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

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

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

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

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

Table of contents

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

• Introduction

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

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

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

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

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

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

Practical and ethical considerations when designing research

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

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

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

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

Types of quantitative research designs

Quantitative designs can be split into four main types.

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

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

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

Types of qualitative research designs

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

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

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

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

Defining the population

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

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

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

• Sampling methods

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

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

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

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

Case selection in qualitative research

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

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

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

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

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

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

Survey methods

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

Observation methods

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

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

Other methods of data collection

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

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

Secondary data

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

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

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

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

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

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

Operationalization

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

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

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

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

Reliability and validity

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

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

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

Sampling procedures

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

That means making decisions about things like:

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

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

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

Data management

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

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

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

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

Quantitative data analysis

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

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

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

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

Using inferential statistics , you can:

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

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

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

Qualitative data analysis

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

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

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

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

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

 Statistics

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

Research bias

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

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

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

Quantitative research designs can be divided into two main categories:

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

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

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

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

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

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

Operationalization means turning abstract conceptual ideas into measurable observations.

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

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

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

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Qualitative Research Design: Start

Qualitative Research Design

What is Qualitative research design?

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

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

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

Research Paradigms 

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

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

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

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

Qualitative Coding

Using Community Data to improve Outcome (Grant Writing)

Survey Design  

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

Community Engagement and Collaboration Event 

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

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

Event Moderators:

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

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

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

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

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

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

Scott Wolovich , Director of New Sun Rising, Pittsburgh 

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

Workshop Organizer

Qualitative Research Methods

What are Qualitative Research methods?

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

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

According to Doody and Bailey (2014);

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

Helps to have a directed research aim and objective.

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

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

Qualitative Research Questions

What constitutes a good Qualitative research question?

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

Examples of good Qualitative Research Questions:

What are people's thoughts on the new library? 

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

Difference example (between Qualitative and Quantitative research questions):

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

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

• Qualitative Research Design Workshop Powerpoint

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

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

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

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

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

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

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

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

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

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

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

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

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

Research Design 101

Everything You Need To Get Started (With Examples)

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

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

Overview: Research Design 101

What is research design.

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

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

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

The problem with defining research design…

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

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

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

Research Design: Quantitative Studies

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

Descriptive Research Design

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

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

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

Correlational Research Design

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

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

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

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

Need a helping hand?

Experimental Research Design

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

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

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

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

Quasi-Experimental Research Design

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

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

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

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

Research Design: Qualitative Studies

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

Phenomenological Research Design

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

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

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

Grounded Theory Research Design

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

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

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

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

Ethnographic Research Design

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

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

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

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

Case Study Design

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

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

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

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

How To Choose A Research Design

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

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

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

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

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

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

Recap: Key Takeaways

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

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

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

Psst… there’s more (for free)

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

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

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

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

This was really helpful. thanks

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

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

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

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

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

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Qualitative Research : Definition

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

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Qualitative Research – Methods, Analysis Types and Guide

Table of Contents

Qualitative Research

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

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

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

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

Focus Groups

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

Ethnographic Studies

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

Text Analysis

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

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

Process of Observation

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

Record Keeping

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

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

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

Qualitative Research Analysis Methods

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

Thematic Analysis

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

Content Analysis

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

Discourse Analysis

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

Grounded Theory Analysis

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

Narrative Analysis

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

Phenomenological Analysis

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

Comparative Analysis

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

Applications of Qualitative Research

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

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

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

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

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

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

Purpose of Qualitative Research

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

Qualitative research can serve multiple purposes, including:

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

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

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

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

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

Advantages of Qualitative Research

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

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

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

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

Also see Research Methods

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Chapter 2. Research Design

Getting started.

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

Research Design Steps

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

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

Researcher Note

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

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

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

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

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

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

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

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

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

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

STOP HERE for a moment

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

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

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

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

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

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

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

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

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

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

The Research Question

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

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

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

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

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

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

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

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

Recommendation

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

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

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

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

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

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

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

Once you have approval, you can begin!

Research Design Checklist

Before data collection begins, do the following:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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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.

Table of contents

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

• 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 ).

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 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.

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 generalise 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, 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.

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 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

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 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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Shona McCombes

Qualitative Research: Characteristics, Design, Methods & Examples

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“Not everything that can be counted counts, and not everything that counts can be counted“ (Albert Einstein)

Qualitative research is a process used for the systematic collection, analysis, and interpretation of non-numerical data (Punch, 2013). 

Qualitative research can be used to: (i) gain deep contextual understandings of the subjective social reality of individuals and (ii) to answer questions about experience and meaning from the participant’s perspective (Hammarberg et al., 2016).

Unlike quantitative research, which focuses on gathering and analyzing numerical data for statistical analysis, qualitative research focuses on thematic and contextual information.

Characteristics of Qualitative Research 

Reality is socially constructed.

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

The primacy of subject matter 

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

Variables are complex, interwoven, and difficult to measure

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

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

Emic (insider’s point of view)

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

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

Why Conduct Qualitative Research? 

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

Qualitative research allows researchers to gain an in-depth understanding, which is difficult to attain using quantitative methods. 

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

This helps to further investigate and understand quantitative data by discovering reasons for the outcome of a study – answering the why question behind statistics. 

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

To design hypotheses, theory must be researched using qualitative methods to find out what is important in order to begin research. 

For example, by conducting interviews or focus groups with key stakeholders to discover what is important to them. 

Examples of qualitative research questions include: 

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

Collecting Qualitative Data

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

Observations

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

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

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

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

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

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

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

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

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

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

Focus groups 

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

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

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

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

Ethnography

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

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

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

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

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

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

Qualitative Data Analysis Methods

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

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

Grounded theory

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

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

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

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

Content analysis

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

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

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

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

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

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

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

Discourse analysis

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

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

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

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

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

Thematic analysis

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

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

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

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

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

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

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

Phases of Thematic Analysis

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

Template analysis

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

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

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

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

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

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

Frame analysis

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

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

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

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

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

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

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

Preventing Bias in Qualitative Research

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

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

Co-coding 

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

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

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

Member checking

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

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

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

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

Reflexivity in qualitative research

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

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

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

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

Reflexivity Example

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

Establishing Trustworthiness in Qualitative Research

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

Credibility in Qualitative Research

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

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

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

Transferability in Qualitative Research

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

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

Dependability in Qualitative Research

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

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

Confirmability in Qualitative Research

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

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

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

Audit Trails in Qualitative Research

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

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

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

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

Discovery of unexpected data

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

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

Flexibility

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

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

Naturalistic settings

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

Limitations

Time-consuming .

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

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

Subjectivity 

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

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

Limited generalizability

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

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

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

Extraneous variables

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

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

What sample size should qualitative research be?

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

Are surveys qualitative or quantitative?

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

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

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

What are the ethical considerations of qualitative research?

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

What is triangulation in qualitative research?

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

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

Why is qualitative research important?

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

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

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

What is coding data in qualitative research?

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

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

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

What is the difference between qualitative and quantitative research?

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

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

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

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

What is trustworthiness in qualitative research?

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

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

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

What is data saturation in qualitative research?

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

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

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

Why is sampling in qualitative research important?

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

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

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

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Types Of Qualitative Research Designs And Methods

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

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

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

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

What Is Qualitative Research Design?

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

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

Let’s define some basic terms.

Qualitative Method

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

Quantitative Method

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

Research Design

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

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

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

Cluster Sampling

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

Random Sampling

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

Focus Groups

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

Observation

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

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

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

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

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

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

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

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

Explanatory Data Analysis

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

Confirmatory Data Analysis

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

Descriptive Data Analysis

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

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

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

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

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Qualitative Research

What is qualitative research.

Qualitative research is the methodology researchers use to gain deep contextual understandings of users via non-numerical means and direct observations. Researchers focus on smaller user samples—e.g., in interviews—to reveal data such as user attitudes, behaviors and hidden factors: insights which guide better designs.

“ There are also unknown unknowns, things we don’t know we don’t know.” — Donald Rumsfeld, Former U.S. Secretary of Defense

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See how you can use qualitative research to expose hidden truths about users and iteratively shape better products.

Qualitative Research Focuses on the “Why”

Qualitative research is a subset of user experience (UX) research and user research . By doing qualitative research, you aim to gain narrowly focused but rich information about why users feel and think the ways they do. Unlike its more statistics-oriented “counterpart”, quantitative research , qualitative research can help expose hidden truths about your users’ motivations, hopes, needs, pain points and more to help you keep your project’s focus on track throughout development. UX design professionals do qualitative research typically from early on in projects because—since the insights they reveal can alter product development dramatically—they can prevent costly design errors from arising later. Compare and contrast qualitative with quantitative research here:

Qualitative research

Quantitative Research

You Aim to Determine

The “why” – to get behind how users approach their problems in their world

The “what”, “where” & “when” of the users’ needs & problems – to help keep your project’s focus on track during development

Loosely structured (e.g., contextual inquiries) – to learn why users behave how they do & explore their opinions

Highly structured (e.g., surveys) – to gather data about what users do & find patterns in large user groups

Number of Representative Users

Often around 5

Ideally 30+

Level of Contact with Users

More direct & less remote (e.g., usability testing to examine users’ stress levels when they use your design)

Less direct & more remote (e.g., analytics)

Statistically

You need to take great care with handling non-numerical data (e.g., opinions), as your own opinions might influence findings

Reliable – given enough test users

Regarding care with opinions, it’s easy to be subjective about qualitative data, which isn’t as comprehensively analyzable as quantitative data. That’s why design teams also apply quantitative research methods, to reinforce the “why” with the “what”.

Qualitative Research Methods You Can Use to Get Behind Your Users

You have a choice of many methods to help gain the clearest insights into your users’ world – which you might want to complement with quantitative research methods. In iterative processes such as user-centered design , you/your design team would use quantitative research to spot design problems, discover the reasons for these with qualitative research, make changes and then test your improved design on users again. The best method/s to pick will depend on the stage of your project and your objectives. Here are some:

Diary studies – You ask users to document their activities, interactions, etc. over a defined period. This empowers users to deliver context-rich information. Although such studies can be subjective—since users will inevitably be influenced by in-the-moment human issues and their emotions—they’re helpful tools to access generally authentic information.

Structured – You ask users specific questions and analyze their responses with other users’.

Semi-structured – You have a more free-flowing conversation with users, but still follow a prepared script loosely.

Ethnographic – You interview users in their own environment to appreciate how they perform tasks and view aspects of tasks.

Usability testing

Moderated – In-person testing in, e.g., a lab.

Unmoderated – Users complete tests remotely: e.g., through a video call.

Guerrilla – “Down-the-hall”/“down-and-dirty” testing on a small group of random users or colleagues.

User observation – You watch users get to grips with your design and note their actions, words and reactions as they attempt to perform tasks.

Qualitative research can be more or less structured depending on the method.

Qualitative Research – How to Get Reliable Results

Some helpful points to remember are:

Participants – Select a number of test users carefully (typically around 5). Observe the finer points such as body language. Remember the difference between what they do and what they say they do.

Moderated vs. unmoderated – You can obtain the richest data from moderated studies, but these can involve considerable time and practice. You can usually conduct unmoderated studies more quickly and cheaply, but you should plan these carefully to ensure instructions are clear, etc.

Types of questions – You’ll learn far more by asking open-ended questions. Avoid leading users’ answers – ask about their experience during, say, the “search for deals” process rather than how easy it was. Try to frame questions so users respond honestly: i.e., so they don’t withhold grievances about their experience because they don’t want to seem impolite. Distorted feedback may also arise in guerrilla testing, as test users may be reluctant to sound negative or to discuss fine details if they lack time.

Location – Think how where users are might affect their performance and responses. If, for example, users’ tasks involve running or traveling on a train, select the appropriate method (e.g., diary studies for them to record aspects of their experience in the environment of a train carriage and the many factors impacting it).

Overall, no single research method can help you answer all your questions. Nevertheless, The Nielsen Norman Group advise that if you only conduct one kind of user research, you should pick qualitative usability testing, since a small sample size can yield many cost- and project-saving insights. Always treat users and their data ethically. Finally, remember the importance of complementing qualitative methods with quantitative ones: You gain insights from the former; you test those using the latter.

Learn More about Qualitative Research

Take our course on User Research to see how to get the most from qualitative research.

Read about the numerous considerations for qualitative research in this in-depth piece.

This blog discusses the importance of qualitative research , with tips.

Explore additional insights into qualitative research here .

Literature on Qualitative Research

Here’s the entire UX literature on Qualitative Research by the Interaction Design Foundation, collated in one place:

Learn more about Qualitative Research

Take a deep dive into Qualitative Research with our course User Research – Methods and Best Practices .

How do you plan to design a product or service that your users will love , if you don't know what they want in the first place? As a user experience designer, you shouldn't leave it to chance to design something outstanding; you should make the effort to understand your users and build on that knowledge from the outset. User research is the way to do this, and it can therefore be thought of as the largest part of user experience design .

In fact, user research is often the first step of a UX design process—after all, you cannot begin to design a product or service without first understanding what your users want! As you gain the skills required, and learn about the best practices in user research, you’ll get first-hand knowledge of your users and be able to design the optimal product—one that’s truly relevant for your users and, subsequently, outperforms your competitors’ .

This course will give you insights into the most essential qualitative research methods around and will teach you how to put them into practice in your design work. You’ll also have the opportunity to embark on three practical projects where you can apply what you’ve learned to carry out user research in the real world . You’ll learn details about how to plan user research projects and fit them into your own work processes in a way that maximizes the impact your research can have on your designs. On top of that, you’ll gain practice with different methods that will help you analyze the results of your research and communicate your findings to your clients and stakeholders—workshops, user journeys and personas, just to name a few!

By the end of the course, you’ll have not only a Course Certificate but also three case studies to add to your portfolio. And remember, a portfolio with engaging case studies is invaluable if you are looking to break into a career in UX design or user research!

We believe you should learn from the best, so we’ve gathered a team of experts to help teach this course alongside our own course instructors. That means you’ll meet a new instructor in each of the lessons on research methods who is an expert in their field—we hope you enjoy what they have in store for you!

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Home » Education » What is Research Design in Qualitative Research

What is Research Design in Qualitative Research

The research design is the overall plan of your research study. It defines the type of study you are going to undertake, sub-type, research problem, hypothesis , variables (dependent and independent), experimental design,  data collection methods, etc. The design of your research may depend on the type of information the researcher wants to uncover as well. Thus, there is a difference between research designs used in quantitative research and qualitative research.

This article looks at, 

1. What is Qualitative Research       – Characteristics of Qualitative Research 2. What is Research Design in Qualitative Research

What is Qualitative Research

Qualitative research is investigative or exploratory in nature and is used by researchers to observe human habits and behaviour. A qualitative approach is used to analyse a problem in depth and develop theories or hypothesis. It is also used to understand underlying causes, opinions, motivations behind something and to discover trends in opinions and thoughts. This is considered to be a subjective approach since this contains observations and descriptions instead of purely statistical data.

Characteristics of Qualitative Research

• Subjective approach
• Used in soft science (social science)
• Complex and broad focus
• Based on observations, communication, and individual interpretation
• Dialectic, inductive reasoning
• Words as the basic element of analysis
• Data collection is done by interviews, observation and analysis of documents.

The design of any research study would depend on the type of information the researcher wants to uncover. There are different types of qualitative research designs; in this article, we are looking at six qualitative research designs:

Figure 1: Types of Qualitative Research Design

Grounded Theory

Grounded theory approach is a special approach whose main purpose is to develop theories. This type of study doesn’t commence with any pre-existing hypothesis or theories . Instead, the theory is developed after the analysis of the collected data. The researcher involved in this research design will first collect data through interviews, observations, review of records or a combination of these methods. He or she will then analyse the collected data and notice recurring ideas and concepts, which will be tagged with codes. As the data analysis progresses, codes will be grouped into concepts and concepts into categories. Categories will then serve as the basis for the theories.

Historical Studies

Historical studies examine past events to understand the present and expect potential future effects. The process involves selecting an appropriate topic after reading related literature, developing research questions, finding an inventory of sources such as achieves, papers, private libraries, etc., verifying their validity and reliability, and collecting data. The analysis of data in this approach will involve the synthesis of all information, and reconciliation of conflicting information.

Case Studies

A case study is a detailed investigation of the development of a single phenomenon or an individual over a period of time. Case studies are generally used to explore complex issues using both qualitative and quantitative data. They are holistic, systematic, context-sensitive and layered. They start with the identification of the research problem, which is then followed by the selection of the cases and the data collection and analysis method. The next step involves the collection of data in the field and analysis. Since case studies focus on a single phenomenon, it is somewhat difficult to use this data to form generalisations.

Action Research

Action research is a type of a research approach that aims to solve an immediate problem. This design can involve a combination of analytical, investigative and evaluative methods designed to diagnose and solve problems. The researcher, who will also act as a participant, will first identify a research problem, clarify theories regarding it and then identify research questions. Next, he will collect data on the problem, and organize them. Then the data will be analyzed and interpreted, and a plan will be created to address the problem. The last steps of this research design involve the implementation of this plan and evaluation of the results of this plan.

Phenomenology

Phenomenology is a study that aims to understand the subjective, lived experiences and perspectives of participants. This is based on the main idea that there are multiple interpretations of the same experience and these multiple interpretations or meanings make up of reality. This approach involves long and intensive interview sessions with various participants in order to gather information about unique individual experiences which offer a rich description of human experiences.

Ethnography

Ethnography is the systematic study of communities and cultures. Researchers engaged in ethnographic studies participate, either overtly or covertly, in the daily lives of the population that are being studied. They spend an extensive time period among this population, watching what happens, listening to what’s being said and asking questions. Interviews, observations and analysis of records are the main methods of data collection in an ethnographic study. The main aim of an ethnographic research is exploring and studying culture from an insider’s point of view.

Conclusion 

As explained above, the research design of a qualitative research study will depend on the type of information the researcher wants to uncover. Although this article only discusses six research approaches, a researcher can use more methods or create his or her own design to discover and evaluate information about a research problem. 

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Choosing a Qualitative Research Approach

Associated data.

Editor's Note: The online version of this article contains a list of further reading resources and the authors' professional information .

The Challenge

Educators often pose questions about qualitative research. For example, a program director might say: “I collect data from my residents about their learning experiences in a new longitudinal clinical rotation. If I want to know about their learning experiences, should I use qualitative methods? I have been told that there are many approaches from which to choose. Someone suggested that I use grounded theory, but how do I know this is the best approach? Are there others?”

What Is Known

Qualitative research is the systematic inquiry into social phenomena in natural settings. These phenomena can include, but are not limited to, how people experience aspects of their lives, how individuals and/or groups behave, how organizations function, and how interactions shape relationships. In qualitative research, the researcher is the main data collection instrument. The researcher examines why events occur, what happens, and what those events mean to the participants studied. 1 , 2

Qualitative research starts from a fundamentally different set of beliefs—or paradigms—than those that underpin quantitative research. Quantitative research is based on positivist beliefs that there is a singular reality that can be discovered with the appropriate experimental methods. Post-positivist researchers agree with the positivist paradigm, but believe that environmental and individual differences, such as the learning culture or the learners' capacity to learn, influence this reality, and that these differences are important. Constructivist researchers believe that there is no single reality, but that the researcher elicits participants' views of reality. 3 Qualitative research generally draws on post-positivist or constructivist beliefs.

Qualitative scholars develop their work from these beliefs—usually post-positivist or constructivist—using different approaches to conduct their research. In this Rip Out, we describe 3 different qualitative research approaches commonly used in medical education: grounded theory, ethnography, and phenomenology. Each acts as a pivotal frame that shapes the research question(s), the method(s) of data collection, and how data are analyzed. 4 , 5

Choosing a Qualitative Approach

Before engaging in any qualitative study, consider how your views about what is possible to study will affect your approach. Then select an appropriate approach within which to work. Alignment between the belief system underpinning the research approach, the research question, and the research approach itself is a prerequisite for rigorous qualitative research. To enhance the understanding of how different approaches frame qualitative research, we use this introductory challenge as an illustrative example.

The clinic rotation in a program director's training program was recently redesigned as a longitudinal clinical experience. Resident satisfaction with this rotation improved significantly following implementation of the new longitudinal experience. The program director wants to understand how the changes made in the clinic rotation translated into changes in learning experiences for the residents.

Qualitative research can support this program director's efforts. Qualitative research focuses on the events that transpire and on outcomes of those events from the perspectives of those involved. In this case, the program director can use qualitative research to understand the impact of the new clinic rotation on the learning experiences of residents. The next step is to decide which approach to use as a frame for the study.

The table lists the purpose of 3 commonly used approaches to frame qualitative research. For each frame, we provide an example of a research question that could direct the study and delineate what outcomes might be gained by using that particular approach.

Methodology Overview

How You Can Start TODAY

• 1 Examine the foundations of the existing literature: As part of the literature review, make note of what is known about the topic and which approaches have been used in prior studies. A decision should be made to determine the extent to which the new study is exploratory and the extent to which findings will advance what is already known about the topic.
• 2 Find a qualitatively skilled collaborator: If you are interested in doing qualitative research, you should consult with a qualitative expert. Be prepared to talk to the qualitative scholar about what you would like to study and why . Furthermore, be ready to describe the literature to date on the topic (remember, you are asking for this person's expertise regarding qualitative approaches—he or she won't necessarily have content expertise). Qualitative research must be designed and conducted with rigor (rigor will be discussed in Rip Out No. 8 of this series). Input from a qualitative expert will ensure that rigor is employed from the study's inception.
• 3 Consider the approach: With a literature review completed and a qualitatively skilled collaborator secured, it is time to decide which approach would be best suited to answering the research question. Questions to consider when weighing approaches might include the following:
• • Will my findings contribute to the creation of a theoretical model to better understand the area of study? ( grounded theory )
• • Will I need to spend an extended amount of time trying to understand the culture and process of a particular group of learners in their natural context? ( ethnography )
• • Is there a particular phenomenon I want to better understand/describe? ( phenomenology )

What You Can Do LONG TERM

• 1 Develop your qualitative research knowledge and skills : A basic qualitative research textbook is a valuable investment to learn about qualitative research (further reading is provided as online supplemental material). A novice qualitative researcher will also benefit from participating in a massive online open course or a mini-course (often offered by professional organizations or conferences) that provides an introduction to qualitative research. Most of all, collaborating with a qualitative researcher can provide the support necessary to design, execute, and report on the study.
• 2 Undertake a pilot study: After learning about qualitative methodology, the next best way to gain expertise in qualitative research is to try it in a small scale pilot study with the support of a qualitative expert. Such application provides an appreciation for the thought processes that go into designing a study, analyzing the data, and reporting on the findings. Alternatively, if you have the opportunity to work on a study led by a qualitative expert, take it! The experience will provide invaluable opportunities for learning how to engage in qualitative research.

Supplementary Material

The views expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Uniformed Services University of the Health Sciences, the Department of the Navy, the Department of Defense, or the US government.

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Faculty & college.

Faculty of Health

Unit description

Equips students with skills to be a scientist-practitioner, including critically reviewing translational research evidence to inform psychological practice, and understanding limitations of evidence-based practice. Students will learn how to design applied research to examine the effectiveness of psychology interventions, including ethical and cultural considerations. Case study design (including N = 1), qualitative analysis, and statistics for psychology practitioners will be covered. Students will also learn how to critically appraise practitioner research methods.

Unit content

• The scientist-practitioner model
• Critically review evidence used by psychology practitioners including research methodology
• Translational research
• Design applied research for psychology
• Single-case research design
• Research methods and statistics appropriate for psychology practitioners

Availabilities

2025 unit offering information will be available in November 2024

Learning outcomes

Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes . The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.

On completion of this unit, students should be able to:

critically appraise and interpret research evidence to guide professional practice in psychology

investigate a substantive research question in professional psychology

design a single-case research study for psychology

select and perform appropriate research methods and statistics for psychology practitioners

Fee information

Commonwealth Supported courses For information regarding Student Contribution Amounts please visit the Student Contribution Amounts .

Fee paying courses For postgraduate or undergraduate full-fee paying courses please check Domestic Postgraduate Fees OR Domestic Undergraduate Fees .

International

Please check the international course and fee list to determine the relevant fees.

Courses that offer this unit

Master of professional psychology (2025), master of professional psychology (2024), any questions we'd love to help.

• Open access
• Published: 08 April 2024

Transformational nurse leadership attributes in German hospitals pursuing organization-wide change via Magnet® or Pathway® principles: results from a qualitative study

• Joan Kleine   ORCID: orcid.org/0009-0005-1727-3683 1 ,
• Julia Köppen   ORCID: orcid.org/0000-0001-7941-641X 1 , 2 ,
• Carolin Gurisch   ORCID: orcid.org/0009-0008-3763-7220 3 &
• Claudia B. Maier   ORCID: orcid.org/0000-0002-7734-2258 2  

BMC Health Services Research volume  24 , Article number:  440 ( 2024 ) Cite this article

19 Accesses

Metrics details

Budget constraints, staff shortages and high workloads pose challenges for German hospitals. Magnet® and Pathway® are concepts for implementing organization-wide change and redesigning work environments. There is limited research on the key elements that characterize nurse leaders driving the implementation of Magnet®/Pathway® principles outside the U.S. We explored the key attributes of nurse leaders driving organization-wide change through Magnet®/Pathway® principles in German hospitals.

Using a qualitative study design, semi-structured interviews ( n  = 18) were conducted with nurse leaders, managers, and clinicians, in five German hospitals known as having started implementing Magnet® or Pathway® principles. The interviews were recorded and transcribed verbatim. Data were analyzed in Atlas.ti using content analysis. For the analysis, a category system was created using a deductive-inductive approach.

Five leadership attributes and eleven sub-attributes were identified as main themes and sub-themes: Visionary leaders who possess and communicate a strong vision and serve as role models to inspire change. Strategic leaders who focus on strategic planning and securing top management support. Supportive leaders who empower, emphasizing employee motivation, individualized support, and team collaboration. Stamina highlights courage, assertiveness, and resilience in the face of challenges. Finally, agility which addresses a leader’s presence, accessibility, and rapid responsiveness, fostering adaptability.

Conclusions

The study demonstrates leadership attributes explicitly focusing on instigating and driving organization-wide change through Magnet®/Pathway® principles in five German hospitals. The findings suggest a need for comprehensive preparation and ongoing development of nurse leaders aimed at establishing and sustaining a positive hospital work environment.

Peer Review reports

European hospitals are facing multiple challenges, including economic pressure, cost containment strategies, technological advancements, and shortages of healthcare professionals, which require constant adaptation [ 1 , 2 , 3 , 4 ]. Particularly concerning is the high burden of mental distress reported by nurses and other healthcare professionals [ 5 , 6 ]. It is increasingly recognized that the root causes of increased stress and burnout among nurses are linked to the work environment in hospitals and other healthcare settings, that is why hospitals should strive to change their working conditions [ 7 , 8 ].

The Magnet Recognition Program® (Magnet) and the Pathway to Excellence® Program (Pathway), both originating in the United States (U.S.) and held at the American Nurses Credentialing Center (ANCC), are designed to facilitate organizational-wide change of work environments, enhancing employee well-being, retention, productivity, and patient outcomes [ 9 , 10 , 11 ]. These concepts can provide a structured approach for European hospitals to tackle the challenges of the future effectively.

Research on Magnet hospitals, primarily conducted in the U.S., suggests that Magnet can enhance working conditions, job satisfaction, and nurse well-being in hospitals [ 12 , 13 , 14 , 15 ], while also improving patient outcomes [ 14 , 15 , 16 ]. However, findings across studies and outcomes vary. In contrast, the impact of Pathway has received less attention in research. Nevertheless, some studies have indicated that Pathway promotes increased nurse autonomy and decision-making authority, fosters leadership development, improves safety and quality standards, enhances employee well-being, and supports professional growth [ 17 , 18 ].

As of December 2023, 591 organizations worldwide had Magnet designation [ 19 ], and 214 had Pathway designation [ 20 ], with the majority in the U.S. Internationally, only 17 hospitals hold Magnet designation [ 19 ] and 16 have Pathway designation [ 20 ]. While none of them are in Germany, some German hospitals have proactively started implementing Magnet/Pathway principles to drive organization-wide changes aiming at enhancing job satisfaction, attracting and retaining healthcare professionals [ 21 , 22 , 23 , 24 ]. Hence, the inclusion of Magnet and Pathway principles as comparable case examples of organization-wide change in the current study is justified by the growing proactive adoption of these concepts by some German hospitals.

Magnet and Pathway focus on promoting nurse engagement and supporting professional nursing practice environments. The difference lies in their specific objectives: Magnet emphasizes sustained quality patient care, nursing excellence, and innovations in professional practice, while Pathway highlights creating supportive practice environments that empower and engage staff and is known for having less stringent data requirements [ 25 , 26 ]. However, both aim to cultivate a culture of nursing care excellence, supported by a transformational leadership style [ 25 ], which is the central focus of the present study.

Leadership skills do play a crucial role in successfully promoting organization-wide change [ 27 , 28 , 29 ] and has also been shown to have a profound impact on employee stress and emotional well-being [ 30 ]. Transformational leadership was identified as one effective leadership style in healthcare settings [ 29 , 31 , 32 , 33 ]. Transformational leaders motivate employees towards an organizational vision by inspiring and empowering them to continuously develop themselves and addressing their individual needs [ 34 , 35 ]. The theoretical framework for transformational leadership was first conceptualized in the 1970s, defining it as a relationship between leaders and employees who motivate, empower, and elevate each other’s moral values in pursuit of fulfilling common interests [ 36 ]. Further expansion by Bass and Avolio introduced four subcategories that represent the characteristics of transformational leaders: Idealized influence, inspirational motivation, intellectual stimulation, and individualized consideration [ 34 , 35 ].

Several U.S. studies have analyzed the relationship between transformational leadership and the implementation of Magnet principles [ 37 , 38 , 39 ]. In a southern U.S. nonprofit acute care hospital seeking Magnet designation, a survey of 115 staff nurses showed that transformational leadership style was positively associated with nurses’ job satisfaction and satisfaction with promotion opportunities [ 37 ]. Magnet hospital CNOs rated their transformational leadership practices highly and reported a strong positive correlation between engagement and leadership practice, with empowering others as the most important practice [ 38 ]. A study of clinical nurse leaders, who attended the 2016 Magnet Conference in Orlando, Florida, showed a positive relationship between transformational leadership practices and work engagement, but observed differences in leadership practices and work engagement based on varying levels of education [ 39 ].

The majority of research conducted outside of the U.S. has focused on investigating the impact of transformational leadership style within healthcare settings, with no focus on the implementation of Magnet/Pathway [ 29 , 31 , 32 , 33 , 37 , 40 , 41 , 42 , 43 , 44 , 45 ]. Several studies found that forms of transformational leadership styles resulted in positive organizational performance, such as improved staff retention, lower turnover, and better quality of care [ 31 , 32 , 33 , 37 , 40 , 41 ]. A systematic review including 12 studies from the US, Canada, Saudi Arabia, China, Ethiopia, Italy, and Jordan, showed a positive correlation between transformational leadership and nurses’ job satisfaction in the hospital setting [ 29 ].

To date, most of the qualitative studies analyzed transformational leadership style from the nurse leaders’ perspective. A study from Finland used a qualitative design to examine nurses’ leadership skills in leading change [ 44 ]. They identified three main roles: First, ‘leading interpersonal relationships’ including competencies of being a team player, coach, and parental figure. Second, ‘leading processes’ including competencies such as organizing, coordinating, and being a conductor based on the organization’s mission. And third, ‘leading a culture’ is defined as advocating values and norms and creating an open, resilient, and evidence-based culture [ibid.]. Another study from 2016 explored senior nurses’ experiences of organization-wide change leadership in three NHS acute hospitals in England through in-depth interviews [ 43 ]. The aspect of leadership was frequently discussed in relation to organization-wide change. An effective nurse leader was characterized as a strong, inspiring, and supportive leader with novel and heroic approaches [ibid.]. Weak leaders were those who did not encourage their teams, had poor presence and were unresponsive to the need for change [ibid]. Another qualitative study used a grounded theory approach to examine the processes nursing management uses to promote change on their wards in five hospitals in Japan [ 45 ]. According to the interviewees, the change management process led by nurse managers consists of having beliefs and being able to empathize with the nursing staff to achieve common goals [ibid.]. Four characteristics of nurse leaders were reported as indispensable factors for change: having both a micro and macro perspective; respecting their own beliefs and external standards; being proactive; having empathy for nursing staff [ibid.]. A 2020 study conducted in a university hospital in Brazil, examined the challenges of exercising transformational leadership and strategies nurses leaders used to address these challenges include being role models for the team, proactively maintaining dialogue with co-workers, and building empathetic relationships [ 42 ].

In German hospitals, a cross-sectional study investigated nursing leadership styles, analyzing the self-assessment of 93 ward managers and the external evaluation of 1,567 employees with the multifactorial leadership questionnaire (MLQ-5X), revealing the presence of transformational leadership practices [ 46 ]. The ward management consistently achieved mean values above the scale mean in all dimensions of transformational leadership, both in the self-assessment and in the external evaluation [ibid.]. However, despite the acknowledged existence of transformational leadership practices in nursing within German hospitals, research on the attributes of nurse leaders that support organization-wide change through implementation of Magnet/Pathway principles remains scarce. This study aims to identify beneficial attributes of nurse leaders from German hospitals, shedding light on their role in driving organization-wide change through Magnet/Pathway and advancing the understanding of leadership practices’ impact within the German healthcare systems. Research on this topic is critical to fill a gap in the literature regarding nurse leader attributes that facilitate organization-wide change and can provides insights that could inform nursing leadership development initiatives tailored to the needs of German hospitals seeking Magnet/Pathway designation.

Design and setting

This study was conducted as part of the German Magnet pioneer study, based on a qualitative research design in five pioneer hospitals. Semi-structured interviews were conducted between March and October 2020 with nurse leaders, managers, and clinicians involved in introducing Magnet or Pathway principles in five German hospitals. Inclusion criteria were as follows: (i) hospitals known as pioneers, defined as early adopters of the Magnet or Pathway principles, (ii) having started the implementation on their own initiative prior to 2020. For the purposes of this study, the primary focus was on the leadership attributes of nurses driving organization-wide change using Magnet/Pathway principles. The research protocol was approved by the Ethics Committee of the Charité (No. EA4/185/19). This study used the consolidated qualitative research reporting criteria (COREQ) [ 47 ].

The semi-structured interview guide contained a total of nine question with a set of probing questions. Topics covered motivation and rationale for implementing Magnet/Pathway, the identification of facilitators and barriers, of which one question was specifically on the role of leadership. However, interviewees referred to leadership attributes and practices throughout the interview in various instances. All interviewees filled out a short questionnaire on demographic characteristics and information about their role in the hospital, position, and years of work experience.

Sample recruitment

The purposive sample consisted of 18 persons from the five hospitals. Hospital size ranged between 200 and 2000 beds. Interviewees were nurse leaders, managers, and clinicians who had gained experience with the implementation of Magnet/Pathway. All requested interview partners agreed to be interviewed.

Data collection and analysis

Interviews were conducted in German and face-to-face by three members of the research team, following the semi-structured interview guide. The interviews lasted between 30 and 135 min. The interviews were anonymized and transcribed verbatim and were coded with ID01-ID18. The analysis of the anonymized transcripts was carried out in a multi-stage procedure based on content analysis, with a content structuring and summarising approach according to Mayring [ 48 ].

A deductive-inductive approach was chosen. The transcripts were coded using the data analysis software ATLAS.ti. For the deductive coding a coding guide was developed prior to the analysis based on the five components of the Magnet model [ 10 ]. Subsequently, the content of the deductive code leadership was re-analyzed in-depth inductively to answer the research question.

Several measures were applied to ensure transparency and quality. This involved investigator triangulation whereby the three researchers were involved in the data collection, analysis, and interpretation of the study [ 49 ].

Prior to the interviews, the three researchers conducted pilot interviews among themselves to ensure consistency. The coding of the interviews was performed by the three researchers who also conducted the interviews. Each coder was familiar with all 18 transcripts. After a pilot analysis phase with three interviews which were coded together and discussed at length to achieve high interrater agreement, the transcripts were randomly allocated. In regularly scheduled meetings, the coders reported the interim status and discussed problems or questions regarding the analysis and reviewed sample content of the codes together. In the next step, themes and sub-themes were formed by the researchers and discussed. Examples of quotes from interviewees are provided in the results section to enhance understanding of the interpretation of the results.

Interviewee characteristics

The 18 interviewees had a mean age of 48.9 (SD: 10.0) years, seven were female and eleven male. The majority ( n  = 16) had a degree in nursing and two a degree in medicine. Leadership and/or staff responsibilities had 17 interviewees and on average they had five (SD: 2.8) years of experience with implementing Magnet/Pathway (see Table  1 ).

All 18 transcripts were included in the analysis, regardless of whether direct quotes are shown in this study. Five main leadership attributes (subsequently referred to as main themes) driving organization-wide change using the Magnet/Pathway principles were identified: visionary, strategic, supportive, stamina, and agility. The main themes consist of eleven sub-themes (see Table  2 ).

Main theme 1: Visionary

Two sub-themes were clustered as the main theme visionary. It emerged that having a vision and acting as a role model were identified as requirement to implement organization-wide change.

Having a vision

Most interviewees agreed that leaders need a vision that they carry with conviction and strive to realize with high motivation. Interviewees suggested that a leader who is visionary would inspire employees for the change process. Furthermore, some interviewees mentioned that it is beneficial if leaders communicate well their vision of the future to their employees.

“With a vision I can inspire people. So, I need something that is strong enough, that really radiates energy, that […] gives people courage.” (ID9) .

It was seen as essential that the visions should be catchy, based on clinical practice and reflect the needs of clinical practitioners. One of the interviewees also mentioned the involvement of employees in the practical elaboration of the vision.

“So, I […] presented the vision to my team. […] And we went into working groups on how we can implement it, how we can live it. We have three keywords in there: human, competent, pioneering.” (ID14) .

The interviewees described the need for people who serve as role models that adhere to their vision, ideals, and values and stand up for them. Leaders acting as role models were identified as being less concerned with fulfilling specific criteria for maintaining a label or certificate but focused on improving the well-being of employees and quality of care. Interviewees explained a role model function of leaders as beneficial when employees could identify with their leaders, as this makes it easier to formulate and accept the vision and values as common goals. One interviewee stressed the importance of the personality of the leader and their manner of communicating with their staff.

“I would almost reduce it to the personalities that drive the whole thing. So, it always depends on how you transmit something, how do you communicate, how do you deal with your staff.” (ID4) .

A role model as an inspiration was suggested to increase the motivation of the employees to develop themselves and eventually to work towards the achievement of common goals.

“For me it was […] exciting to have a nursing director who brought special knowledge and an enthusiasm that I sometimes missed in the nursing field. […] just ahead of the times and […] powerful with motivation and of course that caught me.” (ID2) .

Main theme 2: Strategic

Two sub-themes were identified under the main theme strategic: Critical attributes as strategic planning and convincing top management contribute to effective implementation of positive change.

Strategic planning

Interviewees mentioned that leadership attributes included the ability to plan strategically to meet the goals of the hospital. For example, one of the interviewees described that the implementation of transformational leadership had been the key to driving further changes in the direction of Magnet.

“I think that the key component to live the Magnet concept is transformational leadership. […] I first must manage through leadership to keep people and attract new ones. And if that succeeds, […] then I can bring the other components into life […].” (ID9) .

Some interviewees highlighted the relevance of strategic resource allocation to be able to initiate and sustain the hospital-wide change via Magnet/Pathway principles. This included investing in human resources, e.g. nursing scientists or project coordinators, and in structural development, e.g. data management or digitalization. One interviewee described the strategy of providing budget or other cost-related information for the top management and the board required for Magnet/Pathway implementation.

“There needs to be at least […] an overarching Magnet project manager or director. […] last year I made an initial rough calculation for the board […] as a template, what it would cost the hospital. […] because that is of course indispensable.” (ID7) .

Convincing top management

Most interviewees addressed the importance of seeking and gaining the support of top management to advance change processes.

“The first step, […], was to convince the executive director, because the combination is simply necessary to do anything at all.” (ID4) .

One interviewee underscored the importance of active involvement and dedication from top-level decision makers and management in driving organization-wide change processes.

“So, I think you definitely need […] - the decision makers, the management - they must commit themselves clearly to it, and they must have a vision in this direction […].” (ID5) .

Main theme 3: Supportive

Three sub-themes were clustered under the main theme supportive. To be a supportive leader who fosters an empowering workplace to meet Magnet/Pathway principles, it was described as important to inspire and motivate employees to evolve professionally, support employees individually in developing themselves and their ideas further and cultivate a strong team spirit as a team player to pursue common goals.

Inspiration and motivation

Some of the interviewees talked about encouraging and inspiring employees to go beyond themselves. Increasing employees’ self-confidence enabled them to make their own decisions and motivated them to evolve professionally. This increased the motivation to drive positive change within the organization. One of the interviewees further explained that the higher the motivation in the team, the faster positive changes could be implemented.

“The half of it is […] that you get moving forward and, of course, the more motivated you are, the faster and the better you get moving forward. So, it’s about strengthening motivation and this for the whole team and making sure that you get better professionally.” (ID2) .

A leader should have a passion for the intended changes to persuade and motivate all employees and should take into account the time component of implementing organization-wide change using the Magnet/Pathway concept.

“And you have to be passionate about the topic, otherwise the concept won’t work either. That takes time at first. And then the biggest task is to get all the employees on board.” (ID4) .

Individual support of employees

The individual support of employees by leaders was recognized as indispensable when it comes to empowering them. According to the interviewees it was important to create a trusting working environment and to make employees feel that they are supported in developing themselves and their ideas further.

“[T]he employees must feel something is getting better for me. Managers are standing up for me, they are behind me. That is what is important for employees.” (ID9) .

However, finding the right support for each employee required individual consultation. Only in this way special circumstances and needs could be considered in a targeted manner. In particular, support for the academic training of bedside nurses is mentioned by interviewees as an example which underscores the significance of management’s role in facilitating and encouraging such endeavors.

“[…] there was […] a young [male nurse] sitting there […] who says, ‘Yeah, did I get this right, you want us all to have academic degrees?’ And he says, ‘Listen, I’m 35, I have three kids, I can’t afford to give up one euro right now at all.’ And [the CNO] understands, of course, there are priorities. But then you must see how you can support someone like that. […] If someone wants the [bachelor in nursing] […] then there is massive support, especially at the management level.” (ID7) .

Team player

The interviewees shared the idea that inspiration, motivation, and support of staff succeed more effectively when leaders are perceived as team players. According to the interviewees, a strong team spirit strengthens motivation to pursue common goals and helps not to give up. It also supports the well-being of all employees in their daily work.

“The team spirit is so important because if you motivate a team, if you win a team, and if you, as the leader of such a team, ensure that people enjoy working together and that the day-to-day problems can be sorted out, and if it says at the top and at the front: We are a team, we do this together, and together we are strong, Then you have already won half of everything that can be won.” (ID2) .

An interviewee at a higher managerial level additionally stated that it is important to always maintain a friendly atmosphere and show appreciation to receive important information about current issues and concerns in the teams. Decisions should not be made alone, but should always be considered with the teams, as they know more about the day-to-day matters of the staff members.

“We have […] a very, very friendly interaction, because I think that they are not my subordinates, they are my ward managers and they are the most important source of work for me, so to speak. Without them, I wouldn’t need to show up here to work, without my ward managers interacting with their teams, knowing exactly what’s going on here right now […], where’s the tension right now? What’s going well right now, what’s not going well right now?” (ID17) .

Main theme 4: Stamina

Two of the sub-themes were clustered as the main theme stamina. It emerged that implementing organization-wide change requires leaders who have strong personalities with courage and assertiveness.

The interviews showed that courage and a willingness to take risks in a context of uncertainty, which requires change, is experienced as a beneficial leader attribute. For the interviewees, courage meant being committed to the community and pursuing a vision and goals and being persistent about them. The step of opting for the implementation of organization-wide change with the Magnet/Pathway is described by some interviewees as a dare and leaders should be prepared for negative effects and to face resistance.

“I would say: Yes, you can always change something. And I didn’t let myself be discouraged […]. Sometimes people have said that we can’t really implement the Magnet concept here. And for me it was always important which ideas from the concept can be implemented and this I want to implement […], but I don’t let that stop me. […] And of course you also need leaders who are strong enough to say: ‘I know, even if it sounds crazy, we’re going in that direction now’.” (ID9) .

Nevertheless, especially in times of nursing shortages and high workload, it was important to have a sense of achievement to summon up courage. One of the CNOs interviewed reported that due to a high number of applicants to study nursing in the interviewee’s initial phase at the hospital, the interviewee had gained the courage to believe in the change concept and continued to pursue the interviewee’s vision despite high workloads and poor moods among the nursing staff and continued to pursue their vision.

“[…] despite reports of work overload, which reached me in droves at that time in my starting phase […], and then I was talking about academic training, actually I almost got a slap in the face, but at the same time [many] applied [to study nursing]. And then that was again the point where I had confidence: ‘You’re sticking to it; you have the courage’.” (ID3) .

Assertiveness

Interviewees agreed that implementing organization-wide change requires a high level of commitment and that leaders should have assertiveness. It was mentioned that it is important to prepare for the long term and to be aware of the length of time required to drive change processes using the Magnet/Pathway concept.

“I think the concepts themselves are very, very complex and take an incredible amount of time to implement. But it is possible. You just need someone who has stamina and who stands there and says, ‘So, and I want this, and this is the way, and this is my way, and I’m going to follow through.‘” (ID14) .

A sufficient individual resilience of leaders in hospitals was described as crucial to be able to overcome past failures, learn from them and stay positive. An interviewee described that initial rejection of new intervention plans by employees was initially perceived as a setback, but the leaders remained strong and learned from it.

“Well, that certainly took its time. [The CNO] came back [from U.S.] to the hospital with lots of new ideas and everyone who hears something new first says: ‘Stop, hold this. […], English words, now we only use English words. What does Magnet mean at all?’ and there was already a lot of distance from the employees […]. But then [the CNO] was able to convince […] at least the mangement level.” (ID4) .

Convincing top management was also described as an endeavor and requires the attributes of assertiveness and courage. One example is to advocate for one’s employees.

“And my job as a CNO, of course, is to fight to make sure that my nurse leaders have the resources, from time, to space, to other things, to be able to do good leadership.” (ID9) .

Main theme 5: Agility

In the context of this study, agility means the ability to adapt flexibly and quickly to changing tasks, circumstances, and demands as well as fostering a sense of team spirit. Two of the sub-themes were clustered as the main theme agility; showing presence and demonstrate well and fast accessibility and responsiveness.

Showing presence

It emerged from the statements of the interviewees that showing presence and direct personal contact of the leaders towards the employees was an important competence to keep up the commitment of the employees for implementing positive change within the hospital.

“Of course, I’m also in favour of the director of nursing not working at the bedside anymore […], but they should also not forget the direct contact to those who do the frontline work.“(ID2) .

With personal presence the leader’s appreciation of frontline workers and the interest in their well-being could become more tangible. It would also be a better way to transmit enthusiasm for the overarching, common goal to employees. Likewise, communication lines would be shortened, and employee concerns and needs could be addressed quicker. One of the interviewees shared a key moment when the CNO introduced himself unannounced at a staff meeting, and this sparked a sense of optimism among the employees.

“And I don’t think there’s ever been anything like this before, where a team meets for a dialogue and all of a sudden the CNO comes in and introduces himself and also says something about his philosophy and how he would like it to be. […] And that was the first jolt, because the employees realized, there’s someone who’s not untouchable, but there’s someone who’s like us.” (ID14) .

Another interviewee stated that they were expected as a nurse leader to know as many of the employees personally as possible. This was an essential factor for equal interaction between the professional groups.

“I know a lot of our nurses […], I know all the academic nurses, […] people expect me to take an interest in them. The whole eye-level system means that you really give everyone a name as well, not just a number anymore.” (ID1) .

One of the interviewees acknowledged that a lack of presence at the frontline work, as well as a lack of interest in the processes by the leader, had negatively impacted the success of implementing change processes.

“He [CNO] wasn’t on the wards; he didn’t see that as his responsibility either. It was more like; he gives the strategy and then the others are supposed to do the implementation. That just didn’t work out well. […] it was certainly a barrier that the [CNO] had little understanding of the daily operational problems. […] It would still have been easier if the employees had experienced him as being a little closer to the employees.” (ID10) .

Accessibility and responsiveness

In addition, interviewees explained that by showing presence outside of their own office, leaders should also cultivate an “open door”-culture and be available to meet with employees at short notice. This includes accessibility via various communication channels but also quick responsiveness.

“My door is open all day. I am not the leader who is available once a year for one hour […], but I am permanently there for dialogue, I do have time.” (ID6) . “We do a topical hour with the nursing directorate where they can come and get in touch with science here. [AND] Cappuccino with the nursing directors; where everyone can come without an appointment and also have individual talks […].” (ID3) .

Another interviewee used a current occurrence to stress the importance of responding to employee requests as soon as possible to keep them motivated.

“Right before you came in, there was a colleague who asked me […] if he could do a work shadowing. Within three minutes he got his answer […]. What use has a rigid structure, if you let someone like him wait for two weeks and say ‘Well, I was overworked’? You have to address these things.” (ID2) .

The findings of this study shed light on the attributes of nurse leaders in German hospitals that drive organization-wide change using Magnet/Pathway, which are aimed at improving employee well-being, productivity, and patient outcomes. A key component of the concepts is the practice of transformational leadership [ 9 ]. The results highlight five main themes that encompass beneficial leadership attributes: visionary, strategic, supportive, stamina, and agility.

The theme of visionary underscores the significance of visionary leadership in driving organization-wide change towards Magnet/Pathway. Having a clear and compelling vision that is communicated effectively to employees emerged as a key factor. The role of leaders as role models who embody vision and values was also emphasized. This aligns with existing literature on transformational leadership, which emphasizes the importance of idealized influence and inspirational motivation [ 34 , 35 ]. Leaders who serve as role models and inspire others create a sense of identification and motivation among employees to work towards common goals.

The theme of strategic highlights the role of strategic planning and resource allocation in Magnet/Pathway implementation. Several studies confirmed that strategic thinkers are among the most effective leaders. People with the ability to think strategically are more likely to ensure the sustainable success of an organization and are better able to put existing strategic plans into execution [ 50 , 51 , 52 , 53 ]. Furthermore, this study emphasizes the importance of leaders advocating for Magnet/Pathway principles to gain the support and commitment of the top management. Convincing the top management was seen as crucial for the success of change efforts.

The supportive theme emphasizes the significance of individualized support for employees’ development and well-being. This includes empowering employees to pursue further education, addressing their unique needs, and fostering a trusting work environment. This study highlights the role of leaders in providing resources and support for academic advancement, which aligns with the Magnet key component on structural empowerment. Furthermore, the importance of team spirit and collaboration was emphasized, echoing the Magnet/Pathway principle of exemplary professional practice and a collaborative work environment. Supportive leaders act as team players and inspire and motivate their staff to perform beyond the norm [ 38 , 54 ]. They support staff nurses to assessing their own performance, working out their goals and defining their responsibilities [ 38 , 43 , 44 ]. As a result, nurse leaders can promote knowledge building, intrinsic motivation and innovative work behavior among nurses [ 54 ].

In the German healthcare system, it is noteworthy that not every nursing director automatically holds a position on the hospital’s executive board, underscoring the importance of engaging top management in organizational change initiatives. Additionally, given that lifelong learning and continuous professional development are not standard practices in nursing in Germany, contrasting with the conditions required for Magnet/Pathway implementation, it highlights the crucial role of CNOs in empowering their staff and fostering a culture of lifelong learning and professional growth.

Results of previous qualitative studies analyzing transformational leadership style from the nurse leaders’ perspective confirm these findings. They include competencies such as a strong, inspiring, and supportive leader with novel approaches. The leaders serve as role models and are able to empathize with nursing staff to achieve common goals [ 42 , 43 , 44 , 45 ]. By cultivating a visionary outlook and a supportive stance, nurse leaders can effectively foster work engagement, address burnout, and create a motivating environment for healthcare professionals. Importantly, these leadership qualities can be learned and improved over time among nurses through targeted educational interventions, training, mentoring, and hands-on experiences [ 55 , 56 , 57 ]. Nevertheless, while some leadership skills can be developed through training and experience, certain innate character traits may provide an inherent advantage in the cultivation of effective leadership [ 58 ]. For instance, personality traits such as emotional intelligence, empathy, and authenticity have been linked to leadership effectiveness [ibid.]. Although these traits may not be directly teachable, they may serve as foundational elements that contribute to the development of successful transformational leadership practices.

The alignment between the findings of this study and those from various international contexts raises important implications for both the Magnet/Pathway implementation process and the broader understanding of transformational leadership. The resemblance between the identified leadership attributes and those found in studies conducted in different countries suggests a level of universality in the leadership qualities required for successful organization-wide change, particularly in healthcare settings. Furthermore, the consensus between the leadership attributes identified in this study and those from international research may imply that studies solely focused on transformational leadership can offer relevant insights for organizations pursuing Magnet/Pathway designation.

Given the diversity of leadership approaches across other sectors (including industry), it is important to recognize the contextual relativity of specific leadership traits. While the leadership attributes identified in this study are tailored specifically to nursing within hospitals, they may be relevant in other sectors, but require further evaluations in different contexts. While a leader’s ability to communicate a clear vision and motivate employees is as crucial in the business sector as in healthcare, the best way of communication and motivation may vary.

New insights that expand the understanding of the role of leadership in driving organization-wide change that emerge from this study is the perspective on the themes of stamina and agility in the context of transformational leadership and Magnet/Pathway implementation.

The theme of stamina reflects the perseverance and resilience required for implementing Magnet/Pathway principles. Leaders need courage to navigate uncertainty and take calculated risks. Leaders should want to make changes and push them forward with stamina and assertiveness, and who are not afraid to speak up and ask for support from higher authorities. In the context of transformational leadership, stamina has often been discussed as a leader’s perseverance, determination, and resilience in the face of challenges [ 34 ]. However, the findings of this study emphasize a more profound dimension of stamina as the leader’s ability not only to persevere, but also to inspire and sustain momentum during complex, long-term endeavors such as Magnet/Pathway implementation.

The concept of agility as an essential leadership skill has gained attention in recent years and refers to a leader’s ability to adapt quickly to changing circumstances. This aligns with the dynamic nature of healthcare settings, where leaders must respond to changing demands [ 59 ]. Interviewees in this study emphasized the positive impact of agile leadership, which enables leaders to respond rapidly, purposefully, and individually to different situations [ 59 , 60 , 61 ]. By adapting task structures and difficulty levels to match employees’ needs and commitment, leaders can prevent both under- and over-challenging their team members, thereby facilitating their professional development [ 59 , 60 , 61 ]. With the sub-themes showing presence as well as accessibility and responsiveness, it became clear that leaders should be in regular exchange with their employees to be able to react agilely to the requirements and needs [ 62 ]. In contrast, the findings confirm that the lack of frontline presence as well as the leader’s lack of interest in the processes negatively impacted the success of Magnet/Pathway implementation. However, in the context of Magnet/Pathway implementation, agility goes beyond flexibility to include a dynamic responsiveness to evolving healthcare challenges. The results show that leaders need to be flexible not only in their decision-making, but also in their accessibility and responsiveness to employees. This reflects a proactive approach that not only supports the implementation of the Magnet/Pathway principles, but also ensures that employees remain engaged and motivated throughout the transformation process.

Limitations

This study has several limitations. Firstly, the interviews were conducted in only five German hospitals, yet they were the first ones known to have started introducing Magnet or Pathway in Germany. While these hospitals provided valuable insights into the implementation process, the perspectives shared by leaders and staff are not representative of all hospitals in Germany, limiting the generalizability of the findings. Secondly, the majority of interviewees in this study were nurse managers or individuals with leadership responsibilities. As a result, the findings primarily reflect the management and leadership perspective, potentially overlooking the viewpoints and experiences of frontline nurses. It is important to consider a wider range of perspectives to gain a comprehensive understanding of the challenges and opportunities associated with leadership while implementing Magnet/Pathway principles.

This study provides in-depth insights into the leadership attributes that drives the implementation of organization-wide change through Magnet/Pathway principles in German. It offers guidance for nurse leaders seeking to drive positive organization-wide change and enhance employee well-being.

The interviewees in this study emphasized the importance of leadership competencies such as visionary direction, strategic planning, personalized support, resolute stamina, and adaptive agility. The themes of stamina and agility offer new insights, showcasing the need for courage, assertiveness, and adaptability in leaders driving long-term organization-wide change towards Magnet/Pathway.

Given the vital role of transformational leadership in driving organization-wide change, as well as the fact that transformational leadership skills can be trained, a comprehensive preparation and ongoing development of nurse leaders toward transformational leadership skills may support establishing and sustaining a positive work environment in hospitals.

Data availability

A 32-item checklist for interviews and focus groups (COREQ) and the coding tree are provided as supplementary material. The transcripts used and analyzed during the Magnet pioneer study are available from the corresponding author on reasonable request.

Abbreviations

American Nurses Association

American Nurses Credentialing Center

Chief Nursing Officer

Consolidated Criteria for Reporting Qualitative

Interviewee Identification

Multifactor Leadership Questionnaire

National Health Service

Standard deviation

United Sates of America

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Acknowledgements

We extend our thanks to the 18 interviewees for their time and valuable insights, especially considering the challenges posed by the COVID-19 pandemic during the interview data collection period. Their willingness to participate in this study is greatly appreciated and has significantly contributed to our research. We also thank the consortium of the Magnet4Europe study.

The Magnet pioneer study was funded by the B. Braun Foundation (Grant No. 18001021). Additional time on the study was funded by a grant from Robert Bosch Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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CBM was the PI of the Magnet pioneer study and planned the study and its methodology. CBM and JuK contributed to the study’s design. CBM, JuK and JoK performed data collection and conducted the deductive analysis of the data. JoK conducted the main inductive analyses for the purpose of the current study. CBM and JuK provided critical review and discussion of inductive coding. JoK wrote the first draft manuscript, and prepared tables. CBM, JuK and CG were involved in subsequent iterations and conducted critical review of the manuscript.

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This research has been performed in accordance with the Declaration of Helsinki with ethics approval through the Ethics Committee of the Charité (No. EA4/185/19). Written informed consent was obtained from all interviewees prior to the interviews. For interviewees, neither advantages nor disadvantages resulted from participation or non-participation in the study. Participation could be withdrawn at any time without consequences till anonymizations.

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Kleine, J., Köppen, J., Gurisch, C. et al. Transformational nurse leadership attributes in German hospitals pursuing organization-wide change via Magnet® or Pathway® principles: results from a qualitative study. BMC Health Serv Res 24 , 440 (2024). https://doi.org/10.1186/s12913-024-10862-y

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A qualitative study exploring women’s empowerment in coffee cooperatives in Chiapas, Mexico

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Eissler, Sarah; Rubin, Deborah; and de Anda, Victoria. 2024. A qualitative study exploring women’s empowerment in coffee cooperatives in Chiapas, Mexico. IFPRI Discussion Paper 2248. Washington, DC: International Food Policy Research Institute.

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This study presents findings from a qualitative research study conducted in Chiapas, Mexico that is one component of a larger activity funded by the Walmart Foundation and implemented by the International Food Policy Research Institute (IFPRI), titled Applying New Evidence for Women’s Empowerment (ANEW). ANEW seeks to generate evidence from mixed-methods evaluations of women’s empowerment in production and other entrepreneurial efforts at different nodes of agricultural value chains and aims to develop and validate measures of women’s empowerment that focus on agricultural marketing and collective empowerment at the group level, both of which build upon the project-level Women’s Empowerment in Agriculture Index for Market Inclusion (pro-WEAI+MI). In this report, we present findings of a qualitative study of coffee cooperatives supported by Root Capital in Chiapas, Mexico and how Root Capital engages with them to advance women’s economic empowerment, among other objectives. As part of this study, we aimed to describe the gender dynamics and roles and responsibilities of men and women in the coffee value chain in Chiapas, and the opportunities and barriers faced as a result of these dynamics. This study employed qualitative methods to collect primary data from types of respondents using individual and group interviews. Two coffee cooperatives in Chiapas that work with Root Capital were selected to participate in this study. From June to July 2023, 21 individual interviews and 9 group interviews were conducted with market actors, men and women coffee cooperative leaders, men and women cooperative members and their wives, and Root Capital staff from two municipalities in Chiapas. The data were transcribed into Spanish and then translated into English. These transcripts were analyzed using thematic analysis in NVivo software. A codebook inclusive of inductive and deductive themes was developed to guide the thematic analysis. This study design adhered to best practices for ethical research and received approval from IFPRI’s IRB. Several limitations should be considered when reviewing the findings and conclusions of this study. There exist defined gender roles and divisions of labor at each node of the coffee value chain in Chiapas, and participants often described these roles as expected given social norms or perceived gender-specific limitations of natural abilities that would shape how men or women could engage in different activities. Men and women indicated that while men are in charge of coffee production activities, women do spend time contributing to cleaning and management activities, and that women are heavily involved in the coffee harvest. Both men and women explained that women are responsible for processing activities, which can be time consuming and laborious, but often occur close to the home. Although the coffee harvest activities require physical labor in picking and carrying the baskets of ripened cherries, there is a perception that women cannot participate in other post-harvesting activities, such as transporting bags of coffee, because the lifting is too physically heavy of a task for women. Men are responsible for managing the sale of coffee and directly negotiating with the buyer to the extent that a negotiation happens. In instances when buyers travel to the household as the point of sale, women can participate in sales, typically facilitating the sale under the direction of her husband. However, women still do not lift the coffee bags nor transport the bags for sale. And many coffee producing households prefer to or sometimes need to hire labor to help with coffee harvest activities; they tend to hire men as laborers more out of preference or their availability compared to women. Men and women interviewed for this study also described their perceptions and understanding of empowerment and elements of an empowered person with relation to engaging in the coffee value chain. Overall, while the concept of an empowered person was difficult for both men and women to relate to, they shared perceptions of how relations between men and women had changed over the years. Respecting women’s rights or the perception of respecting women’s rights was more acknowledged at the time of the interviews than in previous years, and it was more common to see men and women both generating incomes for the household. Men and women shared different perspectives regarding attitudes toward intimate partner violence, whereas both acknowledged men often mistreated their wives, but women discussed it as a private matter where men shared concerns over women’s reaction to the mistreatment rather than the mistreatment itself. Varying access to resources limited both men and women farmer’s ability to advance in the coffee value chain, particularly access to credit, which was limited for both men and women in the study areas. Limited access to credit with favorable or reasonable terms limited men’s and women’s ability to hire additional labor on their coffee farm or to purchase machines that would reduce specifically women’s time burdens within the household. Women’s time use is constrained by expectations and normative tasks in ways that men are not constrained. Future research is needed and discussed to better understand these dynamics of gendered roles and relations and elements of empowerment in the coffee value chain in Chiapas. Men and women members of the two respective cooperatives shared differences in how they were able to participate in and benefit from their participation in each cooperative. One cooperative provided more opportunities for members to directly engage in meetings, social activities, and capacity building opportunities whereas the other operated through a more decentralized structure and did not offer opportunities for members to directly participate in decision-making or meetings beyond the representation of their delegate. Members of both cooperatives perceived their cooperatives to be consistent and reliable coffee buyers offering stable prices. The former cooperative was also perceived as a source of support and community for members to advance their coffee production and post-harvesting activities. Both cooperatives also addressed key barriers faced by members, such as providing consistent and reliable pricing. Some members reported that cooperatives offered higher prices than those offered by non-cooperative buyers. Cooperatives also provided transportation options for producers to sell their coffee, which also enables women to have more engagement in coffee sales. However, normative barriers, such as women’s existing time burdens and their need for their husbands’ permission, limits women’s full participation in the cooperatives. Finally, we explored the extent to which Root Capital’s engagement with the cooperatives had supported activities or changes that strengthen women’s empowerment by understanding members and leaders’ perceptions of this engagement. Overall, cooperative members were generally unaware of Root Capital and its engagement with the cooperative. Since Root Capital does not provide direct services to farmers or cooperative members, it was not surprising that many cooperative members were generally unaware of Root Capital and its engagement with the cooperative. However, a few were aware of Root Capital, knowing it had provided their cooperative a loan to purchase and maintain a truck, which was used to reduce barriers faced by producers to bring their coffee to the point of sale and had implications for shifting gender roles to manage coffee sales. Cooperative leaders reflected on the loan that facilitated increased transportation capacity, as well as other benefits from working with Root Capital. However, as Root Capital operates with a client-driven approach, adoption of the Gender Equity Advisory services was limited as these services only became recently available in 2021 and cooperatives opted not to prioritize these until 2023. Therefore, there was limited data to understand how these activities may be influencing cooperative operations, gender dynamics and roles, and perception of women engaged in the coffee value chain at the time of this study. We present several recommendations for areas of future research and considerations for Root Capital to strengthen its approach to gender equity programming.

AGROVOC Keywords

Organizations affiliated to the authors, investors/sponsors, cgiar action areas, collections.