and other categories of healthcare professionals. However, this will require a larger, multicentre validation study. Our findings will be limited to the two hospitals; therefore, the findings may not be generalisable to other hospitals.

Ethics and dissemination

The protocol was approved by the Research Ethics Committee, Faculty of Health Sciences at the University of Pretoria (reference number: 123/2023). The protocol is registered with the National Health Research Database in South Africa (reference number GP_202305_032). The two hospitals also provided permission for the study. Permission to use the EROS was obtained from the copyright authors, Dr Kerrie Pain and Dr Paul Hagler.

The participants will receive an information leaflet and be required to provide written informed consent. The researcher will ensure that the participants’ personal information is anonymised. Participants can give the researcher written permission to share their personal information. During the FGDs and individual interviews in Phase 1, the participants will be asked to use pseudonyms of their choice. In Phases 2 and 3, anonymity will not be possible because the meetings will be in person. However, the participants will be requested to maintain confidentiality. The data will be stored in compliance with the research ethics committee’s guidelines. The findings of the study will be disseminated through conference presentations and publications in peer-reviewed journals. The preparation of this manuscript followed the standards for reporting qualitative research 46 and the guidelines for reporting observational studies. 47

Ethics statements

Patient consent for publication.

Not applicable.

Acknowledgments

The manuscript was written during a writing retreat that was funded by the National Research Foundation through the Ubuntu Community Model of Nursing Project at the University of Pretoria in South Africa. We also thank Dr Cheryl Tosh for editing the manuscript.

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Contributors RG and MFM conceptualised the study, developed the proposal, drafted and revised the manuscript.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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