what does justification of a research study mean

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How to Write the Rationale of the Study in Research (Examples)

What is the Rationale of the Study?

The rationale of the study is the justification for taking on a given study. It explains the reason the study was conducted or should be conducted. This means the study rationale should explain to the reader or examiner why the study is/was necessary. It is also sometimes called the “purpose” or “justification” of a study. While this is not difficult to grasp in itself, you might wonder how the rationale of the study is different from your research question or from the statement of the problem of your study, and how it fits into the rest of your thesis or research paper. 

The rationale of the study links the background of the study to your specific research question and justifies the need for the latter on the basis of the former. In brief, you first provide and discuss existing data on the topic, and then you tell the reader, based on the background evidence you just presented, where you identified gaps or issues and why you think it is important to address those. The problem statement, lastly, is the formulation of the specific research question you choose to investigate, following logically from your rationale, and the approach you are planning to use to do that.

Table of Contents:

How to write a rationale for a research paper , how do you justify the need for a research study.

• Study Rationale Example: Where Does It Go In Your Paper?

The basis for writing a research rationale is preliminary data or a clear description of an observation. If you are doing basic/theoretical research, then a literature review will help you identify gaps in current knowledge. In applied/practical research, you base your rationale on an existing issue with a certain process (e.g., vaccine proof registration) or practice (e.g., patient treatment) that is well documented and needs to be addressed. By presenting the reader with earlier evidence or observations, you can (and have to) convince them that you are not just repeating what other people have already done or said and that your ideas are not coming out of thin air. 

Once you have explained where you are coming from, you should justify the need for doing additional research–this is essentially the rationale of your study. Finally, when you have convinced the reader of the purpose of your work, you can end your introduction section with the statement of the problem of your research that contains clear aims and objectives and also briefly describes (and justifies) your methodological approach. 

When is the Rationale for Research Written?

The author can present the study rationale both before and after the research is conducted. 

• Before conducting research : The study rationale is a central component of the research proposal . It represents the plan of your work, constructed before the study is actually executed.
• Once research has been conducted : After the study is completed, the rationale is presented in a research article or  PhD dissertation  to explain why you focused on this specific research question. When writing the study rationale for this purpose, the author should link the rationale of the research to the aims and outcomes of the study.

What to Include in the Study Rationale

Although every study rationale is different and discusses different specific elements of a study’s method or approach, there are some elements that should be included to write a good rationale. Make sure to touch on the following:

• A summary of conclusions from your review of the relevant literature
• What is currently unknown (gaps in knowledge)
• Inconclusive or contested results  from previous studies on the same or similar topic
• The necessity to improve or build on previous research, such as to improve methodology or utilize newer techniques and/or technologies

There are different types of limitations that you can use to justify the need for your study. In applied/practical research, the justification for investigating something is always that an existing process/practice has a problem or is not satisfactory. Let’s say, for example, that people in a certain country/city/community commonly complain about hospital care on weekends (not enough staff, not enough attention, no decisions being made), but you looked into it and realized that nobody ever investigated whether these perceived problems are actually based on objective shortages/non-availabilities of care or whether the lower numbers of patients who are treated during weekends are commensurate with the provided services.

In this case, “lack of data” is your justification for digging deeper into the problem. Or, if it is obvious that there is a shortage of staff and provided services on weekends, you could decide to investigate which of the usual procedures are skipped during weekends as a result and what the negative consequences are. 

In basic/theoretical research, lack of knowledge is of course a common and accepted justification for additional research—but make sure that it is not your only motivation. “Nobody has ever done this” is only a convincing reason for a study if you explain to the reader why you think we should know more about this specific phenomenon. If there is earlier research but you think it has limitations, then those can usually be classified into “methodological”, “contextual”, and “conceptual” limitations. To identify such limitations, you can ask specific questions and let those questions guide you when you explain to the reader why your study was necessary:

Methodological limitations

• Did earlier studies try but failed to measure/identify a specific phenomenon?
• Was earlier research based on incorrect conceptualizations of variables?
• Were earlier studies based on questionable operationalizations of key concepts?
• Did earlier studies use questionable or inappropriate research designs?

Contextual limitations

• Have recent changes in the studied problem made previous studies irrelevant?
• Are you studying a new/particular context that previous findings do not apply to?

Conceptual limitations

• Do previous findings only make sense within a specific framework or ideology?

Study Rationale Examples

Let’s look at an example from one of our earlier articles on the statement of the problem to clarify how your rationale fits into your introduction section. This is a very short introduction for a practical research study on the challenges of online learning. Your introduction might be much longer (especially the context/background section), and this example does not contain any sources (which you will have to provide for all claims you make and all earlier studies you cite)—but please pay attention to how the background presentation , rationale, and problem statement blend into each other in a logical way so that the reader can follow and has no reason to question your motivation or the foundation of your research.

Background presentation

Since the beginning of the Covid pandemic, most educational institutions around the world have transitioned to a fully online study model, at least during peak times of infections and social distancing measures. This transition has not been easy and even two years into the pandemic, problems with online teaching and studying persist (reference needed) . 

While the increasing gap between those with access to technology and equipment and those without access has been determined to be one of the main challenges (reference needed) , others claim that online learning offers more opportunities for many students by breaking down barriers of location and distance (reference needed) .  

Rationale of the study

Since teachers and students cannot wait for circumstances to go back to normal, the measures that schools and universities have implemented during the last two years, their advantages and disadvantages, and the impact of those measures on students’ progress, satisfaction, and well-being need to be understood so that improvements can be made and demographics that have been left behind can receive the support they need as soon as possible.

Statement of the problem

To identify what changes in the learning environment were considered the most challenging and how those changes relate to a variety of student outcome measures, we conducted surveys and interviews among teachers and students at ten institutions of higher education in four different major cities, two in the US (New York and Chicago), one in South Korea (Seoul), and one in the UK (London). Responses were analyzed with a focus on different student demographics and how they might have been affected differently by the current situation.

How long is a study rationale?

In a research article bound for journal publication, your rationale should not be longer than a few sentences (no longer than one brief paragraph). A  dissertation or thesis  usually allows for a longer description; depending on the length and nature of your document, this could be up to a couple of paragraphs in length. A completely novel or unconventional approach might warrant a longer and more detailed justification than an approach that slightly deviates from well-established methods and approaches.

Consider Using Professional Academic Editing Services

Now that you know how to write the rationale of the study for a research proposal or paper, you should make use of Wordvice AI’s free AI Grammar Checker , or receive professional academic proofreading services from Wordvice, including research paper editing services and manuscript editing services to polish your submitted research documents.

You can also find many more articles, for example on writing the other parts of your research paper , on choosing a title , or on making sure you understand and adhere to the author instructions before you submit to a journal, on the Wordvice academic resources pages.

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• Writing Tips

How to Justify Your Methods in a Thesis or Dissertation

4-minute read

• 1st May 2023

Writing a thesis or dissertation is hard work. You’ve devoted countless hours to your research, and you want your results to be taken seriously. But how does your professor or evaluating committee know that they can trust your results? You convince them by justifying your research methods.

What Does Justifying Your Methods Mean?

In simple terms, your methods are the tools you use to obtain your data, and the justification (which is also called the methodology ) is the analysis of those tools. In your justification, your goal is to demonstrate that your research is both rigorously conducted and replicable so your audience recognizes that your results are legitimate.

The formatting and structure of your justification will depend on your field of study and your institution’s requirements, but below, we’ve provided questions to ask yourself as you outline your justification.

Why Did You Choose Your Method of Gathering Data?

Does your study rely on quantitative data, qualitative data, or both? Certain types of data work better for certain studies. How did you choose to gather that data? Evaluate your approach to collecting data in light of your research question. Did you consider any alternative approaches? If so, why did you decide not to use them? Highlight the pros and cons of various possible methods if necessary. Research results aren’t valid unless the data are valid, so you have to convince your reader that they are.

How Did You Evaluate Your Data?

Collecting your data was only the first part of your study. Once you had them, how did you use them? Do your results involve cross-referencing? If so, how was this accomplished? Which statistical analyses did you run, and why did you choose them? Are they common in your field? How did you make sure your data were statistically significant ? Is your effect size small, medium, or large? Numbers don’t always lend themselves to an obvious outcome. Here, you want to provide a clear link between the Methods and Results sections of your paper.

Did You Use Any Unconventional Approaches in Your Study?

Most fields have standard approaches to the research they use, but these approaches don’t work for every project. Did you use methods that other fields normally use, or did you need to come up with a different way of obtaining your data? Your reader will look at unconventional approaches with a more critical eye. Acknowledge the limitations of your method, but explain why the strengths of the method outweigh those limitations.

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What Relevant Sources Can You Cite?

You can strengthen your justification by referencing existing research in your field. Citing these references can demonstrate that you’ve followed established practices for your type of research. Or you can discuss how you decided on your approach by evaluating other studies. Highlight the use of established techniques, tools, and measurements in your study. If you used an unconventional approach, justify it by providing evidence of a gap in the existing literature.

Two Final Tips:

●  When you’re writing your justification, write for your audience. Your purpose here is to provide more than a technical list of details and procedures. This section should focus more on the why and less on the how .

●  Consider your methodology as you’re conducting your research. Take thorough notes as you work to make sure you capture all the necessary details correctly. Eliminating any possible confusion or ambiguity will go a long way toward helping your justification.

In Conclusion:

Your goal in writing your justification is to explain not only the decisions you made but also the reasoning behind those decisions. It should be overwhelmingly clear to your audience that your study used the best possible methods to answer your research question. Properly justifying your methods will let your audience know that your research was effective and its results are valid.

Want more writing tips? Check out Proofed’s Writing Tips and Academic Writing Tips blogs. And once you’ve written your thesis or dissertation, consider sending it to us. Our editors will be happy to check your grammar, spelling, and punctuation to make sure your document is the best it can be. Check out our services for free .

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How to Write the Rationale for a Research Paper

• Research Process
• Peer Review

A research rationale answers the big SO WHAT? that every adviser, peer reviewer, and editor has in mind when they critique your work. A compelling research rationale increases the chances of your paper being published or your grant proposal being funded. In this article, we look at the purpose of a research rationale, its components and key characteristics, and how to create an effective research rationale.

Updated on September 19, 2022

The rationale for your research is the reason why you decided to conduct the study in the first place. The motivation for asking the question. The knowledge gap. This is often the most significant part of your publication. It justifies the study's purpose, novelty, and significance for science or society. It's a critical part of standard research articles as well as funding proposals.

Essentially, the research rationale answers the big SO WHAT? that every (good) adviser, peer reviewer, and editor has in mind when they critique your work.

A compelling research rationale increases the chances of your paper being published or your grant proposal being funded. In this article, we look at:

• the purpose of a research rationale
• its components and key characteristics
• how to create an effective research rationale

What is a research rationale?

Think of a research rationale as a set of reasons that explain why a study is necessary and important based on its background. It's also known as the justification of the study, rationale, or thesis statement.

Essentially, you want to convince your reader that you're not reciting what other people have already said and that your opinion hasn't appeared out of thin air. You've done the background reading and identified a knowledge gap that this rationale now explains.

A research rationale is usually written toward the end of the introduction. You'll see this section clearly in high-impact-factor international journals like Nature and Science. At the end of the introduction there's always a phrase that begins with something like, "here we show..." or "in this paper we show..." This text is part of a logical sequence of information, typically (but not necessarily) provided in this order:

Here's an example from a study by Cataldo et al. (2021) on the impact of social media on teenagers' lives.

Note how the research background, gap, rationale, and objectives logically blend into each other.

The authors chose to put the research aims before the rationale. This is not a problem though. They still achieve a logical sequence. This helps the reader follow their thinking and convinces them about their research's foundation.

Elements of a research rationale

We saw that the research rationale follows logically from the research background and literature review/observation and leads into your study's aims and objectives.

This might sound somewhat abstract. A helpful way to formulate a research rationale is to answer the question, “Why is this study necessary and important?”

Generally, that something has never been done before should not be your only motivation. Use it only If you can give the reader valid evidence why we should learn more about this specific phenomenon.

A well-written introduction covers three key elements:

• What's the background to the research?
• What has been done before (information relevant to this particular study, but NOT a literature review)?
• Research rationale

Now, let's see how you might answer the question.

1. This study complements scientific knowledge and understanding

Discuss the shortcomings of previous studies and explain how'll correct them. Your short review can identify:

• Methodological limitations . The methodology (research design, research approach or sampling) employed in previous works is somewhat flawed.

Example : Here , the authors claim that previous studies have failed to explore the role of apathy “as a predictor of functional decline in healthy older adults” (Burhan et al., 2021). At the same time, we know a lot about other age-related neuropsychiatric disorders, like depression.

Their study is necessary, then, “to increase our understanding of the cognitive, clinical, and neural correlates of apathy and deconstruct its underlying mechanisms.” (Burhan et al., 2021).

• Contextual limitations . External factors have changed and this has minimized or removed the relevance of previous research.

Example : You want to do an empirical study to evaluate the effects of the COVID-19 pandemic on the number of tourists visiting Sicily. Previous studies might have measured tourism determinants in Sicily, but they preceded COVID-19.

• Conceptual limitations . Previous studies are too bound to a specific ideology or a theoretical framework.

Example : The work of English novelist E. M. Forster has been extensively researched for its social, political, and aesthetic dimensions. After the 1990s, younger scholars wanted to read his novels as an example of gay fiction. They justified the need to do so based on previous studies' reliance on homophobic ideology.

This kind of rationale is most common in basic/theoretical research.

2. This study can help solve a specific problem

Here, you base your rationale on a process that has a problem or is not satisfactory.

For example, patients complain about low-quality hospital care on weekends (staff shortages, inadequate attention, etc.). No one has looked into this (there is a lack of data). So, you explore if the reported problems are true and what can be done to address them. This is a knowledge gap.

Or you set out to explore a specific practice. You might want to study the pros and cons of several entry strategies into the Japanese food market.

It's vital to explain the problem in detail and stress the practical benefits of its solution. In the first example, the practical implications are recommendations to improve healthcare provision.

In the second example, the impact of your research is to inform the decision-making of businesses wanting to enter the Japanese food market.

This kind of rationale is more common in applied/practical research.

3. You're the best person to conduct this study

It's a bonus if you can show that you're uniquely positioned to deliver this study, especially if you're writing a funding proposal .

For an anthropologist wanting to explore gender norms in Ethiopia, this could be that they speak Amharic (Ethiopia's official language) and have already lived in the country for a few years (ethnographic experience).

Or if you want to conduct an interdisciplinary research project, consider partnering up with collaborators whose expertise complements your own. Scientists from different fields might bring different skills and a fresh perspective or have access to the latest tech and equipment. Teaming up with reputable collaborators justifies the need for a study by increasing its credibility and likely impact.

When is the research rationale written?

You can write your research rationale before, or after, conducting the study.

In the first case, when you might have a new research idea, and you're applying for funding to implement it.

Or you're preparing a call for papers for a journal special issue or a conference. Here , for instance, the authors seek to collect studies on the impact of apathy on age-related neuropsychiatric disorders.

In the second case, you have completed the study and are writing a research paper for publication. Looking back, you explain why you did the study in question and how it worked out.

Although the research rationale is part of the introduction, it's best to write it at the end. Stand back from your study and look at it in the big picture. At this point, it's easier to convince your reader why your study was both necessary and important.

How long should a research rationale be?

The length of the research rationale is not fixed. Ideally, this will be determined by the guidelines (of your journal, sponsor etc.).

The prestigious journal Nature , for instance, calls for articles to be no more than 6 or 8 pages, depending on the content. The introduction should be around 200 words, and, as mentioned, two to three sentences serve as a brief account of the background and rationale of the study, and come at the end of the introduction.

If you're not provided guidelines, consider these factors:

• Research document : In a thesis or book-length study, the research rationale will be longer than in a journal article. For example, the background and rationale of this book exploring the collective memory of World War I cover more than ten pages.
• Research question : Research into a new sub-field may call for a longer or more detailed justification than a study that plugs a gap in literature.

Which verb tenses to use in the research rationale?

It's best to use the present tense. Though in a research proposal, the research rationale is likely written in the future tense, as you're describing the intended or expected outcomes of the research project (the gaps it will fill, the problems it will solve).

Example of a research rationale

Research question : What are the teachers' perceptions of how a sense of European identity is developed and what underlies such perceptions?

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology , 3(2), 77-101.

Burhan, A.M., Yang, J., & Inagawa, T. (2021). Impact of apathy on aging and age-related neuropsychiatric disorders. Research Topic. Frontiers in Psychiatry

Cataldo, I., Lepri, B., Neoh, M. J. Y., & Esposito, G. (2021). Social media usage and development of psychiatric disorders in childhood and adolescence: A review. Frontiers in Psychiatry , 11.

CiCe Jean Monnet Network (2017). Guidelines for citizenship education in school: Identities and European citizenship children's identity and citizenship in Europe.

Cohen, l, Manion, L., & Morrison, K. (2018). Research methods in education . Eighth edition. London: Routledge.

de Prat, R. C. (2013). Euroscepticism, Europhobia and Eurocriticism: The radical parties of the right and left “vis-à-vis” the European Union P.I.E-Peter Lang S.A., Éditions Scientifiques Internationales.

European Commission. (2017). Eurydice Brief: Citizenship education at school in Europe.

Polyakova, A., & Fligstein, N. (2016). Is European integration causing Europe to become more nationalist? Evidence from the 2007–9 financial crisis. Journal of European Public Policy , 23(1), 60-83.

Winter, J. (2014). Sites of Memory, Sites of Mourning: The Great War in European Cultural History . Cambridge: Cambridge University Press.

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How to write the Rationale for your research

By charlesworth author services.

• Charlesworth Author Services
• 19 November, 2021

The rationale for one’s research is the justification for undertaking a given study. It states the reason(s) why a researcher chooses to focus on the topic in question, including what the significance is and what gaps the research intends to fill. In short, it is an explanation that rationalises the need for the study. The rationale is typically followed by a hypothesis/ research question (s) and the study objectives.

When is the rationale for research written?

The rationale of a study can be presented both before and after the research is conducted. 

• Before : The rationale is a crucial part of your research proposal , representing the plan of your work as formulated before you execute your study.
• After : Once the study is completed, the rationale is presented in a research paper or dissertation to explain why you focused on the particular question. In this instance, you would link the rationale of your research project to the study aims and outcomes.

Basis for writing the research rationale

The study rationale is predominantly based on preliminary data . A literature review will help you identify gaps in the current knowledge base and also ensure that you avoid duplicating what has already been done. You can then formulate the justification for your study from the existing literature on the subject and the perceived outcomes of the proposed study.

Length of the research rationale

In a research proposal or research article, the rationale would not take up more than a few sentences . A thesis or dissertation would allow for a longer description, which could even run into a couple of paragraphs . The length might even depend on the field of study or nature of the experiment. For instance, a completely novel or unconventional approach might warrant a longer and more detailed justification.

Basic elements of the research rationale

Every research rationale should include some mention or discussion of the following: 

• An overview of your conclusions from your literature review
• Gaps in current knowledge
• Inconclusive or controversial findings from previous studies
• The need to build on previous research (e.g. unanswered questions, the need to update concepts in light of new findings and/or new technical advancements). 

Example of a research rationale

Note: This uses a fictional study.

Abc xyz is a newly identified microalgal species isolated from fish tanks. While Abc xyz algal blooms have been seen as a threat to pisciculture, some studies have hinted at their unusually high carotenoid content and unique carotenoid profile. Carotenoid profiling has been carried out only in a handful of microalgal species from this genus, and the search for microalgae rich in bioactive carotenoids has not yielded promising candidates so far. This in-depth examination of the carotenoid profile of Abc xyz will help identify and quantify novel and potentially useful carotenoids from an untapped aquaculture resource .

In conclusion

It is important to describe the rationale of your research in order to put the significance and novelty of your specific research project into perspective. Once you have successfully articulated the reason(s) for your research, you will have convinced readers of the importance of your work!

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What is the Significance of the Study?

• By DiscoverPhDs
• August 25, 2020

• what the significance of the study means,
• why it’s important to include in your research work,
• where you would include it in your paper, thesis or dissertation,
• how you write one
• and finally an example of a well written section about the significance of the study.

What does Significance of the Study mean?

The significance of the study is a written statement that explains why your research was needed. It’s a justification of the importance of your work and impact it has on your research field, it’s contribution to new knowledge and how others will benefit from it.

Why is the Significance of the Study important?

The significance of the study, also known as the rationale of the study, is important to convey to the reader why the research work was important. This may be an academic reviewer assessing your manuscript under peer-review, an examiner reading your PhD thesis, a funder reading your grant application or another research group reading your published journal paper. Your academic writing should make clear to the reader what the significance of the research that you performed was, the contribution you made and the benefits of it.

How do you write the Significance of the Study?

When writing this section, first think about where the gaps in knowledge are in your research field. What are the areas that are poorly understood with little or no previously published literature? Or what topics have others previously published on that still require further work. This is often referred to as the problem statement.

The introduction section within the significance of the study should include you writing the problem statement and explaining to the reader where the gap in literature is.

Then think about the significance of your research and thesis study from two perspectives: (1) what is the general contribution of your research on your field and (2) what specific contribution have you made to the knowledge and who does this benefit the most.

For example, the gap in knowledge may be that the benefits of dumbbell exercises for patients recovering from a broken arm are not fully understood. You may have performed a study investigating the impact of dumbbell training in patients with fractures versus those that did not perform dumbbell exercises and shown there to be a benefit in their use. The broad significance of the study would be the improvement in the understanding of effective physiotherapy methods. Your specific contribution has been to show a significant improvement in the rate of recovery in patients with broken arms when performing certain dumbbell exercise routines.

This statement should be no more than 500 words in length when written for a thesis. Within a research paper, the statement should be shorter and around 200 words at most.

Significance of the Study: An example

Building on the above hypothetical academic study, the following is an example of a full statement of the significance of the study for you to consider when writing your own. Keep in mind though that there’s no single way of writing the perfect significance statement and it may well depend on the subject area and the study content.

Here’s another example to help demonstrate how a significance of the study can also be applied to non-technical fields:

The significance of this research lies in its potential to inform clinical practices and patient counseling. By understanding the psychological outcomes associated with non-surgical facial aesthetics, practitioners can better guide their patients in making informed decisions about their treatment plans. Additionally, this study contributes to the body of academic knowledge by providing empirical evidence on the effects of these cosmetic procedures, which have been largely anecdotal up to this point.

The statement of the significance of the study is used by students and researchers in academic writing to convey the importance of the research performed; this section is written at the end of the introduction and should describe the specific contribution made and who it benefits.

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A Review of the Quality Indicators of Rigor in Qualitative Research

Jessica l. johnson.

a William Carey University School of Pharmacy, Biloxi, Mississippi

Donna Adkins

Sheila chauvin.

b Louisiana State University, School of Medicine, New Orleans, Louisiana

Attributes of rigor and quality and suggested best practices for qualitative research design as they relate to the steps of designing, conducting, and reporting qualitative research in health professions educational scholarship are presented. A research question must be clear and focused and supported by a strong conceptual framework, both of which contribute to the selection of appropriate research methods that enhance trustworthiness and minimize researcher bias inherent in qualitative methodologies. Qualitative data collection and analyses are often modified through an iterative approach to answering the research question. Researcher reflexivity, essentially a researcher’s insight into their own biases and rationale for decision-making as the study progresses, is critical to rigor. This article reviews common standards of rigor, quality scholarship criteria, and best practices for qualitative research from design through dissemination.

INTRODUCTION

Within the past 20 years, qualitative research in health professions education has increased significantly, both in practice and publication. Today, one can pick up most any issue of a wide variety of health professions education journals and find at least one article that includes some type of qualitative research, whether a full study or the inclusion of a qualitative component within a quantitative or mixed methods study. Simultaneously, there have been recurrent calls for enhancing rigor and quality in qualitative research.

As members of the academic community, we share responsibility for ensuring rigor in qualitative research, whether as researchers who design and implement, manuscript reviewers who critique, colleagues who discuss and learn from each other, or scholarly teachers who draw upon results to enhance and innovate education. Therefore, the purpose of this article is to summarize standards of rigor and suggested best practices for designing, conducting, and reporting high-quality qualitative research. To begin, Denzin and Lincoln’s definition of qualitative research, a long-standing cornerstone in the field, provides a useful foundation for summarizing quality standards and best practices:

Qualitative research involves the studied use and collection of a variety of empirical materials – case study; personal experience; introspection; life story; interview; artifacts; cultural texts and productions; observational, historical, interactional, and visual texts – that describe the routine and problematic moments and meanings in individual lives. Accordingly, qualitative researchers deploy a wide range of interconnected interpretative practices, hoping always to get a better understanding of the subject matter at hand. It is understood, however, that each practice makes the world visible in a different way. Hence there is frequently a commitment to using more than one interpretative practice in any study. 1

In recent years, multiple publications have synthesized quality criteria and recommendations for use by researchers and peer reviewers alike, often in the form of checklists. 2-6 Some authors have raised concerns about the use of such checklists and adherence to strict, universal criteria because they do not afford sufficient flexibility to accommodate the diverse approaches and multiple interpretive practices often represented in qualitative studies. 7-11 They argue that a strict focus on using checklists of specific technical criteria may stifle the diversity and multiplicity of practices that are so much a part of achieving quality and rigor within the qualitative paradigm. As an alternative, some of these authors have published best practice guidelines for use by researchers and peer reviewers to achieve and assess methodological rigor and research quality. 12,13

Some journals within the field of health professions education have also established best practice guidance, as opposed to strict criteria or a checklist, for qualitative research. These have been disseminated as guiding questions or evaluation categories. In 2015, Academic Medicine produced an expanded second edition of a researcher/author manual that includes specific criteria with extensive explanations and examples. 14 Still others have disseminated best practice guidelines through a series of methodological articles within journal publications. 2

In this article, attributes of rigor and quality and suggested best practices are presented as they relate to the steps of designing, conducting, and reporting qualitative research in a step-wise approach.

BEST PRACTICES: STEP-WISE APPROACH

Step 1: identifying a research topic.

Identifying and developing a research topic is comprised of two major tasks: formulating a research question, and developing a conceptual framework to support the study. Formulating a research question is often stimulated by real-life observations, experiences, or events in the researcher’s local setting that reflect a perplexing problem begging for systematic inquiry. The research question begins as a problem statement or set of propositions that describe the relationship among certain concepts, behaviors, or experiences. Agee 15 and others 16,17 note that initial questions are usually too broad in focus and too vague regarding the specific context of the study to be answerable and researchable. Creswell reminds us that initial qualitative research questions guide inquiry, but they often change as the author’s understanding of the issue develops throughout the study. 16 Developing and refining a primary research question focused on both the phenomena of interest and the context in which it is situated is essential to research rigor and quality.

Glassick, Huber, and Maeroff identified six criteria applicable to assessing the quality of scholarship. 18,19 Now commonly referred to as the Glassick Criteria ( Table 1 ), these critical attributes outline the essential elements of any scholarly approach and serve as a general research framework for developing research questions and designing studies. The first two criteria, clear purpose and adequate preparation, are directly related to formulating effective research questions and a strong conceptual framework.

Glassick’s Criteria for Assessing the Quality of Scholarship of a Research Study 18

Generating and refining a qualitative research question requires thorough, systematic, and iterative review of the literature, and the use of those results to establish a clear context and foundation for the question and study design. Using an iterative approach, relevant concepts, principles, theories or models, and prior evidence are identified to establish what is known, and more importantly, what is not known. The iterative process contributes to forming a better research question, the criteria for which can be abbreviated by the acronym FINER, ie, f easible, i nteresting, n ovel, e thical, and r elevant, that is answerable and researchable, in terms of research focus, context specificity, and the availability of time, logistics, and resources to carry out the study. Developing a FINER research question is critical to study rigor and quality and should not be rushed, as all other aspects of research design depend on the focus and clarity of the research question(s) guiding the study. 15 Agee provides clear and worthwhile additional guidance for developing qualitative research questions. 15

Reflexivity, the idea that a researcher’s preconceptions and biases can influence decisions and actions throughout qualitative research activities, is a critical aspect of rigor even at the earliest stages of the study. A researcher’s background, beliefs, and experiences may affect any aspect of the research from choosing which specific question to investigate through determining how to present the results. Therefore, even at this early stage, the potential effect of researcher bias and any ethical considerations should be acknowledged and addressed. That is, how will the question’s influence on study design affect participants’ lives, position the researcher in relationship with others, or require specific methods for addressing potential areas of research bias and ethical considerations?

A conceptual framework is then actively constructed to provide a logical and convincing argument for the research. The framework defines and justifies the research question, the methodology selected to answer that question, and the perspectives from which interpretation of results and conclusions will be made. 5,6,20 Developing a well-integrated conceptual framework is essential to establishing a research topic based upon a thorough and integrated review of relevant literature (addressing Glassick criteria #1 and #2: clear purpose and adequate preparation). Key concepts, principles, assumptions, best practices, and theories are identified, defined, and integrated in ways that clearly demonstrate the problem statement and corresponding research question are answerable, researchable, and important to advancing thinking and practice.

Ringsted, Hodges, and Sherpbier describe three essential parts to an effective conceptual framework: theories and/or concepts and principles relevant to the phenomenon of interest; what is known and unknown from prior work, observations, and examples; and the researcher’s observations, ideas, and suppositions regarding the research problem statement and question. 21 Lingard describes four types of unknowns to pursue during literature review: what no one knows; what is not yet well understood; what controversy or conflicting results, understandings, or perspectives exist; and what are unproven assumptions. 22 In qualitative research, these unknowns are critical to achieving a well-developed conceptual framework and a corresponding rigorous study design.

Recent contributions from Ravitch and colleagues present best practices in developing frameworks for conceptual and methodological coherence within a study design, regardless of the research approach. 23,24 Their recommendations and arguments are highly relevant to qualitative research. Figure 1 reflects the primary components of a conceptual framework adapted from Ravitch and Carl 23 and how all components contribute to decisions regarding research design, implementation, and applications of results to future thinking, study, and practice. Notice that each element of the framework interacts with and influences other elements in a dynamic and interactive process from the beginning to the end of a research project. The intersecting bidirectional arrows represent direct relationships between elements as they relate to specific aspects of a qualitative research study.

Adaptation of Ravitch and Carl’s Components of a Conceptual Framework 23

Maxwell also provides useful guidance for developing an effective conceptual framework specific to the qualitative research paradigm. 17 The 2015 second edition of the Review Criteria for Research Manuscripts 14 and work by Ravitch and colleagues 23,24 provide specific guidance for applying the conceptual framework to each stage of the research process to enhance rigor and quality. Quality criteria for assessing a study’s problem statement, conceptual framework, and research question include the following: introduction builds a logical case and provides context for the problem statement; problem statement is clear and well-articulated; conceptual framework is explicit and justified; research purpose and/or question is clearly stated; and constructs being investigated are clearly identified and presented. 14,24,25 As best practice guidelines, these criteria facilitate quality and rigor while providing sufficient flexibility in how each is achieved and demonstrated.

While a conceptual framework is important to rigor in qualitative research, Huberman and Miles caution qualitative researchers about developing and using a framework to the extent that it influences qualitative design deductively because this would violate the very principles of induction that define the qualitative research paradigm. 25 Our profession’s recent emphasis on a holistic admissions process for pharmacy students provides a reasonable example of inductive and deductive reasoning and their respective applications in qualitative and quantitative research studies. Principles of inductive reasoning are applied when a qualitative research study examines a representative group of competent pharmacy professionals to generate a theory about essential cognitive and affective skills for patient-centered care. Deductive reasoning could then be applied to design a hypothesis-driven prospective study that compares the outcomes of two cohorts of students, one group admitted using traditional criteria and one admitted based on a holistic admissions process revised to value the affective skills of applicants. Essentially, the qualitative researcher must carefully generate a conceptual framework that guides the research question and study design without allowing the conceptual framework to become so rigid as to dictate a testable hypothesis, which is the founding principle of deductive reasoning. 26

Step 2: Qualitative Study Design

The development of a strong conceptual framework facilitates selection of appropriate study methods to minimize the bias inherent in qualitative studies and help readers to trust the research and the researcher (see Glassick criteria #3 in Table 1 ). Although researchers can employ great flexibility in the selection of study methods, inclusion of best practice methods for assuring the rigor and trustworthiness of results is critical to study design. Lincoln and Guba outline four criteria for establishing the overall trustworthiness of qualitative research results: credibility, the researcher ensures and imparts to the reader supporting evidence that the results accurately represent what was studied; transferability, the researcher provides detailed contextual information such that readers can determine whether the results are applicable to their or other situations; dependability, the researcher describes the study process in sufficient detail that the work could be repeated; confirmability, the researcher ensures and communicates to the reader that the results are based on and reflective of the information gathered from the participants and not the interpretations or bias of the researcher. 27

Specific best practice methods used in the sampling and data collection processes to increase the rigor and trustworthiness of qualitative research include: clear rationale for sampling design decisions, determination of data saturation, ethics in research design, member checking, prolonged engagement with and persistent observation of study participants, and triangulation of data sources. 28

Qualitative research is focused on making sense of lived, observed phenomenon in a specific context with specifically selected individuals, rather than attempting to generalize from sample to population. Therefore, sampling design in qualitative research is not random but defined purposively to include the most appropriate participants in the most appropriate context for answering the research question. Qualitative researchers recognize that certain participants are more likely to be “rich” with data or insight than others, and therefore, more relevant and useful in achieving the research purpose and answering the question at hand. The conceptual framework contributes directly to determining sample definitions, size, and recruitment of participants. A typical best practice is purposive sampling methods, and when appropriate, convenience sampling may be justified. 29

Purposive sampling reflects intentional selection of research participants to optimize data sources for answering the research question. For example, the research question may be best answered by persons who have particular experience (critical case sampling) or certain expertise (key informant sampling). Similarly, additional participants may be referred for participation by active participants (snowball sampling) or may be selected to represent either similar or opposing viewpoints (confirming or disconfirming samples). Again, the process of developing and using a strong conceptual framework to guide and justify methodological decisions, in this case defining and establishing the study sample, is critical to rigor and quality. 30 Convenience sampling, using the most accessible research participants, is the least rigorous approach to defining a study sample and may result in low accuracy, poor representativeness, low credibility, and lack of transferability of study results.

Qualitative studies typically reflect designs in which data collection and analysis are done concurrently, with results of ongoing analysis informing continuing data collection. Determination of a final sample size is largely based on having sufficient opportunity to collect relevant data until new information is no longer emerging from data collection, new coding is not feasible, and/or no new themes are emerging; that is, reaching data saturation , a common standard of rigor for data collection in qualitative studies . Thus, accurately predicting a sample size during the planning phases of qualitative research can be challenging. 30 Care should be taken that sufficient quantity (think thick description) and quality (think rich description) of data have been collected prior to concluding that data saturation has been achieved. A poor decision regarding sample size is a direct consequence of sampling strategy and quality of data generated, which leaves the researcher unable to fully answer the research question in sufficient depth. 30

Though data saturation is probably the most common terminology used to describe the achievement of sufficient sample size, it does not apply to all study designs. For example, one could argue that in some approaches to qualitative research, data collection could continue infinitely if the event continues infinitely. In education, we often anecdotally observe variations in the personality and structure of a class of students, and as generations of students continue to evolve with time, so too would the data generated from observing each successive class. In such situations, data saturation might never be achieved. Conversely, the number of participants available for inclusion in a sample may be small and some risk of not reaching data saturation may be unavoidable. Thus, the idea of fully achieving data saturation may be unrealistic when applied to some populations or research questions. In other instances, attrition and factors related to time and resources may contribute to not reaching data saturation within the limits of the study. By being transparent in the process and reporting of results when saturation may not have been possible, the resulting data may still contribute to the field and to further inquiry. Replication of the study using other samples and conducting additional types of follow-up studies are other options for better understanding the research phenomenon at hand. 31

In addition to defining the sample and selecting participants, other considerations related to sampling bias may impact the quantity and quality of data generated and therefore the quality of the study result. These include: methods of recruiting, procedures for informed consent, timing of the interviews in relation to experience or emotion, procedures for ensuring participant anonymity/confidentiality, interview setting, and methods of recording/transcribing the data. Any of these factors could potentially change the nature of the relationship between the researcher and the study participants and influence the trustworthiness of data collected or the study result. Thus, ongoing application of previously mentioned researcher reflexivity is critical to the rigor of the study and quality of sampling. 29,30

Common qualitative data collection methods used in health professions education include interview, direct observation methods, and textual/document analysis. Given the unique and often highly sensitive nature of data being collected by the researcher, trustworthiness is an essential component of the researcher-participant relationship. Ethical conduct refers to how moral principles and values are part of the research process. Participants’ perceptions of ethical conduct are fundamental to a relationship likely to generate high quality data. During each step of the research process, care must be taken to protect the confidentiality of participants and shield them from harm relating to issues of respect and dignity. Researchers must be respectful of the participants’ contributions and quotes, and results must be reported truthfully and honestly. 8

Interview methods range from highly structured to increase dependability or completely open-ended to allow for interviewers to clarify a participant’s response for increased credibility and confirmability. Regardless, interview protocols and structure are often modified or refined, based on concurrent data collection and analysis processes to support or refute preliminary interpretations and refine focus and continuing inquiry. Researcher reflexivity, or acknowledgement of researcher bias, is absolutely critical to the credibility and trustworthiness of data collection and analysis in such study designs. 32

Interviews should be recorded and transcribed verbatim prior to coding and analysis. 28 Member checking, a common standard of rigor, is a practice to increase study credibility and confirmability that involves asking a research subject to verify the transcription of an interview. 1,16,28 The research subject is asked to verify the completeness and accuracy of an interview transcript to ensure the transcript truthfully reflects the meaning and intent of the subject’s contribution.

Prolonged engagement involves the researcher gaining familiarity and understanding of the culture and context surrounding the persons or situations being studied. This strategy supports reflexivity, allowing the researcher to determine how they themselves may be a source of bias during the data collection process by altering the nature of how individuals behave or interact with others in the presence of the researcher. Facial expressions, spoken language, body language, style of dress, age, race, gender, social status, culture, and the researcher’s relationship with the participants may potentially influence either participants’ responses or how the researcher interprets those responses. 33 “Fitting in” by demonstrating an appreciation and understanding of the cultural norms of the population being studied potentially allows the researcher to obtain more open and honest responses from participants. However, if the research participants or topic are too familiar or personal, this may also influence data collection or analysis and interpretation of the results. 33 The possible applications of this section to faculty research with student participants in the context of pharmacy education are obvious, and researcher reflexivity is critical to rigor.

Some researchers using observational methods adopt a strategy of direct field observation, while others play partial or full participant roles in the activity being observed. In both observation scenarios, it is impossible to separate the researcher from the environment, and researcher reflexivity is essential. The pros and cons of observation approach, relative to the research question and study purpose, should be evaluated by the researcher, and the justification for the observational strategy selected should be made clear. 34 Regardless of the researcher’s degree of visibility to the study participants, persistent observation of the targeted sample is critical to the confirmability standard and to achieving data saturation. That is, study conclusions must be clearly grounded in persistent phenomena witnessed during the study, rather than on a fluke event. 28

Researchers acknowledge that observational methodologies are limited by the reality that the researcher carries a bias in determining what is observed, what is recorded, how it is recorded, and how it is transcribed for analysis. A study’s conceptual framework is critical to achieving rigor and quality and provides guidance in developing predetermined notions or plans for what to observe, how to record, and how to minimize the influence of potential bias. 34 Researcher notes should be recorded as soon as possible after the observation event to optimize accuracy. The more detailed and complete the notes, the more accurate and useful they can be in data analysis or in auditing processes for enhancing rigor in the interpretation phase of the study. 34

Triangulation is among the common standards of rigor applied within the qualitative research paradigm. Data triangulation is used to identify convergence of data obtained through multiple data sources and methods (eg, observation field notes and interview transcripts) to avoid or minimize error or bias and optimize accuracy in data collection and analysis processes. 33,35,36

Again, researcher practice in reflexivity throughout research processes is integral to rigor in study design and implementation. Researchers must demonstrate attention to appropriate methods and reflective critique, which are represented in both core elements of the conceptual framework ( Figure 1 ) and Glassick criteria ( Table 1 ). In so doing, the researcher will be well-prepared to justify sampling design and data collection decisions to manuscript reviewers and, ultimately, readers.

Step 3: Data Analysis

In many qualitative studies, data collection runs concurrently with data analysis. Specific standards of rigor are commonly used to ensure trustworthiness and integrity within the data analysis process, including use of computer software, peer review, audit trail, triangulation, and negative case analysis.

Management and analyses of qualitative data from written text, observational field notes, and interview transcriptions may be accomplished using manual methods or the assistance of computer software applications for coding and analysis. When managing very large data sets or complex study designs, computer software can be very helpful to assist researchers in coding, sorting, organizing, and weighting data elements. Software applications can facilitate ease in calculating semi-quantitative descriptive statistics, such as counts of specific events, that can be used as evidence that the researcher’s analysis is based on a representative majority of data collected ( inclusivism ) rather than focusing on selected rarities ( anecdotalism ). Using software to code data can also make it easier to identify deviant cases, detect coding errors, and estimate interrater reliability among multiple coders. 37 While such software helps to manage data, the actual analyses and interpretation still reside with the researcher.

Peer review, another common standard of rigor, is a process by which researchers invite an independent third-party researcher to analyze a detailed audit trail maintained by the study author. The audit trail methodically describes the step-by-step processes and decision-making throughout the study. Review of this audit trail occurs prior to manuscript development and enhances study confirmability. 1,16 The peer reviewer offers a critique of the study methods and validation of the conclusions drawn by the author as a thorough check on researcher bias.

Triangulation also plays a role in data analysis, as the term can also be used to describe how multiple sources of data can be used to confirm or refute interpretation, assertions, themes, and study conclusions. If a theme or theory can be arrived at and validated using multiple sources of data, the result of the study has greater credibility and confirmability. 16,33,36 Should any competing or controversial theories emerge during data collection or analysis, it is vital to the credibility and trustworthiness of the study that the author disclose and explore those negative cases. Negative case analysis refers to actively seeking out and scrutinizing data that do not fit or support the researcher’s interpretation of the data. 16

The use of best practices applying to data collection and data analysis facilitates the full examination of data relative to the study purpose and research question and helps to prevent premature closure of the study. Rather than stopping at the initial identification of literal, first-level assertion statements and themes, authors must progress to interpreting how results relate to, revise, or expand the conceptual framework, or offer an improved theory or model for explaining the study phenomenon of interest. Closing the loop on data collection is critical and is achieved when thorough and valid analysis can be linked back to the conceptual framework, as addressed in the next section.

Step 4: Drawing Valid Conclusions

Lingard and Kennedy 38 succinctly state that the purpose of qualitative research is to deepen one’s understanding of specific perspectives, observations, experiences, or events evidenced through the behaviors or products of individuals and groups as they are situated in specific contexts or circumstances. Conclusions generated from study results should enhance the conceptual framework, or contribute to a new theory or model development, and are most often situated within the discussion and conclusion sections of a manuscript.

The discussion section should include interpretation of the results and recommendations for practice. Interpretations should go beyond first-level results or literal description of observed behaviors, patterns, and themes from analysis. The author’s challenge is to provide a complete and thorough examination and explanation of how specific results relate to each other, contribute to answering the research question, and achieve the primary purpose of the research endeavor. The discussion should “close the loop” by integrating study results and analysis with the original conceptual framework. The discussion section should also provide a parsimonious narrative or graphical explanation and interpretation of study results that enhances understanding of the targeted phenomena.

The conclusion section should provide an overall picture or synopsis of the study, including its important and unique contributions to the field from the perspective of both conceptual and practical significance. The conclusion should also include personal and theoretical perspectives and future directions for research. Together, the discussion and conclusion should include responses to the larger questions of the study’s contributions, such as: So what? Why do these results matter? What next?

The strength of conclusions is dependent upon the extent to which standards of rigor and best practices were demonstrated in design, data collection, data analysis, and interpretation, as described in previous sections of this article. 4,12,17,23,24 Quality and rigor expectations for drawing valid conclusions and generating new theories are reflected in the following essential features of rigor and quality, which include: “Close the loop” to clearly link research questions, study design, data collection and analysis, and interpretation of results. Reflect effective integration of the study results with the conceptual framework and explain results in ways that relate, support, elaborate, and/or challenge conclusions of prior scholarship. Descriptions of new or enhanced frameworks or models are clear and effectively grounded in the study results and conclusions. Practical or theoretical implications are effectively discussed, including guidance for future studies. Limitations and issues of reflexivity and ethics are clearly and explicitly described, including references to actions taken to address these areas. 3,4,12,14

Step 5: Reporting Research Results

Key to quality reporting of qualitative research results are clarity, organization, completeness, accuracy, and conciseness in communicating the results to the reader of the research manuscript. O’Brien and others 4 proposed a standardized framework specifically for reporting qualitative studies known as the Standards for Reporting Qualitative Research (SRQR, Table 2 ). This framework provides detailed explanations of what should be reported in each of 21 sections of a qualitative research manuscript. While the SRQR does not explicitly mention a conceptual framework, the descriptions and table footnote clarification for the introduction and problem statement reflect the essential elements and focus of a conceptual framework. Ultimately, readers of published work determine levels of credibility, trustworthiness, and the like. A manuscript reviewer, the first reader of a study report, has the responsibility and privilege of providing critique and guidance to authors regarding achievement of quality criteria, execution and reporting of standards of rigor, and the extent to which meaningful contributions to thinking and practice in the field are presented. 13,39

An Adaptation of the 21 Elements of O’Brien and Colleagues’ Standards for Reporting Qualitative Research (SRQR) 4

Authors must avoid language heavy with connotations or adjectives that insert the researcher’s opinion into the database or manuscript. 14,40 The researcher should be as neutral and objective as possible in interpreting data and in presenting results. Thick and rich descriptions, where robust descriptive language is used to provide sufficient contextual information, enable the reader to determine credibility, transferability, dependability, and confirmability .

The process of demonstrating the credibility of research is rooted in honest and transparent reporting of how biases and other possible confounders were identified and addressed throughout study processes. Such reporting, first described within the study’s conceptual framework, should be revisited in reporting the work. Confounders may include the researcher’s training and previous experiences, personal connections to the background theory, access to the study population, and funding sources. These elements and processes are best represented in Glassick’s criteria for effective presentation and reflective critique ( Table 1 , criteria 5 and 6). Transferability is communicated, in part, through description of sampling factors such as: geographical location of the study, number and characteristics of participants, and the timeframe of data collection and analysis. 40 Such descriptions also contribute to the credibility of the results and readers’ determination of transfer to their and other contexts. To ensure dependability, the research method must be reported in detail such that the reader can determine proper research practices have been followed and that future researchers can repeat the study. 40 The confirmability of the results is influenced by reducing or at a minimum explaining any researcher influence on the result by applying and meeting standards of rigor such as member checking, triangulation, and peer review. 29,33

In qualitative studies, the researcher is often the primary instrument for data collection. Any researcher biases not adequately addressed or errors in judgement can affect the quality of data and subsequent research results. 33 Thus, due to the creative interpretative and contextually bound nature of qualitative studies, the application of standards of rigor and adherence to systematic processes well-documented in an audit trail are essential. The application of rigor and quality criteria extend beyond the researcher and are also important to effective peer review processes within a study and for scholarly dissemination. The goal of rigor in qualitative research can be described as ensuring that the research design, method, and conclusions are explicit, public, replicable, open to critique, and free of bias. 41 Rigor in the research process and results are achieved when each element of study methodology is systematic and transparent through complete, methodical, and accurate reporting. 33 Beginning the study with a well-developed conceptual framework and active use of both researcher reflexivity and rigorous peer review during study implementation can drive both study rigor and quality.

As the number of published qualitative studies in health professions educational research increases, it is important for our community of health care educators to keep in mind the unique aspects of rigor in qualitative studies presented here. Qualitative researchers should select and apply any of the above referenced study methods and research practices, as appropriate to the research question, to achieve rigor and quality. As in any research paradigm, the goal of quality and rigor in qualitative research is to minimize the risk of bias and maximize the accuracy and credibility of research results. Rigor is best achieved through thoughtful and deliberate planning, diligent and ongoing application of researcher reflexivity, and honest communication between the researcher and the audience regarding the study and its results.

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

What Is a Research Design | Types, Guide & Examples

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

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

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

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

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

Table of contents

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

• Introduction

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

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

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

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

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

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

Practical and ethical considerations when designing research

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

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

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

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

Types of quantitative research designs

Quantitative designs can be split into four main types.

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

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

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

Types of qualitative research designs

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

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

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

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

Defining the population

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

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

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

• Sampling methods

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

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

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

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

Case selection in qualitative research

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

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

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

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

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

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

Survey methods

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

Observation methods

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

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

Other methods of data collection

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

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

Secondary data

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

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

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

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

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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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