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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.

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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how to write research design for qualitative research

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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Knowledge Base
Methodology

Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

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

Your overall aims and approach
The type of research design you’ll use
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 aims and that you use the right kind of analysis for your data.

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.

Prevent plagiarism, run a free check.

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, while 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 ).

Types of qualitative research designs

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 analysing 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, organisations, 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 generalise 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.

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 generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

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, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, 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 data collection methods they used.

Secondary data

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

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

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

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

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

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

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation 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.

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 bias and ensure a representative sample?

Data management

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

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

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

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

Quantitative data analysis

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

Using descriptive statistics , you can summarise 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

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

There are many other ways of analysing 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.

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.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation 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, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

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

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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

McCombes, S. (2023, March 20). Research Design | Step-by-Step Guide with Examples. Scribbr. Retrieved 2 April 2024, from https://www.scribbr.co.uk/research-methods/research-design/

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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.

Purpose types: Basic Research, Applied Research, Summative Evaluation, Formative Evaluation, Action Research

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.

Uncomplicated Reviews of Educational Research Methods

Qualitative Research Design

.pdf version of this page

This review provides an overview of qualitative methods and designs using examples of research. Note that qualitative researchers frequently employ several methods in a single study.

Basic Qualitative Research Characteristics

Design is generally based on a social constructivism perspective.
Research problems become research questions based on prior research experience.
Sample sizes can be as small as one.
Data collection involves interview, observation, and/or archival (content) data.
Interpretation is based on a combination of researcher perspective and data collected.
Transcribing is the process of converting audio or video data to text for analysis.
Coding is the process of reviewing notes and discovering common “themes.”
Themes describe the patterns/phenomenon as results.

Overview of Methods

1. Interview (Individual, focus groups)

What is the difference between an interview and a survey? Primarily, open-ended questions differentiate the two. Qualitative researchers are concerned with making inference based on perspective, so it is extremely important to get as much data as possible for later analysis. Researchers spend a considerable amount of time designing interview questions. Interviews are designed to generate participant perspectives about ideas, opinions, and experiences.

2. Observation (Individual, group, location)

How is data derived from an observation? The researcher may use a variety of methods for observing, including taking general notes, using checklists, or time-and-motion logs. The considerable time it takes for even a short observation deters many researchers from using this method. Also, the researcher risks his or her interpretation when taking notes, which is accepted by qualitative researchers, but meets resistance from post-positivists . Observations are designed to generate data on activities and behaviors, and are generally more focused on setting than other methods.

3. Document Analysis (Content analysis of written data)

What types of documents do qualitative researchers analyze? Virtually anything that supports the question asked. Print media has long been a staple data source for qualitative researchers, but electronic media (email, blogs, user Web pages, and even social network profiles) have extended the data qualitative researchers can collect and analyze. The greatest challenge offered by document analysis can be sifting through all of the data to make general observations.

A Few Qualitative Research Designs

1. Biographical Study

A biographical study is often the first design type that comes to mind for most people. For example, consider O’Brien’s John F. Kennedy: A Biography . The author takes a collection of archival documents (interviews, speeches, and other writings) and various media (pictures, audio, and video footage) to present a comprehensive story of JFK. In the general sense, a biographical study is considered an exhaustive account of a life experience; however, just as some studies are limited to single aspects of a phenomenon, the focus of a biographical study can be much narrower. The film Madame Curie is an example. Crawford studies the film from a biographical perspective to present the reader with an examination of how all aspects of a film (director’s perspective, actors, camera angles, historical setting) work to present a biography. Read the introduction and scan the text to get a feel for this perspective.

2. Phenomenology

Your first step should be to take this word apart – phenomenon refers to an occurrence or experience, logical refers to a path toward understanding. So, we have a occurrence and a path (let’s go with an individual’s experience), which leads to a way of looking at the phenomenon from an individual’s point of view. The reactions, perceptions, and feelings of an individual (or group of individuals) as she/he experienced an event are principally important to the phenomenologist looking to understand an event beyond purely quantitative details. Gaston-Gayles, et al.’s (2005) look at how the civil rights era changed the role of college administrators is a good example. The authors interview men and women who were administrators during that time to identify how the profession changed as a result.

3. Grounded Theory

In a grounded theory study, interpretations are continually derived from raw data. A keyword to remember is emergent . The story emerges from the data. Often, researchers will begin with a broad topic, then use qualitative methods to gather information that defines (or further refines) a research question. For example, a teacher might want to know what effects the implementation of a dress code might have on discipline. Instead of formulating specific questions, a grounded theorist would begin by interviewing students, parents, and/or teachers, and perhaps asking students to write an essay about their thoughts on a dress code. The researcher would then follow the process of developing themes from reading the text by coding specific examples (using a highlighter, maybe) of where respondents mentioned common things. Resistance might be a common pattern emerging from the text, which may then become a topic for further analysis.

A grounded theory study is dynamic, in that it can be continually revised throughout nearly all phases of the study. You can imagine that this would frustrate a quantitative researcher. However, remember that perspective is centrally important to the qualitative researcher. While the end result of a grounded theory study is to generate some broad themes, the researcher is not making an attempt to generalize the study in the same, objective way characteristic of quantitative research. Here is a link to a grounded theory article on student leadership .

4. Ethnography

Those with sociology or anthropology backgrounds will be most familiar with this design. Ethnography focuses on meaning, largely through direct field observation. Researchers generally (though not always) become part of a culture that they wish to study, then present a picture of that culture through the “eyes” of its members. One of the most famous ethnographers is Jane Goodall, who studied chimpanzees by living among them in their native East African habitat.

5. Case Study

A case study is an in-depth analysis of people, events, and relationships, bounded by some unifying factor. An example is principal leadership in middle schools. Important aspects include not only the principal’s behaviors and views on leadership, but also the perceptions of those who interact with her/him, the context of the school, outside constituents, comparison to other principals, and other quantitative “variables.” Often, you may see a case study labeled “ethnographic case study” which generally refers to a more comprehensive study focused on a person or group of people, as the above example.

Case studies do not have to be people-focused, however, as a case study to look at a program might be conducted to see how it accomplishes its intended outcomes. For example, the Department of Education might conduct a case study on a curricular implementation in a school district – examining how new curriculum moves from development to implementation to outcomes at each level of interaction (developer, school leadership, teacher, student).

How to Write a Research Design – Guide with Examples

Published by Alaxendra Bets at August 14th, 2021 , Revised On October 3, 2023

A research design is a structure that combines different components of research. It involves the use of different data collection and data analysis techniques logically to answer the research questions .

It would be best to make some decisions about addressing the research questions adequately before starting the research process, which is achieved with the help of the research design.

Below are the key aspects of the decision-making process:

Data type required for research
Research resources
Participants required for research
Hypothesis based upon research question(s)
Data analysis methodologies
Variables (Independent, dependent, and confounding)
The location and timescale for conducting the data
The time period required for research

The research design provides the strategy of investigation for your project. Furthermore, it defines the parameters and criteria to compile the data to evaluate results and conclude.

Your project’s validity depends on the data collection and interpretation techniques. A strong research design reflects a strong dissertation , scientific paper, or research proposal .

Step 1: Establish Priorities for Research Design

Before conducting any research study, you must address an important question: “how to create a research design.”

The research design depends on the researcher’s priorities and choices because every research has different priorities. For a complex research study involving multiple methods, you may choose to have more than one research design.

Multimethodology or multimethod research includes using more than one data collection method or research in a research study or set of related studies.

If one research design is weak in one area, then another research design can cover that weakness. For instance, a dissertation analyzing different situations or cases will have more than one research design.

For example:

Experimental research involves experimental investigation and laboratory experience, but it does not accurately investigate the real world.
Quantitative research is good for the statistical part of the project, but it may not provide an in-depth understanding of the topic .
Also, correlational research will not provide experimental results because it is a technique that assesses the statistical relationship between two variables.

While scientific considerations are a fundamental aspect of the research design, It is equally important that the researcher think practically before deciding on its structure. Here are some questions that you should think of;

Do you have enough time to gather data and complete the write-up?
Will you be able to collect the necessary data by interviewing a specific person or visiting a specific location?
Do you have in-depth knowledge about the different statistical analysis and data collection techniques to address the research questions or test the hypothesis ?

If you think that the chosen research design cannot answer the research questions properly, you can refine your research questions to gain better insight.

Step 2: Data Type you Need for Research

Decide on the type of data you need for your research. The type of data you need to collect depends on your research questions or research hypothesis. Two types of research data can be used to answer the research questions:

Primary Data Vs. Secondary Data

Qualitative vs. quantitative data.

Also, see; Research methods, design, and analysis .

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Step 3: Data Collection Techniques

Once you have selected the type of research to answer your research question, you need to decide where and how to collect the data.

It is time to determine your research method to address the research problem . Research methods involve procedures, techniques, materials, and tools used for the study.

For instance, a dissertation research design includes the different resources and data collection techniques and helps establish your dissertation’s structure .

The following table shows the characteristics of the most popularly employed research methods.

Research Methods

Step 4: Procedure of Data Analysis

Use of the correct data and statistical analysis technique is necessary for the validity of your research. Therefore, you need to be certain about the data type that would best address the research problem. Choosing an appropriate analysis method is the final step for the research design. It can be split into two main categories;

Quantitative Data Analysis

The quantitative data analysis technique involves analyzing the numerical data with the help of different applications such as; SPSS, STATA, Excel, origin lab, etc.

This data analysis strategy tests different variables such as spectrum, frequencies, averages, and more. The research question and the hypothesis must be established to identify the variables for testing.

Qualitative Data Analysis

Qualitative data analysis of figures, themes, and words allows for flexibility and the researcher’s subjective opinions. This means that the researcher’s primary focus will be interpreting patterns, tendencies, and accounts and understanding the implications and social framework.

You should be clear about your research objectives before starting to analyze the data. For example, you should ask yourself whether you need to explain respondents’ experiences and insights or do you also need to evaluate their responses with reference to a certain social framework.

Step 5: Write your Research Proposal

The research design is an important component of a research proposal because it plans the project’s execution. You can share it with the supervisor, who would evaluate the feasibility and capacity of the results and conclusion .

Read our guidelines to write a research proposal if you have already formulated your research design. The research proposal is written in the future tense because you are writing your proposal before conducting research.

The research methodology or research design, on the other hand, is generally written in the past tense.

How to Write a Research Design – Conclusion

A research design is the plan, structure, strategy of investigation conceived to answer the research question and test the hypothesis. The dissertation research design can be classified based on the type of data and the type of analysis.

Above mentioned five steps are the answer to how to write a research design. So, follow these steps to formulate the perfect research design for your dissertation .

ResearchProspect writers have years of experience creating research designs that align with the dissertation’s aim and objectives. If you are struggling with your dissertation methodology chapter, you might want to look at our dissertation part-writing service.

Our dissertation writers can also help you with the full dissertation paper . No matter how urgent or complex your need may be, ResearchProspect can help. We also offer PhD level research paper writing services.

Frequently Asked Questions

What is research design.

Research design is a systematic plan that guides the research process, outlining the methodology and procedures for collecting and analysing data. It determines the structure of the study, ensuring the research question is answered effectively, reliably, and validly. It serves as the blueprint for the entire research project.

How to write a research design?

To write a research design, define your research question, identify the research method (qualitative, quantitative, or mixed), choose data collection techniques (e.g., surveys, interviews), determine the sample size and sampling method, outline data analysis procedures, and highlight potential limitations and ethical considerations for the study.

How to write the design section of a research paper?

In the design section of a research paper, describe the research methodology chosen and justify its selection. Outline the data collection methods, participants or samples, instruments used, and procedures followed. Detail any experimental controls, if applicable. Ensure clarity and precision to enable replication of the study by other researchers.

How to write a research design in methodology?

To write a research design in methodology, clearly outline the research strategy (e.g., experimental, survey, case study). Describe the sampling technique, participants, and data collection methods. Detail the procedures for data collection and analysis. Justify choices by linking them to research objectives, addressing reliability and validity.

31 Writing Up Qualitative Research

Jane F. Gilgun, School of Social Work, University of Minnesota, Twin Cities

Published: 04 August 2014
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This chapter provides guidelines for writing journal articles based on qualitative approaches. The guidelines are part of the tradition of the Chicago School of Sociology and the author’s experience as a writer and reviewer. The guidelines include understanding experiences in context, immersion, interpretations grounded in accounts of informants’ lived experiences, and research as action-oriented. The chapter also covers writing articles that report findings based on ethnographies, autoethnographies, performances, poetry, and photography and other graphic media.

How researchers write up results for journal publications depends on the purposes of the research and the methodologies they use. Some topics are standard, such as statements about methods and methodologies, but how to represent other topics, like related research and theory, reflexivity, and informants’ accounts, may vary. For example, articles based on ethnographic research may be structured differently from writing up research whose purpose is theory development. Journal editors and reviewers often are familiar with variations in style of write-ups, but, when they are not, they may ask for modifications that violate the methodological principles of the research. A common reviewer request is for percentages, which has little meaning in almost all forms of qualitative research because the purpose of the research is to identify patterns of meanings and not distributions of variables. For example, Irvine’s (2013) ethnography of the meanings of pets to homeless people shows a variety of meaning without giving the number of participants from which she drew.

Authors sometimes move easily through the review process, but most often they do not, not only because reviewers might not “get it,” but also because authors have left out, underemphasized, or been less than clear about aspects of their research that reviewers and editors believe are important. Working with editors and reviewers frequently results in improved articles.

The purpose of this chapter is to provide guidelines for writing journal articles based on qualitative approaches. My intended audience is composed of researchers, reviewers for journals, and journal editors. Reviewers for funding agencies may also find this chapter useful. I use the terms “journal article” and “research report” as synonyms, even though some journal articles are not reports of research. I have derived the guidelines from ideas associated with the Chicago School of Sociology and my experience as an author and reviewer. Although the Chicago School was, as Becker (1999) wrote, “open to various ways of doing sociology” (p. 10), the ideas in this chapter are part of the tradition, but they are not representative of the entire tradition. Furthermore, the ideas are not fixed but are open-ended because they evolve over time. I have followed the principles of the Chicago School of Sociology throughout my career, augmented by updates to these ideas, experiments with other traditions, and the sense I make of my own experiences as researcher, author, and reviewer.

The ideas on which I draw include understanding experiences in context, immersion, interpretations grounded in accounts of informants’ lived experiences, and research as action-oriented ( Bulmer, 1984 ; Faris, 1967 ; Gilgun, 1999 d ; 2005 a ; 2012 a ; 2013 b ). To follow these principles, researchers do in-depth studies that take into account the multiple contextual factors that influence meanings and interpretations, seek multiple points of view, and often use multiple methods such as interviews, observations, and document analysis. Researchers do this style of research not only because what they learn is interesting, but because they want to do useful research; that is, research that leads to social actions and even transformations in policies, programs, and interventions. Authors and reviewers pay attention to these principles. Authors convey them in their write-ups, and reviewers look for them as they develop their appraisals.

Excellent writing up of qualitative research matches these principles. In other words, write-ups convey lived experience within multiple contexts, multiple points of view, and analyses that deepen understandings. In addition, if the research is applied, then authors write about how findings may contribute to quality of life. Qualitative researchers from other traditions may follow similar or different guidelines in their write-ups, and I sometimes note other styles of write-ups. Often these variations are related to terminology and not procedures. The reach of the Chicago School of Sociology is wide and deep.

Following these guidelines does not guarantee an easy review process, but this article will be helpful to researchers as they plan and craft their articles and as they respond to reviewers’ and editors’ comments. After almost thirty years of publishing research based on qualitative approaches, almost as many years as a reviewer, and the editing of three collections of qualitative research reports ( Gilgun, Daly, & Handel, 1992 ; Gilgun & Sussman, 1996 : Gilgun & Sands, 2012 ), I am positioned to offer helpful guidelines, not only to authors but also to reviewers and journal editors.

I begin this chapter with a discussion of general principles and then cover the content of typical sections of research reports. Some of the general material fits into various sections of reports, such as methods and findings. In those cases, I do not repeat material already covered and assume that my writing is clear enough so that readers know how the general material fits into particular sections of articles.

Although most of this chapter addresses the writing of conventional research reports, I also cover writing articles that report findings through ethnographies, autoethnographies, performances, poetry, and photography and other graphic media. Ethnographies are based on researchers’ immersion in the field, where they do extensive observations, interviews, and often document analysis (see Block, 2012 ). Geertz’s (1973) notion of “thick description” is associated with ethnographies. Thick description is characterized by research reports that show the matrix of meanings that researchers identify and attempt to represent in their reports. Autoethnographies are in-depth reflective accounts of individual lives that the narrators themselves write ( Ellis, 2009 ). Ethnographies and autoethnographies involve reflections on meanings, contexts, and other wider influences on individual lives. They are studies of intersections of individual lives and wider cultural themes and practices. Reports of these types of research can look different from conventional research reports in that they appear less formal; the usual sections of methods, literature review, findings, and analysis may have different names; and the sections may be in places that fit the logical flow of the research and not the typical structure of introductory material, methods, results, and discussion. Despite these superficial differences, researchers who write these kinds of articles seek to deepen understandings and hope to move audiences to action through conveying lived experience in context and through multiple points of view. They also typically seek transformations of persons and societies. Links between these forms of research and Chicago School traditions are self-evident.

Some General Principles

Research reports that have these characteristics depend on the quality of the data on which the reports are based, the quality of the analysis, and the skills of researchers in conveying the analysis concisely and with “grab” ( Glaser, 1978 ), which means writing that is vivid and memorable ( Gilgun, 2005 b ). Grab brings findings to life. With grab, human experiences jump off the page. Priority is given to the voices of research participants, whom I call informants, with citations and the wisdom of other researchers providing important contextual information. The voices and analyses of researchers do not dominate ( Gilgun, 2005 c ), except in some articles whose purpose is theory development or the presentation of a theory. Researcher analyses often are important, especially in putting forth social action recommendations that stem from the experiences of informants.

A well-done report shows consistency between research traditions and the writing-up of research. For example, reflexivity statements, writing with grab, and copious excerpts from fieldnotes, interviews, and documents of various sorts are consistent with phenomenological approaches whose emphasis is on lived experience and interpretations that informants make of their experiences. Researchers new to qualitative research, however, often mix their traditions without realizing it, which works when the traditions are compatible. When the traditions are not compatible, the write-ups can be confusing and even contradictory ( Gilgun, 2005 d ). Some authors may write in distanced, third-person styles while attempting to convey informants’ lived experiences. These scholars may, therefore, have difficulty getting their articles accepted. Hopefully, this chapter will facilitate the writing of research reports that show consistency across their many parts and save scholars from rejections of work over which they have taken much care.

Details on These General Principles

In this section, I provide more detail on writing up qualitative research. I begin with a discussion of the need for high-quality data, high-quality analysis, and grab. I then move on to the details of the report, such as the place of prior research and theory, contents of methods sections, organization of findings, and the balance between descriptive material and authors’ interpretations. Dilemmas abound. Writing up qualitative research is not for the faint of heart.

High-Quality Data

Since qualitative researchers seek to understand the subjective experiences of research informants in various contexts, high-quality data result in large part from the degree that researchers practice immersion and to the degree that both researchers and informants develop rapport and engage with each other. Through active engagement, informants share their experiences with the kind of detail that brings their experiences to life. How to develop rapport is beyond the scope of this article, but openness and acceptance of whatever informants say are fundamental to engagement. Interviewers do not have to agree with the values that informants’ accounts convey, as when I interview murderers and rapists ( Gilgun, 2008 ), but we do maintain a neutrality that allows the dialogue to continue ( Gilgun & Anderson, 2013 ). The content of interviews is not about us and our preferences, but about understanding informants.

Prolonged engagement can result in quality data. In interview research, prolonged engagement allows for informants’ multiple perspectives to emerge, including inconsistencies, contradictions, ambiguities, and ambivalences. In addition, prolonged engagement facilitates the kind of trust needed for informants to share personal, sensitive information in detail, which are the kinds of data that qualitative researchers seek. Prolonged engagement also gives researchers time to reflect on what they are learning and experiencing through the interviews. This provides opportunities to develop new understandings and test new understandings through subsequent research. Their understandings thus deepen and broaden. Informants, too, can reflect, reconsider, and deepen the accounts they share.

Prolonged engagement means in-depth interviews, typically multiple interviews of more than an hour each. As mentioned earlier, time between interviews allows researchers and informants to reflect on the previous interview and prepare for the next. Researchers can do background reading, discuss emerging ideas with others, and formulate pertinent new questions. Informants may retrieve long-forgotten memories and interpretations through interviews. If they have only one interview, they have no opportunity to share with researchers the material that arises after the single interview is concluded.

There are exceptions to multiple interviews as necessary for immersion and high-quality data. When researchers have expertise in interviewing and when the topic is focused, one interview of between ninety minutes to two hours could provide some depth. Even under these conditions, however, more than one interview is ideal. I did a study that involved one ninety-minute interview with perpetrators of child sexual abuse in order to understand the circumstances under which their abusive behaviors became known to law enforcement. Thus, the interview was focused. The interviewees were volunteers who had talked about the topic many times in the course of their involvement in sex abuse treatment programs. They shared their stories with depth and breadth. I, too, was well-prepared. By then, I had had about twenty-five years of experience interviewing people about personal, sensitive topics. The informants provided accounts not only because the topic was focused, but because they were willing to share and I was willing to listen and to ask questions about their sexually abusive behaviors. With one interview, however, I knew relatively little about their social histories and general worldviews. Thus, I did not have the specifics necessary to place their accounts into context. The material they provided remained valuable and resulted in one publication ( Sharma & Gilgun, 2008 ) and others in planning stages. I prefer two or more interviews because of the importance of contextual data.

In observational studies, prolonged engagement means that researchers do multiple observations over time to obtain the nuances and details that compose human actions. Observational studies often have interview components and also may have document analysis as well. In document analysis, prolonged engagement means researchers base their analyses on an ample storehouse of documents and not just flit in and out of the documents. The quality of document analysis depends on whether the analysis shows multiple perspectives, patterns, and variations within patterns. Ethnographies have these characteristics. Block’s (2012) ethnographic research on AIDS orphans in Lesotho, Africa, is an example of a well-done ethnography.

Sample Size

In principle, the size of the sample and the depth of the interview affect whether researchers can claim immersion. The more depth and breadth each case in a study has, the smaller the sample size can be. For example, researchers can engage in immersion through a single in-depth case study when they do multiple interviews and if multiple facets of the case are examined. Case studies are investigations of single units. The case can be composed of an individual, a couple, a family, a group, a nation, or a region. Single case studies are useful in the illustration, development, and testing of theories, as well as in in-depth descriptions.

The more focused the questions, the larger the sample will be. A study on long-term marriage would require a minimum of two or three interviews because the topic is complicated. The sample would include at least ten participants and up to twenty or thirty, depending on the number of interviews, to account for some of the many patterns that are likely to emerge in a study of a topic this complex. In the one-interview study I did of how sexual abuse came to the notice of law enforcement, one interview was adequate because of the tight focus of the question. Yet, I used a sample size of thirty-two to maximize the possibility of identifying a variety of patterns, which the study accomplished. As mentioned, the one interview, however, did not allow me to contextualize the stories the informants told. Fortunately, I have another large sample that involved multiple, in-depth interviews in which informants discussed multiple contexts over time. This other study was helpful to me in understanding the accounts from the single-interview study.

Recruitment can be difficult. When it is, researchers may not be able to obtain an adequate sample. For example, a sample of seven participants engaging in a single sixty- to ninety-minute interview may not provide enough data on which to base a credible analysis. In a similar vein, articles based on a single or even a few focus groups may not provide enough depth to be informative. Some depth is possible if, in a single-interview study of less than fifteen or twenty interviewees, researchers meet with informants a second time to go over what researchers understand about informants’ accounts. This sometimes is called member-checking , and it provides additional data on which to base the analysis. In summary, the more depth and breadth to a study, the smaller the sample size can be—even as small as one or two—depending on the questions and the complexity of the cases.

Quality of the Analysis

A quality analysis begins with initial planning of the research and continues until the article is accepted for publication. An excellent research report has transparency , meaning the write-up is clear in what researchers did, how they did it, and why. I often tell students they can do almost anything reasonable and ethical, as long as they make a clear account in the write-up.

During planning, some researchers identify those concepts that they can use as sensitizing concepts once in the field. Transparency about the sources of sensitizing concepts characterizes well-done reports. The sources are literature reviews and reflexivity statements. Most researchers, however, have only a limited awareness of the importance of being clear about the sources of sensitizing concepts and other notions that become part of research coding schemes. Sensitizing concepts are notions that researchers identify before beginning their research and that help researchers notice and name social processes that they might not have noticed otherwise ( Blumer, 1986 ). Other researchers wait until data analysis to begin to identify concepts that they may use as codes and that may also become core concepts that organize findings. Either approach is acceptable and depends on purpose and methodologies.

During data collection, researchers reflect on what they are learning, typically talk to other researchers about their emerging understandings, and read relevant research and theory to enlarge and deepen their understandings. Researchers also keep fieldnotes that are a form of reflection. Based on their various reflections, researchers can reformulate interview and research questions and formulate new ones, do within—and across—case comparisons while in the field, and develop new insights into the meanings of the material.

Also, while in the field, researchers identify promising patterns of meanings and identify tentative core concepts, sometimes called categories , which are ideas that organize the copious material that they amass. Once researchers identify tentative core concepts, they seek to test whether they hold up, and, when they do, they further develop the patterns and concepts. Sometimes researchers think they have “struck gold” when they identify a possible core concept or pattern, only to find that the data—or metaphorical vein of gold—peter out (Phyllis Stern, personal communication, November 2002). They then go on to identify and follow-up on other concepts and patterns that show promise of becoming viable.

Core concepts become viable when researchers are able to dimensionalize them ( Schatzman, 1991 ) through selective coding ( Corbin & Strauss, 2008 ). This means that researchers have found data that show the multiple facets of concepts, such as patterns and exceptions to any general patterns. Authors may use other terms to describe what they did, such as thematic analysis. What is important is to describe the processes and produces; and what researchers call them is of less importance.

Core concepts may begin as sensitizing concepts. Researchers sometimes identify, name, and code core concepts through notions that are part of their general stores of knowledge but were not part of the literature review or reflexivity statement. Glaser (1978) called the practice “theoretical sensitivity.” The names researchers choose may be words or phrases informants have used. However derived, core concepts are central to the organization of findings ( Gilgun, 2012 a ).

At some point, data collection stops, but analysis does not. Researchers carry analysis that occurred in the field into the next phases of the research. Immersion at this point means that researchers read and code transcripts of interviews, observations, and any documentary material they find useful. They carry forward the core concepts they identified in the field. An example of a core concept is “resilience,” which in my own research organized a great deal of interview material. The concept of resilience has been an organizing idea in several of the articles I have written and plan to write ( Gilgun, 1996 a ; 1996 b ; 2002 a ; 2002 b ; 2004 a ; 2004 b ; 2005 a ; 2006 , 2008 ; 2010 ; Gilgun & Abrams, 2005 ; Gilgun, Keskinen, Marti, & Rice, 1999 ; Gilgun, Klein, & Pranis, 2000 ).

Corbin and Strauss (2008) stated that selective coding helps researchers to decide if a concept can become a core concept, meaning it organizes a great deal of data that have multiple dimensions. An example of dimensionalization is a study of social workers in Australia whose clients were Aboriginal people. The researchers identified several core concepts, among them critical self-awareness ( Bennet, Zubrzycki, & Bacon, 2011 ). The dimensions of critical self-awareness included understanding motivations to work with Aboriginal people, fears of working with Aboriginal people, and personalization and internalization of the anger that some Aboriginal people express.

Like many other researchers, Bennet et al. (2011) were not working within an explicit Chicago School tradition. They therefore do not use terms such as core concepts, dimensionalization, and selective coding. Instead, they described their procedures as thematic analysis, conceptual mapping, and a search for meaning. However, they did use the term “saturation,” which is part of the Chicago School tradition.

A single core concept or multiple related core concepts compose research reports. The Bennet et al. (2011) article, for example, linked multiple core concepts. The authors showed how critical self-awareness leads to meaningful relationships that in turn connect to “acquiring Aboriginal knowledge” (p. 30).

With viable core concepts and rich data, researchers are positioned to present their findings in ways that are memorable and interesting; that is, with “grab” ( Glaser, 1978 ). “Grab” requires compelling descriptive material: excerpts from interviews, field notes, and various types of documents, as well as researchers’ paraphrases of these materials. An example of a research report with grab is Irvine’s (2013) account of her study of the meanings of pets to homeless people. She provided vivid descriptions of her interactions with the participants and compelling quotes that show what pets mean. Here, an example from Denise’s account of her relationship with her cat Ivy:

I have a history with depression up to suicide ideation, and Ivy, I refer to her as my suicide barrier. And I don’t say that in any light way. I would say, most days, she’s the reason why I keep going.... She is the only source of daily, steady affection and companionship that I have. (p. 19)

These and other quotes, as well as Irvine’s well-written, detailed descriptive material, show what grab means.

Grab equates with excellence in writing. Irvine’s (2013) article is an example. In terms of the grab of her article, her work is in the Chicago School tradition. She wrote in the first person. She told complete stories in which she quoted extensively from the interviews, described the persons she interviewed and the settings in which she interviewed them, and provided biographical sketches. Robert Park and Ernest Burgess, both of whom trained generations of graduate students in qualitative research at the University of Chicago in the first quarter of the twentieth century, held seminars on the use of literary techniques, such as those used in novels and autobiographies, in writing up research ( Bulmer, 1984 ; Gilgun, 1999 d ; 2012 a ). These educators wanted researchers to report on their “first-hand observation.” Park told a class of graduate students to

[g]o and sit in the lounges of the luxury hotels and on the doorsteps of the flophouses; sit on the Gold Coast settees and on the slum shakedowns; sit in the Orchestra Hall and in the Star and Garter Burlesk. In short, gentlemen [sic], go get the seat of your pants dirty. ( McKinney, 1966 , p. 71)

Park suggested to Pauline Young (1928 ; 1932) to “think and feel” like the residents of Russian Town, the subject of her dissertation, published in 1932 ( Faris, 1967 ). Irvine’s work shows these qualities. She immersed herself in the settings, she conducted in-depth interviews, and she conveyed her first-hand experiences in vivid terms.

The Chicago School also encouraged students to write in the first person. A good example is a report by Dollard (1937) , who was concerned about the racial practices of the Southern town where he was doing fieldwork. He said he was afraid that other white people watched as he talked to “Negroes” on his front porch, when he knew that custom regarding the “proper” place of “Negroes” was at the back door. He wrote

My Negro friend brought still another Negro up on the porch to meet me. Should we shake hands? Would he be insulted if I did not, or would he accept the situation? I kept my hands in pockets and did not do it, a device that was often useful in resolving such a situation. (p. 7)

This description is a portrait of a pivotal moment in Dollard’s fieldwork, and it is full of connotations about the racist practices of the time ( Gilgun, 1999 d ; 2012 a ).

Irvine (2013) also wrote in the first person. Here’s an example:

I met Trish on a cold December day in Boulder. She stood on the median at the exit of a busy shopping center with her Jack Russell Terrier bundled up in a dog bed beside her. She was “flying a sign,” or panhandling, with a piece of cardboard neatly lettered in black marker to read, “Sober. Doing the best I can. Please help.” (p. 14)

These two excerpts illustrate a methodological point Small (1916) made in his chapter on the first fifty years of sociological research in the United States: namely, the importance of going beyond “technical treatises” and providing first-person “frank judgments” that can help future generations interpret sociology. Without such contexts, “the historical significance of treatises will be misunderstood” (p. 722). Throughout his chapter, Small wrote in the first-person and provided his views—or frank judgments—on the events he narrated. From then until now, research reports in the Chicago tradition are vivid and contextual, conveying to the extent possible what it was like to be persons in situations.

There are many other examples of well-done research reports. Eck’s (2013) article on never-married men includes the basic elements that are present in almost all reports based on qualitative methods. It is transparent in its procedures, situated within scholarly traditions, well-organized, vivid, and instructive both for those new to qualitative research and for long-term researchers like me. The other articles I cite in this chapter also show many desirable qualities in research reports.

Research Report Sections

The main sections of standard reports based on qualitative methods are the same as for articles based on other types of methods: Introduction, Methods, Findings, and Discussion. The American Psychological Association (APA) manual (2009) provides information on what goes into each of these sections. Research reports in sociology journals follow a similar format, although the citation style is slightly different. The American Sociological Association uses first and last names in the reference section, a practice I support. In articles based on qualitative approaches, researchers sometimes change the names of sections, add or omit some, or reorder them. When changes are made, the general guideline is whether the changes make sense and are consistent with the purpose of the research. As Saldaña (2003) pointed out, researchers choose how to present their findings on the basis of credibility, vividness, and persuasive qualities and not for the sake of novelty. Because some articles report findings as fictionalized accounts, poetry, plays, songs, and performances (including plays), it makes sense that the sections on these findings vary from the standard format that I discuss here.

Although there are no rigid rules about how to write journal articles based on qualitative research, much depends on the methodological perspectives, purposes of the research, and the editorial guidelines of particular journals. For example, if researchers want to develop a theory, it is important to be clear from the beginning of the article to state this as the purpose of the research. The entire article should then focus on how the authors developed the theory. Research and theory cited in the literature review should have direct relevance to the substantive area on which the authors theorized. The methods section should explain what the researchers did to develop the theory. The findings section should begin with a statement of the theory that the researchers developed. The rest of the findings section should usually be composed of three parts. The first is composed of excerpts from those data that support the concepts of the theory. This is the grounding of the theory in something clear and concrete. The second is the authors’ thinking or interpretation of the meanings of each of the concepts. The third is an analysis of how the theory contributes to what is already known, such as how the findings elaborate on and call into question what is known. Thus, a research report on the development of a theory should contain a lot of scholarship that others have developed.

A report based on narrative principles or one based on an ethnography should contain copious excerpts from interviews, citing less scholarship than an article whose purpose is to develop theory. However, it is good practice to bring in related research and theory in the results section when this literature helps in interpretation, when findings have connections to other bodies of thought, and when findings are facets of a larger issue. In my now older publication on incest perpetrators ( Gilgun, 1995 ), the editors suggested that I show that when therapists engage in sexual relationships with clients, they are engaging in abuses of power similar to those of incest perpetrators. I was at first indignant that the editors wanted me to do even more work on the article, but I soon was glad they did. It is important to show that incest or any human phenomenon is not isolated from other phenomenon but is part of a larger picture. Doing so fit my purposes, which was to show how to do theory-testing/theory-guided qualitative research. Showing how findings fit into related research and theory is part of this type of research.

Whenever researchers are ready to submit an article for publication, it is wise to read recent issues of journals in which they would like to publish. If they can identify an article whose structure, methodologies, and general purpose are similar to theirs, they could study how those authors presented their material. If, for example, in a report on narrative research, the introductory material is relatively brief, and the findings and discussion sections compose most of the pages, researchers would do well to format their articles in similar ways. I study journals in which I have interest and model much of my own articles after those published in these journals. I make sure, however, that I cover topics that in my judgment are important to cover.

Prior Research and Theory

In my experience, something as simple as the place of prior research and theory can get complicated in the writing of reports based on qualitative research, even when the purpose of the article is primarily descriptive and is not to construct an explicit theory. In general, related research and theory literature can be presented at the beginning of a report as part of a review of pertinent research and theory, in the findings section when prior work helps in the interpretation and analysis of findings, or in the discussion section, where authors may reflect on how their findings add to, undermine, or correct what is known and even add something new.

Readers expect and journal editors typically want articles to begin with literature review, with some exceptions. A perusal of journals that publish qualitative studies shows this. Yet there are exceptions. Valásquez (2011) began her report on her encounter with scientology with an extended and rather meandering first-person narrative. Her literature review began toward the end of the article. She tailored the review to the report that preceded it. In this article and others, the literature review helped in the interpretation of findings and helped to situate the report in its scholarly contexts. In other articles, the literature review appears in the introductory section. This sets the scholarly context of the research, highlights the significance of topics, and identifies gaps in knowledge. Neither authors nor reviewers should have rigid expectations about where the scholarship of others belongs. It belongs where it makes the most sense and has the most impact.

For many, the placement of literature reviews seems self-evident. Yet, some well-known approaches, such as grounded theory, can set authors up for confusion about where the literature review belongs. This can result in delays in writing up their results. The procedures of grounded theory are open-ended and designed to find new aspects of phenomena—often underresearched—and then develop theories from the findings. At the outset of their work, researchers cannot anticipate what they will find. Therefore, teachers such as Strauss and Glaser advised students not to do literature reviews until they had identified basic social processes that become the focus of the research ( Covan, 2007 ; Glaser & Strauss, 1967 ).

How, then, do researchers write up research reports when they are doing an open-ended study that, by definition, will culminate in unanticipated findings? Do they write their reports as records on how they proceeded chronologically, or do they follow APA style and the dominant tradition that says the literature review comes first? For the most part, I follow the tradition, as, apparently, do most researchers. However, to structure reports in this way sometimes feels strained and artificial. I would prefer to write a more chronological account, in which I can share with readers the lines of inquiry and procedures I followed. The literature review at the beginning of the report, therefore, would be brief. The methods section is quite detailed in how I went about developing the theory. The findings section would have the three-part format I discussed earlier: statement of the theory, presentations of excerpts that support assertions that certain concepts compose the theory, my interpretation of the meanings of the concepts and the excerpts that support them, and then the use of related research and theory to further develop the theory and to situate it in its scholarly traditions.

In all but one of the research reports that I have published, I did the literature after I had identified findings. The one exception was research I did based on the method of analytic induction, in which researchers can use literature reviews to focus their research from the outset ( Gilgun, 1995 , 2007 ). In this research, I used concepts from theories on justice and care to analyze transcripts of interviews I had previously conducted on how perpetrators view child sexual abuse. Even though I was familiar with the transcripts, I found that the concepts of justice and care and their definitions sensitized me to see things in the material that I had not noticed as I did data collection and during previous analyses of the data.

Furthermore, in writing up the results, I brought in research that was not part of the literature review to help me to interpret findings and to show how findings fit with and added to what was already known. I did not place this material in the introductory literature review. Placing related research and theory as parts of the results and discussion sections is common and may be necessary in articles that are reporting on a theory that the authors developed. For descriptive studies whose purpose is not theory-building, such as ethnographies, some findings sections include the addition of research and theory not present in the introductory section. Often, however, authors do not follow this pattern. An example is found in Ahmed (2013) , who described how migrants experience settling into a new country. She presents excerpts from interviews and her interpretation of them, including organizing them into a typology, but she does not bring additional research and theory into her interpretations.

Tensions can arise between how much space to give to literature reviews and how much to allot to presentation of informants’ accounts/findings ( Gilgun, 2005 c ). This happened in the most recent article I co-wrote, which is on mothers’ perspectives on the signs of child sexual abuse ( Gilgun & Anderson, 2013 ). We believed the literature review was important because it not only set up our research but summarized a great deal of information that was important to our intended audience of social service professionals. We also wanted to anticipate the expectations of reviewers and the journal editor. Yet, we put much effort into making the literature review as concise as possible in order to have reasonable space for findings. We wrote the literature review before we did data analysis. When we wrote up the results, the first draft was probably three times longer than any journal article could be.

We had written case studies first to be sure that we understood each case in detail. We had wanted to share what the women said in the kind of detail that had helped us deepen our own understandings, so we cut back on the case material. The article was still too long. We decided to exclude the few instances we had in which women knew of the abuse but tried to handle it themselves or did not believe the children when told. We did more summarizing of the literature review. We eliminated many references.

After much effort, we finally had a manuscript that was the required length of twenty-two pages. It included a literature review that set up the research in good form, an adequate accounting of the method, and findings that conveyed with grab the complexities of the signs and lack of signs of child sexual abuse. We wove points made in the literature review into our interpretations, yet we had to leave out important patterns for the sake of space. The editor’s decision was a revise and resubmit, which we did. The main recommendation was to elaborate on applications. This was a great suggestion, and we dug deep to think about this. We are pleased with the results. We had to do further reading on topics we had not anticipated at the onset of our project, and we squeezed in a few new citations in the discussion section that related to implications of the research. This additional material greatly enhanced the meanings and usefulness of the research.

There is much more to say about qualitative research and literature reviews. Sometimes researchers get stuck, as I have more than once. I have research that I have not yet published because I have been unable to figure out how to do the multiple literature reviews I think I must show how my theory builds on, adds to, and challenges what is already known. I have written up this research as conference papers, where expectations about literature reviews are more relaxed ( Gilgun, 1996c , 1998 , 1999c , 2000 ). One of these. papers was on a comprehensive theory of interpersonal violence ( Gilgun, 2000 ). I wanted to write my theory first and then show how the findings contribute to what is already known. Doing so doesn’t seem so outlandish today, and I now can imagine writing it up exactly as I would want to. At the same time, I wonder if I would? I really don’t know if any journal that would publish a theory of violence would also accept an article that places a literature review after findings. Furthermore, my writing up of the theory would take so many pages that I would not have enough space to do a comprehensive literature review. As of today, the theory I am developing has links to sixteen or more bodies of literature. No way can I publish a journal-length article that will accommodate that much research and theory!

So, here I am, many years into the development of a comprehensive theory, still reflecting on how to create journal articles out of my analysis. I have published many articles in social media outlets exploring ideas that are the basis for the theory. I have put these articles into collections that are available on the internet ( Gilgun, 2012 b ; 2012 c ; 2013 a ). The theory is so complex that writing bits and pieces over the years and having a place to put them have been very helpful.

Finally, some articles may cite few if any related research and theory. This may fit articles whose purpose is to convey lived experience that stands on its own. These articles feature performances, plays, autoethnographies, fictionalized accounts, poetry, and song, among others. Egbe (2013) wrote two poems that she explained were accounts of her experiences of doing research in Nigeria with young smokers. She said she was “dazed by the vast opportunity this method gives a researcher to dig deep into a research problem and be submerged into the world of participants” (p. 353). Her two-page article is composed of two poems and her explanation. The article showed grab, evidence of immersion, experiences in contexts, and multiple perspectives. Her work, therefore, followed well-established guidelines for writing up qualitative research. Egbe not only omitted a literature review, but she did not write about how to use the results of her research, assuming that its uses are self-evident. Obviously, she thought a literature review unnecessary; the reviewers and journal editors agreed with her.

Reflexivity Statements

A growing number of journals encourage researchers to include reflexivity statements in research reports. Researchers may place these in the introductory material of an article, after the literature review and before the methods section; this probably is the most important place to put them because reflexivity statements often influence the focus and design of the research, including the choice of sensitizing concepts and codes. Reflexivity statements may also appear in the methods and findings and methods sections when important. Reflexivity statements are accounts of researchers’ experiences with the topic of research; accounts of their expectations regarding informant issues and their relationships to informants, especially in regard to power differentials and other ethical concerns; and accounts of their reflections on various issues related to possible experiences that informants may have had. They also may include the experience they had while participating in the research ( D’Cruz, Gillingham, & Melendez, 2007 ; Presser, 2005 ). My article on doing research on violence is an extended reflexivity statement ( Gilgun, 2008 ). There appears to be no standard content for reflexivity statements and no standard places for them to appear. Personal and professional experiences and reflections on power differentials may be the emergent standard. Whatever decisions researchers make about reflexivity statements, they alert audiences to researchers’ perspectives, which can be helpful to readers as they attempt to make sense of research reports.

An example of a reflexivity statement is found in Winter (2010) work. Winter is a practitioner turned researcher who had a previous relationship as a guardian ad litem with the children with whom she later conducted the research that she was reporting. Winter was reflexive about the implications of her prior relationship with these children. I imagine, based on my own experience, that she put only a fraction of her thinking into her article. Not only did she write in her reflexivity statement that she had a prior relationship with the children, but she also wrote about the ethical issues involved.

Ethical issues have a place in reflexivity statements. I have run into ethical questions over the course of my research career. One situation that stands out is the encounter I had with a mother and her eleven-year-old daughter who had participated in my dissertation research on child sexual abuse ( Gilgun, 1983 ). The mother cried and told her daughter how sorry she was that she had been unable to protect her from sexual abuse. The girl was touched but did not seem to know what to do. I suggested that she go stand by her mother. When she got close, the mother and daughter hugged each other and cried. This is a significant event with ethical implications that I included in the findings section of my dissertation and in a subsequent research report ( Gilgun, 1984 ). The ethical issue is, first, whether I should have stepped out of my role as detached researcher and guided the girl to go to her mother, and, second, whether I should have made my blurring of boundaries public by publishing them.

As far as the placement of reflexivity statements, the initial statement has a logical location after the literature review because the reflexivity statement contributes to the development of the research questions, the identification of sensitizing concepts, the interview schedule, and the overall design of research procedures. Accounts of ongoing reflexivity could be part the findings section and of the discussion section. Reflexivity statements are not a standard part of research reports, but they can contribute to readers’ understandings of the research.

Along with the literature review, reflexivity statements contribute to practical and applied significance statements and may also help to identify gaps in knowledge. Literature reviews and reflexivity statements contain key concepts. The concepts that researchers define at the end of introductory sections typically become codes during analysis, although researchers may not label the concepts as codes either in the introductory section or in the methods section. I am unsure why such labeling has not become routine. When concepts carry the label code , this clarifies where codes come from. Without naming codes and stating where they come from, much of analysis is mystified. Many reports read as if the codes appear out of nowhere during analysis. Even Glaser’s (1978) notion of theoretical sensitivity mystifies the origins of codes. How, for example, do researchers become theoretically sensitive? What if researchers are beginning their scholarly careers? How theoretically sensitive are they ( Covan, 2007 )? What are the implications for the quality of the analysis?

Research Questions, Hypotheses, and Definitions

The final part of the introductory section of a research report is devoted to research questions, hypotheses to be tested (if any), and definitions of core concepts. In general, in qualitative research, hypotheses are statements of relationships between concepts. Theories usually are composed of two or more hypotheses, although, at times, some researchers may use the term theory to designate a single hypothesis ( Gilgun, 2005 b ). Concepts are extractions from concrete data. Sometimes concepts are called second-order concepts and data first-order concepts .

Research questions may be absent. In their place are purpose statements that make the focus of the report clear. Hypotheses are rarely present in qualitative research. When they are, the purpose of the research is to test them and typically to develop them more fully. This type of research has in the past been called analytic induction ( Gilgun, 1995 e), whereas a more up-to-date version of qualitative hypothesis testing and theory-guided research is called deductive qualitative analysis ( Gilgun, 2005 d ; 2013 ). Analytic induction and deductive qualitative analysis are part of the Chicago School tradition.

Methods Section

Most methods sections for reports based on qualitative approaches have the same elements as any other research report. Descriptions of the sample, recruitment, interview schedule, and plans for data analysis are standard. The APA manual provides guidelines ( American Psychological Association, 2009 ) that fit many types of qualitative research reports. However, reports based on autoethnographies, poetry, and performances may have brief or no methods sections. As is clear by now, the report’s contents depend on the purposes and methodologies of the research and on the editorial requirements of journals.

Accounts of Methodologies

In writing up qualitative research, methods sections usually contain a brief overview of the research methodology, which is the set of principles that guided the research. The following is an account of the methodology used in a research report on cancer treatment in India:

For this project we drew upon interpretive traditions within qualitative research. This involved us taking an in-depth exploratory approach to data collection, aimed at documenting the subjective and complex experiences of the respondents. Our aim was to achieve a detailed understanding of the varying positions adhered to, and to locate those within a broader spectrum underlying beliefs and/or agendas. ( Broom & Doron, 2013 , p. 57)

Sometimes, statements of methodology are much more elaborate, but in research reports, such a statement is sufficient, again depending on the editorial policies of particular journals. A few citations, which this article had, round out an adequate statement of methodology.

However, many reports are written in a clear and straightforward way with scant or no account of methodologies. Examples are the work of Eck (2013) and Spermon, Darlington, and Gibney (2013) . These kinds of well-done write-ups might eventually be considered generic. Spermon et al. said their study was phenomenological, which sets up assumptions that the report will be primarily descriptive. In actuality, the intent was to develop theory. Such mixing of methodologies may be the wave of the future; in many ways, distinctions between phenomenological studies whose purposes are descriptive and those whose purposes are to build theory are blurred. Such blurring may have been the case for decades because it is possible and often desirable to build theories based on phenomenological perspectives; that is, in-depth descriptions of lived experience. However, authors are wise to state in one place what their methodologies are and how they put them to use, such as for descriptive purposes or for theory-building.

Description of Sample

Placing descriptions of sample size and the demographics of the sample in the methods sections is typical. As mentioned earlier, evaluation of sample size depends on the depth and breadth of the study. The more depth a study has, the smaller the number of cases can be. The more breadth and the sharper the focus, the larger sample sizes typically are. Samples on which a study is based must provide enough material on which to base a credible article. A sample size of one may be adequate if researchers show their work demonstrates the basic principles of almost all forms of qualitative research: perspectives of persons who participate in the research, researcher immersion into the settings or the life stories of persons interviewed, multiple perspectives, contextual information of various types, and applications. Autoethnographies often have an n of one, but joint autoethnographies are possible. Ethnographies may not give a sample size, as was the case in the performance ethnography of Valásquez (2011) who wrote in the first person about her experience with scientology. In her first-person ethnography, Irvine (2013) also did not mention sample size. She said that the narratives she used for the article were from a larger study on the meanings of animals to people who have no homes. She did not describe the usual demographics of age, gender, social class, and ethnicity.

Most articles describe the demographics of the sample. In a recently accepted article ( Gilgun & Anderson, 2013 ), I saw no relevance in mentioning the size of the larger sample from which we drew in order to tell the stories of how mothers responded to their learning that their husbands or life partners had sexually abused their children. We included an exact count of the larger sample because we assumed that it would be the journal’s expectations. We also gave particulars of the demographics. Except for social class and ethnicity, we saw little relevance for the other descriptors. These status variables were relevant to us because most of the sample was white and middle or upper class. This is important because much research on child sexual abuse is done with poor people, and there are stereotypes that poor families and families of color are more likely to experience incest than are white middle and upper class families. Overall, as with some other issues related to writing, the adequacy of the sample description depends on the methodological principles of the research and the journal’s editorial policies.

Recruitment

Accounts of recruitment procedures are important because researchers want to show that their work is ethical. Respect for the autonomy or freedom of choice of participants needs to be demonstrated. In addition, often the persons in whose lives we are interested have vulnerabilities. To show that the research procedures have not exploited these vulnerabilities is part of ethical considerations. Most articles have these accounts. Furthermore, when there are accounts of recruitment procedures, it becomes obvious why the sample is not randomly selected. Irvine’s (2013) account of recruitment is exemplary. She recruited through veterinary clinics that took care of the pets of homeless persons. She did not approach potential participants herself. Doing so risked making refusals difficult. The staff informed persons of the research and its purposes. If individuals said they were interested, they gave permission for the staff to give their names to researchers. The research interviews took place in the clinics.

The ethics of recruitment revolve around values, such as respect for autonomy, dignity, and worth. Other ethical issues that are important to mention in reports include the use of incentives for participation. Although many human subjects committees now require monetary incentives for participation, this has ethical implications. Irvine (2013) solved this by giving gift cards after the interviews were completed. Reports on ethical issues have a place in methods sections.

Data Collection and Analysis

Accounts of data collection and analysis are part of the methods section. Data collection procedures should be detailed for many reasons. Primary among them is the need for transparency in terms of the ethical standards the researchers followed, as well as the need to allow for replication of the study. Such details also provide guidelines for others who might be interested in using the methods. In addition, there are many different schools of thought and procedures for each of the methods used with the three general types of data collection: interviews, observations, and documents. It is helpful to state which particular data collection procedures the researchers used. Researchers often provide examples of the kinds of questions asked and procedures used for recording observations and excerpts from documents. Some researchers may omit such an accounting, as with some autoethnographies and articles that turn research material into performances.

How researchers analyzed data is part of the methods sections. As with data collection, there are so many types of analysis that researchers need to describe the particular forms that they used. For figuring out how to report on data analysis, researchers would do well to study articles in journals in which they want to publish. Irvine (2013) used a method of analysis I have never heard of called “personal narrative analysis” (p. 8). She gave enough detail to provide the general idea of what she did and a sufficient number of citations for additional information.

The level of detail can vary. In some sociology journals, for example, researchers may say little about analysis and sometimes little about data collection. This is because the journal editors, reviewers, and those who publish in and read the articles have assumptions that they for the most part take for granted. Even in these journals, however, researchers may want to account for their analytic procedures, especially if they are writing on topics outside of what is usual in such journals.

Other journals require a great deal of detail. In those instances, researchers first decide what they think is essential and then shape their accounts to fit what appears to be usual practice in the journal. The following paragraphs describe data analysis in a recently accepted article on signs of child sexual abuse in families ( Gilgun & Anderson, 2013 ).

Data Analysis

In the analysis of data, the first author read the transcripts multiple times and coded them for instances related to disclosures of child sexual abuse and associated signs of the abuse, such as how and when the women first learned of the abuse or suspected it was occurring in their families, their responses, and their reflections on the signs of abuse they might have missed, as well as child and perpetrator behaviors that they did not realize were related to child sexual abuse. Their initial and longer term responses and reflections were also coded. The second author independently read and coded about one-third of the transcripts using this coding scheme to arrive at a 100 percent agreement.

Sources of the codes were our professional experiences in the area of child sexual abuse, the review of research, and the first author’s familiarity with the content of the interviews because she had been the interviewer. These codes served as sensitizing concepts, which, as Blumer (1986) explained, are ideas that guide researchers to see aspects of phenomena that they might otherwise not notice. Although altering researchers’ ideas to what might be significant serves an obvious useful purpose, sensitizing concepts might also may blind researchers to other aspects of phenomena that might be important. Therefore, we also used negative case analysis, which is a procedure that guides researchers to look for aspects of phenomena that contradict or do not fit with emerging understandings. In this way, researchers are positioned to see patterns, variations within patterns, exceptions, and contradictions in findings ( Becker et al., 1961 ; Bogdan & Biklen, 2007 ; Cressey, 1953 ; Lindesmith, 1947 ).

As we wrote this section, we were aware of the limited space that we had to fill. Yet we were committed to accounting for where our codes came from for reviewers and editors who may be unfamiliar with pre-established codes. As discussed earlier, many reports are written as if codes appear by magic. We decided that, in this report, we would be as clear as possible about where our codes came from. We also reasoned that we would have to call on the authority of well-respected methodologists if reviewers and editors had questions about what we had done. Furthermore, we were aware of the dated nature of the references; we could do nothing about that because there has not been much written recently about pre-established codes. I have written about this quite a bit, but as one of the authors, I not only had to be anonymous during the review process, but I could not be the sole authority.

Generalizability

Many reviewers and editors have questions about the generalizability of the results of qualitative research. Authors themselves sometimes question the generalizability of their own findings. That’s why it remains important to provide clear guidelines in research reports about how the authors view the usefulness of their findings. The following ideas may be helpful to authors as they write their reports and to reviewers who are positioned as gatekeepers. The results of qualitative research are not meant to be generalized in a probabilistic sense. But because dropouts and refusals limit the randomness of samples, most forms of research can’t be generalized in a probabilistic sense.

Conversely, as Cronbach (1975) wrote almost forty years ago, the results of any form of research are working hypotheses that must be tested in local settings. Thus, the applicability of qualitative or any other kind of research can be demonstrated only through attempts at application. Do the findings illuminate other situations? Do the results provide researchers, policy makers, and direct practitioners with ideas on how to proceed? Those who apply the research expect to have to adjust findings to fit particular new situations. Many researchers and some journal editors and reviewers know through common sense and everyday experience how to use the results of qualitative research. Our personal lives are extended case studies. What we learn in one situation, we carry over into another. We know we have to test what we have learned in past situations for fit with new situations. If we do not, we impose our ideas on situations that may demand new perspectives. This common practice of applying results to all situations is disrespectful of local conditions and autonomy of persons. We want to avoid such disrespect in how we suggest readers use the results of our research.

Trustworthiness and Authenticity

Pointing out the trustworthiness of procedures and the findings that result from them sometimes are parts of methods sections. Related to trustworthiness are issues of authenticity ( Guba & Lincoln, 2005 ). Both trustworthiness and authenticity arise from immersion, seeking to understand the perspectives of others in context, reflexivity, and seeking multiple points of view. Researchers who have applied these principles will produce reports that are trustworthy and authentic. In addition, the reports will have grab. Extended discussions related to these issues are beyond the scope of this chapter and the scope of research reports as well.

I get more requests for revisions of methods sections, especially for accounts of data collection and analysis, than for any other parts of a manuscript. This is not surprising, given the multiple possible variations. I never know who the reviewers will be and what their expectations are. I rely first on my beliefs about what I want in the procedures section and then I study articles the journal has already publishes. I include what journal editors appear to expect, but I also add information that I think is important, even when it is not part of what I see in methods sections.

Findings Sections

Findings sections in research reports include both descriptive and conceptual material. Descriptive material is composed of researchers’ paraphrasing and summarizing of what they found and excerpts from interviews, fieldnotes, and documents. The descriptive material, at its best, is detailed and lively; it not only is informative, it has grab. This material contributes to understandings of human experiences in context. In addition, descriptive material is the basis of researchers’ theorizing and it also provides documentation and illustrations of assertions that researchers make.

Conceptual material comprises the analysis and is made up of inferences such as the general statements, concepts, and hypotheses that researchers develop from the material (data). One way to think about the relationship between descriptive and conceptual material is to think of descriptive material as composed of first-order concepts and conceptual material as composed of second-order concepts. Each type depends on the other. Credible conceptual material is based on descriptive material, some of which is contained in the article. Qualitative research yields mountains of data, a fraction of which can be placed into a published article.

As with other sections of research reports, findings sections have many possible variations that depend on the purpose of the research and the methodologies on which the research is based. Thus, the findings can range from heavily descriptive to heavily conceptual. Heavily conceptual research reports arise from research whose purpose is theoretical, in which researchers set out to test, refine, reformulate, or develop theory. Theoretical reports require some descriptive material to show the basis of theoretical statements, but they are often relatively short on descriptive material.

Reports that are primarily descriptive are composed of excerpts from data. Theoretical material appears in often subtle ways, such as in the form of concepts that organize findings. Irvine’s (2013) study of homeless people and their pets is largely descriptive, composed of excerpts from the interviews and Irvine’s paraphrases and narration of what she did, how, and when. The findings were narrative case studies based on interviews and observations. The details of the narratives were vivid and had the kind of grab that Glaser (1978) recommended. They showed multiples perspectives and variations on what it meant to homeless informants to have pets in their lives. The first three pages were a review of relevant literature and a presentation of method. The last five pages were a discussion of the findings.

As lengthy as the descriptive material is, conceptual material frames the entire report. In the literature review, Irvine introduced notions of positive identity, generativity, and redemption. She used them to analyze her data and organize findings, which were the narrative case studies. She used the concept of redemption as the core or organizing concept, going into some detail about how the research material supports the significance of this idea of pets as redemptive for homeless people.

This analysis is based squarely on the descriptive material. For instance, Irvine wrote that in the stories she presented in her article, “animals provide the vehicle for redemption.” She illustrated this point with a quote from one of the narratives and then reminded readers that the narratives “contain variations on the theme” of “ life is better because this animal is in it ” (p. 20; emphasis in original). Readers do not take this on faith because the basis of this general statement in presented multiple times in the case studies. Irvine has much more material on which she based these ideas, but there is not enough room in a journal-length article to show all of her evidence.

An example of an article that is theoretical in purpose and short on descriptive material is found in the work of Cordeau (2012) . She developed a grounded theory of the “transition from student to professional nurse” when student nurses work with “mannequins as simulated patients” (p. 90). Based on interviews, observations, and reports that the students wrote on their clinical experiences, the study was composed of about 10 percent descriptive material. This material included excerpts interviews and student reports. In the results section, she used this descriptive material to illustrate and possibly document the grounded theory she constructed. The theory’s “core category” was “linking,” which had four components, called properties. She documented the properties, primarily with her own thinking about her research material and also with excerpts from interviews, observations, and student reports.

Like Irvine’s (2013) study, the purpose of Cordeau’s (2012) work was applied where she wanted to build theory that would contribute to the development of clinical expertise in nursing students. She also devoted about one page of her study to applications.

Core Concepts

I’ve previously provided an extended discussion of core concepts. This section highlights some key points and illustrates them. Core concepts, often called core categories , organize findings. I prefer the term concept because concept is the term used in discussing theory, such as “concepts are the building blocks of theory,” and theory is one of several possible products of qualitative research. Researchers decide on which concepts are core in the course of analysis. Researchers are ready to write up their reports when they have settled on, named, and dimensionalized one or more core concepts. The terms “core concepts” and “core categories” are associated with grounded theory ( Charmaz, 2006 ; Corbin & Strauss, 2008 ), but they are useful in other types of qualitative research, such as interpretive phenomenology and narrative analysis. Core concepts both organize findings and, typically, bring together a great deal of information. The term “dimension” means that researchers account for as many aspects of the core concepts as they can in order to show the multiple perspectives and patterns that typically compose concepts.

In reporting on core concepts, I recommend that researchers name them, introduce them, describe them using excerpts from the research material, comment on them, and then situate each of the concepts and their commentaries within their scholarly contexts. As discussed earlier, this shows how the findings fit with what is already known, or add to, force modification of, or refute what is known. Although many researchers, do not situate findings in their scholarly contexts, they usually cover the other topics.

No matter how authors report findings, they should do so with grab. An example of a report exemplary for its grab is the work of Scott (2003) on what it means to be a professional with a physical disability. Scott began her article not with a literature review but with three reviewer comments on other articles she had written. She then stated that the present article was a response to these comments. She followed up with a description of three male students who waited to speak to her after class about her disability and the notion of embodiment that she discussed in class. She brought in related literature throughout the article. Through her own reflections, reports on how others have responded to her, reports on the accounts that three other women with disabilities gave to her as a person with cerebral palsy, and her literature review, Scott not only showed the meanings of disabilities to persons who have them, but also what others say about their own disabilities, what some people who are able-bodied say about women with disabilities, and how all of this connects to what is known about disabilities and to wide-spread beliefs about disabilities. Her article is full of grab, such as the header that read, “The Day I Became Human.” With the authors’ own experience as the centerpiece, this article exemplifies write-ups that demonstrate the meanings of lived experience in various contexts, immersion, grab, and implications for social action. The analysis she presented as part of her findings is exemplary.

In the production of quality research, no matter the type of write-up, there are no short cuts. Research reports based on poetry, for example, are held to the same standards as any other article: grab, immersion, lived experience in context, and implications for action. In addition, such research reports typically locate themselves within social and human sciences traditions. Furman’s (2007) reflections and analysis of poetry that he wrote over the course of many years provide an example of how poetry can be used in qualitative analysis. This kind of research is a type of document analysis. In performance studies, researchers create a theater production of informant’s accounts of their experiences whose purpose is to transform audiences and move them to action ( Saldaña, 2003 ). The performances are the equivalent of research reports and when they are effective, they have the four characteristics of qualitative research under discussion.

Discussion Sections

In traditional research reports, the discussion section follows the results section. In discussion sections, authors reflect on findings, including what the findings are, how findings contribute to understandings of phenomena of interest, the lines of inquiry the results open up, and implications for policy and practice. Other generic topics to consider are those related to the focus of the journal. For example, if the journal’s focus is related to health, then authors show how findings are related to health.

Discussion sections present the author with opportunities to advocate for how his or her research can be used. The applied purposes of Irvine’s (2013) research come through when she devoted an entire page to make observations about implications. She pointed out how her research contributes to a transformation of images of homeless persons as isolated to images of them as engaged in relationships not only with their pets but with other persons, too. She noted that rehousing homeless persons requires a change in policy that would allow them to have pets. Furthermore, she said that caring for a pet “can turn things around” (p. 24).

In the discussion section I wrote with Anderson ( Gilgun & Anderson, 2013 ), we addressed methodological issues, such as the probable existence of other patterns in addition to those we identified and the nonrandom nature of our sample. We also acknowledged the difficulties in working with families in which child sexual abuse has occurred. Since qualitative researchers want to understand lived experiences, we had to prepare ourselves to deal effectively in research areas that are difficult emotionally for us as researchers. Although we may acknowledge the emotional challenges of some topics in reflexivity statements, discussion sections are opportunities for authors to acknowledge the difficulties of using the results we produce. In the article I wrote with Anderson, we made such an acknowledgment, one that we hoped would facilitate more effective practice. We wrote

Practitioners themselves may experience shock, rage, and disgust. The practice of neutrality, in its therapeutic sense, is important in these cases ( Gil & Johnson, 1993 ; Rober, 2011 ). Neutrality means that practitioners maintain their analytic stances while at the same time they remain attuned not only to service users but also to themselves. When practicing neutrality, service providers regulate their own emotional responses in order to remain emotionally available to service users. Neutrality also means that service providers remain open-minded so that they can hear stories that they may not expect to hear; in other words, to make room for the unexpected ( Rober, 2011 ). Attunement to inner processes is a form of reflection that can facilitate the development of trust between service users and providers. When providers are reflective, they are less likely to tune out, close down, and otherwise stop listening to what services users express. When they listen and hear what service users say, they are more likely to facilitate the best possible outcomes in difficult situations ( Weingarten, 2012 ).

Doing research on lived experience can be difficult for informants and for researchers. Acknowledgment of the implications of these difficulties for users of the research has a place in discussion sections.

In summary, most articles are fairly straightforward in their write-ups: focused literature reviews, reflexivity statements in many cases, clear statements of purpose, clarity about sources of research questions and/or hypotheses, identification and definition of key concepts, identification of codes the researcher develops from literature reviews and reflexivity statements, succinct accounting of methods, and findings organized logically by core concepts around which the researcher organizes the multiple dimensions of those concepts. Excellent writing makes articles interesting and accessible. Some kinds of write-ups deviate from these components, but they are held to the same standards of immersion, experiences in context, multiple perspectives, and implications for action and other applications. When authors have the good fortune to have a recommendation to revise and resubmit, suggestions for revisions often improve the quality of the article.

The seemingly endless variations that are possible in the write-up of qualitative research makes writing and reviewing manuscripts challenging, especially when compared to traditions in which rigid rules prevail. However, it is important that approaches to qualitative research continue to evolve to meet with our ever-changing understandings of human phenomena. The clarity and transparency of reports are the fundamental guidelines for making judgments about quality. I often tell my students that the guidelines for doing qualitative research are flexible, and what is important is to be clear about what you did, why you did it, and what you came up with.

The notion of grab is central to write-up. Since qualitative research seeks to understand lived experiences, it is logical that findings report on the lived experiences in vivid terms, replete with quotes from data. This is not to undermine the importance of analysis, but grab is possible even in write-ups that require a great deal of analysis. Grab becomes possible because researchers must provide the evidence for the theories and concepts they develop.

When there are questions about priorities related to informants’ voices, researchers’ interpretations, and prior research, I hope that authors, reviewers, and editors remember that as important as analysis and previous work may be, the voices of informants bring these other important parts of manuscripts to life. Researchers make decisions about whose voices take priority.

There is no one way to respond to these dilemmas. Authors must make their own decisions about what is important to them and then search for journals that will welcome what they want to convey. It’s important to consider pushing the boundaries and writing an article in a way that the researcher thinks will best convey his or her findings.

The importance of quality data, quality analysis, and “grab” are foundational. I began this chapter with a discussion of the balance between description and analysis. I then considered core concepts as organizers of findings, the place of literature reviews, styles of presenting methods and methodologies, and the balance between the voices of informants and researchers. I concluded with the many variations in types of reports that result from the various purposes that qualitative research projects can have. There are many different types of qualitative research and many styles of write-ups. This chapter may sensitize readers to enduring issues in the writing of research reports. Like qualitative research itself, there are multiple points of view on how to write up qualitative research.

Ahmed, A. ( 2013 ). Structural narrative analysis: Understanding experiences of lifestyle migration through two plot typologies. Qualitative Inquiry , 19 , 231–243.

Google Scholar

American Psychological Association. ( 2009 ). The publication manual of the American Psychological Association (6th ed.). Washington, DC: American Psychological Association.

Google Preview

Becker, H. S. ( 1999 ). The Chicago School, so-called. Qualitative Sociology , 22 (1), 3–12.

Becker, H. S. , Geer, B. , Hughes, E. C. , & Strauss, A. L. ( 1961 ). Boys in white: Student culture in medical school . Chicago: University of Chicago Press.

Block, E. ( 2012 ). “That’s what I see:” Enhancing AIDS intervention research through deep ethnography. Qualitative Social Work 14 ( 4 ), 379–394.

Bogdan, R. C. , & Biklen, S. K. ( 2007 ). Qualitative research for education: An introduction to theories and methods (5th ed.). Boston, MA: Allyn & Bacon.

Bennet, B. , Zubrzycki, J. , & Bacon, V. ( 2011 ). What do we know? The experiences of social workers working alongside aboriginal people. Australian Social Work , 64 (1), 20–37.

Blumer, H. ( 1986 ). The methodological position of symbolic interactionism. In H. Blumer (Ed.), Symbolic interactionism: Perspective and method (pp. 1–60). Berkeley: University of California Press.

Bulmer, M. ( 1984 ). The Chicago School of Sociology: Institutionalization, diversity, and the rise of sociological research . Chicago: University of Chicago Press.

Broom, A. F. , & Doron, A. ( 2013 ). Traditional medicines, collective negotiation, and representations of risks in Indian cancer care. Qualitative Health Research , 23 (1), 54–65.

Charmaz, K. ( 2006 ). Constructing Grounded Theory: A practical guide through qualitative analysis . London: Sage.

Corbin, J. , & Straus, A. ( 2008 ). Basics of qualitative research (3rd. ed.). Thousand Oaks, CA: Sage.

Cordeau, M. A. ( 2012 ). Linking the transition: A substantive theory of high stakes clinical simulation. Advances in Nursing Science , 35 (3), E90–E102.

Covan, E. K. ( 2007 ). The discovery of grounded theory in practice: The legacy of multiple methods. In A. Bryant & K. Charmaz (Eds.), The Sage handbook of grounded theory (pp. 58–93). Thousand Oaks, CA: Sage.

Cressey, D. R. ( 1953 ). Other people’s money . Belmont, CA: Wadsworth.

Cronbach, L. ( 1975 ). Beyond the two disciplines of scientific psychology. American Psychologist , 30 , 116–127.

D’Cruz, H. , Gillingham, P. , & Melendez, S. ( 2007 ). Reflexivity, its meanings and relevance for social work: A critical review of the literature. British Journal of Social Work , 37 (1), 73–90.

Dollard, J. ( 1937 ). Caste and class in a southern town . New Haven, CT: Yale University Press.

Eck, B. ( 2013 ). How never-married men make sense of an unintended identity. Journal of Contemporary Ethnography , 42 (1), 31–63.

Egbe, C. O. ( 2013 ). Descriptive poems on a qualitative research with young smokers in southern Nigeria (2013). Qualitative Inquiry , 19 (5), 353–354.

Ellis, C. ( 2009 ). Revision: Autoethnographic reflections on life and work . Walnut Creek, CA: Left Coast Press.

Faris, R. E. L. ( 1967 ). Chicago sociology 1920-1932 . Chicago: University of Chicago Press.

Furman, R. ( 2007 ). Poetry and narrative as qualitative data: Explorations into existential theory. The Indo-Pacific Journal of Phenomenology , 7 , 1–9.

Geertz, C. ( 1973 ). The interpretation of culture . New York: Basic.

Gil, E. , & Johnson, T. C. ( 1993 ). Sexualized children: Assessment and treatment of sexualized children and children who molest . Rockville, MD: Launch Press.

Gilgun, J. F. ( 1983 ). The sexual abuse of the young female in life course perspective. 3058 . Ann Arbor, MI: Dissertations Abstracts International.

Gilgun, J. F. (1984). A non-coercive method of helping children discuss their own sexual abuse. Part II: An example of intervention by multiple qualitative case studies. Scribd.com . Retrieved from http://www.scribd.com/doc/117051267/A-Non-Coercive-Method-of-Helping-Children-Discuss-Their-Own-Sexual-Abuse .

Gilgun, J. F. ( 1995 ). “We shared something special”: The moral discourse of incest perpetrators. Journal of Marriage and the Family , 57 , 265–281.

Gilgun, J. F. ( 1996 a). Human development and adversity in ecological perspective: Part 1: A conceptual framework. Families in Society , 77 , 395–402.

Gilgun, J. F. ( 1996 b). Human development and adversity in ecological perspective, Part 2: Three patterns. Families in Society , 77 , 459–576.

Gilgun, Jane F. (l996c November). The phenomenology of family violence. Paper presented at the Preconference Workshop on Theory Construction and Research Methodology, National Council on Family Relations, Kansas City, MO, November 5.

Gilgun, J. F. (1998, November). A comprehensive theory of family violence. Paper presented at the 28th Preconference Workshop on Theory Construction and Research Methodology, National Council on Family Relations , Milwaukee, WI.

Gilgun, J. F. ( 1999 a). CASPARS: New tools for assessing client risks and strengths. Families in Society , 80 (5), 450–459.

Gilgun, J. F. (1999c, November). In their own words: Men talk about their violence . Paper presented at the 29th Preconference Workshop on Theory Construction and Research Methodology, National Council on Family Relations , Irvine, CA.

Gilgun, Jane F. ( 1999 d ). Methodological pluralism and qualitative family research. In Suzanne K. Steinmetz , Marvin B. Sussman , and Gary W. Peterson (Eds.), Handbook of Marriage and the Family (2nd ed.) (pp. 219–261). New York: Plenum.

Gilgun, J. F. (2000, June 25–28). A comprehensive theory of interpersonal violence . Paper presented at the Victimization of Children and Youth: An International Research Conference, Durham, NH .

Gilgun, J. F. ( 2002 a). Completing the circle: American Indian medicine wheels and the promotion of resilience in children and youth in care. Journal of Human Behavior and the Social Environment , 6 (2), 65–84.

Gilgun, J. F. ( 2002 b). Social work and the assessment of the potential for violence. In T. N. Tiong & I. Dodds (Eds.), Social work around the world II (pp. 58–74). Berne, Switzerland: International Federation of Social Workers.

Gilgun, J. F. ( 2004 a). A strengths-based approach to child and family assessment. In D. R. Catheral (Ed.), Handbook of stress, trauma and the family (pp. 307–324). New York: Bruner-Routledge.

Gilgun, J. F. ( 2004 b). The 4-D: Strengths-based assessments for youth who’ve experienced adversities. Journal of Human Behavior in the Social Environment , 10 (4), 51–73 .

Gilgun, J. F. ( 2005 a). Evidence-based practice, descriptive research, and the resilience-schema-gender-brain (RSGB) assessment. British Journal of Social Work , 35 (6), 843–862.

Gilgun, J. F. ( 2005 b). “ Grab” and good science: Writing up the results of qualitative research. Qualitative Health Research , 15 (2), 256–262.

Gilgun, J. F. ( 2005 c). Lighten up! The citation dilemma in qualitative research. Qualitative Health Research , 15 (5), 721–725.

Gilgun, J. F. ( 2005 d). Qualitative research and family psychology. Journal of Family Psychology , 19 (1), 40–50.

Gilgun, J. F. ( 2006 ). Children and adolescents with problematic sexual behaviors: Lessons from research on resilience. In R. Longo & D. Prescott (Eds.), Current perspectives on working with sexually aggressive youth and youth with sexual behavior problems (pp. 383–394). Holyoke, MA: Neari Press.

Gilgun, Jane F. (2007, November). The legacy of the Chicago School of Sociology for family theory-building, Pre-Conference Workshop on Theory Construction and Research Methodology, National Council on Family Relation, Pittsburgh, PA, November 7.

Gilgun, J. F. ( 2008 ). Lived experience, reflexivity, and research on perpetrators of interpersonal violence. Qualitative Social Work , 7 (2), 181–197.

Gilgun, J. F. ( 2010 ). Reflections on 25 years of research on violence. Reflections: Narratives of Professional Helping , 16 (4), 50–59.

Gilgun, J. F. ( 2012 a). Enduring themes in qualitative family research. Journal of Family Theory and Review , 4 , 80–95.

Gilgun, J. F. (2012b). School shootings are not senseless and other essays on violence . Amazon. http://www.amazon.com/s/ref=nb_sb_noss?url=search-alias%3Ddigital-text&field-keywords=school+shootings+are+not+senseless . Retrieved 2 January 2014.

Gilgun, J. F. (2012c). The thin blue line of police brutality & other essays . Amazon. http://www.amazon.com/s/ref=nb_sb_noss?url=search-alias%3Ddigital-text&field-keywords=the+thin+blue+line+of+police+brutality&rh=n%3A133140011%2Ck%3Athe+thin+blue+line+of+police+brutality . Retrieved 2 January 2014.

Gilgun, J. F. (2013a). The logic of murderous rampages & other essays on violence and its prevention (2nd ed.). Amazon. http://www.amazon.com/Murderous-Rampages-Essays-Violence-Prevention-ebook/dp/B00AYPR18A/ref=sr_1_2?s=digital-text&ie=UTF8&qid=1388681278&sr=1-2&keywords=the+logic+of+murderous+rampages . Retrieved 2 January 2014.

Gilgun, J. F. ( 2013 b). Qualitative family research: Enduring themes and contemporary variations. In G. F. Peterson & K. Bush (Eds.), Handbook of marriage and the family (3rd ed., pp. 91–119). New York: Plenum.

Gilgun, J. F. , & Abrams, L. S. ( 2005 ). Gendered adaptations, resilience, and the perpetration of violence. In M. Ungar (Ed.), Handbook for working with children and Youth: Pathways to resilience across cultures and context (pp. 57–70). Toronto: University of Toronto Press.

Gilgun, J. F. , & Anderson, G. ( 2013 ). Mothers’ perspectives on signs of child sexual abuse in their families. Families in Society , 94 (4), 259–267.

Gilgun, J. F. , Daly, K. , & Handel, G. (Eds.). ( 1992 ). Qualitative methods in family research . Newbury Park, CA: SAGE Publications.

Gilgun, J. F. , Keskinen, S. , Marti, D. J. , & Rice, K. ( 1999 ). Clinical applications of the CASPARS instruments: Boys who act out sexually. Families in Society , 80 (6), 629–641.

Gilgun, J. F. , Klein, C. , & Pranis, K. ( 2000 ). The significance of resources in models of risk. Journal of Interpersonal Violence , 14 , 627–646.

Gilgun, J. F. , & Sands, R. G. (Eds.). ( 2012 ). Special issue: The contributions of qualitative approaches to developmental intervention research. Qualitative Social Work: Research and Practice , 11 (4), 80–95.

Gilgun, J. F. , & Sussman, M. B. (Eds.). ( 1996 ). The methods and methodologies of qualitative family research . New York: Haworth. Also published as a special issue of Marriage and Family Review , 41 (1–2).

Glaser, B. ( 1978 ). Theoretical sensitivity . Mill Valley, CA: Sociology Press.

Glaser, B. , & Strauss, A. ( 1967 ). The discovery of grounded theory . Chicago: Aldine.

Guba, E. G. , & Lincoln, Y. S. ( 2005 ). Paradigmatic controversies, contradictions, and emerging confluences. In N. K. Denzin & Y. S. Lincoln (Eds.), The Sage handbook of qualitative research (3rd ed.). Thousand Oaks, CA: Sage.

Irvine, L. ( 2013 ). Animals as lifechangers and lifesavers: Pets in the redemptive narratives of homeless people. Journal of Contemporary Ethnography , 42 (1), 3–30.

Lindesmith, A. ( 1947 ). Opiate addictions . Bloomington, IN: Principia.

McKinney, J. C. ( 1966 ). Constructive typology and social theory . New York: Appleton-Century-Crofts.

Presser, L. ( 2005 ). Negotiating power and narrative in research: Implications for feminist methodology. Signs: Journal of Women in Culture and Society , 30 (4), 2067–2090.

Rober, P. ( 2011 ). The therapist’s experiencing in family therapy practice. Journal of Family Therapy , 33 , 233–255.

Saldaña, J. ( 2003 ). Dramatizing data: A primer. Qualitative Inquiry , 9 , 218–236.

Schatzman, L. ( 1991 ). Dimensional analysis: Notes on an alternative approach to the grounding of theory in qualitative research. In D. R. Maines (Ed.), Social organizations and social process: Essays in honor of Anselm Strauss (pp. 303–314). New York: Aldine de Gruyter.

Scott, J. A. ( 2003 ). Problematizing a researcher’s performance of “insider status:” An autoethnography of “designer disabled” identity. Qualitative Inquiry , 19 , 101–115.

Sharma, A. , & Gilgun, J. F. ( 2008 ). What perpetrators say about child sexual abuse. Indian Journal of Social Work , 69 (3), 321–338.

Small, A. W. ( 1916 ). Fifty years of sociology in the United States, 1865–1915. American Journal of Sociology , 21 , 712–864.

Spermon, D. Darlington, Y , & Gibney, P. ( 2013 ). Complex posttraumatic stress disorder: Voice of healing. Qualitative Health Research , 24 (1), 43–53.

Velásquez, G. ( 2011 ). Inside the Church of Scientology: An ethnographic performance script. Qualitative Inquiry , 17 , 824–836.

Weingarten, K. ( 2012 ). Sorrow: A therapist’s reflection on the inevitable and the unknowable. Family Process , 51 (4), 440–455.

Winter, K. ( 2010 ). The perspectives of young children in care. Child and Family Social Work , 15 , 186–195.

Young, P. V. (l928). The reorganization of Jewish family life in America. Social Forces , 7 , 238–243.

Young, P. V. (l932). The Pilgrims of Russian Town . Chicago: University of Chicago Press.

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Qualitative research design (and planning)

When many people think of ‘research design’, they think of choosing methods or a methodology. But the design for a qualitative project should also consider existing research, epistemology, how you are going to recruit, and analyse the data from the methods you choose.

Daniel Turner

First of all, you didn’t decide to do qualitative research before considering the question right? That’s the wrong way round. The research question, what you want to find out, should always choose the methodology, not the other way around. However, sometimes an assignment tells you to use qualitative methods – that’s a good exception!

Your methods and research design also need to be practical for the resource limitations of the project. What’s your budget, and how much time do you have to complete it? Can you afford to fly across the world to interview people in every continent? Do you have years to do a situated ethnography? It’s OK to have an initial aspirational plan that you would do with unlimited time and money, but make sure your final design is something you can achieve. Set aside time for things to go wrong (recruitment always takes longer than you think) and also for time to analyse and write up findings. A lot of people plan to keep doing data collection going until a week before the project is due, and then panic when they realise how little time is left. I get a lot of emails from people who say ‘I have one day to finish my analysis’ which is just never enough time.

1. Epistemology

You first need to think and write about your epistemology: this is how you understand knowledge, research, science and what can be understood about the world. Are you a positivist, structural realist or post-positivist? All of these things are important to understand, and in most qualitative research it is necessary to situate your identity as a researcher within one (or more) of these philosophical turns. From this should stem the research questions you have, how you can answer them, the methods you choose, and your interpretation and application of data, be it qualitative or otherwise. Thus it is a key kernel of what will grow into your research design, and how it all flows from your theoretical underpinnings.

Part of this might be a reflexivity and positionality statement , which lays out your background and potential biases. It’s also something ethics boards, journals and funders are increasingly looking for.

2. Literature review (and secondary data scoping)

Before you even begin to design a qualitative study, you need to do at least a basic literature review. This should aim to find out:

How much is already known about this topic?

Has this been done before?

You might find that something similar has been done, possibly in a different population group, or with a different focus. But you might have a good reason to suspect that something would be different in a different population, or with an in-depth qualitative approach there might be something more complicated underneath that you could investigate to explain other findings.

A good literature review should start by looking at both qualitative and quantitative research, because a large quantitative study might be really good context for a follow-on qualitative study that can explain trends or questions and unexpected findings in the research.

Fortunately qualitative software is a great tool for doing literature reviews! You can bring in PDF files of your textbook chapters or journal articles, and not only create a bibliography, but also code important themes and discoveries across them. It makes it easy to compare across papers, and when you come to write up, you can quickly find all the quotes from the literature you will want to quote (and be able to see where they come from). There’s a whole video tutorial on using software for systematic and literature reviews here.

Now, you might be thinking you are going to collect your own data, but secondary data analysis is also a good option to consider. There are lots of choices, including social media, qualitative data archives, documents and sources of data from to colleagues. So have a quick search for other data sources that you can analyse first, it might be these will do most of the work for you, or you can complement them with some smaller primary qualitative research. Our post on using secondary qualitative data can help you find some sources, and notes some issues to be aware of.

3. Sampling and recruitment

Once you have a good idea of what is out there, and what your unique question will be, NOW you can start thinking about methods. But really, you should consider recruitment and sampling first. That is – who do I need to talk to so I can answer these questions? How can I approach these people? Will they be willing to talk to me, or will I have to get access through gatekeepers? Will I be able to meet these people face to face - especially if they live abroad, or are senior people?

Often sampling (which is choosing which people and how many) and recruitment (actually getting them to take part) is overlooked, but it can really make or break good research, and thinking about your potential respondents is important before choosing an appropriate method. If you want to talk to a bunch of murderers held in different prisons, a focus group is going to be difficult (and potentially dangerous) to pull off! We’ve got blog post articles on both sampling and recruitment that will give you a lot more information.

It’s also this process that ethics/instiutional review boards (aka IRBs or ethics committees) will be particularity interested in. You’ll usually need to go through a process like this before your university will allow you to start collecting data. Part of the research design process should be planning for this and creating consent forms that explain your project and what you will do with the data.

Now you know what to ask which people, you can think about how. This is usually when qualitative methods are chosen – the conditions above are right, and a qualitative study is suitable! And there are many to choose from, interviews, focus groups, ethnography, diaries, and we have blog posts on all of these (and more) that will help you choose the right tools to investigate your research question . But there are many more methods beyond these basic ones, so try and consider one of these 10 alternative creative methods! They can be fun, and also more revealing than the standard focus group / interview combo.

You can also do ‘mixed methods’. This technically means using more than one type of method, even if they are all qualitative. However, the term is often used to mean combining qualitative and quantitative methods. This can be very powerful because it gives you the combination of a statistically significant finding which might apply to a large population, and a detailed deep understanding of the reasons behind that finding from the qualitative data. However, combining these different types of answers in a meaningful way is a serious challenge, and if you are planning any type of mixed methods study, you will want to consider how to triangulate the results .

5. Analysis

Qualitative analysis takes a long time. It obviously depends greatly on the type and amount of data, but you should schedule weeks and probably months for this task. You should also consider if you are going to transcribe your data from audio recordings. This can take weeks itself if you are doing it yourself, or you might consider sending to a professional to transcribe. Even automated transcription can look like it will save a lot of time, but always has errors, and you need to read through these carefully and fix mis-hearings. You should also set aside time before analysing your data to read it slowly and carefully so you have a good idea what is across the whole data set.

You also need to think about what type of analysis you are going to do. Approaches like grounded theory or IPA are often seen as just an analytic technique, but they affect the data collection approach and methodology too. With grounded theory, you should probably be collecting and analysing data as you go, rather than waiting till the end. It’s a prime example of how why you should consider all aspects of the research process (even the analysis) before you start.

Qualitative analysis is also not a linear process. This means that many researchers will try multiple types of analysis, look at the data in different ways, and hit dead ends when an approach doesn’t work. So having a very tight deadline for analysis can not only be stressful, but not leave enough time for the flexibility and moments of insight which can make qualitative research so rewarding.

Of course, qualitative analysis software (like Quirkos) can help with the analysis process, it doesn’t take any of the mental work or creative process away, but can help keep things in order and make it easier to find things when writing up. We have many blog post articles on different ways that CAQDAS software can help analysis , but this one on why it’s a good idea to think about what software you will use before you start collecting data is a great fit with putting together a qualitative research plan.

6. Writing up

This is another classic stage that people don’t leave enough time for, writing up can be a very time consuming and laborious process, but can be speeded up immensely by a good research plan. If you’ve done a good literature review, this will help write the introduction and first few chapters. If you’ve got a good practical plan because you had everything in place for your IRB, had realistic expectations for recruitment and gave yourself plenty of time for analysis, you will have all the components to need to plug together and write up. If you’ve used qualitative analysis software, this can also greatly speed up the writing process, because it makes it so quick to find and collate quotes on different themes.

Regardless of whether you are writing a journal article, monograph or thesis, there are some basic tips to improve the quality of written academic material, which this blog post goes into more detail . But the basic take-home message is: consider your audience. Who is reading the paper, for what purpose, what do they know already, and what do they want to know. The final point is always ‘what makes this research unique’ or ‘what does it add to the literature’? Again, a good research design and planning process makes it easy to explain why you’ve chosen a research question, and show that no-one else has done it before.

Conclusions!

Hopefully, this blog post has made a good case for considering holistic research design when planning a qualitative project, but what should this look like? Generally it will be a working document, either on paper or a word-processor document, with at least the key headings above, and some basic information under each section. This can get filled in as you go through the process, and although your institution may have a template or guideline for a similar document, most of the key points above should still be considered.

Finally, if you are applying for funding at any time, be it for a masters/PhD studentship, placement, grant, scholarship or award, you will almost certainly need to share some kind of research plan or proposal, and considering all the aspects of design here will make that a lot easier.

If you are considering what qualitative analysis tool to consider in your research design, and to help with your qualitative research, why not give Quirkos a try? It’s visual and intuitive, inexpensive and easy to learn, and has helped thousands of researchers across the world with their qualitative research. You can download a free trial here , or get a quick guide and overview from some of our free tutorial videos .

Sign up for more like this.

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The word qualitative implies an emphasis on the qualities of entities and on processes and meanings that are not experimentally examined or measured [if measured at all] in terms of quantity, amount, intensity, or frequency. Qualitative researchers stress the socially constructed nature of reality, the intimate relationship between the researcher and what is studied, and the situational constraints that shape inquiry. Such researchers emphasize the value-laden nature of inquiry. They seek answers to questions that stress how social experience is created and given meaning. In contrast, quantitative studies emphasize the measurement and analysis of causal relationships between variables, not processes. Qualitative forms of inquiry are considered by many social and behavioral scientists to be as much a perspective on how to approach investigating a research problem as it is a method.

Denzin, Norman. K. and Yvonna S. Lincoln. “Introduction: The Discipline and Practice of Qualitative Research.” In The Sage Handbook of Qualitative Research . Norman. K. Denzin and Yvonna S. Lincoln, eds. 3 rd edition. (Thousand Oaks, CA: Sage, 2005), p. 10.

Characteristics of Qualitative Research

Below are the three key elements that define a qualitative research study and the applied forms each take in the investigation of a research problem.

Naturalistic -- refers to studying real-world situations as they unfold naturally; non-manipulative and non-controlling; the researcher is open to whatever emerges [i.e., there is a lack of predetermined constraints on findings].
Emergent -- acceptance of adapting inquiry as understanding deepens and/or situations change; the researcher avoids rigid designs that eliminate responding to opportunities to pursue new paths of discovery as they emerge.
Purposeful -- cases for study [e.g., people, organizations, communities, cultures, events, critical incidences] are selected because they are “information rich” and illuminative. That is, they offer useful manifestations of the phenomenon of interest; sampling is aimed at insight about the phenomenon, not empirical generalization derived from a sample and applied to a population.

The Collection of Data

Data -- observations yield a detailed, "thick description" [in-depth understanding]; interviews capture direct quotations about people’s personal perspectives and lived experiences; often derived from carefully conducted case studies and review of material culture.
Personal experience and engagement -- researcher has direct contact with and gets close to the people, situation, and phenomenon under investigation; the researcher’s personal experiences and insights are an important part of the inquiry and critical to understanding the phenomenon.
Empathic neutrality -- an empathic stance in working with study respondents seeks vicarious understanding without judgment [neutrality] by showing openness, sensitivity, respect, awareness, and responsiveness; in observation, it means being fully present [mindfulness].
Dynamic systems -- there is attention to process; assumes change is ongoing, whether the focus is on an individual, an organization, a community, or an entire culture, therefore, the researcher is mindful of and attentive to system and situational dynamics.

The Analysis

Unique case orientation -- assumes that each case is special and unique; the first level of analysis is being true to, respecting, and capturing the details of the individual cases being studied; cross-case analysis follows from and depends upon the quality of individual case studies.
Inductive analysis -- immersion in the details and specifics of the data to discover important patterns, themes, and inter-relationships; begins by exploring, then confirming findings, guided by analytical principles rather than rules.
Holistic perspective -- the whole phenomenon under study is understood as a complex system that is more than the sum of its parts; the focus is on complex interdependencies and system dynamics that cannot be reduced in any meaningful way to linear, cause and effect relationships and/or a few discrete variables.
Context sensitive -- places findings in a social, historical, and temporal context; researcher is careful about [even dubious of] the possibility or meaningfulness of generalizations across time and space; emphasizes careful comparative case study analysis and extrapolating patterns for possible transferability and adaptation in new settings.
Voice, perspective, and reflexivity -- the qualitative methodologist owns and is reflective about her or his own voice and perspective; a credible voice conveys authenticity and trustworthiness; complete objectivity being impossible and pure subjectivity undermining credibility, the researcher's focus reflects a balance between understanding and depicting the world authentically in all its complexity and of being self-analytical, politically aware, and reflexive in consciousness.

Berg, Bruce Lawrence. Qualitative Research Methods for the Social Sciences . 8th edition. Boston, MA: Allyn and Bacon, 2012; Denzin, Norman. K. and Yvonna S. Lincoln. Handbook of Qualitative Research . 2nd edition. Thousand Oaks, CA: Sage, 2000; Marshall, Catherine and Gretchen B. Rossman. Designing Qualitative Research . 2nd ed. Thousand Oaks, CA: Sage Publications, 1995; Merriam, Sharan B. Qualitative Research: A Guide to Design and Implementation . San Francisco, CA: Jossey-Bass, 2009.

Basic Research Design for Qualitative Studies

Unlike positivist or experimental research that utilizes a linear and one-directional sequence of design steps, there is considerable variation in how a qualitative research study is organized. In general, qualitative researchers attempt to describe and interpret human behavior based primarily on the words of selected individuals [a.k.a., “informants” or “respondents”] and/or through the interpretation of their material culture or occupied space. There is a reflexive process underpinning every stage of a qualitative study to ensure that researcher biases, presuppositions, and interpretations are clearly evident, thus ensuring that the reader is better able to interpret the overall validity of the research. According to Maxwell (2009), there are five, not necessarily ordered or sequential, components in qualitative research designs. How they are presented depends upon the research philosophy and theoretical framework of the study, the methods chosen, and the general assumptions underpinning the study. Goals Describe the central research problem being addressed but avoid describing any anticipated outcomes. Questions to ask yourself are: Why is your study worth doing? What issues do you want to clarify, and what practices and policies do you want it to influence? Why do you want to conduct this study, and why should the reader care about the results? Conceptual Framework Questions to ask yourself are: What do you think is going on with the issues, settings, or people you plan to study? What theories, beliefs, and prior research findings will guide or inform your research, and what literature, preliminary studies, and personal experiences will you draw upon for understanding the people or issues you are studying? Note to not only report the results of other studies in your review of the literature, but note the methods used as well. If appropriate, describe why earlier studies using quantitative methods were inadequate in addressing the research problem. Research Questions Usually there is a research problem that frames your qualitative study and that influences your decision about what methods to use, but qualitative designs generally lack an accompanying hypothesis or set of assumptions because the findings are emergent and unpredictable. In this context, more specific research questions are generally the result of an interactive design process rather than the starting point for that process. Questions to ask yourself are: What do you specifically want to learn or understand by conducting this study? What do you not know about the things you are studying that you want to learn? What questions will your research attempt to answer, and how are these questions related to one another? Methods Structured approaches to applying a method or methods to your study help to ensure that there is comparability of data across sources and researchers and, thus, they can be useful in answering questions that deal with differences between phenomena and the explanation for these differences [variance questions]. An unstructured approach allows the researcher to focus on the particular phenomena studied. This facilitates an understanding of the processes that led to specific outcomes, trading generalizability and comparability for internal validity and contextual and evaluative understanding. Questions to ask yourself are: What will you actually do in conducting this study? What approaches and techniques will you use to collect and analyze your data, and how do these constitute an integrated strategy? Validity In contrast to quantitative studies where the goal is to design, in advance, “controls” such as formal comparisons, sampling strategies, or statistical manipulations to address anticipated and unanticipated threats to validity, qualitative researchers must attempt to rule out most threats to validity after the research has begun by relying on evidence collected during the research process itself in order to effectively argue that any alternative explanations for a phenomenon are implausible. Questions to ask yourself are: How might your results and conclusions be wrong? What are the plausible alternative interpretations and validity threats to these, and how will you deal with these? How can the data that you have, or that you could potentially collect, support or challenge your ideas about what’s going on? Why should we believe your results? Conclusion Although Maxwell does not mention a conclusion as one of the components of a qualitative research design, you should formally conclude your study. Briefly reiterate the goals of your study and the ways in which your research addressed them. Discuss the benefits of your study and how stakeholders can use your results. Also, note the limitations of your study and, if appropriate, place them in the context of areas in need of further research.

Chenail, Ronald J. Introduction to Qualitative Research Design. Nova Southeastern University; Heath, A. W. The Proposal in Qualitative Research. The Qualitative Report 3 (March 1997); Marshall, Catherine and Gretchen B. Rossman. Designing Qualitative Research . 3rd edition. Thousand Oaks, CA: Sage, 1999; Maxwell, Joseph A. "Designing a Qualitative Study." In The SAGE Handbook of Applied Social Research Methods . Leonard Bickman and Debra J. Rog, eds. 2nd ed. (Thousand Oaks, CA: Sage, 2009), p. 214-253; Qualitative Research Methods. Writing@CSU. Colorado State University; Yin, Robert K. Qualitative Research from Start to Finish . 2nd edition. New York: Guilford, 2015.

Strengths of Using Qualitative Methods

The advantage of using qualitative methods is that they generate rich, detailed data that leave the participants' perspectives intact and provide multiple contexts for understanding the phenomenon under study. In this way, qualitative research can be used to vividly demonstrate phenomena or to conduct cross-case comparisons and analysis of individuals or groups.

Among the specific strengths of using qualitative methods to study social science research problems is the ability to:

Obtain a more realistic view of the lived world that cannot be understood or experienced in numerical data and statistical analysis;
Provide the researcher with the perspective of the participants of the study through immersion in a culture or situation and as a result of direct interaction with them;
Allow the researcher to describe existing phenomena and current situations;
Develop flexible ways to perform data collection, subsequent analysis, and interpretation of collected information;
Yield results that can be helpful in pioneering new ways of understanding;
Respond to changes that occur while conducting the study ]e.g., extended fieldwork or observation] and offer the flexibility to shift the focus of the research as a result;
Provide a holistic view of the phenomena under investigation;
Respond to local situations, conditions, and needs of participants;
Interact with the research subjects in their own language and on their own terms; and,
Create a descriptive capability based on primary and unstructured data.

Anderson, Claire. “Presenting and Evaluating Qualitative Research.” American Journal of Pharmaceutical Education 74 (2010): 1-7; Denzin, Norman. K. and Yvonna S. Lincoln. Handbook of Qualitative Research . 2nd edition. Thousand Oaks, CA: Sage, 2000; Merriam, Sharan B. Qualitative Research: A Guide to Design and Implementation . San Francisco, CA: Jossey-Bass, 2009.

Limitations of Using Qualitative Methods

It is very much true that most of the limitations you find in using qualitative research techniques also reflect their inherent strengths . For example, small sample sizes help you investigate research problems in a comprehensive and in-depth manner. However, small sample sizes undermine opportunities to draw useful generalizations from, or to make broad policy recommendations based upon, the findings. Additionally, as the primary instrument of investigation, qualitative researchers are often embedded in the cultures and experiences of others. However, cultural embeddedness increases the opportunity for bias generated from conscious or unconscious assumptions about the study setting to enter into how data is gathered, interpreted, and reported.

Some specific limitations associated with using qualitative methods to study research problems in the social sciences include the following:

Drifting away from the original objectives of the study in response to the changing nature of the context under which the research is conducted;
Arriving at different conclusions based on the same information depending on the personal characteristics of the researcher;
Replication of a study is very difficult;
Research using human subjects increases the chance of ethical dilemmas that undermine the overall validity of the study;
An inability to investigate causality between different research phenomena;
Difficulty in explaining differences in the quality and quantity of information obtained from different respondents and arriving at different, non-consistent conclusions;
Data gathering and analysis is often time consuming and/or expensive;
Requires a high level of experience from the researcher to obtain the targeted information from the respondent;
May lack consistency and reliability because the researcher can employ different probing techniques and the respondent can choose to tell some particular stories and ignore others; and,
Generation of a significant amount of data that cannot be randomized into manageable parts for analysis.

Research Tip

Human Subject Research and Institutional Review Board Approval

Almost every socio-behavioral study requires you to submit your proposed research plan to an Institutional Review Board. The role of the Board is to evaluate your research proposal and determine whether it will be conducted ethically and under the regulations, institutional polices, and Code of Ethics set forth by the university. The purpose of the review is to protect the rights and welfare of individuals participating in your study. The review is intended to ensure equitable selection of respondents, that you have met the requirements for obtaining informed consent , that there is clear assessment and minimization of risks to participants and to the university [read: no lawsuits!], and that privacy and confidentiality are maintained throughout the research process and beyond. Go to the USC IRB website for detailed information and templates of forms you need to submit before you can proceed. If you are unsure whether your study is subject to IRB review, consult with your professor or academic advisor.

Chenail, Ronald J. Introduction to Qualitative Research Design. Nova Southeastern University; Labaree, Robert V. "Working Successfully with Your Institutional Review Board: Practical Advice for Academic Librarians." College and Research Libraries News 71 (April 2010): 190-193.

Another Research Tip

Finding Examples of How to Apply Different Types of Research Methods

SAGE publications is a major publisher of studies about how to design and conduct research in the social and behavioral sciences. Their SAGE Research Methods Online and Cases database includes contents from books, articles, encyclopedias, handbooks, and videos covering social science research design and methods including the complete Little Green Book Series of Quantitative Applications in the Social Sciences and the Little Blue Book Series of Qualitative Research techniques. The database also includes case studies outlining the research methods used in real research projects. This is an excellent source for finding definitions of key terms and descriptions of research design and practice, techniques of data gathering, analysis, and reporting, and information about theories of research [e.g., grounded theory]. The database covers both qualitative and quantitative research methods as well as mixed methods approaches to conducting research.

SAGE Research Methods Online and Cases

NOTE : For a list of online communities, research centers, indispensable learning resources, and personal websites of leading qualitative researchers, GO HERE .

For a list of scholarly journals devoted to the study and application of qualitative research methods, GO HERE .

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Research Design – Types, Methods and Examples

Table of Contents

Research Design

Definition:

Research design refers to the overall strategy or plan for conducting a research study. It outlines the methods and procedures that will be used to collect and analyze data, as well as the goals and objectives of the study. Research design is important because it guides the entire research process and ensures that the study is conducted in a systematic and rigorous manner.

Types of Research Design

Types of Research Design are as follows:

Descriptive Research Design

This type of research design is used to describe a phenomenon or situation. It involves collecting data through surveys, questionnaires, interviews, and observations. The aim of descriptive research is to provide an accurate and detailed portrayal of a particular group, event, or situation. It can be useful in identifying patterns, trends, and relationships in the data.

Correlational Research Design

Correlational research design is used to determine if there is a relationship between two or more variables. This type of research design involves collecting data from participants and analyzing the relationship between the variables using statistical methods. The aim of correlational research is to identify the strength and direction of the relationship between the variables.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This type of research design involves manipulating one variable and measuring the effect on another variable. It usually involves randomly assigning participants to groups and manipulating an independent variable to determine its effect on a dependent variable. The aim of experimental research is to establish causality.

Quasi-experimental Research Design

Quasi-experimental research design is similar to experimental research design, but it lacks one or more of the features of a true experiment. For example, there may not be random assignment to groups or a control group. This type of research design is used when it is not feasible or ethical to conduct a true experiment.

Case Study Research Design

Case study research design is used to investigate a single case or a small number of cases in depth. It involves collecting data through various methods, such as interviews, observations, and document analysis. The aim of case study research is to provide an in-depth understanding of a particular case or situation.

Longitudinal Research Design

Longitudinal research design is used to study changes in a particular phenomenon over time. It involves collecting data at multiple time points and analyzing the changes that occur. The aim of longitudinal research is to provide insights into the development, growth, or decline of a particular phenomenon over time.

Structure of Research Design

The format of a research design typically includes the following sections:

Introduction : This section provides an overview of the research problem, the research questions, and the importance of the study. It also includes a brief literature review that summarizes previous research on the topic and identifies gaps in the existing knowledge.
Research Questions or Hypotheses: This section identifies the specific research questions or hypotheses that the study will address. These questions should be clear, specific, and testable.
Research Methods : This section describes the methods that will be used to collect and analyze data. It includes details about the study design, the sampling strategy, the data collection instruments, and the data analysis techniques.
Data Collection: This section describes how the data will be collected, including the sample size, data collection procedures, and any ethical considerations.
Data Analysis: This section describes how the data will be analyzed, including the statistical techniques that will be used to test the research questions or hypotheses.
Results : This section presents the findings of the study, including descriptive statistics and statistical tests.
Discussion and Conclusion : This section summarizes the key findings of the study, interprets the results, and discusses the implications of the findings. It also includes recommendations for future research.
References : This section lists the sources cited in the research design.

Example of Research Design

An Example of Research Design could be:

Research question: Does the use of social media affect the academic performance of high school students?

Research design:

Research approach : The research approach will be quantitative as it involves collecting numerical data to test the hypothesis.
Research design : The research design will be a quasi-experimental design, with a pretest-posttest control group design.
Sample : The sample will be 200 high school students from two schools, with 100 students in the experimental group and 100 students in the control group.
Data collection : The data will be collected through surveys administered to the students at the beginning and end of the academic year. The surveys will include questions about their social media usage and academic performance.
Data analysis : The data collected will be analyzed using statistical software. The mean scores of the experimental and control groups will be compared to determine whether there is a significant difference in academic performance between the two groups.
Limitations : The limitations of the study will be acknowledged, including the fact that social media usage can vary greatly among individuals, and the study only focuses on two schools, which may not be representative of the entire population.
Ethical considerations: Ethical considerations will be taken into account, such as obtaining informed consent from the participants and ensuring their anonymity and confidentiality.

How to Write Research Design

Writing a research design involves planning and outlining the methodology and approach that will be used to answer a research question or hypothesis. Here are some steps to help you write a research design:

Define the research question or hypothesis : Before beginning your research design, you should clearly define your research question or hypothesis. This will guide your research design and help you select appropriate methods.
Select a research design: There are many different research designs to choose from, including experimental, survey, case study, and qualitative designs. Choose a design that best fits your research question and objectives.
Develop a sampling plan : If your research involves collecting data from a sample, you will need to develop a sampling plan. This should outline how you will select participants and how many participants you will include.
Define variables: Clearly define the variables you will be measuring or manipulating in your study. This will help ensure that your results are meaningful and relevant to your research question.
Choose data collection methods : Decide on the data collection methods you will use to gather information. This may include surveys, interviews, observations, experiments, or secondary data sources.
Create a data analysis plan: Develop a plan for analyzing your data, including the statistical or qualitative techniques you will use.
Consider ethical concerns : Finally, be sure to consider any ethical concerns related to your research, such as participant confidentiality or potential harm.

When to Write Research Design

Research design should be written before conducting any research study. It is an important planning phase that outlines the research methodology, data collection methods, and data analysis techniques that will be used to investigate a research question or problem. The research design helps to ensure that the research is conducted in a systematic and logical manner, and that the data collected is relevant and reliable.

Ideally, the research design should be developed as early as possible in the research process, before any data is collected. This allows the researcher to carefully consider the research question, identify the most appropriate research methodology, and plan the data collection and analysis procedures in advance. By doing so, the research can be conducted in a more efficient and effective manner, and the results are more likely to be valid and reliable.

Purpose of Research Design

The purpose of research design is to plan and structure a research study in a way that enables the researcher to achieve the desired research goals with accuracy, validity, and reliability. Research design is the blueprint or the framework for conducting a study that outlines the methods, procedures, techniques, and tools for data collection and analysis.

Some of the key purposes of research design include:

Providing a clear and concise plan of action for the research study.
Ensuring that the research is conducted ethically and with rigor.
Maximizing the accuracy and reliability of the research findings.
Minimizing the possibility of errors, biases, or confounding variables.
Ensuring that the research is feasible, practical, and cost-effective.
Determining the appropriate research methodology to answer the research question(s).
Identifying the sample size, sampling method, and data collection techniques.
Determining the data analysis method and statistical tests to be used.
Facilitating the replication of the study by other researchers.
Enhancing the validity and generalizability of the research findings.

Applications of Research Design

There are numerous applications of research design in various fields, some of which are:

Social sciences: In fields such as psychology, sociology, and anthropology, research design is used to investigate human behavior and social phenomena. Researchers use various research designs, such as experimental, quasi-experimental, and correlational designs, to study different aspects of social behavior.
Education : Research design is essential in the field of education to investigate the effectiveness of different teaching methods and learning strategies. Researchers use various designs such as experimental, quasi-experimental, and case study designs to understand how students learn and how to improve teaching practices.
Health sciences : In the health sciences, research design is used to investigate the causes, prevention, and treatment of diseases. Researchers use various designs, such as randomized controlled trials, cohort studies, and case-control studies, to study different aspects of health and healthcare.
Business : Research design is used in the field of business to investigate consumer behavior, marketing strategies, and the impact of different business practices. Researchers use various designs, such as survey research, experimental research, and case studies, to study different aspects of the business world.
Engineering : In the field of engineering, research design is used to investigate the development and implementation of new technologies. Researchers use various designs, such as experimental research and case studies, to study the effectiveness of new technologies and to identify areas for improvement.

Advantages of Research Design

Here are some advantages of research design:

Systematic and organized approach : A well-designed research plan ensures that the research is conducted in a systematic and organized manner, which makes it easier to manage and analyze the data.
Clear objectives: The research design helps to clarify the objectives of the study, which makes it easier to identify the variables that need to be measured, and the methods that need to be used to collect and analyze data.
Minimizes bias: A well-designed research plan minimizes the chances of bias, by ensuring that the data is collected and analyzed objectively, and that the results are not influenced by the researcher’s personal biases or preferences.
Efficient use of resources: A well-designed research plan helps to ensure that the resources (time, money, and personnel) are used efficiently and effectively, by focusing on the most important variables and methods.
Replicability: A well-designed research plan makes it easier for other researchers to replicate the study, which enhances the credibility and reliability of the findings.
Validity: A well-designed research plan helps to ensure that the findings are valid, by ensuring that the methods used to collect and analyze data are appropriate for the research question.
Generalizability : A well-designed research plan helps to ensure that the findings can be generalized to other populations, settings, or situations, which increases the external validity of the study.

Research Design Vs Research Methodology

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Designing a Research Proposal in Qualitative Research

First Online: 27 October 2022

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Md. Ismail Hossain 4 ,
Nafiul Mehedi 4 &
Iftakhar Ahmad 4

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The chapter discusses designing a research proposal in qualitative research. The main objective is to outline the major components of a qualitative research proposal with example(s) so that the students and novice scholars easily get an understanding of a qualitative proposal. The chapter highlights the major components of a qualitative research proposal and discusses the steps involved in designing a proposal. In each step, an example is given with some essential tips. Following these steps and tips, a novice researcher can easily prepare a qualitative research proposal. Readers, especially undergraduate and master’s students, might use this as a guideline while preparing a thesis proposal. After reading this chapter, they can easily prepare a qualitative proposal.

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Abdulai, R. T., & Owusu-Ansah, A. (2014). Essential ingredients of a good research proposal for undergraduate and postgraduate students in the social sciences. SAGE Open, 4 (3), 2158244014548178.

Article Google Scholar

Ahmad, S., Wasim, S., Irfan, S., Gogoi, S., Srivastava, A., & Farheen, Z. (2019). Qualitative versus quantitative research. Population, 1 , 2.

Google Scholar

Al-Riyami, A. (2008). How to prepare a research proposal. Oman Medical Journal, 23 (2), 66.

Aspers, P., & Corte, U. (2019). What is qualitative in qualitative research? Qualitative Sociology, 42 (2), 139–160.

Balakumar, P., Inamdar, M. N., & Jagadeesh, G. (2013). The critical steps for successful research: The research proposal and scientific writing (A report on the pre-conference workshop held in conjunction with the 64th annual conference of the Indian Pharmaceutical Congress-2012). Journal of Pharmacology & Pharmacotherapeutics, 4 (2), 130.

Becker, H. (1996). The epistemology of qualitative research. In R. Jessor, A. Colby & R. A Shweder (Eds.), Ethnography and human development: Context and meaning in social inquiry .

Boeije, H. (2010). Analysis in qualitative research . Los Angeles Sage Publications.

Bryman, A., Bresnen, M., Beardsworth, A., & Keil, T. (1988). Qualitative research and the study of leadership. Human Relations, 41 (1), 13–29.

Campbell, D. T., & Stanley, J. C. (2015). Experimental and quasi-experimental designs for research . Ravenio Books.

Creswell, J. W. (1994). Research design: Qualitative and quantitative approach . London: Publications.

Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches (4th Edn.). London: SAGE Publications, Inc.

Davis, B. (2021). What is the scope of the study in research proposal? Retrieved from https://www.mvorganizing.org/what-is-the-scope-of-the-study-in-research-proposal-4/#What_are_strengths_and_limitations . Accessed on August 28, 2021.

Denzin, N. K., & Lincoln, Y. S. (2005). Introduction: The discipline and practice of qualitative research. In N. K. Denzin & Y. S. Lincoln (Eds.), The Sage handbook of qualitative research (pp. 1–32). Sage Publications Ltd.

DJS Research. (2021). Qualitative research design . Retrieved from https://www.djsresearch.co.uk/glossary/item/Qualitative-Research-Design . Accessed on September 12, 2021.

Durrheim, K. (2006). Research design. In M. T. Blanche, M. J. T. Blanche, K. Durrheim, & D. Painter (Eds.), Research in practice: Applied methods for the social sciences (Vol. 2, pp. 33–59). Juta and Company Ltd.

Editage Insights. (2019). How do I present the scope of my study? Retrieved from https://www.editage.com/insights/how-do-i-present-scope-of-my-study . Accessed on August 31, 2021.

Fry, J., Scammell, J., & Barker, S. (2017). Drowning in muddied waters or swimming downstream? A critical analysis of literature reviewing in a phenomenological study through an exploration of the lifeworld, reflexivity and role of the researcher. Indo-Pacific Journal of Phenomenology , 17 (1).

Grove, S. K., Burns, N., & Gray, J. (2012). The practice of nursing research: Appraisal, synthesis, and generation of evidence . Elsevier Health Sciences.

Islam, M. R. (2019). Designing a Ph.D. proposal in qualitative research. In Social research methodology and new techniques in analysis, interpretation, and writing (pp. 1–22). IGI Global.

James, N., & Busher, H. (2009). Epistemological dimensions in qualitative research: The construction of knowledge online. SAGE Internet Research Methods , 5–18.

Liamputtong, P., & Ezzy, D. (2005). Qualitative research methods. Second . Oxford University Press.

Morse, J. M., & Field, P. A. (1996). The purpose of qualitative research. In Nursing research (pp. 1–17). Springer.

Mouton, J., & Marais, H. C. (1990). Basic concepts in the methodology of the social sciences (Revised). Human Sciences Research Council.

Parahoo, K. (2014). Nursing research: principles, process and issues (3rd ed.). Palgrave.

Pathak, V., Jena, B., & Kalra, S. (2013). Qualitative research. Perspectives in Clinical Research, 4 (3), 192. https://doi.org/10.4103/2229-3485.115389

Patton, A. J. (2001). Modelling time-varying exchange rate dependence using the conditional copula.

Pietilä, A. M., Nurmi, S. M., Halkoaho, A., & Kyngäs, H. (2020). Qualitative research: Ethical considerations. In The application of content analysis in nursing science research (pp. 49–69). Springer.

Rosenthal, M. (2016). Qualitative research methods: Why, when, and how to conduct interviews and focus groups in pharmacy research. Currents in Pharmacy Teaching and Learning, 8 (4), 509–516.

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

Sandelowski, M., & Barroso, J. (2003). Writing the proposal for a qualitative research methodology project. Qualitative Health Research, 13 (6), 781–820.

Strauss, A., & Corbin, J. (1990). Basics of qualitative research . Sage publications.

Walker, W. (2007). Ethical considerations in phenomenological research. Nurse researcher , 14 (3).

Wilson, A. (2015). A guide to phenomenological research. Nursing Standard, 29 (34), 38–43.

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Hossain, M.I., Mehedi, N., Ahmad, I. (2022). Designing a Research Proposal in Qualitative Research. In: Islam, M.R., Khan, N.A., Baikady, R. (eds) Principles of Social Research Methodology. Springer, Singapore. https://doi.org/10.1007/978-981-19-5441-2_18

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1 Institut für Bildungswissenschaft, Universität Wien, Sensengasse 3a, 1090 Wien, Austria

R. Burke Johnson

2 Department of Professional Studies, University of South Alabama, UCOM 3700, 36688-0002 Mobile, AL USA

This article provides researchers with knowledge of how to design a high quality mixed methods research study. To design a mixed study, researchers must understand and carefully consider each of the dimensions of mixed methods design, and always keep an eye on the issue of validity. We explain the seven major design dimensions: purpose, theoretical drive, timing (simultaneity and dependency), point of integration, typological versus interactive design approaches, planned versus emergent design, and design complexity. There also are multiple secondary dimensions that need to be considered during the design process. We explain ten secondary dimensions of design to be considered for each research study. We also provide two case studies showing how the mixed designs were constructed.

Zusammenfassung

Der Beitrag gibt einen Überblick darüber, wie das Forschungsdesign bei Mixed Methods-Studien angelegt sein sollte. Um ein Mixed Methods-Forschungsdesign aufzustellen, müssen Forschende sorgfältig alle Dimensionen von Methodenkombinationen abwägen und von Anfang an auf die Güte und damit verbundene etwaige Probleme achten. Wir erklären und diskutieren die für Forschungsdesigns relevanten sieben Dimensionen von Methodenkombinationen: Untersuchungsziel, Rolle von Theorie im Forschungsprozess, Timing (Simultanität und Abhängigkeit), Schnittstellen, an denen Integration stattfindet, systematische vs. interaktive Design-Ansätze, geplante vs. emergente Designs und Komplexität des Designs. Es gibt außerdem zahlreiche sekundäre Dimensionen, die bei der Aufstellung des Forschungsdesigns berücksichtigt werden müssen, von denen wir zehn erklären. Der Beitrag schließt mit zwei Fallbeispielen ab, anhand derer konkret gezeigt wird, wie Mixed Methods-Forschungsdesigns aufgestellt werden können.

What is a mixed methods design?

This article addresses the process of selecting and constructing mixed methods research (MMR) designs. The word “design” has at least two distinct meanings in mixed methods research (Maxwell 2013 ). One meaning focuses on the process of design; in this meaning, design is often used as a verb. Someone can be engaged in designing a study (in German: “eine Studie konzipieren” or “eine Studie designen”). Another meaning is that of a product, namely the result of designing. The result of designing as a verb is a mixed methods design as a noun (in German: “das Forschungsdesign” or “Design”), as it has, for example, been described in a journal article. In mixed methods design, both meanings are relevant. To obtain a strong design as a product, one needs to carefully consider a number of rules for designing as an activity. Obeying these rules is not a guarantee of a strong design, but it does contribute to it. A mixed methods design is characterized by the combination of at least one qualitative and one quantitative research component. For the purpose of this article, we use the following definition of mixed methods research (Johnson et al. 2007 , p. 123):

Mixed methods research is the type of research in which a researcher or team of researchers combines elements of qualitative and quantitative research approaches (e. g., use of qualitative and quantitative viewpoints, data collection, analysis, inference techniques) for the broad purposes of breadth and depth of understanding and corroboration.

Mixed methods research (“Mixed Methods” or “MM”) is the sibling of multimethod research (“Methodenkombination”) in which either solely multiple qualitative approaches or solely multiple quantitative approaches are combined.

In a commonly used mixed methods notation system (Morse 1991 ), the components are indicated as qual and quan (or QUAL and QUAN to emphasize primacy), respectively, for qualitative and quantitative research. As discussed below, plus (+) signs refer to concurrent implementation of components (“gleichzeitige Durchführung der Teilstudien” or “paralleles Mixed Methods-Design”) and arrows (→) refer to sequential implementation (“Sequenzielle Durchführung der Teilstudien” or “sequenzielles Mixed Methods-Design”) of components. Note that each research tradition receives an equal number of letters (four) in its abbreviation for equity. In this article, this notation system is used in some depth.

A mixed methods design as a product has several primary characteristics that should be considered during the design process. As shown in Table 1 , the following primary design “dimensions” are emphasized in this article: purpose of mixing, theoretical drive, timing, point of integration, typological use, and degree of complexity. These characteristics are discussed below. We also provide some secondary dimensions to consider when constructing a mixed methods design (Johnson and Christensen 2017 ).

List of Primary and Secondary Design Dimensions

On the basis of these dimensions, mixed methods designs can be classified into a mixed methods typology or taxonomy. In the mixed methods literature, various typologies of mixed methods designs have been proposed (for an overview see Creswell and Plano Clark 2011 , p. 69–72).

The overall goal of mixed methods research, of combining qualitative and quantitative research components, is to expand and strengthen a study’s conclusions and, therefore, contribute to the published literature. In all studies, the use of mixed methods should contribute to answering one’s research questions.

Ultimately, mixed methods research is about heightened knowledge and validity. The design as a product should be of sufficient quality to achieve multiple validities legitimation (Johnson and Christensen 2017 ; Onwuegbuzie and Johnson 2006 ), which refers to the mixed methods research study meeting the relevant combination or set of quantitative, qualitative, and mixed methods validities in each research study.

Given this goal of answering the research question(s) with validity, a researcher can nevertheless have various reasons or purposes for wanting to strengthen the research study and its conclusions. Following is the first design dimension for one to consider when designing a study: Given the research question(s), what is the purpose of the mixed methods study?

A popular classification of purposes of mixed methods research was first introduced in 1989 by Greene, Caracelli, and Graham, based on an analysis of published mixed methods studies. This classification is still in use (Greene 2007 ). Greene et al. ( 1989 , p. 259) distinguished the following five purposes for mixing in mixed methods research:

1. Triangulation seeks convergence, corroboration, correspondence of results from different methods; 2. Complementarity seeks elaboration, enhancement, illustration, clarification of the results from one method with the results from the other method; 3. Development seeks to use the results from one method to help develop or inform the other method, where development is broadly construed to include sampling and implementation, as well as measurement decisions; 4. Initiation seeks the discovery of paradox and contradiction, new perspectives of frameworks, the recasting of questions or results from one method with questions or results from the other method; 5. Expansion seeks to extend the breadth and range of inquiry by using different methods for different inquiry components.

In the past 28 years, this classification has been supplemented by several others. On the basis of a review of the reasons for combining qualitative and quantitative research mentioned by the authors of mixed methods studies, Bryman ( 2006 ) formulated a list of more concrete rationales for performing mixed methods research (see Appendix). Bryman’s classification breaks down Greene et al.’s ( 1989 ) categories into several aspects, and he adds a number of additional aspects, such as the following:

(a) Credibility – refers to suggestions that employing both approaches enhances the integrity of findings. (b) Context – refers to cases in which the combination is justified in terms of qualitative research providing contextual understanding coupled with either generalizable, externally valid findings or broad relationships among variables uncovered through a survey. (c) Illustration – refers to the use of qualitative data to illustrate quantitative findings, often referred to as putting “meat on the bones” of “dry” quantitative findings. (d) Utility or improving the usefulness of findings – refers to a suggestion, which is more likely to be prominent among articles with an applied focus, that combining the two approaches will be more useful to practitioners and others. (e) Confirm and discover – this entails using qualitative data to generate hypotheses and using quantitative research to test them within a single project. (f) Diversity of views – this includes two slightly different rationales – namely, combining researchers’ and participants’ perspectives through quantitative and qualitative research respectively, and uncovering relationships between variables through quantitative research while also revealing meanings among research participants through qualitative research. (Bryman, p. 106)

Views can be diverse (f) in various ways. Some examples of mixed methods design that include a diversity of views are:

Iteratively/sequentially connecting local/idiographic knowledge with national/general/nomothetic knowledge;
Learning from different perspectives on teams and in the field and literature;
Achieving multiple participation, social justice, and action;
Determining what works for whom and the relevance/importance of context;
Producing interdisciplinary substantive theory, including/comparing multiple perspectives and data regarding a phenomenon;
Juxtaposition-dialogue/comparison-synthesis;
Breaking down binaries/dualisms (some of both);
Explaining interaction between/among natural and human systems;
Explaining complexity.

The number of possible purposes for mixing is very large and is increasing; hence, it is not possible to provide an exhaustive list. Greene et al.’s ( 1989 ) purposes, Bryman’s ( 2006 ) rationales, and our examples of a diversity of views were formulated as classifications on the basis of examination of many existing research studies. They indicate how the qualitative and quantitative research components of a study relate to each other. These purposes can be used post hoc to classify research or a priori in the design of a new study. When designing a mixed methods study, it is sometimes helpful to list the purpose in the title of the study design.

The key point of this section is for the researcher to begin a study with at least one research question and then carefully consider what the purposes for mixing are. One can use mixed methods to examine different aspects of a single research question, or one can use separate but related qualitative and quantitative research questions. In all cases, the mixing of methods, methodologies, and/or paradigms will help answer the research questions and make improvements over a more basic study design. Fuller and richer information will be obtained in the mixed methods study.

Theoretical drive

In addition to a mixing purpose, a mixed methods research study might have an overall “theoretical drive” (Morse and Niehaus 2009 ). When designing a mixed methods study, it is occasionally helpful to list the theoretical drive in the title of the study design. An investigation, in Morse and Niehaus’s ( 2009 ) view, is focused primarily on either exploration-and-description or on testing-and-prediction. In the first case, the theoretical drive is called “inductive” or “qualitative”; in the second case, it is called “deductive” or “quantitative”. In the case of mixed methods, the component that corresponds to the theoretical drive is referred to as the “core” component (“Kernkomponente”), and the other component is called the “supplemental” component (“ergänzende Komponente”). In Morse’s notation system, the core component is written in capitals and the supplemental component is written in lowercase letters. For example, in a QUAL → quan design, more weight is attached to the data coming from the core qualitative component. Due to the decisive character of the core component, the core component must be able to stand on its own, and should be implemented rigorously. The supplemental component does not have to stand on its own.

Although this distinction is useful in some circumstances, we do not advise to apply it to every mixed methods design. First, Morse and Niehaus contend that the supplemental component can be done “less rigorously” but do not explain which aspects of rigor can be dropped. In addition, the idea of decreased rigor is in conflict with one key theme of the present article, namely that mixed methods designs should always meet the criterion of multiple validities legitimation (Onwuegbuzie and Johnson 2006 ).

The idea of theoretical drive as explicated by Morse and Niehaus has been criticized. For example, we view a theoretical drive as a feature not of a whole study, but of a research question, or, more precisely, of an interpretation of a research question. For example, if one study includes multiple research questions, it might include several theoretical drives (Schoonenboom 2016 ).

Another criticism of Morse and Niehaus’ conceptualization of theoretical drive is that it does not allow for equal-status mixed methods research (“Mixed Methods Forschung, bei der qualitative und quantitative Methoden die gleiche Bedeutung haben” or “gleichrangige Mixed Methods-Designs”), in which both the qualitative and quantitative component are of equal value and weight; this same criticism applies to Morgan’s ( 2014 ) set of designs. We agree with Greene ( 2015 ) that mixed methods research can be integrated at the levels of method, methodology, and paradigm. In this view, equal-status mixed methods research designs are possible, and they result when both the qualitative and the quantitative components, approaches, and thinking are of equal value, they take control over the research process in alternation, they are in constant interaction, and the outcomes they produce are integrated during and at the end of the research process. Therefore, equal-status mixed methods research (that we often advocate) is also called “interactive mixed methods research”.

Mixed methods research can have three different drives, as formulated by Johnson et al. ( 2007 , p. 123):

Qualitative dominant [or qualitatively driven] mixed methods research is the type of mixed research in which one relies on a qualitative, constructivist-poststructuralist-critical view of the research process, while concurrently recognizing that the addition of quantitative data and approaches are likely to benefit most research projects. Quantitative dominant [or quantitatively driven] mixed methods research is the type of mixed research in which one relies on a quantitative, postpositivist view of the research process, while concurrently recognizing that the addition of qualitative data and approaches are likely to benefit most research projects. (p. 124) The area around the center of the [qualitative-quantitative] continuum, equal status , is the home for the person that self-identifies as a mixed methods researcher. This researcher takes as his or her starting point the logic and philosophy of mixed methods research. These mixed methods researchers are likely to believe that qualitative and quantitative data and approaches will add insights as one considers most, if not all, research questions.

We leave it to the reader to decide if he or she desires to conduct a qualitatively driven study, a quantitatively driven study, or an equal-status/“interactive” study. According to the philosophies of pragmatism (Johnson and Onwuegbuzie 2004 ) and dialectical pluralism (Johnson 2017 ), interactive mixed methods research is very much a possibility. By successfully conducting an equal-status study, the pragmatist researcher shows that paradigms can be mixed or combined, and that the incompatibility thesis does not always apply to research practice. Equal status research is most easily conducted when a research team is composed of qualitative, quantitative, and mixed researchers, interacts continually, and conducts a study to address one superordinate goal.

Timing: simultaneity and dependence

Another important distinction when designing a mixed methods study relates to the timing of the two (or more) components. When designing a mixed methods study, it is usually helpful to include the word “concurrent” (“parallel”) or “sequential” (“sequenziell”) in the title of the study design; a complex design can be partially concurrent and partially sequential. Timing has two aspects: simultaneity and dependence (Guest 2013 ).

Simultaneity (“Simultanität”) forms the basis of the distinction between concurrent and sequential designs. In a sequential design , the quantitative component precedes the qualitative component, or vice versa. In a concurrent design , both components are executed (almost) simultaneously. In the notation of Morse ( 1991 ), concurrence is indicated by a “+” between components (e. g., QUAL + quan), while sequentiality is indicated with a “→” (QUAL → quan). Note that the use of capital letters for one component and lower case letters for another component in the same design suggest that one component is primary and the other is secondary or supplemental.

Some designs are sequential by nature. For example, in a conversion design, qualitative categories and themes might be first obtained by collection and analysis of qualitative data, and then subsequently quantitized (Teddlie and Tashakkori 2009 ). Likewise, with Greene et al.’s ( 1989 ) initiation purpose, the initiation strand follows the unexpected results that it is supposed to explain. In other cases, the researcher has a choice. It is possible, e. g., to collect interview data and survey data of one inquiry simultaneously; in that case, the research activities would be concurrent. It is also possible to conduct the interviews after the survey data have been collected (or vice versa); in that case, research activities are performed sequentially. Similarly, a study with the purpose of expansion can be designed in which data on an effect and the intervention process are collected simultaneously, or they can be collected sequentially.

A second aspect of timing is dependence (“Abhängigkeit”) . We call two research components dependent if the implementation of the second component depends on the results of data analysis in the first component. Two research components are independent , if their implementation does not depend on the results of data analysis in the other component. Often, a researcher has a choice to perform data analysis independently or not. A researcher could analyze interview data and questionnaire data of one inquiry independently; in that case, the research activities would be independent. It is also possible to let the interview questions depend upon the outcomes of the analysis of the questionnaire data (or vice versa); in that case, research activities are performed dependently. Similarly, the empirical outcome/effect and process in a study with the purpose of expansion might be investigated independently, or the process study might take the effect/outcome as given (dependent).

In the mixed methods literature, the distinction between sequential and concurrent usually refers to the combination of concurrent/independent and sequential/dependent, and to the combination of data collection and data analysis. It is said that in a concurrent design, the data collection and data analysis of both components occurs (almost) simultaneously and independently, while in a sequential design, the data collection and data analysis of one component take place after the data collection and data analysis of the other component and depends on the outcomes of the other component.

In our opinion, simultaneity and dependence are two separate dimensions. Simultaneity indicates whether data collection is done concurrent or sequentially. Dependence indicates whether the implementation of one component depends upon the results of data analysis of the other component. As we will see in the example case studies, a concurrent design could include dependent data analysis, and a sequential design could include independent data analysis. It is conceivable that one simultaneously conducts interviews and collects questionnaire data (concurrent), while allowing the analysis focus of the interviews to depend on what emerges from the survey data (dependence).

Dependent research activities include a redirection of subsequent research inquiry. Using the outcomes of the first research component, the researcher decides what to do in the second component. Depending on the outcomes of the first research component, the researcher will do something else in the second component. If this is so, the research activities involved are said to be sequential-dependent, and any component preceded by another component should appropriately build on the previous component (see sequential validity legitimation ; Johnson and Christensen 2017 ; Onwuegbuzie and Johnson 2006 ).

It is under the purposive discretion of the researcher to determine whether a concurrent-dependent design, a concurrent-independent design, a sequential-dependent design, or a sequential-dependent design is needed to answer a particular research question or set of research questions in a given situation.

Point of integration

Each true mixed methods study has at least one “point of integration” – called the “point of interface” by Morse and Niehaus ( 2009 ) and Guest ( 2013 ) –, at which the qualitative and quantitative components are brought together. Having one or more points of integration is the distinguishing feature of a design based on multiple components. It is at this point that the components are “mixed”, hence the label “mixed methods designs”. The term “mixing”, however, is misleading, as the components are not simply mixed, but have to be integrated very carefully.

Determining where the point of integration will be, and how the results will be integrated, is an important, if not the most important, decision in the design of mixed methods research. Morse and Niehaus ( 2009 ) identify two possible points of integration: the results point of integration and the analytical point of integration.

Most commonly, integration takes place in the results point of integration . At some point in writing down the results of the first component, the results of the second component are added and integrated. A joint display (listing the qualitative and quantitative findings and an integrative statement) might be used to facilitate this process.

In the case of an analytical point of integration , a first analytical stage of a qualitative component is followed by a second analytical stage, in which the topics identified in the first analytical stage are quantitized. The results of the qualitative component ultimately, and before writing down the results of the analytical phase as a whole, become quantitative; qualitizing also is a possible strategy, which would be the converse of this.

Other authors assume more than two possible points of integration. Teddlie and Tashakkori ( 2009 ) distinguish four different stages of an investigation: the conceptualization stage, the methodological experimental stage (data collection), the analytical experimental stage (data analysis), and the inferential stage. According to these authors, in all four stages, mixing is possible, and thus all four stages are potential points or integration.

However, the four possible points of integration used by Teddlie and Tashakkori ( 2009 ) are still too coarse to distinguish some types of mixing. Mixing in the experiential stage can take many different forms, for example the use of cognitive interviews to improve a questionnaire (tool development), or selecting people for an interview on the basis of the results of a questionnaire (sampling). Extending the definition by Guest ( 2013 ), we define the point of integration as “any point in a study where two or more research components are mixed or connected in some way”. Then, the point of integration in the two examples of this paragraph can be defined more accurately as “instrument development”, and “development of the sample”.

It is at the point of integration that qualitative and quantitative components are integrated. Some primary ways that the components can be connected to each other are as follows:

(1) merging the two data sets, (2) connecting from the analysis of one set of data to the collection of a second set of data, (3) embedding of one form of data within a larger design or procedure, and (4) using a framework (theoretical or program) to bind together the data sets (Creswell and Plano Clark 2011 , p. 76).

More generally, one can consider mixing at any or all of the following research components: purposes, research questions, theoretical drive, methods, methodology, paradigm, data, analysis, and results. One can also include mixing views of different researchers, participants, or stakeholders. The creativity of the mixed methods researcher designing a study is extensive.

Substantively, it can be useful to think of integration or mixing as comparing and bringing together two (or more) components on the basis of one or more of the purposes set out in the first section of this article. For example, it is possible to use qualitative data to illustrate a quantitative effect, or to determine whether the qualitative and the quantitative component yield convergent results ( triangulation ). An integrated result could also consist of a combination of a quantitatively established effect and a qualitative description of the underlying process . In the case of development, integration consists of an adjustment of an, often quantitative, for example, instrument or model or interpretation, based on qualitative assessments by members of the target group.

A special case is the integration of divergent results. The power of mixed methods research is its ability to deal with diversity and divergence. In the literature, we find two kinds of strategies for dealing with divergent results. A first set of strategies takes the detected divergence as the starting point for further analysis, with the aim to resolve the divergence. One possibility is to carry out further research (Cook 1985 ; Greene and Hall 2010 ). Further research is not always necessary. One can also look for a more comprehensive theory, which is able to account for both the results of the first component and the deviating results of the second component. This is a form of abduction (Erzberger and Prein 1997 ).

A fruitful starting point in trying to resolve divergence through abduction is to determine which component has resulted in a finding that is somehow expected, logical, and/or in line with existing research. The results of this research component, called the “sense” (“Lesart”), are subsequently compared to the results of the other component, called the “anti-sense” (“alternative Lesart”), which are considered dissonant, unexpected, and/or contrary to what had been found in the literature. The aim is to develop an overall explanation that fits both the sense and the anti-sense (Bazeley and Kemp 2012 ; Mendlinger and Cwikel 2008 ). Finally, a reanalysis of the data can sometimes lead to resolving divergence (Creswell and Plano Clark 2011 ).

Alternatively, one can question the existence of the encountered divergence. In this regard, Mathison ( 1988 ) recommends determining whether deviating results shown by the data can be explained by knowledge about the research and/or knowledge of the social world. Differences between results from different data sources could also be the result of properties of the methods involved, rather than reflect differences in reality (Yanchar and Williams 2006 ). In general, the conclusions of the individual components can be subjected to an inference quality audit (Teddlie and Tashakkori 2009 ), in which the researcher investigates the strength of each of the divergent conclusions. We recommend that researchers first determine whether there is “real” divergence, according to the strategies mentioned in the last paragraph. Next, an attempt can be made to resolve cases of “true” divergence, using one or more of the methods mentioned in this paragraph.

Design typology utilization

As already mentioned in Sect. 1, mixed methods designs can be classified into a mixed methods typology or taxonomy. A typology serves several purposes, including the following: guiding practice, legitimizing the field, generating new possibilities, and serving as a useful pedagogical tool (Teddlie and Tashakkori 2009 ). Note, however, that not all types of typologies are equally suitable for all purposes. For generating new possibilities, one will need a more exhaustive typology, while a useful pedagogical tool might be better served by a non-exhaustive overview of the most common mixed methods designs. Although some of the current MM design typologies include more designs than others, none of the current typologies is fully exhaustive. When designing a mixed methods study, it is often useful to borrow its name from an existing typology, or to construct a superior and nuanced clear name when your design is based on a modification of one or more of the designs.

Various typologies of mixed methods designs have been proposed. Creswell and Plano Clark’s ( 2011 ) typology of some “commonly used designs” includes six “major mixed methods designs”. Our summary of these designs runs as follows:

Convergent parallel design (“paralleles Design”) (the quantitative and qualitative strands of the research are performed independently, and their results are brought together in the overall interpretation),
Explanatory sequential design (“explanatives Design”) (a first phase of quantitative data collection and analysis is followed by the collection of qualitative data, which are used to explain the initial quantitative results),
Exploratory sequential design (“exploratives Design”) (a first phase of qualitative data collection and analysis is followed by the collection of quantitative data to test or generalize the initial qualitative results),
Embedded design (“Einbettungs-Design”) (in a traditional qualitative or quantitative design, a strand of the other type is added to enhance the overall design),
Transformative design (“politisch-transformatives Design”) (a transformative theoretical framework, e. g. feminism or critical race theory, shapes the interaction, priority, timing and mixing of the qualitative and quantitative strand),
Multiphase design (“Mehrphasen-Design”) (more than two phases or both sequential and concurrent strands are combined over a period of time within a program of study addressing an overall program objective).

Most of their designs presuppose a specific juxtaposition of the qualitative and quantitative component. Note that the last design is a complex type that is required in many mixed methods studies.

The following are our adapted definitions of Teddlie and Tashakkori’s ( 2009 ) five sets of mixed methods research designs (adapted from Teddlie and Tashakkori 2009 , p. 151):

Parallel mixed designs (“paralleles Mixed-Methods-Design”) – In these designs, one has two or more parallel quantitative and qualitative strands, either with some minimal time lapse or simultaneously; the strand results are integrated into meta-inferences after separate analysis are conducted; related QUAN and QUAL research questions are answered or aspects of the same mixed research question is addressed.
Sequential mixed designs (“sequenzielles Mixed-Methods-Design”) – In these designs, QUAL and QUAN strands occur across chronological phases, and the procedures/questions from the later strand emerge/depend/build on on the previous strand; the research questions are interrelated and sometimes evolve during the study.
Conversion mixed designs (“Transfer-Design” or “Konversionsdesign”) – In these parallel designs, mixing occurs when one type of data is transformed to the other type and then analyzed, and the additional findings are added to the results; this design answers related aspects of the same research question,
Multilevel mixed designs (“Mehrebenen-Mixed-Methods-Design”) – In these parallel or sequential designs, mixing occurs across multiple levels of analysis, as QUAN and QUAL data are analyzed and integrated to answer related aspects of the same research question or related questions.
Fully integrated mixed designs (“voll integriertes Mixed-Methods-Design”) – In these designs, mixing occurs in an interactive manner at all stages of the study. At each stage, one approach affects the formulation of the other, and multiple types of implementation processes can occur. For example, rather than including integration only at the findings/results stage, or only across phases in a sequential design, mixing might occur at the conceptualization stage, the methodological stage, the analysis stage, and the inferential stage.

We recommend adding to Teddlie and Tashakkori’s typology a sixth design type, specifically, a “hybrid” design type to include complex combinations of two or more of the other design types. We expect that many published MM designs will fall into the hybrid design type.

Morse and Niehaus ( 2009 ) listed eight mixed methods designs in their book (and suggested that authors create more complex combinations when needed). Our shorthand labels and descriptions (adapted from Morse and Niehaus 2009 , p. 25) run as follows:

QUAL + quan (inductive-simultaneous design where, the core component is qualitative and the supplemental component is quantitative)
QUAL → quan (inductive-sequential design, where the core component is qualitative and the supplemental component is quantitative)
QUAN + qual (deductive-simultaneous design where, the core component is quantitative and the supplemental component is qualitative)
QUAN → qual (deductive-sequential design, where the core component is quantitative and the supplemental component is qualitative)
QUAL + qual (inductive-simultaneous design, where both components are qualitative; this is a multimethod design rather than a mixed methods design)
QUAL → qual (inductive-sequential design, where both components are qualitative; this is a multimethod design rather than a mixed methods design)
QUAN + quan (deductive-simultaneous design, where both components are quantitative; this is a multimethod design rather than a mixed methods design)
QUAN → quan (deductive-sequential design, where both components are quantitative; this is a multimethod design rather than a mixed methods design).

Notice that Morse and Niehaus ( 2009 ) included four mixed methods designs (the first four designs shown above) and four multimethod designs (the second set of four designs shown above) in their typology. The reader can, therefore, see that the design notation also works quite well for multimethod research designs. Notably absent from Morse and Niehaus’s book are equal-status or interactive designs. In addition, they assume that the core component should always be performed either concurrent with or before the supplemental component.

Johnson, Christensen, and Onwuegbuzie constructed a set of mixed methods designs without these limitations. The resulting mixed methods design matrix (see Johnson and Christensen 2017 , p. 478) contains nine designs, which we can label as follows (adapted from Johnson and Christensen 2017 , p. 478):

QUAL + QUAN (equal-status concurrent design),
QUAL + quan (qualitatively driven concurrent design),
QUAN + qual (quantitatively driven concurrent design),
QUAL → QUAN (equal-status sequential design),
QUAN → QUAL (equal-status sequential design),
QUAL → quan (qualitatively driven sequential design),
qual → QUAN (quantitatively driven sequential design),
QUAN → qual (quantitatively driven sequential design), and
quan → QUAL (qualitatively driven sequential design).

The above set of nine designs assumed only one qualitative and one quantitative component. However, this simplistic assumption can be relaxed in practice, allowing the reader to construct more complex designs. The Morse notation system is very powerful. For example, here is a three-stage equal-status concurrent-sequential design:

The key point here is that the Morse notation provides researchers with a powerful language for depicting and communicating the design constructed for a specific research study.

When designing a mixed methods study, it is sometimes helpful to include the mixing purpose (or characteristic on one of the other dimensions shown in Table 1 ) in the title of the study design (e. g., an explanatory sequential MM design, an exploratory-confirmatory MM design, a developmental MM design). Much more important, however, than a design name is for the author to provide an accurate description of what was done in the research study, so the reader will know exactly how the study was conducted. A design classification label can never replace such a description.

The common complexity of mixed methods design poses a problem to the above typologies of mixed methods research. The typologies were designed to classify whole mixed methods studies, and they are basically based on a classification of simple designs. In practice, many/most designs are complex. Complex designs are sometimes labeled “complex design”, “multiphase design”, “fully integrated design”, “hybrid design” and the like. Because complex designs occur very often in practice, the above typologies are not able to classify a large part of existing mixed methods research any further than by labeling them “complex”, which in itself is not very informative about the particular design. This problem does not fully apply to Morse’s notation system, which can be used to symbolize some more complex designs.

Something similar applies to the classification of the purposes of mixed methods research. The classifications of purposes mentioned in the “Purpose”-section, again, are basically meant for the classification of whole mixed methods studies. In practice, however, one single study often serves more than one purpose (Schoonenboom et al. 2017 ). The more purposes that are included in one study, the more difficult it becomes to select a design on the basis of the purpose of the investigation, as advised by Greene ( 2007 ). Of all purposes involved, then, which one should be the primary basis for the design? Or should the design be based upon all purposes included? And if so, how? For more information on how to articulate design complexity based on multiple purposes of mixing, see Schoonenboom et al. ( 2017 ).

It should be clear to the reader that, although much progress has been made in the area of mixed methods design typologies, the problem remains in developing a single typology that is effective in comprehensively listing a set of designs for mixed methods research. This is why we emphasize in this article the importance of learning to build on simple designs and construct one’s own design for one’s research questions. This will often result in a combination or “hybrid” design that goes beyond basic designs found in typologies, and a methodology section that provides much more information than a design name.

Typological versus interactive approaches to design

In the introduction, we made a distinction between design as a product and design as a process. Related to this, two different approaches to design can be distinguished: typological/taxonomic approaches (“systematische Ansätze”), such as those in the previous section, and interactive approaches (“interaktive Ansätze”) (the latter were called “dynamic” approaches by Creswell and Plano Clark 2011 ). Whereas typological/taxonomic approaches view designs as a sort of mold, in which the inquiry can be fit, interactive approaches (Maxwell 2013 ) view design as a process, in which a certain design-as-a-product might be the outcome of the process, but not its input.

The most frequently mentioned interactive approach to mixed methods research is the approach by Maxwell and Loomis ( 2003 ). Maxwell and Loomis distinguish the following components of a design: goals, conceptual framework, research question, methods, and validity. They argue convincingly that the most important task of the researcher is to deliver as the end product of the design process a design in which these five components fit together properly. During the design process, the researcher works alternately on the individual components, and as a result, their initial fit, if it existed, tends to get lost. The researcher should therefore regularly check during the research and continuing design process whether the components still fit together, and, if not, should adapt one or the other component to restore the fit between them. In an interactive approach, unlike the typological approach, design is viewed as an interactive process in which the components are continually compared during the research study to each other and adapted to each other.

Typological and interactive approaches to mixed methods research have been presented as mutually exclusive alternatives. In our view, however, they are not mutually exclusive. The interactive approach of Maxwell is a very powerful tool for conducting research, yet this approach is not specific to mixed methods research. Maxwell’s interactive approach emphasizes that the researcher should keep and monitor a close fit between the five components of research design. However, it does not indicate how one should combine qualitative and quantitative subcomponents within one of Maxwell’s five components (e. g., how one should combine a qualitative and a quantitative method, or a qualitative and a quantitative research question). Essential elements of the design process, such as timing and the point of integration are not covered by Maxwell’s approach. This is not a shortcoming of Maxwell’s approach, but it indicates that to support the design of mixed methods research, more is needed than Maxwell’s model currently has to offer.

Some authors state that design typologies are particularly useful for beginning researchers and interactive approaches are suited for experienced researchers (Creswell and Plano Clark 2011 ). However, like an experienced researcher, a research novice needs to align the components of his or her design properly with each other, and, like a beginning researcher, an advanced researcher should indicate how qualitative and quantitative components are combined with each other. This makes an interactive approach desirable, also for beginning researchers.

We see two merits of the typological/taxonomic approach . We agree with Greene ( 2007 ), who states that the value of the typological approach mainly lies in the different dimensions of mixed methods that result from its classifications. In this article, the primary dimensions include purpose, theoretical drive, timing, point of integration, typological vs. interactive approaches, planned vs. emergent designs, and complexity (also see secondary dimensions in Table 1 ). Unfortunately, all of these dimensions are not reflected in any single design typology reviewed here. A second merit of the typological approach is the provision of common mixed methods research designs, of common ways in which qualitative and quantitative research can be combined, as is done for example in the major designs of Creswell and Plano Clark ( 2011 ). Contrary to other authors, however, we do not consider these designs as a feature of a whole study, but rather, in line with Guest ( 2013 ), as a feature of one part of a design in which one qualitative and one quantitative component are combined. Although one study could have only one purpose, one point of integration, et cetera, we believe that combining “designs” is the rule and not the exception. Therefore, complex designs need to be constructed and modified as needed, and during the writing phase the design should be described in detail and perhaps given a creative and descriptive name.

Planned versus emergent designs

A mixed methods design can be thought out in advance, but can also arise during the course of the conduct of the study; the latter is called an “emergent” design (Creswell and Plano Clark 2011 ). Emergent designs arise, for example, when the researcher discovers during the study that one of the components is inadequate (Morse and Niehaus 2009 ). Addition of a component of the other type can sometimes remedy such an inadequacy. Some designs contain an emergent component by their nature. Initiation, for example, is the further exploration of unexpected outcomes. Unexpected outcomes are by definition not foreseen, and therefore cannot be included in the design in advance.

The question arises whether researchers should plan all these decisions beforehand, or whether they can make them during, and depending on the course of, the research process. The answer to this question is twofold. On the one hand, a researcher should decide beforehand which research components to include in the design, such that the conclusion that will be drawn will be robust. On the other hand, developments during research execution will sometimes prompt the researcher to decide to add additional components. In general, the advice is to be prepared for the unexpected. When one is able to plan for emergence, one should not refrain from doing so.

Dimension of complexity

Next, mixed methods designs are characterized by their complexity. In the literature, simple and complex designs are distinguished in various ways. A common distinction is between simple investigations with a single point of integration versus complex investigations with multiple points of integration (Guest 2013 ). When designing a mixed methods study, it can be useful to mention in the title whether the design of the study is simple or complex. The primary message of this section is as follows: It is the responsibility of the researcher to create more complex designs when needed to answer his or her research question(s) .

Teddlie and Tashakkori’s ( 2009 ) multilevel mixed designs and fully integrated mixed designs are both complex designs, but for different reasons. A multilevel mixed design is more complex ontologically, because it involves multiple levels of reality. For example, data might be collected both at the levels of schools and students, neighborhood and households, companies and employees, communities and inhabitants, or medical practices and patients (Yin 2013 ). Integration of these data does not only involve the integration of qualitative and quantitative data, but also the integration of data originating from different sources and existing at different levels. Little if any published research has discussed the possible ways of integrating data obtained in a multilevel mixed design (see Schoonenboom 2016 ). This is an area in need of additional research.

The fully-integrated mixed design is more complex because it contains multiple points of integration. As formulated by Teddlie and Tashakkori ( 2009 , p. 151):

In these designs, mixing occurs in an interactive manner at all stages of the study. At each stage, one approach affects the formulation of the other, and multiple types of implementation processes can occur.

Complexity, then, not only depends on the number of components, but also on the extent to which they depend on each other (e. g., “one approach affects the formulation of the other”).

Many of our design dimensions ultimately refer to different ways in which the qualitative and quantitative research components are interdependent. Different purposes of mixing ultimately differ in the way one component relates to, and depends upon, the other component. For example, these purposes include dependencies, such as “x illustrates y” and “x explains y”. Dependencies in the implementation of x and y occur to the extent that the design of y depends on the results of x (sequentiality). The theoretical drive creates dependencies, because the supplemental component y is performed and interpreted within the context and the theoretical drive of core component x. As a general rule in designing mixed methods research, one should examine and plan carefully the ways in which and the extent to which the various components depend on each other.

The dependence among components, which may or may not be present, has been summarized by Greene ( 2007 ). It is seen in the distinction between component designs (“Komponenten-Designs”), in which the components are independent of each other, and integrated designs (“integrierte Designs”), in which the components are interdependent. Of these two design categories, integrated designs are the more complex designs.

Secondary design considerations

The primary design dimensions explained above have been the focus of this article. There are a number of secondary considerations for researchers to also think about when they design their studies (Johnson and Christensen 2017 ). Now we list some secondary design issues and questions that should be thoughtfully considered during the construction of a strong mixed methods research design.

Phenomenon: Will the study be addressing (a) the same part or different parts of one phenomenon? (b) different phenomena?, or (c) the phenomenon/phenomena from different perspectives? Is the phenomenon (a) expected to be unique (e. g., historical event, particular group)?, (b) something expected to be part of a more regular and predictable phenomenon, or (c) a complex mixture of these?
Social scientific theory: Will the study generate a new substantive theory, test an already constructed theory, or achieve both in a sequential arrangement? Or is the researcher not interested in substantive theory based on empirical data?
Ideological drive: Will the study have an explicitly articulated ideological drive (e. g., feminism, critical race paradigm, transformative paradigm)?
Combination of sampling methods: What specific quantitative sampling method(s) will be used? What specific qualitative sampling methods(s) will be used? How will these be combined or related?
Degree to which the research participants will be similar or different: For example, participants or stakeholders with known differences of perspective would provide participants that are quite different.
Degree to which the researchers on the research team will be similar or different: For example, an experiment conducted by one researcher would be high on similarity, but the use of a heterogeneous and participatory research team would include many differences.
Implementation setting: Will the phenomenon be studied naturalistically, experimentally, or through a combination of these?
Degree to which the methods similar or different: For example, a structured interview and questionnaire are fairly similar but administration of a standardized test and participant observation in the field are quite different.
Validity criteria and strategies: What validity criteria and strategies will be used to address the defensibility of the study and the conclusions that will be drawn from it (see Chapter 11 in Johnson and Christensen 2017 )?
Full study: Will there be essentially one research study or more than one? How will the research report be structured?

Two case studies

The above design dimensions are now illustrated by examples. A nice collection of examples of mixed methods studies can be found in Hesse-Biber ( 2010 ), from which the following examples are taken. The description of the first case example is shown in Box 1.

Box 1

Summary of Roth ( 2006 ), research regarding the gender-wage gap within Wall Street securities firms. Adapted from Hesse-Biber ( 2010 , pp. 457–458)

Louise Marie Roth’s research, Selling Women Short: Gender and Money on Wall Street ( 2006 ), tackles gender inequality in the workplace. She was interested in understanding the gender-wage gap among highly performing Wall Street MBAs, who on the surface appeared to have the same “human capital” qualifications and were placed in high-ranking Wall Street securities firms as their first jobs. In addition, Roth wanted to understand the “structural factors” within the workplace setting that may contribute to the gender-wage gap and its persistence over time. […] Roth conducted semistructured interviews, nesting quantitative closed-ended questions into primarily qualitative in-depth interviews […] In analyzing the quantitative data from her sample, she statistically considered all those factors that might legitimately account for gendered differences such as number of hours worked, any human capital differences, and so on. Her analysis of the quantitative data revealed the presence of a significant gender gap in wages that remained unexplained after controlling for any legitimate factors that might otherwise make a difference. […] Quantitative findings showed the extent of the wage gap while providing numerical understanding of the disparity but did not provide her with an understanding of the specific processes within the workplace that might have contributed to the gender gap in wages. […] Her respondents’ lived experiences over time revealed the hidden inner structures of the workplace that consist of discriminatory organizational practices with regard to decision making in performance evaluations that are tightly tied to wage increases and promotion.

This example nicely illustrates the distinction we made between simultaneity and dependency. On the two aspects of the timing dimension, this study was a concurrent-dependent design answering a set of related research questions. The data collection in this example was conducted simultaneously, and was thus concurrent – the quantitative closed-ended questions were embedded into the qualitative in-depth interviews. In contrast, the analysis was dependent, as explained in the next paragraph.

One of the purposes of this study was explanation: The qualitative data were used to understand the processes underlying the quantitative outcomes. It is therefore an explanatory design, and might be labelled an “explanatory concurrent design”. Conceptually, explanatory designs are often dependent: The qualitative component is used to explain and clarify the outcomes of the quantitative component. In that sense, the qualitative analysis in the case study took the outcomes of the quantitative component (“the existence of the gender-wage gap” and “numerical understanding of the disparity”), and aimed at providing an explanation for that result of the quantitative data analysis , by relating it to the contextual circumstances in which the quantitative outcomes were produced. This purpose of mixing in the example corresponds to Bryman’s ( 2006 ) “contextual understanding”. On the other primary dimensions, (a) the design was ongoing over a three-year period but was not emergent, (b) the point of integration was results, and (c) the design was not complex with respect to the point of integration, as it had only one point of integration. Yet, it was complex in the sense of involving multiple levels; both the level of the individual and the organization were included. According to the approach of Johnson and Christensen ( 2017 ), this was a QUAL + quan design (that was qualitatively driven, explanatory, and concurrent). If we give this study design a name, perhaps it should focus on what was done in the study: “explaining an effect from the process by which it is produced”. Having said this, the name “explanatory concurrent design” could also be used.

The description of the second case example is shown in Box 2.

Box 2

Summary of McMahon’s ( 2007 ) explorative study of the meaning, role, and salience of rape myths within the subculture of college student athletes. Adapted from Hesse-Biber ( 2010 , pp. 461–462)

Sarah McMahon ( 2007 ) wanted to explore the subculture of college student athletes and specifically the meaning, role, and salience of rape myths within that culture. […] While she was looking for confirmation between the quantitative ([structured] survey) and qualitative (focus groups and individual interviews) findings, she entered this study skeptical of whether or not her quantitative and qualitative findings would mesh with one another. McMahon […] first administered a survey [instrument] to 205 sophomore and junior student athletes at one Northeast public university. […] The quantitative data revealed a very low acceptance of rape myths among this student population but revealed a higher acceptance of violence among men and individuals who did not know a survivor of sexual assault. In the second qualitative (QUAL) phase, “focus groups were conducted as semi-structured interviews” and facilitated by someone of the same gender as the participants (p. 360). […] She followed this up with a third qualitative component (QUAL), individual interviews, which were conducted to elaborate on themes discovered in the focus groups and determine any differences in students’ responses between situations (i. e., group setting vs. individual). The interview guide was designed specifically to address focus group topics that needed “more in-depth exploration” or clarification (p. 361). The qualitative findings from the focus groups and individual qualitative interviews revealed “subtle yet pervasive rape myths” that fell into four major themes: “the misunderstanding of consent, the belief in ‘accidental’ and fabricated rape, the contention that some women provoke rape, and the invulnerability of female athletes” (p. 363). She found that the survey’s finding of a “low acceptance of rape myths … was contradicted by the findings of the focus groups and individual interviews, which indicated the presence of subtle rape myths” (p. 362).

On the timing dimension, this is an example of a sequential-independent design. It is sequential, because the qualitative focus groups were conducted after the survey was administered. The analysis of the quantitative and qualitative data was independent: Both were analyzed independently, to see whether they yielded the same results (which they did not). This purpose, therefore, was triangulation. On the other primary dimensions, (a) the design was planned, (b) the point of integration was results, and (c) the design was not complex as it had only one point of integration, and involved only the level of the individual. The author called this a “sequential explanatory” design. We doubt, however, whether this is the most appropriate label, because the qualitative component did not provide an explanation for quantitative results that were taken as given. On the contrary, the qualitative results contradicted the quantitative results. Thus, a “sequential-independent” design, or a “sequential-triangulation” design or a “sequential-comparative” design would probably be a better name.

Notice further that the second case study had the same point of integration as the first case study. The two components were brought together in the results. Thus, although the case studies are very dissimilar in many respects, this does not become visible in their point of integration. It can therefore be helpful to determine whether their point of extension is different. A point of extension is the point in the research process at which the second (or later) component comes into play. In the first case study, two related, but different research questions were answered, namely the quantitative question “How large is the gender-wage gap among highly performing Wall Street MBAs after controlling for any legitimate factors that might otherwise make a difference?”, and the qualitative research question “How do structural factors within the workplace setting contribute to the gender-wage gap and its persistence over time?” This case study contains one qualitative research question and one quantitative research question. Therefore, the point of extension is the research question. In the second case study, both components answered the same research question. They differed in their data collection (and subsequently in their data analysis): qualitative focus groups and individual interviews versus a quantitative questionnaire. In this case study, the point of extension was data collection. Thus, the point of extension can be used to distinguish between the two case studies.

Summary and conclusions

The purpose of this article is to help researchers to understand how to design a mixed methods research study. Perhaps the simplest approach is to design is to look at a single book and select one from the few designs included in that book. We believe that is only useful as a starting point. Here we have shown that one often needs to construct a research design to fit one’s unique research situation and questions.

First, we showed that there are there are many purposes for which qualitative and quantitative methods, methodologies, and paradigms can be mixed. This must be determined in interaction with the research questions. Inclusion of a purpose in the design name can sometimes provide readers with useful information about the study design, as in, e. g., an “explanatory sequential design” or an “exploratory-confirmatory design”.

The second dimension is theoretical drive in the sense that Morse and Niehaus ( 2009 ) use this term. That is, will the study have an inductive or a deductive drive, or, we added, a combination of these. Related to this idea is whether one will conduct a qualitatively driven, a quantitatively driven, or an equal-status mixed methods study. This language is sometimes included in the design name to communicate this characteristic of the study design (e. g., a “quantitatively driven sequential mixed methods design”).

The third dimension is timing , which has two aspects: simultaneity and dependence. Simultaneity refers to whether the components are to be implemented concurrently, sequentially, or a combination of these in a multiphase design. Simultaneity is commonly used in the naming of a mixed methods design because it communicates key information. The second aspect of timing, dependence , refers to whether a later component depends on the results of an earlier component, e. g., Did phase two specifically build on phase one in the research study? The fourth design dimension is the point of integration, which is where the qualitative and quantitative components are brought together and integrated. This is an essential dimension, but it usually does not need to be incorporated into the design name.

The fifth design dimension is that of typological vs. interactive design approaches . That is, will one select a design from a typology or use a more interactive approach to construct one’s own design? There are many typologies of designs currently in the literature. Our recommendation is that readers examine multiple design typologies to better understand the design process in mixed methods research and to understand what designs have been identified as popular in the field. However, when a design that would follow from one’s research questions is not available, the researcher can and should (a) combine designs into new designs or (b) simply construct a new and unique design. One can go a long way in depicting a complex design with Morse’s ( 1991 ) notation when used to its full potential. We also recommend that researchers understand the process approach to design from Maxwell and Loomis ( 2003 ), and realize that research design is a process and it needs, oftentimes, to be flexible and interactive.

The sixth design dimension or consideration is whether a design will be fully specified during the planning of the research study or if the design (or part of the design) will be allowed to emerge during the research process, or a combination of these. The seventh design dimension is called complexity . One sort of complexity mentioned was multilevel designs, but there are many complexities that can enter designs. The key point is that good research often requires the use of complex designs to answer one’s research questions. This is not something to avoid. It is the responsibility of the researcher to learn how to construct and describe and name mixed methods research designs. Always remember that designs should follow from one’s research questions and purposes, rather than questions and purposes following from a few currently named designs.

In addition to the six primary design dimensions or considerations, we provided a set of additional or secondary dimensions/considerations or questions to ask when constructing a mixed methods study design. Our purpose throughout this article has been to show what factors must be considered to design a high quality mixed methods research study. The more one knows and thinks about the primary and secondary dimensions of mixed methods design the better equipped one will be to pursue mixed methods research.

Acknowledgments

Open access funding provided by University of Vienna.

Biographies

1965, Dr., Professor of Empirical Pedagogy at University of Vienna, Austria. Research Areas: Mixed Methods Design, Philosophy of Mixed Methods Research, Innovation in Higher Education, Design and Evaluation of Intervention Studies, Educational Technology. Publications: Mixed methods in early childhood education. In: M. Fleer & B. v. Oers (Eds.), International handbook on early childhood education (Vol. 1). Dordrecht, The Netherlands: Springer 2017; The multilevel mixed intact group analysis: A mixed method to seek, detect, describe and explain differences between intact groups. Journal of Mixed Methods Research 10, 2016; The realist survey: How respondents’ voices can be used to test and revise correlational models. Journal of Mixed Methods Research 2015. Advance online publication.

1957, PhD, Professor of Professional Studies at University of South Alabama, Mobile, Alabama USA. Research Areas: Methods of Social Research, Program Evaluation, Quantitative, Qualitative and Mixed Methods, Philosophy of Social Science. Publications: Research methods, design and analysis. Boston, MA 2014 (with L. Christensen and L. Turner); Educational research: Quantitative, qualitative and mixed approaches. Los Angeles, CA 2017 (with L. Christensen); The Oxford handbook of multimethod and mixed methods research inquiry. New York, NY 2015 (with S. Hesse-Biber).

Bryman’s ( 2006 ) scheme of rationales for combining quantitative and qualitative research 1

Triangulation or greater validity – refers to the traditional view that quantitative and qualitative research might be combined to triangulate findings in order that they may be mutually corroborated. If the term was used as a synonym for integrating quantitative and qualitative research, it was not coded as triangulation.
Offset – refers to the suggestion that the research methods associated with both quantitative and qualitative research have their own strengths and weaknesses so that combining them allows the researcher to offset their weaknesses to draw on the strengths of both.
Completeness – refers to the notion that the researcher can bring together a more comprehensive account of the area of enquiry in which he or she is interested if both quantitative and qualitative research are employed.
Process – quantitative research provides an account of structures in social life but qualitative research provides sense of process.
Different research questions – this is the argument that quantitative and qualitative research can each answer different research questions but this item was coded only if authors explicitly stated that they were doing this.
Explanation – one is used to help explain findings generated by the other.
Unexpected results – refers to the suggestion that quantitative and qualitative research can be fruitfully combined when one generates surprising results that can be understood by employing the other.
Instrument development – refers to contexts in which qualitative research is employed to develop questionnaire and scale items – for example, so that better wording or more comprehensive closed answers can be generated.
Sampling – refers to situations in which one approach is used to facilitate the sampling of respondents or cases.
Credibility – refer s to suggestions that employing both approaches enhances the integrity of findings.
Context – refers to cases in which the combination is rationalized in terms of qualitative research providing contextual understanding coupled with either generalizable, externally valid findings or broad relationships among variables uncovered through a survey.
Illustration – refers to the use of qualitative data to illustrate quantitative findings, often referred to as putting “meat on the bones” of “dry” quantitative findings.
Utility or improving the usefulness of findings – refers to a suggestion, which is more likely to be prominent among articles with an applied focus, that combining the two approaches will be more useful to practitioners and others.
Confirm and discover – this entails using qualitative data to generate hypotheses and using quantitative research to test them within a single project.
Diversity of views – this includes two slightly different rationales – namely, combining researchers’ and participants’ perspectives through quantitative and qualitative research respectively, and uncovering relationships between variables through quantitative research while also revealing meanings among research participants through qualitative research.
Enhancement or building upon quantitative/qualitative findings – this entails a reference to making more of or augmenting either quantitative or qualitative findings by gathering data using a qualitative or quantitative research approach.
Other/unclear.
Not stated.

1 Reprinted with permission from “Integrating quantitative and qualitative research: How is it done?” by Alan Bryman ( 2006 ), Qualitative Research, 6, pp. 105–107.

Contributor Information

Judith Schoonenboom, Email: [email protected] .

R. Burke Johnson, Email: ude.amabalahtuos@nosnhojb .

Bazeley, Pat, Lynn Kemp Mosaics, triangles, and DNA: Metaphors for integrated analysis in mixed methods research. Journal of Mixed Methods Research. 2012; 6 :55–72. doi: 10.1177/1558689811419514. [ CrossRef ] [ Google Scholar ]
Bryman A. Integrating quantitative and qualitative research: how is it done? Qualitative Research. 2006; 6 :97–113. doi: 10.1177/1468794106058877. [ CrossRef ] [ Google Scholar ]
Cook TD. Postpositivist critical multiplism. In: Shotland RL, Mark MM, editors. Social science and social policy. Beverly Hills: SAGE; 1985. pp. 21–62. [ Google Scholar ]
Creswell JW, Plano Clark VL. Designing and conducting mixed methods research. 2. Los Angeles: SAGE; 2011. [ Google Scholar ]
Erzberger C, Prein G. Triangulation: Validity and empirically-based hypothesis construction. Quality and Quantity. 1997; 31 :141–154. doi: 10.1023/A:1004249313062. [ CrossRef ] [ Google Scholar ]
Greene JC. Mixed methods in social inquiry. San Francisco: Jossey-Bass; 2007. [ Google Scholar ]
Greene JC. Preserving distinctions within the multimethod and mixed methods research merger. Sharlene Hesse-Biber and R. Burke Johnson. New York: Oxford University Press; 2015. [ Google Scholar ]
Greene JC, Valerie J, Caracelli, Graham WF. Toward a conceptual framework for mixed-method evaluation designs. Educational Evaluation and Policy Analysis. 1989; 11 :255–274. doi: 10.3102/01623737011003255. [ CrossRef ] [ Google Scholar ]
Greene JC, Hall JN. Dialectics and pragmatism. In: Tashakkori A, Teddlie C, editors. SAGE handbook of mixed methods in social & behavioral research. 2. Los Angeles: SAGE; 2010. pp. 119–167. [ Google Scholar ]
Guest, Greg Describing mixed methods research: An alternative to typologies. Journal of Mixed Methods Research. 2013; 7 :141–151. doi: 10.1177/1558689812461179. [ CrossRef ] [ Google Scholar ]
Hesse-Biber S. Qualitative approaches to mixed methods practice. Qualitative Inquiry. 2010; 16 :455–468. doi: 10.1177/1077800410364611. [ CrossRef ] [ Google Scholar ]
Johnson BR. Dialectical pluralism: A metaparadigm whose time has come. Journal of Mixed Methods Research. 2017; 11 :156–173. doi: 10.1177/1558689815607692. [ CrossRef ] [ Google Scholar ]
Johnson BR, Christensen LB. Educational research: Quantitative, qualitative, and mixed approaches. 6. Los Angeles: SAGE; 2017. [ Google Scholar ]
Johnson BR, Onwuegbuzie AJ. Mixed methods research: a research paradigm whose time has come. Educational Researcher. 2004; 33 (7):14–26. doi: 10.3102/0013189X033007014. [ CrossRef ] [ Google Scholar ]
Johnson BR, Onwuegbuzie AJ, Turner LA. Toward a definition of mixed methods research. Journal of Mixed Methods Research. 2007; 1 :112–133. doi: 10.1177/1558689806298224. [ CrossRef ] [ Google Scholar ]
Mathison S. Why triangulate? Educational Researcher. 1988; 17 :13–17. doi: 10.3102/0013189X017002013. [ CrossRef ] [ Google Scholar ]
Maxwell JA. Qualitative research design: An interactive approach. 3. Los Angeles: SAGE; 2013. [ Google Scholar ]
Maxwell, Joseph A., and Diane M. Loomis. 2003. Mixed methods design: An alternative approach. In Handbook of mixed methods in social & behavioral research , Eds. Abbas Tashakkori and Charles Teddlie, 241–271. Thousand Oaks: Sage.
McMahon S. Understanding community-specific rape myths: Exploring student athlete culture. Affilia. 2007; 22 :357–370. doi: 10.1177/0886109907306331. [ CrossRef ] [ Google Scholar ]
Mendlinger S, Cwikel J. Spiraling between qualitative and quantitative data on women’s health behaviors: A double helix model for mixed methods. Qualitative Health Research. 2008; 18 :280–293. doi: 10.1177/1049732307312392. [ PubMed ] [ CrossRef ] [ Google Scholar ]
Morgan DL. Integrating qualitative and quantitative methods: a pragmatic approach. Los Angeles: Sage; 2014. [ Google Scholar ]
Morse JM. Approaches to qualitative-quantitative methodological triangulation. Nursing Research. 1991; 40 :120–123. doi: 10.1097/00006199-199103000-00014. [ PubMed ] [ CrossRef ] [ Google Scholar ]
Morse JM, Niehaus L. Mixed method design: Principles and procedures. Walnut Creek: Left Coast Press; 2009. [ Google Scholar ]
Onwuegbuzie AJ, Burke Johnson R. The “validity” issue in mixed research. Research in the Schools. 2006; 13 :48–63. [ Google Scholar ]
Roth LM. Selling women short: Gender and money on Wall Street. Princeton: Princeton University Press; 2006. [ Google Scholar ]
Schoonenboom J. The multilevel mixed intact group analysis: a mixed method to seek, detect, describe and explain differences between intact groups. Journal of Mixed Methods Research. 2016; 10 :129–146. doi: 10.1177/1558689814536283. [ CrossRef ] [ Google Scholar ]
Schoonenboom, Judith, R. Burke Johnson, and Dominik E. Froehlich. 2017, in press. Combining multiple purposes of mixing within a mixed methods research design. International Journal of Multiple Research Approaches .
Teddlie CB, Tashakkori A. Foundations of mixed methods research: Integrating quantitative and qualitative approaches in the social and behavioral sciences. Los Angeles: Sage; 2009. [ Google Scholar ]
Yanchar SC, Williams DD. Reconsidering the compatibility thesis and eclecticism: Five proposed guidelines for method use. Educational Researcher. 2006; 35 (9):3–12. doi: 10.3102/0013189X035009003. [ CrossRef ] [ Google Scholar ]
Yin RK. Case study research: design and methods. 5. Los Angeles: SAGE; 2013. [ Google Scholar ]

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How to write qualitative research questions.

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

What is qualitative research?

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

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

What are research questions?

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

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

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

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

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

Discover the fundamentals of qualitative research

Quantitative vs. qualitative research questions

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

Quantitative research questions

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

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

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

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

What is the connection?

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

For example:

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

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

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

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

Qualitative research questions

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

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

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

A few example qualitative research questions:

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

Qualitative research question types

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

Exploratory questions

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

Explanatory questions

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

Descriptive questions

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

Predictive questions

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

Why are good qualitative research questions important?

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

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

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

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

Developing good qualitative research questions

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

1. Keep it specific

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

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

Weak example: Do people feel different about gender now?

2. Be original

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

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

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

3. Make it research-worthy

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

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

Weak example: What languages are spoken in India?

4. Focus your question

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

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

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

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

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

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

Weak example: How can hate crimes be prevented?

5. Ask something researchable

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

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

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

Related resources

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

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Satellite photo showing a container ship entangled with the wreckage of a bridge.

Baltimore bridge collapse: a bridge engineer explains what happened, and what needs to change

Associate Professor, Civil Engineering, Monash University

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Colin Caprani receives funding from the Department of Transport (Victoria) and the Level Crossing Removal Project. He is also Chair of the Confidential Reporting Scheme for Safer Structures - Australasia, Chair of the Australian Regional Group of the Institution of Structural Engineers, and Australian National Delegate for the International Association for Bridge and Structural Engineering.

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When the container ship MV Dali, 300 metres long and massing around 100,000 tonnes, lost power and slammed into one of the support piers of the Francis Scott Key Bridge in Baltimore, the bridge collapsed in moments . Six people are presumed dead, several others injured, and the city and region are expecting a months-long logistical nightmare in the absence of a crucial transport link.

It was a shocking event, not only for the public but for bridge engineers like me. We work very hard to ensure bridges are safe, and overall the probability of being injured or worse in a bridge collapse remains even lower than the chance of being struck by lightning.

However, the images from Baltimore are a reminder that safety can’t be taken for granted. We need to remain vigilant.

So why did this bridge collapse? And, just as importantly, how might we make other bridges more safe against such collapse?

A 20th century bridge meets a 21st century ship

The Francis Scott Key Bridge was built through the mid 1970s and opened in 1977. The main structure over the navigation channel is a “continuous truss bridge” in three sections or spans.

The bridge rests on four supports, two of which sit each side of the navigable waterway. It is these two piers that are critical to protect against ship impacts.

And indeed, there were two layers of protection: a so-called “dolphin” structure made from concrete, and a fender. The dolphins are in the water about 100 metres upstream and downstream of the piers. They are intended to be sacrificed in the event of a wayward ship, absorbing its energy and being deformed in the process but keeping the ship from hitting the bridge itself.

The fender is the last layer of protection. It is a structure made of timber and reinforced concrete placed around the main piers. Again, it is intended to absorb the energy of any impact.

Fenders are not intended to absorb impacts from very large vessels . And so when the MV Dali, weighing more than 100,000 tonnes, made it past the protective dolphins, it was simply far too massive for the fender to withstand.

Read more: I've captained ships into tight ports like Baltimore, and this is how captains like me work with harbor pilots to avoid deadly collisions

Video recordings show a cloud of dust appearing just before the bridge collapsed, which may well have been the fender disintegrating as it was crushed by the ship.

Once the massive ship had made it past both the dolphin and the fender, the pier – one of the bridge’s four main supports – was simply incapable of resisting the impact. Given the size of the vessel and its likely speed of around 8 knots (15 kilometres per hour), the impact force would have been around 20,000 tonnes .

Bridges are getting safer

This was not the first time a ship hit the Francis Scott Bridge. There was another collision in 1980 , damaging a fender badly enough that it had to be replaced.

Around the world, 35 major bridge collapses resulting in fatalities were caused by collisions between 1960 and 2015, according to a 2018 report from the World Association for Waterborne Transport Infrastructure. Collisions between ships and bridges in the 1970s and early 1980s led to a significant improvement in the design rules for protecting bridges from impact.

A greenish book cover with the title Ship Collision With Bridges.

Further impacts in the 1970s and early 1980s instigated significant improvements in the design rules for impact.

The International Association for Bridge and Structural Engineering’s Ship Collision with Bridges guide, published in 1993, and the American Association of State Highway and Transporation Officials’ Guide Specification and Commentary for Vessel Collision Design of Highway Bridges (1991) changed how bridges were designed.

In Australia, the Australian Standard for Bridge Design (published in 2017) requires designers to think about the biggest vessel likely to come along in the next 100 years, and what would happen if it were heading for any bridge pier at full speed. Designers need to consider the result of both head-on collisions and side-on, glancing blows. As a result, many newer bridges protect their piers with entire human-made islands.

Of course, these improvements came too late to influence the design of the Francis Scott Key Bridge itself.

Lessons from disaster

So what are the lessons apparent at this early stage?

First, it’s clear the protection measures in place for this bridge were not enough to handle this ship impact. Today’s cargo ships are much bigger than those of the 1970s, and it seems likely the Francis Scott Key Bridge was not designed with a collision like this in mind.

So one lesson is that we need to consider how the vessels near our bridges are changing. This means we cannot just accept the structure as it was built, but ensure the protection measures around our bridges are evolving alongside the ships around them.

Photo shows US Coast Guard boat sailing towards a container ship entangled in the wreckage of a large bridge.

Second, and more generally, we must remain vigilant in managing our bridges. I’ve written previously about the current level of safety of Australian bridges, but also about how we can do better.

This tragic event only emphasises the need to spend more on maintaining our ageing infrastructure. This is the only way to ensure it remains safe and functional for the demands we put on it today.

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COMMENTS

What Is a Research Design
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.
Planning Qualitative Research: Design and Decision Making for New
While many books and articles guide various qualitative research methods and analyses, there is currently no concise resource that explains and differentiates among the most common qualitative approaches. We believe novice qualitative researchers, students planning the design of a qualitative study or taking an introductory qualitative research course, and faculty teaching such courses can ...
Research Design
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.. Example: Qualitative research If you want to generate new ideas for online teaching strategies, a qualitative approach would make the most sense. You can use this type of research to explore exactly what teachers and students ...
Chapter 2. Research Design
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.
Qualitative research design (JARS-Qual)
JARS-Qual, developed in 2018, mark the first time APA Style has included qualitative standards. They outline what should be reported in qualitative research manuscripts to make the review process easier. The seventh edition of the Publication Manual also includes content on qualitative studies, including standards for journal article ...
PDF A Guide to Using Qualitative Research Methodology
However, for many research projects, there are different sorts of questions that need answering, some requiring quantitative methods, and some requiring qualitative methods. If the question is a qualitative one, then the most appropriate and rigorous way of answering it is to use qualitative methods. For instance, if you
20
In other words, qualitative research uncovers social processes and mechanisms undergirding human behavior. In this chapter, we will discuss how to design a qualitative research project using two of the most common qualitative research methods: in-depth interviewing and ethnographic observations (also known as ethnography or participant ...
PDF How to Design a Qualitative Project and Create A Research Question
how to design a qualitative project 39 the very real danger of limiting your scope of inquiry. If researchers in the area of cohabi-tation had continued to rest on previous research, they might have failed to see declining stigma associated with cohabitation or that non-married and married cohabitating couples experience many of the same challenges.
Research Design in Qualitative Research
A research design is based on an integration of the theories, concepts, goals, contexts, beliefs, and sets of relationships that shape a specific topic. In addition, it is shaped by responding to the realities and perspectives of participants and contexts of a study. In a solid qualitative research design, framing theory and key constructs are ...
A Practical Guide to Writing Quantitative and Qualitative Research
INTRODUCTION. Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses.1,2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results.3,4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the ...
PDF Qualitative Research Design
that the research design of a qualitative study differs from that of a study that starts with an understanding to be tested, where often the hypothesis literally dictates the form, quantity, and scope of required data. This sort of design preempts other ways of looking at the research question. Qualitative research is usually not preemptive ...
Qualitative Research Design
A Few Qualitative Research Designs. 1. Biographical Study. ... and/or teachers, and perhaps asking students to write an essay about their thoughts on a dress code. The researcher would then follow the process of developing themes from reading the text by coding specific examples (using a highlighter, maybe) of where respondents mentioned common ...
How to Write a Research Design
Step 2: Data Type you Need for Research. Decide on the type of data you need for your research. The type of data you need to collect depends on your research questions or research hypothesis. Two types of research data can be used to answer the research questions: Primary Data Vs. Secondary Data.
31 Writing Up Qualitative Research
Abstract. This chapter provides guidelines for writing journal articles based on qualitative approaches. The guidelines are part of the tradition of the Chicago School of Sociology and the author's experience as a writer and reviewer. The guidelines include understanding experiences in context, immersion, interpretations grounded in accounts ...
Criteria for Good Qualitative Research: A Comprehensive Review
This review aims to synthesize a published set of evaluative criteria for good qualitative research. The aim is to shed light on existing standards for assessing the rigor of qualitative research encompassing a range of epistemological and ontological standpoints. Using a systematic search strategy, published journal articles that deliberate criteria for rigorous research were identified. Then ...
Qualitative research design (and planning)
Part of the research design process should be planning for this and creating consent forms that explain your project and what you will do with the data. 4. Methods. Now you know what to ask which people, you can think about how. This is usually when qualitative methods are chosen - the conditions above are right, and a qualitative study is ...
Qualitative Methods
Although Maxwell does not mention a conclusion as one of the components of a qualitative research design, you should formally conclude your study. ... eds. 2nd ed. (Thousand Oaks, CA: Sage, 2009), p. 214-253; Qualitative Research Methods. Writing@CSU. Colorado State University; Yin, Robert K. Qualitative Research from Start to Finish. 2nd ...
PDF Asking the Right Question: Qualitative Research Design and Analysis
Limitations of Qualitative Research. Lengthy and complicated designs, which do not draw large samples. Validity of reliability of subjective data. Difficult to replicate study because of central role of the researcher and context. Data analysis and interpretation is time consuming. Subjective - open to misinterpretation.
Research Design
How to Write Research Design. Writing a research design involves planning and outlining the methodology and approach that will be used to answer a research question or hypothesis. Here are some steps to help you write a research design: ... Common research methodologies include qualitative, quantitative, and mixed-methods approaches.
Designing a Research Proposal in Qualitative Research
The chapter discusses designing a research proposal in qualitative research. The main objective is to outline the major components of a qualitative research proposal with example (s) so that the students and novice scholars easily get an understanding of a qualitative proposal. The chapter highlights the major components of a qualitative ...
How to Construct a Mixed Methods Research Design
Quantitative dominant [or quantitatively driven] mixed methods research is the type of mixed research in which one relies on a quantitative, postpositivist view of the research process, while concurrently recognizing that the addition of qualitative data and approaches are likely to benefit most research projects. (p.
How to Write Qualitative Research Questions
This is especially important with qualitative questions, where there may be exploratory or inductive methods in use that introduce researchers to new and interesting areas of inquiry. Here are some tips for writing good qualitative research questions. 1. Keep it specific. Broader research questions are difficult to act on.
Baltimore bridge collapse: a bridge engineer explains what happened
The Francis Scott Key Bridge was built through the mid 1970s and opened in 1977. The main structure over the navigation channel is a "continuous truss bridge" in three sections or spans. The ...

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What Is a Research Design | Types, Guide & Examples

Table of contents

Practical and ethical considerations when designing research

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Types of quantitative research designs

Types of qualitative research designs

Defining the population

Case selection in qualitative research

Survey methods

Observation methods

Other methods of data collection

Secondary data

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Operationalization

Reliability and validity

Sampling procedures

Data management

Quantitative data analysis

Qualitative data analysis

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Research Design | Step-by-Step Guide with Examples

Table of contents

Practical and ethical considerations when designing research

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Types of quantitative research designs

Types of qualitative research designs

Defining the population

Sampling methods

Case selection in qualitative research

Survey methods

Observation methods

Other methods of data collection

Secondary data

Operationalisation

Reliability and validity

Sampling procedures

Data management

Quantitative data analysis

Qualitative data analysis

Cite this Scribbr article

Is this article helpful?

Shona McCombes

Chapter 2. Research Design

Research Design Steps

The Research Question

Research Design Checklist

Uncomplicated Reviews of Educational Research Methods

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How to Write a Research Design – Guide with Examples

Step 1: Establish Priorities for Research Design

Step 2: Data Type you Need for Research

Primary Data Vs. Secondary Data

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Step 3: Data Collection Techniques

Step 4: Procedure of Data Analysis

Quantitative Data Analysis

Qualitative Data Analysis

Step 5: Write your Research Proposal

How to Write a Research Design – Conclusion

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