what should a research question be

How to Write a Research Question: Types and Examples 

The first step in any research project is framing the research question. It can be considered the core of any systematic investigation as the research outcomes are tied to asking the right questions. Thus, this primary interrogation point sets the pace for your research as it helps collect relevant and insightful information that ultimately influences your work.   

Typically, the research question guides the stages of inquiry, analysis, and reporting. Depending on the use of quantifiable or quantitative data, research questions are broadly categorized into quantitative or qualitative research questions. Both types of research questions can be used independently or together, considering the overall focus and objectives of your research.  

What is a research question?

A research question is a clear, focused, concise, and arguable question on which your research and writing are centered. 1 It states various aspects of the study, including the population and variables to be studied and the problem the study addresses. These questions also set the boundaries of the study, ensuring cohesion. 

Designing the research question is a dynamic process where the researcher can change or refine the research question as they review related literature and develop a framework for the study. Depending on the scale of your research, the study can include single or multiple research questions. 

A good research question has the following features: 

• It is relevant to the chosen field of study. 
• The question posed is arguable and open for debate, requiring synthesizing and analysis of ideas. 
• It is focused and concisely framed. 
• A feasible solution is possible within the given practical constraint and timeframe. 

A poorly formulated research question poses several risks. 1   

• Researchers can adopt an erroneous design. 
• It can create confusion and hinder the thought process, including developing a clear protocol.  
• It can jeopardize publication efforts.  
• It causes difficulty in determining the relevance of the study findings.  
• It causes difficulty in whether the study fulfils the inclusion criteria for systematic review and meta-analysis. This creates challenges in determining whether additional studies or data collection is needed to answer the question.  
• Readers may fail to understand the objective of the study. This reduces the likelihood of the study being cited by others. 

Now that you know “What is a research question?”, let’s look at the different types of research questions. 

Types of research questions

Depending on the type of research to be done, research questions can be classified broadly into quantitative, qualitative, or mixed-methods studies. Knowing the type of research helps determine the best type of research question that reflects the direction and epistemological underpinnings of your research. 

The structure and wording of quantitative 2 and qualitative research 3 questions differ significantly. The quantitative study looks at causal relationships, whereas the qualitative study aims at exploring a phenomenon. 

• Quantitative research questions:  
• Seeks to investigate social, familial, or educational experiences or processes in a particular context and/or location.  
• Answers ‘how,’ ‘what,’ or ‘why’ questions. 
• Investigates connections, relations, or comparisons between independent and dependent variables. 

Quantitative research questions can be further categorized into descriptive, comparative, and relationship, as explained in the Table below. 

• Qualitative research questions  

Qualitative research questions are adaptable, non-directional, and more flexible. It concerns broad areas of research or more specific areas of study to discover, explain, or explore a phenomenon. These are further classified as follows: 

• Mixed-methods studies  

Mixed-methods studies use both quantitative and qualitative research questions to answer your research question. Mixed methods provide a complete picture than standalone quantitative or qualitative research, as it integrates the benefits of both methods. Mixed methods research is often used in multidisciplinary settings and complex situational or societal research, especially in the behavioral, health, and social science fields. 

What makes a good research question

A good research question should be clear and focused to guide your research. It should synthesize multiple sources to present your unique argument, and should ideally be something that you are interested in. But avoid questions that can be answered in a few factual statements. The following are the main attributes of a good research question. 

• Specific: The research question should not be a fishing expedition performed in the hopes that some new information will be found that will benefit the researcher. The central research question should work with your research problem to keep your work focused. If using multiple questions, they should all tie back to the central aim. 
• Measurable: The research question must be answerable using quantitative and/or qualitative data or from scholarly sources to develop your research question. If such data is impossible to access, it is better to rethink your question. 
• Attainable: Ensure you have enough time and resources to do all research required to answer your question. If it seems you will not be able to gain access to the data you need, consider narrowing down your question to be more specific. 
• You have the expertise 
• You have the equipment and resources 
• Realistic: Developing your research question should be based on initial reading about your topic. It should focus on addressing a problem or gap in the existing knowledge in your field or discipline. 
• Based on some sort of rational physics 
• Can be done in a reasonable time frame 
• Timely: The research question should contribute to an existing and current debate in your field or in society at large. It should produce knowledge that future researchers or practitioners can later build on. 
• Novel 
• Based on current technologies. 
• Important to answer current problems or concerns. 
• Lead to new directions. 
• Important: Your question should have some aspect of originality. Incremental research is as important as exploring disruptive technologies. For example, you can focus on a specific location or explore a new angle. 
• Meaningful whether the answer is “Yes” or “No.” Closed-ended, yes/no questions are too simple to work as good research questions. Such questions do not provide enough scope for robust investigation and discussion. A good research question requires original data, synthesis of multiple sources, and original interpretation and argumentation before providing an answer. 

Steps for developing a good research question

The importance of research questions cannot be understated. When drafting a research question, use the following frameworks to guide the components of your question to ease the process. 4  

• Determine the requirements: Before constructing a good research question, set your research requirements. What is the purpose? Is it descriptive, comparative, or explorative research? Determining the research aim will help you choose the most appropriate topic and word your question appropriately. 
• Select a broad research topic: Identify a broader subject area of interest that requires investigation. Techniques such as brainstorming or concept mapping can help identify relevant connections and themes within a broad research topic. For example, how to learn and help students learn. 
• Perform preliminary investigation: Preliminary research is needed to obtain up-to-date and relevant knowledge on your topic. It also helps identify issues currently being discussed from which information gaps can be identified. 
• Narrow your focus: Narrow the scope and focus of your research to a specific niche. This involves focusing on gaps in existing knowledge or recent literature or extending or complementing the findings of existing literature. Another approach involves constructing strong research questions that challenge your views or knowledge of the area of study (Example: Is learning consistent with the existing learning theory and research). 
• Identify the research problem: Once the research question has been framed, one should evaluate it. This is to realize the importance of the research questions and if there is a need for more revising (Example: How do your beliefs on learning theory and research impact your instructional practices). 

How to write a research question

Those struggling to understand how to write a research question, these simple steps can help you simplify the process of writing a research question. 

Sample Research Questions

The following are some bad and good research question examples 

• Example 1 

• Example 2 

References:  

• Thabane, L., Thomas, T., Ye, C., & Paul, J. (2009). Posing the research question: not so simple.  Canadian Journal of Anesthesia/Journal canadien d’anesthésie ,  56 (1), 71-79. 
• Rutberg, S., & Bouikidis, C. D. (2018). Focusing on the fundamentals: A simplistic differentiation between qualitative and quantitative research.  Nephrology Nursing Journal ,  45 (2), 209-213. 
• Kyngäs, H. (2020). Qualitative research and content analysis.  The application of content analysis in nursing science research , 3-11. 
• Mattick, K., Johnston, J., & de la Croix, A. (2018). How to… write a good research question.  The clinical teacher ,  15 (2), 104-108. 
• Fandino, W. (2019). Formulating a good research question: Pearls and pitfalls.  Indian Journal of Anaesthesia ,  63 (8), 611. 
• Richardson, W. S., Wilson, M. C., Nishikawa, J., & Hayward, R. S. (1995). The well-built clinical question: a key to evidence-based decisions.  ACP journal club ,  123 (3), A12-A13 

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Creating a Good Research Question

• Advice & Growth
• Process in Practice

Successful translation of research begins with a strong question. How do you get started? How do good research questions evolve? And where do you find inspiration to generate good questions in the first place?  It’s helpful to understand existing frameworks, guidelines, and standards, as well as hear from researchers who utilize these strategies in their own work.

In the fall and winter of 2020, Naomi Fisher, MD, conducted 10 interviews with clinical and translational researchers at Harvard University and affiliated academic healthcare centers, with the purpose of capturing their experiences developing good research questions. The researchers featured in this project represent various specialties, drawn from every stage of their careers. Below you will find clips from their interviews and additional resources that highlight how to get started, as well as helpful frameworks and factors to consider. Additionally, visit the Advice & Growth section to hear candid advice and explore the Process in Practice section to hear how researchers have applied these recommendations to their published research.

• Naomi Fisher, MD , is associate professor of medicine at Harvard Medical School (HMS), and clinical staff at Brigham and Women’s Hospital (BWH). Fisher is founder and director of Hypertension Services and the Hypertension Specialty Clinic at the BWH, where she is a renowned endocrinologist. She serves as a faculty director for communication-related Boundary-Crossing Skills for Research Careers webinar sessions and the Writing and Communication Center .
• Christopher Gibbons, MD , is associate professor of neurology at HMS, and clinical staff at Beth Israel Deaconess Medical Center (BIDMC) and Joslin Diabetes Center. Gibbons’ research focus is on peripheral and autonomic neuropathies.
• Clare Tempany-Afdhal, MD , is professor of radiology at HMS and the Ferenc Jolesz Chair of Research, Radiology at BWH. Her major areas of research are MR imaging of the pelvis and image- guided therapy.
• David Sykes, MD, PhD , is assistant professor of medicine at Massachusetts General Hospital (MGH), he is also principal investigator at the Sykes Lab at MGH. His special interest area is rare hematologic conditions.
• Elliot Israel, MD , is professor of medicine at HMS, director of the Respiratory Therapy Department, the director of clinical research in the Pulmonary and Critical Care Medical Division and associate physician at BWH. Israel’s research interests include therapeutic interventions to alter asthmatic airway hyperactivity and the role of arachidonic acid metabolites in airway narrowing.
• Jonathan Williams, MD, MMSc , is assistant professor of medicine at HMS, and associate physician at BWH. He focuses on endocrinology, specifically unravelling the intricate relationship between genetics and environment with respect to susceptibility to cardiometabolic disease.
• Junichi Tokuda, PhD , is associate professor of radiology at HMS, and is a research scientist at the Department of Radiology, BWH. Tokuda is particularly interested in technologies to support image-guided “closed-loop” interventions. He also serves as a principal investigator leading several projects funded by the National Institutes of Health and industry.
• Osama Rahma, MD , is assistant professor of medicine at HMS and clinical staff member in medical oncology at Dana-Farber Cancer Institute (DFCI). Rhama is currently a principal investigator at the Center for Immuno-Oncology and Gastroenterology Cancer Center at DFCI. His research focus is on drug development of combinational immune therapeutics.
• Sharmila Dorbala, MD, MPH , is professor of radiology at HMS and clinical staff at BWH in cardiovascular medicine and radiology. She is also the president of the American Society of Nuclear Medicine. Dorbala’s specialty is using nuclear medicine for cardiovascular discoveries.
• Subha Ramani, PhD, MBBS, MMed , is associate professor of medicine at HMS, as well as associate physician in the Division of General Internal Medicine and Primary Care at BWH. Ramani’s scholarly interests focus on innovative approaches to teaching, learning and assessment of clinical trainees, faculty development in teaching, and qualitative research methods in medical education.
• Ursula Kaiser, MD , is professor at HMS and chief of the Division of Endocrinology, Diabetes and Hypertension, and senior physician at BWH. Kaiser’s research focuses on understanding the molecular mechanisms by which pulsatile gonadotropin-releasing hormone regulates the expression of luteinizing hormone and follicle-stimulating hormone genes.

Insights on Creating a Good Research Question

Play Junichi Tokuda video

Play Ursula Kaiser video

Start Successfully: Build the Foundation of a Good Research Question

Start Successfully Resources

Ideation in Device Development: Finding Clinical Need Josh Tolkoff, MS A lecture explaining the critical importance of identifying a compelling clinical need before embarking on a research project. Play Ideation in Device Development video .

Radical Innovation Jeff Karp, PhD This ThinkResearch podcast episode focuses on one researcher’s approach using radical simplicity to break down big problems and questions. Play Radical Innovation .

Using Healthcare Data: How can Researchers Come up with Interesting Questions? Anupam Jena, MD, PhD Another ThinkResearch podcast episode addresses how to discover good research questions by using a backward design approach which involves analyzing big data and allowing the research question to unfold from findings. Play Using Healthcare Data .

Important Factors: Consider Feasibility and Novelty

Refining Your Research Question 

Play video of Clare Tempany-Afdhal

Play Elliott Israel video

Frameworks and Structure: Evaluate Research Questions Using Tools and Techniques

Frameworks and Structure Resources

Designing Clinical Research Hulley et al. A comprehensive and practical guide to clinical research, including the FINER framework for evaluating research questions. Learn more about the book .

Translational Medicine Library Guide Queens University Library An introduction to popular frameworks for research questions, including FINER and PICO. Review translational medicine guide .

Asking a Good T3/T4 Question  Niteesh K. Choudhry, MD, PhD This video explains the PICO framework in practice as participants in a workshop propose research questions that compare interventions. Play Asking a Good T3/T4 Question video

Introduction to Designing & Conducting Mixed Methods Research An online course that provides a deeper dive into mixed methods’ research questions and methodologies. Learn more about the course

Network and Support: Find the Collaborators and Stakeholders to Help Evaluate Research Questions

Network & Support Resource

Bench-to-bedside, Bedside-to-bench Christopher Gibbons, MD In this lecture, Gibbons shares his experience of bringing research from bench to bedside, and from bedside to bench. His talk highlights the formation and evolution of research questions based on clinical need. Play Bench-to-bedside. 

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How To Write a Research Question

Academic writing and research require a distinct focus and direction. A well-designed research question gives purpose and clarity to your research. In addition, it helps your readers understand the issue you are trying to address and explore.

Every time you want to know more about a subject, you will pose a question. The same idea is used in research as well. You must pose a question in order to effectively address a research problem. That's why the research question is an integral part of the research process. Additionally, it offers the author writing and reading guidelines, be it qualitative research or quantitative research.

In your research paper , you must single out just one issue or problem. The specific issue or claim you wish to address should be included in your thesis statement in order to clarify your main argument.

A good research question must have the following characteristics.

• Should include only one problem in the research question
• Should be able to find the answer using primary data and secondary data sources
• Should be possible to resolve within the given time and other constraints
• Detailed and in-depth results should be achievable
• Should be relevant and realistic.
• It should relate to your chosen area of research

While a larger project, like a thesis, might have several research questions to address, each one should be directed at your main area of study. Of course, you can use different research designs and research methods (qualitative research or quantitative research) to address various research questions. However, they must all be pertinent to the study's objectives.

What is a Research Question?

A research question is an inquiry that the research attempts to answer. It is the heart of the systematic investigation. Research questions are the most important step in any research project. In essence, it initiates the research project and establishes the pace for the specific research A research question is:

• Clear : It provides enough detail that the audience understands its purpose without any additional explanation.
• Focused : It is so specific that it can be addressed within the time constraints of the writing task.
• Succinct: It is written in the shortest possible words.
• Complex : It is not possible to answer it with a "yes" or "no", but requires analysis and synthesis of ideas before somebody can create a solution.
• Argumental : Its potential answers are open for debate rather than accepted facts.

A good research question usually focuses on the research and determines the research design, methodology, and hypothesis. It guides all phases of inquiry, data collection, analysis, and reporting. You should gather valuable information by asking the right questions.

Why are Research Questions so important?

Regardless of whether it is a qualitative research or quantitative research project, research questions provide writers and their audience with a way to navigate the writing and research process. Writers can avoid "all-about" papers by asking straightforward and specific research questions that help them focus on their research and support a specific thesis.

Types of Research Questions

There are two types of research: Qualitative research and Quantitative research . There must be research questions for every type of research. Your research question will be based on the type of research you want to conduct and the type of data collection.

The first step in designing research involves identifying a gap and creating a focused research question.

Below is a list of common research questions that can be used in a dissertation. Keep in mind that these are merely illustrations of typical research questions used in dissertation projects. The real research questions themselves might be more difficult.

Example Research Questions

The following are a few examples of research questions and research problems to help you understand how research questions can be created for a particular research problem.

Steps to Write Research Questions

You can focus on the issue or research gaps you're attempting to solve by using the research questions as a direction.

If you're unsure how to go about writing a good research question, these are the steps to follow in the process:

• Select an interesting topic Always choose a topic that interests you. Because if your curiosity isn’t aroused by a subject, you’ll have a hard time conducting research around it. Alos, it’s better that you pick something that’s neither too narrow or too broad.
• Do preliminary research on the topic Search for relevant literature to gauge what problems have already been tackled by scholars. You can do that conveniently through repositories like Scispace , where you’ll find millions of papers in one place. Once you do find the papers you’re looking for, try our reading assistant, SciSpace Copilot to get simple explanations for the paper . You’ll be able to quickly understand the abstract, find the key takeaways, and the main arguments presented in the paper. This will give you a more contextual understanding of your subject and you’ll have an easier time identifying knowledge gaps in your discipline.

     Also: ChatPDF vs. SciSpace Copilot: Unveiling the best tool for your research

• Consider your audience It is essential to understand your audience to develop focused research questions for essays or dissertations. When narrowing down your topic, you can identify aspects that might interest your audience.
• Ask questions Asking questions will give you a deeper understanding of the topic. Evaluate your question through the What, Why, When, How, and other open-ended questions assessment.
• Assess your question Once you have created a research question, assess its effectiveness to determine if it is useful for the purpose. Refine and revise the dissertation research question multiple times.

Additionally, use this list of questions as a guide when formulating your research question.

Are you able to answer a specific research question? After identifying a gap in research, it would be helpful to formulate the research question. And this will allow the research to solve a part of the problem. Is your research question clear and centered on the main topic? It is important that your research question should be specific and related to your central goal. Are you tackling a difficult research question? It is not possible to answer the research question with a simple yes or no. The problem requires in-depth analysis. It is often started with "How" and "Why."

Start your research Once you have completed your dissertation research questions, it is time to review the literature on similar topics to discover different perspectives.

Strong  Research Question Samples

Uncertain: How should social networking sites work on the hatred that flows through their platform?

Certain: What should social media sites like Twitter or Facebook do to address the harm they are causing?

This unclear question does not specify the social networking sites that are being used or what harm they might be causing. In addition, this question assumes that the "harm" has been proven and/or accepted. This version is more specific and identifies the sites (Twitter, Facebook), the type and extent of harm (privacy concerns), and who might be suffering from that harm (users). Effective research questions should not be ambiguous or interpreted.

Unfocused: What are the effects of global warming on the environment?

Focused: What are the most important effects of glacial melting in Antarctica on penguins' lives?

This broad research question cannot be addressed in a book, let alone a college-level paper. Focused research targets a specific effect of global heating (glacial  melting), an area (Antarctica), or a specific animal (penguins). The writer must also decide which effect will have the greatest impact on the animals affected. If in doubt, narrow down your research question to the most specific possible.

Too Simple: What are the U.S. doctors doing to treat diabetes?

Appropriately complex: Which factors, if any, are most likely to predict a person's risk of developing diabetes?

This simple version can be found online. It is easy to answer with a few facts. The second, more complicated version of this question is divided into two parts. It is thought-provoking and requires extensive investigation as well as evaluation by the author. So, ensure that a quick Google search should not answer your research question.

How to write a strong Research Question?

The foundation of all research is the research question. You should therefore spend as much time as necessary to refine your research question based on various data.

You can conduct your research more efficiently and analyze your results better if you have great research questions for your dissertation, research paper , or essay .

The following criteria can help you evaluate the strength and importance of your research question and can be used to determine the strength of your research question:

• Researchable
• It should only cover one issue.
• A subjective judgment should not be included in the question.
• It can be answered with data analysis and research.
• Specific and Practical
• It should not contain a plan of action, policy, or solution.
• It should be clearly defined
• Within research limits
• Complex and Arguable
• It shouldn't be difficult to answer.
• To find the truth, you need in-depth knowledge
• Allows for discussion and deliberation
• Original and Relevant
• It should be in your area of study
• Its results should be measurable
• It should be original

Conclusion - How to write Research Questions?

Research questions provide a clear guideline for research. One research question may be part of a larger project, such as a dissertation. However, each question should only focus on one topic.

Research questions must be answerable, practical, specific, and applicable to your field. The research type that you use to base your research questions on will determine the research topic. You can start by selecting an interesting topic and doing preliminary research. Then, you can begin asking questions, evaluating your questions, and start your research.

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How to write a research question

Last updated

7 February 2023

Reviewed by

Miroslav Damyanov

In this article, we take an in-depth look at what a research question is, the different types of research questions, and how to write one (with examples). Read on to get started with your thesis, dissertation, or research paper .

Make research less tedious

Dovetail streamlines research to help you uncover and share actionable insights

• What is a research question?

A research question articulates exactly what you want to learn from your research. It stems directly from your research objectives, and you will arrive at an answer through data analysis and interpretation.

However, it is not that simple to write a research question—even when you know the question you intend to answer with your study. The main characteristics of a good research question are:

Feasible. You need to have the resources and abilities to examine the question, collect the data, and give answers.

Interesting. Create research questions that offer fascinating insights into your industry.

Novel. Research questions have to offer something new within your field of study.

Ethical. The research question topic should be approved by the relevant authorities and review boards.

Relevant. Your research question should lead to visible changes in society or your industry.

Usually, you write one single research question to guide your entire research paper. The answer becomes the thesis statement—the central position of your argument. A dissertation or thesis, on the other hand, may require multiple problem statements and research questions. However, they should be connected and focused on a specific problem.

• Importance of the research question

A research question acts as a guide for your entire study. It serves two vital purposes:

to determine the specific issue your research paper addresses

to identify clear objectives

Therefore, it helps split your research into small steps that you need to complete to provide answers.

Your research question will also provide boundaries for your study, which help set limits and ensure cohesion.

Finally, it acts as a frame of reference for assessing your work. Bear in mind that research questions can evolve, shift, and change during the early stages of your study or project.

• Types of research questions

The type of research you are conducting will dictate the type of research question to use. Primarily, research questions are grouped into three distinct categories of study:

qualitative

quantitative

mixed-method

Let’s look at each of these in turn:

Quantitative research questions

The number-one rule of quantitative research questions is that they are precise. They mainly include:

independent and dependent variables

the exact population being studied

the research design to be used

Therefore, you must frame and finalize quantitative research questions before starting the study.

Equally, a quantitative research question creates a link between itself and the research design. These questions cannot be answered with simple 'yes' or' no' responses, so they begin with words like 'does', 'do', 'are', and 'is'.

Quantitative research questions can be divided into three categories:

Relationship research questions usually leverage words such as 'trends' and 'association' because they include independent and dependent variables. They seek to define or explore trends and interactions between multiple variables.

Comparative research questions tend to analyze the differences between different groups to find an outcome variable. For instance, you may decide to compare two distinct groups where a specific variable is present in one and absent in the other.

Descriptive research questions usually start with the word 'what' and aim to measure how a population will respond to one or more variables.

Qualitative research questions

Like quantitative research questions, these questions are linked to the research design. However, qualitative research questions may deal with a specific or broad study area. This makes them more flexible, very adaptable, and usually non-directional.

Use qualitative research questions when your primary aim is to explain, discover, or explore.

There are seven types of qualitative research questions:

Explanatory research questions investigate particular topic areas that aren't well known.

Contextual research questions describe the workings of what is already in existence.

Evaluative research questions examine the effectiveness of specific paradigms or methods.

Ideological research questions aim to advance existing ideologies.

Descriptive research questions describe an event.

Generative research questions help develop actions and theories by providing new ideas.

Emancipatory research questions increase social action engagement, usually to benefit disadvantaged people.

Mixed-methods studies

With mixed-methods studies, you combine qualitative and quantitative research elements to get answers to your research question. This approach is ideal when you need a more complete picture. through a blend of the two approaches.

Mixed-methods research is excellent in multidisciplinary settings, societal analysis, and complex situations. Consider the following research question examples, which would be ideal candidates for a mixed-methods approach

How can non-voter and voter beliefs about democracy (qualitative) help explain Town X election turnout patterns (quantitative)?

How does students’ perception of their study environment (quantitative) relate to their test score differences (qualitative)?

• Developing a strong research question—a step-by-step guide

Research questions help break up your study into simple steps so you can quickly achieve your objectives and find answers. However, how do you develop a good research question? Here is our step-by-step guide:

1. Choose a topic

The first step is to select a broad research topic for your study. Pick something within your expertise and field that interests you. After all, the research itself will stem from the initial research question.

2. Conduct preliminary research

Once you have a broad topic, dig deeper into the problem by researching past studies in the field and gathering requirements from stakeholders if you work in a business setting.

Through this process, you will discover articles that mention areas not explored in that field or products that didn’t resonate with people’s expectations in a particular industry. For instance, you could explore specific topics that earlier research failed to study or products that failed to meet user needs.

3. Keep your audience in mind

Is your audience interested in the particular field you want to study? Are the research questions in your mind appealing and interesting to the audience? Defining your audience will help you refine your research question and ensure you pick a question that is relatable to your audience.

4. Generate a list of potential questions

Ask yourself numerous open-ended questions on the topic to create a potential list of research questions. You could start with broader questions and narrow them down to more specific ones. Don’t forget that you can challenge existing assumptions or use personal experiences to redefine research issues.

5. Review the questions

Evaluate your list of potential questions to determine which seems most effective. Ensure you consider the finer details of every question and possible outcomes. Doing this helps you determine if the questions meet the requirements of a research question.

6. Construct and evaluate your research question

Consider these two frameworks when constructing a good research question: PICOT and PEO. 

PICOT stands for:

P: Problem or population

I: Indicator or intervention to be studied

C: Comparison groups

O: Outcome of interest

T: Time frame

PEO stands for:

P: Population being studied

E: Exposure to any preexisting conditions

To evaluate your research question once you’ve constructed it, ask yourself the following questions:

Is it clear?

Your study should produce precise data and observations. For qualitative studies, the observations need to be delineable across categories. Quantitative studies must have measurable and empirical data.

Is it specific and focused?

An excellent research question must be specific enough to ensure your testing yields objective results. General or open-ended research questions are often ambiguous and subject to different kinds of interpretation.

Is it sufficiently complex?

Your research needs to yield substantial and consequential results to warrant the study. Merely supporting or reinforcing an existing paper is not good enough.

• Examples of good research questions

A robust research question actively contributes to a specific body of knowledge; it is a question that hasn’t been answered before within your research field.

Here are some examples of good and bad research questions :

Good: How effective are A and B policies at reducing the rates of Z?

Bad: Is A or B a better policy?

The first is more focused and researchable because it isn't based on value judgment. The second fails to give clear criteria for answering the question.

Good: What is the effect of daily Twitter use on the attention span of college students?

Bad: What is the effect of social media use on people's minds?

The first includes specific and well-defined concepts, which the second lacks.

Ensure all terms within your research question have precise meanings. Avoid vague or general language that makes the topic too broad.

• The bottom line

The success of any research starts with formulating the right questions that ensure you collect the most insightful data. A good research question will showcase the objectives of your systematic investigation and emphasize specific contexts.

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How to Craft a Strong Research Question (With Research Question Examples)

A sound and effective research question is a key element that must be identified and pinned down before researchers can even begin their research study or work. A strong research question lays the foundation for your entire study, guiding your investigation and shaping your findings. Hence, it is critical that researchers spend considerable time assessing and refining the research question based on in-depth reading and comprehensive literature review. In this article, we will discuss how to write a strong research question and provide you with some good examples of research questions across various disciplines.

Table of Contents

The importance of a research question

A research question plays a crucial role in driving scientific inquiry, setting the direction and purpose of your study, and guiding your entire research process. By formulating a clear and focused research question, you lay the foundation for your investigation, ensuring that your research remains on track and aligned with your objectives so you can make meaningful contribution to the existing body of knowledge. A well-crafted research question also helps you define the scope of your study and identify the appropriate methodologies and data collection techniques to employ.

Key components of a strong research question

A good research question possesses several key components that contribute to the quality and impact of your study. Apart from providing a clear framework to generate meaningful results, a well-defined research question allows other researchers to understand the purpose and significance of your work. So, when working on your research question, incorporate the following elements:

• Specificity : A strong research question should be specific about the main focus of your study, enabling you to gather precise data and draw accurate conclusions. It clearly defines the variables, participants, and context involved, leaving no room for ambiguity.
• Clarity : A good research question is clear and easily understood, so articulate the purpose and intent of your study concisely without being generic or vague. Ensuring clarity in your research question helps both you and your readers grasp the research objective.
• Feasibility : While crafting a research question, consider the practicality of conducting the research and availability of necessary data or access to participants. Think whether your study is realistic and achievable within the constraints of time, resources, and ethical considerations.

How to craft a well-defined research question

A first step that will help save time and effort is knowing what your aims are and thinking about a few problem statements on the area or aspect one wants to study or do research on. Contemplating these statements as one undertakes more progressive reading can help the researcher in reassessing and fine-tuning the research question. This can be done over time as they read and learn more about the research topic, along with a broad literature review and parallel discussions with peer researchers and supervisors. In some cases, a researcher can have more than one research question if the research being undertaken is a PhD thesis or dissertation, but try not to cover multiple concerns on a topic.

A strong research question must be researchable, original, complex, and relevant. Here are five simple steps that can make the entire process easier.

• Identify a broad topic from your areas of interest, something that is relevant, and you are passionate about since you’ll be spending a lot of time conducting your research.
• Do a thorough literature review to weed out potential gaps in research and stay updated on what’s currently being done in your chosen topic and subject area.
• Shortlist possible research questions based on the research gaps or see how you can build on or refute previously published ideas and concepts.
• Assess your chosen research question using the FINER criteria that helps you evaluate whether the research is Feasible, Interesting, Novel, Ethical, and Relevant. 1
• Formulate the final research question, while ensuring it is clear, well-written, and addresses all the key elements of a strong research question.

Examples of research questions

Remember to adapt your research question to suit your purpose, whether it’s exploratory, descriptive, comparative, experimental, qualitative, or quantitative. Embrace the iterative nature of the research process, continually evaluating and refining your question as you progress. Here are some good examples of research questions across various disciplines.

Exploratory research question examples

• How does social media impact interpersonal relationships among teenagers?
• What are the potential benefits of incorporating mindfulness practices in the workplace?

Descriptive research question examples

• What factors influence customer loyalty in the e-commerce industry?
• Is there a relationship between socioeconomic status and academic performance among elementary school students?

Comparative research question examples

• How does the effectiveness of traditional teaching methods compare to online learning platforms in mathematics education?
• What is the impact of different healthcare policies on patient outcomes in various countries?

Experimental research question examples

• What are the effects of a new drug on reducing symptoms of a specific medical condition?
• Does a dietary intervention have an impact on weight loss among individuals with obesity?

Qualitative research question examples

• What are the lived experiences of immigrants adapting to a new culture?
• What factors influence job satisfaction among healthcare professionals?

Quantitative research question examples

• Is there a relationship between sleep duration and academic performance among college students?
• How effective is a specific intervention in reducing anxiety levels among individuals with phobias?

With these simple guidelines and inspiring examples of research questions, you are equipped to embark on your research journey with confidence and purpose. Here’s wishing you all the best for your future endeavors!

References:

• How to write a research question: Steps and examples. Indeed Career Guide. Available online at https://www.indeed.com/career-advice/career-development/how-to-write-research-questions

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Developing a Research Question Video Tutorial

To learn more about developing a research question, watch  this tutorial from Wilfrid Laurier University Library.

Some content on this page was developed George Mason University Writing Center. (2018, Aug. 8).   How to Write a Research Question. https://writingcenter.gmu.edu/writing-resources/research-based-writing/how-to-write-a-research-question

What is a research question? A research question is the question around which you center your research. It should be:

• clear : it provides enough specifics that one’s audience can easily understand its purpose without needing additional explanation.
• focused : it is narrow enough that it can be answered thoroughly in the space the writing task allows.
• concise : it is expressed in the fewest possible words.
• complex : it is not answerable with a simple “yes” or “no,” but rather requires synthesis and analysis of ideas and sources prior to composition of an answer.
• arguable : its potential answers are open to debate rather than accepted facts.

You should ask a question about an issue that you are genuinely curious and/or passionate about.

The question you ask should be developed for the discipline you are studying. A question appropriate for Biology, for instance, is different from an appropriate one in Political Science or Sociology. If you are developing your question for a course other than first-year composition, you may want to discuss your ideas for a research question with your professor.

Why is a research question essential to the research process? Research questions help writers focus their research by providing a path through the research and writing process. The specificity of a well-developed research question helps writers avoid the “all-about” paper and work toward supporting a specific, arguable thesis.

Steps to developing a research question:

• Choose an interesting general topic.  Most professional researchers focus on topics they are genuinely interested in studying. Writers should choose a broad topic about which they genuinely would like to know more. An example of a general topic might be “Slavery in the American South” or “Films of the 1930s.”
• Do some preliminary research on your general topic.  Do a few quick searches in current periodicals and journals on your topic to see what’s already been done and to help you narrow your focus. What issues are scholars and researchers discussing, when it comes to your topic? What questions occur to you as you read these articles?
• Consider your audience.  For most college papers, your audience will be academic, but always keep your audience in mind when narrowing your topic and developing your question. Would that particular audience be interested in the question you are developing?
• Start asking questions.  Taking into consideration all of the above, start asking yourself open-ended “how” and “why” questions about your general topic. For example, “Why were slave narratives effective tools in working toward the abolishment of slavery?” or “How did the films of the 1930s reflect or respond to the conditions of the Great Depression?”
• Is your research question clear?  With so much research available on any given topic, research questions must be as clear as possible in order to be effective in helping the writer direct his or her research.
• Is your research question focused?  Research questions must be specific enough to be well covered in the space available.
• Is your research question complex?  Research questions should not be answerable with a simple “yes” or “no” or by easily-found facts.  They should, instead, require both research and analysis on the part of the writer. They often begin with “How” or “Why.”
• Begin your research .  After you’ve come up with a question, think about the possible paths your research could take. What sources should you consult as you seek answers to your question? What research process will ensure that you find a variety of perspectives and responses to your question?

Sample Research Questions

Unclear:  How should social networking sites address the harm they cause? Clear:  What action should social networking sites like MySpace and Facebook take to protect users’ personal information and privacy? The unclear version of this question doesn’t specify which social networking sites or suggest what kind of harm the sites might be causing. It also assumes that this “harm” is proven and/or accepted. The clearer version specifies sites (MySpace and Facebook), the type of potential harm (privacy issues), and who may be experiencing that harm (users). A strong research question should never leave room for ambiguity or interpretation. Unfocused:   What is the effect on the environment from global warming? Focused:   What is the most significant effect of glacial melting on the lives of penguins in Antarctica?

The unfocused research question is so broad that it couldn’t be adequately answered in a book-length piece, let alone a standard college-level paper. The focused version narrows down to a specific effect of global warming (glacial melting), a specific place (Antarctica), and a specific animal that is affected (penguins). It also requires the writer to take a stance on which effect has the greatest impact on the affected animal. When in doubt, make a research question as narrow and focused as possible.

Too simple:   How are doctors addressing diabetes in the U.S.? Appropriately Complex:    What main environmental, behavioral, and genetic factors predict whether Americans will develop diabetes, and how can these commonalities be used to aid the medical community in prevention of the disease?

The simple version of this question can be looked up online and answered in a few factual sentences; it leaves no room for analysis. The more complex version is written in two parts; it is thought provoking and requires both significant investigation and evaluation from the writer. As a general rule of thumb, if a quick Google search can answer a research question, it’s likely not very effective.

A well defined question should address a gap in the current literature and is the essential starting point of your research.

You can use the following frameworks to help construct your research question.

PICO for Quantitative Studies P        Population/Problem I         Intervention/Exposure C        Comparison O       Outcome Example: Is  gabapentin  (intervention),   compared to  placebo  (comparison),   effective in  decreasing pain symptoms  (outcome) in  middle aged male amputees suffering phantom limb pain  (population)?

PICo for Qualitative Studies P        Population/Problem I         Phenomenon of Interest  Co     Context Example: What are the  experiences  (phenomenon of interest) of  caregivers providing home based care to patients with Alzheimer's disease  (population) in  Australia  (context)?

SPICE S     Setting P    Perspective (for whom) I     Intervention/Exposure C    Comparison E    Evaluation Example: What are the  benefits  (evaluation) of a  doula  (intervention) for  low income mothers  (perspective) in the  developed world  (setting) compared to  no support  (comparison)?

SPIDER S      Sample PI    Phenomenon of Interest D     Design E      Evaluation R     Research Type Example: What are the  experiences  (evaluation) of  wome n (sample)  undergoing IVF treatment  (phenomenon of interest) as assessed?

Design:   questionnaire or survey or interview

Study Type:  qualitative or mixed method

The above was adapted from Cornell University A Guide to Evidence Synthesis: 1. Develop a Research Question  https://guides.library.cornell.edu/evidence-synthesis/research-question

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Developing a Research Question

by acburton | Mar 22, 2024 | Resources for Students , Writing Resources

Selecting your research question and creating a clear goal and structure for your writing can be challenging – whether you are doing it for the first time or if you’ve done it many times before. It can be especially difficult when your research question starts to look and feel a little different somewhere between your first and final draft. Don’t panic! It’s normal for your research question to change a little (or even quite a bit) as you move through and engage with the writing process. Anticipating this can remind you to stay on track while you work and that it’ll be okay even if the literature takes you in a different direction.

What Makes an Effective Research Question?

The most effective research question will usually be a critical thinking question and should use “how” or “why” to ensure it can move beyond a yes/no or one-word type of answer. Consider how your research question can aim to reveal something new, fill in a gap, even if small, and contribute to the field in a meaningful way; How might the proposed project move knowledge forward about a particular place or process? This should be specific and achievable!

The CEWC’s Grad Writing Consultant Tariq says, “I definitely concentrated on those aspects of what I saw in the field where I believed there was an opportunity to move the discipline forward.”

General Tips

Do your research.

Utilize the librarians at your university and take the time to research your topic first. Try looking at very general sources to get an idea of what could be interesting to you before you move to more academic articles that support your rough idea of the topic. It is important that research is grounded in what you see or experience regarding the topic you have chosen and what is already known in the literature. Spend time researching articles, books, etc. that supports your thesis. Once you have a number of sources that you know support what you want to write about, formulate a research question that serves as the interrogative form of your thesis statement.

Grad Writing Consultant Deni advises, “Delineate your intervention in the literature (i.e., be strategic about the literature you discuss and clear about your contributions to it).”

Start Broadly…. then Narrow Your Topic Down to Something Manageable

When brainstorming your research question, let your mind veer toward connections or associations that you might have already considered or that seem to make sense and consider if new research terms, language or concepts come to mind that may be interesting or exciting for you as a researcher. Sometimes testing out a research question while doing some preliminary researching is also useful to see if the language you are using or the direction you are heading toward is fruitful when trying to search strategically in academic databases. Be prepared to focus on a specific area of a broad topic.

Writing Consultant Jessie recommends outlining: “I think some rough outlining with a research question in mind can be helpful for me. I’ll have a research question and maybe a working thesis that I feel may be my claim to the research question based on some preliminary materials, brainstorming, etc.” — Jessie, CEWC Writing Consultant

Try an Exercise

In the earliest phase of brainstorming, try an exercise suggested by CEWC Writing Specialist, Percival! While it is normally used in classroom or workshop settings, this exercise can easily be modified for someone working alone. The flow of the activity, if done within a group setting, is 1) someone starts with an idea, 2) three other people share their idea, and 3) the starting person picks two of these new ideas they like best and combines their original idea with those. The activity then begins again with the idea that was not chosen. The solo version of this exercise substitutes a ‘word bank,’ created using words, topics, or ideas similar to your broad, overarching theme. Pick two words or phrases from your word bank, combine it with your original idea or topic, and ‘start again’ with two different words. This serves as a replacement for different people’s suggestions. Ideas for your ‘word bank’ can range from vague prompts about mapping or webbing (e.g., where your topic falls within the discipline and others like it), to more specific concepts that come from tracing the history of an idea (its past, present, future) or mapping the idea’s related ideas, influences, etc. Care for a physics analogy? There is a particle (your topic) that you can describe, a wave that the particle traces, and a field that the particle is mapped on.

Get Feedback and Affirm Your Confidence!

Creating a few different versions of your research question (they may be the same topic/issue/theme or differ slightly) can be useful during this process. Sharing these with trusted friends, colleagues, mentors, (or tutors!) and having conversations about your questions and ideas with other people can help you decide which version you may feel most confident or interested in. Ask colleagues and mentors to share their research questions with you to get a lot of examples. Once you have done the work of developing an effective research question, do not forget to affirm your confidence! Based on your working thesis, think about how you might organize your chapters or paragraphs and what resources you have for supporting this structure and organization. This can help boost your confidence that the research question you have created is effective and fruitful.

Be Open to Change

Remember, your research question may change from your first to final draft. For questions along the way, make an appointment with the Writing Center. We are here to help you develop an effective and engaging research question and build the foundation for a solid research paper!

Example 1: In my field developing a research question involves navigating the relationship between 1) what one sees/experiences at their field site and 2) what is already known in the literature. During my preliminary research, I found that the financial value of land was often a matter of precisely these cultural factors. So, my research question ended up being: How do the social and material qualities of land entangle with processes of financialization in the city of Lahore. Regarding point #1, this question was absolutely informed by what I saw in the field. But regarding point #2, the question was also heavily shaped by the literature. – Tariq

Example 2: A research question should not be a yes/no question like “Is pollution bad?”; but an open-ended question where the answer has to be supported with reasons and explanation. The question also has to be narrowed down to a specific topic—using the same example as before—”Is pollution bad?” can be revised to “How does pollution affect people?” I would encourage students to be more specific then; e.g., what area of pollution do you want to talk about: water, air, plastic, climate change… what type of people or demographic can we focus on? …how does this affect marginalized communities, minorities, or specific areas in California? After researching and deciding on a focus, your question might sound something like: How does government policy affect water pollution and how does it affect the marginalized communities in the state of California? -Janella

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How to Write a Good Research Question (w/ Examples)

What is a Research Question?

A research question is the main question that your study sought or is seeking to answer. A clear research question guides your research paper or thesis and states exactly what you want to find out, giving your work a focus and objective. Learning  how to write a hypothesis or research question is the start to composing any thesis, dissertation, or research paper. It is also one of the most important sections of a research proposal . 

A good research question not only clarifies the writing in your study; it provides your readers with a clear focus and facilitates their understanding of your research topic, as well as outlining your study’s objectives. Before drafting the paper and receiving research paper editing (and usually before performing your study), you should write a concise statement of what this study intends to accomplish or reveal.

Research Question Writing Tips

Listed below are the important characteristics of a good research question:

A good research question should:

• Be clear and provide specific information so readers can easily understand the purpose.
• Be focused in its scope and narrow enough to be addressed in the space allowed by your paper
• Be relevant and concise and express your main ideas in as few words as possible, like a hypothesis.
• Be precise and complex enough that it does not simply answer a closed “yes or no” question, but requires an analysis of arguments and literature prior to its being considered acceptable. 
• Be arguable or testable so that answers to the research question are open to scrutiny and specific questions and counterarguments.

Some of these characteristics might be difficult to understand in the form of a list. Let’s go into more detail about what a research question must do and look at some examples of research questions.

The research question should be specific and focused 

Research questions that are too broad are not suitable to be addressed in a single study. One reason for this can be if there are many factors or variables to consider. In addition, a sample data set that is too large or an experimental timeline that is too long may suggest that the research question is not focused enough.

A specific research question means that the collective data and observations come together to either confirm or deny the chosen hypothesis in a clear manner. If a research question is too vague, then the data might end up creating an alternate research problem or hypothesis that you haven’t addressed in your Introduction section .

The research question should be based on the literature 

An effective research question should be answerable and verifiable based on prior research because an effective scientific study must be placed in the context of a wider academic consensus. This means that conspiracy or fringe theories are not good research paper topics.

Instead, a good research question must extend, examine, and verify the context of your research field. It should fit naturally within the literature and be searchable by other research authors.

References to the literature can be in different citation styles and must be properly formatted according to the guidelines set forth by the publishing journal, university, or academic institution. This includes in-text citations as well as the Reference section . 

The research question should be realistic in time, scope, and budget

There are two main constraints to the research process: timeframe and budget.

A proper research question will include study or experimental procedures that can be executed within a feasible time frame, typically by a graduate doctoral or master’s student or lab technician. Research that requires future technology, expensive resources, or follow-up procedures is problematic.

A researcher’s budget is also a major constraint to performing timely research. Research at many large universities or institutions is publicly funded and is thus accountable to funding restrictions. 

The research question should be in-depth

Research papers, dissertations and theses , and academic journal articles are usually dozens if not hundreds of pages in length.

A good research question or thesis statement must be sufficiently complex to warrant such a length, as it must stand up to the scrutiny of peer review and be reproducible by other scientists and researchers.

Research Question Types

Qualitative and quantitative research are the two major types of research, and it is essential to develop research questions for each type of study. 

Quantitative Research Questions

Quantitative research questions are specific. A typical research question involves the population to be studied, dependent and independent variables, and the research design.

In addition, quantitative research questions connect the research question and the research design. In addition, it is not possible to answer these questions definitively with a “yes” or “no” response. For example, scientific fields such as biology, physics, and chemistry often deal with “states,” in which different quantities, amounts, or velocities drastically alter the relevance of the research.

As a consequence, quantitative research questions do not contain qualitative, categorical, or ordinal qualifiers such as “is,” “are,” “does,” or “does not.”

Categories of quantitative research questions

Qualitative Research Questions

In quantitative research, research questions have the potential to relate to broad research areas as well as more specific areas of study. Qualitative research questions are less directional, more flexible, and adaptable compared with their quantitative counterparts. Thus, studies based on these questions tend to focus on “discovering,” “explaining,” “elucidating,” and “exploring.”

Categories of qualitative research questions

Quantitative and Qualitative Research Question Examples

Good and Bad Research Question Examples

Below are some good (and not-so-good) examples of research questions that researchers can use to guide them in crafting their own research questions.

Research Question Example 1

The first research question is too vague in both its independent and dependent variables. There is no specific information on what “exposure” means. Does this refer to comments, likes, engagement, or just how much time is spent on the social media platform?

Second, there is no useful information on what exactly “affected” means. Does the subject’s behavior change in some measurable way? Or does this term refer to another factor such as the user’s emotions?

Research Question Example 2

In this research question, the first example is too simple and not sufficiently complex, making it difficult to assess whether the study answered the question. The author could really only answer this question with a simple “yes” or “no.” Further, the presence of data would not help answer this question more deeply, which is a sure sign of a poorly constructed research topic.

The second research question is specific, complex, and empirically verifiable. One can measure program effectiveness based on metrics such as attendance or grades. Further, “bullying” is made into an empirical, quantitative measurement in the form of recorded disciplinary actions.

Steps for Writing a Research Question

Good research questions are relevant, focused, and meaningful. It can be difficult to come up with a good research question, but there are a few steps you can follow to make it a bit easier.

1. Start with an interesting and relevant topic

Choose a research topic that is interesting but also relevant and aligned with your own country’s culture or your university’s capabilities. Popular academic topics include healthcare and medical-related research. However, if you are attending an engineering school or humanities program, you should obviously choose a research question that pertains to your specific study and major.

Below is an embedded graph of the most popular research fields of study based on publication output according to region. As you can see, healthcare and the basic sciences receive the most funding and earn the highest number of publications. 

2. Do preliminary research  

You can begin doing preliminary research once you have chosen a research topic. Two objectives should be accomplished during this first phase of research. First, you should undertake a preliminary review of related literature to discover issues that scholars and peers are currently discussing. With this method, you show that you are informed about the latest developments in the field.

Secondly, identify knowledge gaps or limitations in your topic by conducting a preliminary literature review . It is possible to later use these gaps to focus your research question after a certain amount of fine-tuning.

3. Narrow your research to determine specific research questions

You can focus on a more specific area of study once you have a good handle on the topic you want to explore. Focusing on recent literature or knowledge gaps is one good option. 

By identifying study limitations in the literature and overlooked areas of study, an author can carve out a good research question. The same is true for choosing research questions that extend or complement existing literature.

4. Evaluate your research question

Make sure you evaluate the research question by asking the following questions:

Is my research question clear?

The resulting data and observations that your study produces should be clear. For quantitative studies, data must be empirical and measurable. For qualitative, the observations should be clearly delineable across categories.

Is my research question focused and specific?

A strong research question should be specific enough that your methodology or testing procedure produces an objective result, not one left to subjective interpretation. Open-ended research questions or those relating to general topics can create ambiguous connections between the results and the aims of the study. 

Is my research question sufficiently complex?

The result of your research should be consequential and substantial (and fall sufficiently within the context of your field) to warrant an academic study. Simply reinforcing or supporting a scientific consensus is superfluous and will likely not be well received by most journal editors.  

Editing Your Research Question

Your research question should be fully formulated well before you begin drafting your research paper. However, you can receive English paper editing and proofreading services at any point in the drafting process. Language editors with expertise in your academic field can assist you with the content and language in your Introduction section or other manuscript sections. And if you need further assistance or information regarding paper compositions, in the meantime, check out our academic resources , which provide dozens of articles and videos on a variety of academic writing and publication topics.

Literature Searching

Characteristics of a good research question

The first step in a literature search is to construct a well-defined question.  This helps in ensuring a comprehensive and efficient search of the available literature for relevant publications on your topic.  The well-constructed research question provides guidance for determining search terms and search strategy parameters.

A good or well-constructed research question is:

• Original and of interest to the researcher and the outside world
• It is clear and focused: it provides enough specifics that it is easy to understand its purpose and it is narrow enough that it can be answered. If the question is too broad it may not be possible to answer it thoroughly. If it is too narrow you may not find enough resources or information to develop a strong argument or research hypothesis.  
• The question concept is researchable in terms of time and access to a suitable amount of quality research resources.
• It is analytical rather than descriptive.  The research question should allow you to produce an analysis of an issue or problem rather than a simple description of it.  In other words, it is not answerable with a simple “yes” or “no” but requires a synthesis and analysis of ideas and sources.
• The results are potentially important and may change current ideas and/or practice
• And there is the potential to develop further projects with similar themes

The question you ask should be developed for the discipline you are studying. A question appropriate for Physical Therapy, for instance, is different from an appropriate one in Sociology, Political Science or Microbiology .

The well-constructed question provides guidance for determining search terms and search strategy parameters. The process of developing a good question to research involves taking your topic and breaking each aspect of it down into its component parts. 

One well-established way that can be used both for creating research questions and developing strategies is known as PICO(T). The PICO framework was designed primarily for questions that include clinical interventions and comparisons, however other types of questions may also be able to follow its principles.  If the PICO framework does not precisely fit your question, using its principles can help you to think about what you want to explore even if you do not end up with a true PICO question.

References/Additional Resources

Fandino W. (2019). Formulating a good research question: Pearls and pitfalls.   Indian journal of anaesthesia ,  63 (8), 611–616. 

Vandenbroucke, J. P., & Pearce, N. (2018). From ideas to studies: how to get ideas and sharpen them into research questions .  Clinical epidemiology ,  10 , 253–264.

Ratan, S. K., Anand, T., & Ratan, J. (2019). Formulation of Research Question - Stepwise Approach .  Journal of Indian Association of Pediatric Surgeons ,  24 (1), 15–20.

Lipowski, E.E. (2008). Developing great research questions. American Journal of Health-System Pharmacy, 65(17) , 1667–1670.

FINER Criteria

Another set of criteria for developing a research question was proposed by Hulley (2013) and is known as the FINER criteria. 

FINER stands for:

Feasible – Writing a feasible research question means that it CAN be answered under objective aspects like time, scope, resources, expertise, or funding. Good questions must be amenable to the formulation of clear hypotheses.

Interesting – The question or topic should be of interest to the researcher and the outside world. It should have a clinical and/or educational significance – the “so what?” factor. 

Novel – In scientific literature, novelty defines itself by being an answer to an existing gap in knowledge. Filling one of these gaps is highly rewarding for any researcher as it may represent a real difference in peoples’ lives.

Good research leads to new information. An investigation which simply reiterates what is previously proven is not worth the effort and cost. A question doesn’t have to be completely original. It may ask whether an earlier observation could be replicated, whether the results in one population also apply to others, or whether enhanced measurement methods can make clear the relationship between two variables.  

Ethical – In empirical research, ethics is an absolute MUST. Make sure that safety and confidentiality measures are addressed, and according to the necessary IRB protocols.

Relevant – An idea that is considered relevant in the healthcare community has better chances to be discussed upon by a larger number of researchers and recognized experts, leading to innovation and rapid information dissemination.

The results could potentially be important and may change current ideas and/or practice.

Cummings, S.R., Browner, W.S., & Hulley, S.B. (2013). Conceiving the research question and developing the study plan. In: Designing clinical research (Hulley, S. R. Cummings, W. S. Browner, D. Grady, & T. B. Newman, Eds.; Fourth edition.). Wolters Kluwer/Lippincott Williams & Wilkins. Pp. 14-22.    

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Research Toolkit: Creating a Research Question

• Understand Your Assignment
• Choosing a Topic
• Creating a Research Question
• Where to Begin Your Search
• Find a Book
• Find Articles - The Basics
• Find an Article - Advanced Strategies
• Books from Another Library
• Find a Scholarly Article
• Found Too Much/Too Little
• Quickly evaluate a book
• Quickly evaluate an article
• Quickly evaluate a website
• What is peer review?
• Quickly Read an Article or Book
• Lateral Reading
• Know when to cite
• Cite Specific Source
• Find a Citation Tool
• Find a Source Again
• Google vs. Library Resources
• Discover Google Search Tips
• Use Google Scholar
• Using LibKey Nomad

  Prepare to Research

 find books, articles &  other sources,   evaluating sources  (are they any good),   citing sources,  use the web for  research, create a research question, choosing a research topic.

What is a Research Question?

A research question focuses your research and centers your thinking.  A good research question requires you to think critically and ask further questions. It is broad enough that you can find plenty of sources, and focused enough that you can fully consider it.  Your research question should be interesting to you and get you excited to learn more.  If a question leaves you asking “so what?” or “who cares?,” it is not worth investigating. Your research question can evolve as you learn more about your topic, and you can revise or modify your question as you learn more.

Elements of a good research question:

• Clear and focused - your question makes sense and is not vague.
• Arguable - your question is open to debate and cannot be answered with a report of facts.
• Complex - your question requires critical analysis of ideas and sources; it cannot be answered with a simple “yes” or “no.”

Adapted from an explanation by Dr. Jennifer Einspahr, with many thanks.

How to develop your research question:

• Before you can develop a research question, you need to choose a topic .
• Choose an idea or issue that you are curious and passionate about.
• Think critically and ask further questions: Ask “how” and “why” questions about your topic. For example, “How did films from the 1930s reflect or respond to the conditions of the Great Depression?”
• What issues are scholars and researchers discussing?
• What questions come up as you read these sources?
• Search library databases for encyclopedias, scholarly books, and articles.
• Consult bibliographies of sources you have read in class.
• Is your research question clear and understandable ? 
• Is your research question focused ?  - Research questions must be specific in order to be covered in depth.
• Is your research question complex ?  - Research questions should not be answerable with “yes” or “no,” or by easily found facts. They require research and analysis, and they often begin with “How” or “Why.”
• Intensify your research.   What are the possible paths your research question could take? What types of sources should you consult? What approach to your research will ensure that you find a variety of perspectives and responses to your question?

Example Research Questions

Unclear : How should social networking sites address the harm they cause? Clear : What action should social networking sites like Instagram and Facebook take to protect users’ personal information and privacy?

The unclear version of this question doesn’t specify which social networking sites or suggest what kind of harm the sites might be causing. It also assumes that this “harm” is proven and/or accepted. The clearer version specifies sites (Instagram and Facebook), the type of potential harm (privacy issues), and who may be experiencing that harm (users). A strong research question leaves no room for ambiguity or misinterpretation.

Unfocused :  What is the effect on the environment from global warming? Focused :  What is the most significant effect of glacial melting on the lives of penguins in Antarctica?

The unfocused research question is so broad that it couldn’t be adequately answered in a book-length work, let alone a standard college-level paper. The focused version is narrowed to a specific effect of global warming (glacial melting), a specific place (Antarctica), and a specific animal that is affected (penguins). It also requires the writer to take a stance on which effect has the greatest impact on the affected animal. When in doubt, make a research question as narrow and focused as possible.

Too simple :  How are doctors addressing diabetes in the U.S.? Appropriately Complex :   What environmental, behavioral, and genetic factors predict whether some Americans will develop diabetes, and how can these commonalities be analysed to further medical research toward prevention of the disease?

The simple version of this question can be looked up online and answered in a few factual sentences, leaving no room for analysis. The more complex version is written in two parts; it is thought provoking and requires both significant investigation and evaluation from the writer. If a quick Google search can answer a research question, then the question does not pose sufficient analysis and critical thinking.

Adapted from George Mason University Writing Center. (2018). How to write a research question. Retrieved from http://writingcenter.gmu.edu/guides/how-to-write-a-research-question

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• Last Updated: Jun 18, 2024 11:54 AM
• URL: https://libguides.kzoo.edu/researchtoolkit

• How it works

How to Write the Research Questions – Tips & Examples

Published by Owen Ingram at August 13th, 2021 , Revised On October 3, 2023

Conducting research and writing an academic paper requires a clear direction and focus.

A good research question provides purpose to your research and clarifies the direction. It further helps your readers to understand what issue your research aims to explore and address.

If you are unsure about how to write research questions, here is a list of the attributes of a good research question;

• The research question should contain only a single problem
• You should be able to find the answer to it using  primary and secondary data sources
• You should be able to address it within the time limit and other constraints
• Can attain in-depth and detailed results
• Relevant and applicable
• Should relate to your chosen field of research

Whenever you want to discover something new about a  topic , you will ask a question about it. Therefore, the research question is important in the overall research process  and provides the author with the reading and writing guidelines.

In a research paper or an essay, you will need to create a single research question that highlights just one problem or issue. The thesis statement should include the specific problem you aim to investigate to establish your argument’s central position or claim.

A larger project such as a  dissertation or thesis , on the other hand, can have multiple research questions, but every question should focus on your main  research problem .  Different types of research will help you answer different research questions, but they should all be relevant to the research scope.

How to Write a Research Question

Steps to develop your research question.

• Choose a topic  with a wide range of published literature
• Read and skim relevant articles to find out different problems and issues
• Specify a theoretical or practical  research problem  that your research question will address
• Narrow down the focus of your selected core niche

Example Research Question (s)

Here are examples of research problems and research questions to help you understand how to create a research question for a given research problem.

Types of Research Questions

There are two main types of research;  quantitative and qualitative research . Both types of research require research questions. What research question you will answer is dependent on the type of research you wish to employ.

The first part of  designing research  is to find a gap and create a fully focused research question.

The following table shows common research questions for a dissertation project. However, it is important to note that these examples of dissertation research questions are straightforward, and the actual research questions may be more complicated than these examples.

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• Find out by hiring an expert from ResearchProspect today!
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Steps to Write Research Questions

The research question provides you with a path and focuses on the real problem and the research gap you aim to fill. These are steps you need to take if you are unsure about how to write a research question:

Choose an Interesting Topic

Choose a topic  of research according to your interest. The selected topic should be neither too broad nor too narrow.

Do Preliminary Research on the Topic

Find articles, books, journals, and theses relevant to your chosen topic. Understand what research problem each scholar addressed as part of their research project.

Consider your Audience

It is necessary to know your audience to develop focused research questions for your essay or dissertation. You can find aspects of your topic that could be interesting to your audience when narrowing your topic.

Start Asking Questions

What, why, when, how, and other open-ended questions will provide in-depth knowledge about the topic.

Evaluate your Question

After formulating a research question, evaluate to check its effectiveness and how it can serve the purpose. Revise and refine the dissertation research question.

• Do you have a clear research question? 

It would help if you formed the research question after finding a research gap. This approach will enable the research to solve part of the problem.

• Do you have a focused research question?

It is necessary that the research question is specific and relating to the central aim of your research.

• Do you have a complex research question? 

The research question cannot be answered by yes or no but requires in-depth analysis. It often begins with “How” or “Why.”

Begin your Research

After you have prepared dissertation research questions, you should research the existing literature on similar topics to find various perspectives.

Also See: Formulation of Research Question

If you have been struggling to devise research questions for your dissertation or are unsure about which topic would be suitable for your needs, then you might be interested in taking advantage of our dissertation topic and outline service, which includes several topic ideas in your preferred area of study and a 500/1000 words plan on your chosen topic. Our topic and outline service will help you jump-start your dissertation project.

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Tips on How to Write a Strong Research Question

A research question is the foundation of the entire research. Therefore, you should spend as much time as required to refine the research question.

If you have good research questions for the dissertation, research paper , or essay, you can perform the research and analyse your results more effectively. You can evaluate the strength of the research question with the help of the following criteria. Your research question should be;

Intensive and Researchable

• It should cover a single issue
• The question shouldn’t include a subjective judgment
• It can be answerable with the data analysis or research=

Practical and Specific

• It should not include a course of action, policy, or solution
• It should be well-defined
• Answerable within research limits

Complicated and Arguable

• It should not be simple to answer
• Need in-depth knowledge to find facts
• Provides scope for debate and deliberation

Unique and Relevant

• It should lie in your field of study
• Its results should be contributable
• It should be unique

Conclusion – How to Write Research Questions

A research question provides a clear direction for research work. A bigger project, such as a dissertation, may have more than one research question, but every question should focus on one issue only.

Your research questions should be researchable, feasible to answer, specific to find results, complex (for Masters and PhD projects), and relevant to your field of study. Dissertation research questions depend upon the research type you are basing your paper on.

Start creating a research question by choosing an interesting topic, do some preliminary research, consider your audience, start asking questions, evaluating your question, and begin your research.

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Frequently Asked Questions

How are research questions written.

Research questions are written by:

• Identifying your topic.
• Considering what you want to explore.
• Making questions clear and concise.
• Ensuring they’re researchable.
• Avoiding bias or leading language.
• Focusing on one main idea per question.

What are examples of research questions?

• Does regular exercise improve mental well-being in adults over 50?
• How do online courses impact student engagement compared to traditional classes?
• What are the economic effects of prolonged pandemic lockdowns?
• How does early childhood nutrition influence academic performance in later life?
• Does urban green space reduce stress levels?

How to write a research question?

• Identify a specific topic or issue of interest.
• Conduct preliminary research to understand existing knowledge.
• Narrow the focus to address gaps or unresolved issues.
• Phrase the question to be clear, concise, and researchable.
• Ensure it is specific enough for systematic investigation.

How to formulate my research questions for my geography dissertation?

• Identify a geographical topic or phenomenon of interest.
• Review existing literature to find gaps.
• Consider spatial, temporal, environmental, or societal aspects.
• Ensure questions are specific, feasible, and significant.
• Frame questions to guide methodology: quantitative, qualitative, or mixed.
• Seek feedback from peers/advisors.

You May Also Like

To help students organise their dissertation proposal paper correctly, we have put together detailed guidelines on how to structure a dissertation proposal.

Repository of ten perfect research question examples will provide you a better perspective about how to create research questions.

Struggling to find relevant and up-to-date topics for your dissertation? Here is all you need to know if unsure about how to choose dissertation topic.

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• How It Works

Writing Studio

Formulating your research question (rq).

In an effort to make our handouts more accessible, we have begun converting our PDF handouts to web pages. Download this page as a PDF: Formulating Your Research Question Return to Writing Studio Handouts

In a research paper, the emphasis is on generating a unique question and then synthesizing diverse sources into a coherent essay that supports your argument about the topic. In other words, you integrate information from publications with your own thoughts in order to formulate an argument. Your topic is your starting place: from here, you will develop an engaging research question. Merely presenting a topic in the form of a question does not transform it into a good research question.

Research Topic Versus Research Question Examples

1. broad topic versus narrow question, 1a. broad topic.

“What forces affect race relations in America?”

1b. NARROWER QUESTION

“How do corporate hiring practices affect race relations in Nashville?”

The question “What is the percentage of racial minorities holding management positions in corporate offices in Nashville?” is much too specific and would yield, at best, a statistic that could become part of a larger argument.

2. Neutral Topic Versus Argumentative Question

2a. neutral topic.

“How does KFC market its low-fat food offerings?”

2b. Argumentative question

“Does KFC put more money into marketing its high-fat food offerings than its lower-fat ones?”

The latter question is somewhat better, since it may lead you to take a stance or formulate an argument about consumer awareness or benefit.

3. Objective Topic Versus Subjective Question

Objective subjects are factual and do not have sides to be argued. Subjective subjects are those about which you can take a side.

3a. Objective topic

“How much time do youth between the ages of 10 and 15 spend playing video games?”

3b. Subjective Question

“What are the effects of video-gaming on the attention spans of youth between the ages of 10 and 15?”

The first question is likely to lead to some data, though not necessarily to an argument or issue. The second question is somewhat better, since it might lead you to formulate an argument for or against time spent playing video games.

4. Open-Ended Topic Versus Direct Question

4a. open-ended topic.

“Does the author of this text use allusion?”

4b. Direct question (gives direction to research)

“Does the ironic use of allusion in this text reveal anything about the author’s unwillingness to divulge his political commitments?”

The second question gives focus by putting the use of allusion into the specific context of a question about the author’s political commitments and perhaps also about the circumstances under which the text was produced.

Research Question (RQ) Checklist

• Is my RQ something that I am curious about and that others might care about? Does it present an issue on which I can take a stand?
• Does my RQ put a new spin on an old issue, or does it try to solve a problem?
• Is my RQ too broad, too narrow, or OK?
• within the time frame of the assignment?
• given the resources available at my location?
• Is my RQ measurable? What type of information do I need? Can I find actual data to support or contradict a position?
• What sources will have the type of information that I need to answer my RQ (journals, books, internet resources, government documents, interviews with people)?

Final Thoughts

The answer to a good research question will often be the THESIS of your research paper! And the results of your research may not always be what you expected them to be. Not only is this ok, it can be an indication that you are doing careful work!

Adapted from an online tutorial at Empire State College: http://www.esc.edu/htmlpages/writerold/menus.htm#develop (broken link)

Last revised: November 2022 | Adapted for web delivery: November 2022

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How to Develop a Good Research Question? — Types & Examples

Cecilia is living through a tough situation in her research life. Figuring out where to begin, how to start her research study, and how to pose the right question for her research quest, is driving her insane. Well, questions, if not asked correctly, have a tendency to spiral us!

Image Source: https://phdcomics.com/

Questions lead everyone to answers. Research is a quest to find answers. Not the vague questions that Cecilia means to answer, but definitely more focused questions that define your research. Therefore, asking appropriate question becomes an important matter of discussion.

A well begun research process requires a strong research question. It directs the research investigation and provides a clear goal to focus on. Understanding the characteristics of comprising a good research question will generate new ideas and help you discover new methods in research.

In this article, we are aiming to help researchers understand what is a research question and how to write one with examples.

Table of Contents

What Is a Research Question?

A good research question defines your study and helps you seek an answer to your research. Moreover, a clear research question guides the research paper or thesis to define exactly what you want to find out, giving your work its objective. Learning to write a research question is the beginning to any thesis, dissertation , or research paper. Furthermore, the question addresses issues or problems which is answered through analysis and interpretation of data.

Why Is a Research Question Important?

A strong research question guides the design of a study. Moreover, it helps determine the type of research and identify specific objectives. Research questions state the specific issue you are addressing and focus on outcomes of the research for individuals to learn. Therefore, it helps break up the study into easy steps to complete the objectives and answer the initial question.

Types of Research Questions

Research questions can be categorized into different types, depending on the type of research you want to undergo. Furthermore, knowing the type of research will help a researcher determine the best type of research question to use.

1. Qualitative Research Question

Qualitative questions concern broad areas or more specific areas of research. However, unlike quantitative questions, qualitative research questions are adaptable, non-directional and more flexible. Qualitative research question focus on discovering, explaining, elucidating, and exploring.

i. Exploratory Questions

This form of question looks to understand something without influencing the results. The objective of exploratory questions is to learn more about a topic without attributing bias or preconceived notions to it.

Research Question Example: Asking how a chemical is used or perceptions around a certain topic.

ii. Predictive Questions

Predictive research questions are defined as survey questions that automatically predict the best possible response options based on text of the question. Moreover, these questions seek to understand the intent or future outcome surrounding a topic.

Research Question Example: Asking why a consumer behaves in a certain way or chooses a certain option over other.

iii. Interpretive Questions

This type of research question allows the study of people in the natural setting. The questions help understand how a group makes sense of shared experiences with regards to various phenomena. These studies gather feedback on a group’s behavior without affecting the outcome.

Research Question Example: How do you feel about AI assisting publishing process in your research?

2. Quantitative Research Question

Quantitative questions prove or disprove a researcher’s hypothesis through descriptions, comparisons, and relationships. These questions are beneficial when choosing a research topic or when posing follow-up questions that garner more information.

i. Descriptive Questions

It is the most basic type of quantitative research question and it seeks to explain when, where, why, or how something occurred. Moreover, they use data and statistics to describe an event or phenomenon.

Research Question Example: How many generations of genes influence a future generation?

ii. Comparative Questions

Sometimes it’s beneficial to compare one occurrence with another. Therefore, comparative questions are helpful when studying groups with dependent variables.

Example: Do men and women have comparable metabolisms?

iii. Relationship-Based Questions

This type of research question answers influence of one variable on another. Therefore, experimental studies use this type of research questions are majorly.

Example: How is drought condition affect a region’s probability for wildfires.  

How to Write a Good Research Question?

1. Select a Topic

The first step towards writing a good research question is to choose a broad topic of research. You could choose a research topic that interests you, because the complete research will progress further from the research question. Therefore, make sure to choose a topic that you are passionate about, to make your research study more enjoyable.

2. Conduct Preliminary Research

After finalizing the topic, read and know about what research studies are conducted in the field so far. Furthermore, this will help you find articles that talk about the topics that are yet to be explored. You could explore the topics that the earlier research has not studied.

3. Consider Your Audience

The most important aspect of writing a good research question is to find out if there is audience interested to know the answer to the question you are proposing. Moreover, determining your audience will assist you in refining your research question, and focus on aspects that relate to defined groups.

4. Generate Potential Questions

The best way to generate potential questions is to ask open ended questions. Questioning broader topics will allow you to narrow down to specific questions. Identifying the gaps in literature could also give you topics to write the research question. Moreover, you could also challenge the existing assumptions or use personal experiences to redefine issues in research.

5. Review Your Questions

Once you have listed few of your questions, evaluate them to find out if they are effective research questions. Moreover while reviewing, go through the finer details of the question and its probable outcome, and find out if the question meets the research question criteria.

6. Construct Your Research Question

There are two frameworks to construct your research question. The first one being PICOT framework , which stands for:

• Population or problem
• Intervention or indicator being studied
• Comparison group
• Outcome of interest
• Time frame of the study.

The second framework is PEO , which stands for:

• Population being studied
• Exposure to preexisting conditions
• Outcome of interest.

Research Question Examples

• How might the discovery of a genetic basis for alcoholism impact triage processes in medical facilities?
• How do ecological systems respond to chronic anthropological disturbance?
• What are demographic consequences of ecological interactions?
• What roles do fungi play in wildfire recovery?
• How do feedbacks reinforce patterns of genetic divergence on the landscape?
• What educational strategies help encourage safe driving in young adults?
• What makes a grocery store easy for shoppers to navigate?
• What genetic factors predict if someone will develop hypothyroidism?
• Does contemporary evolution along the gradients of global change alter ecosystems function?

How did you write your first research question ? What were the steps you followed to create a strong research question? Do write to us or comment below.

Frequently Asked Questions

Research questions guide the focus and direction of a research study. Here are common types of research questions: 1. Qualitative research question: Qualitative questions concern broad areas or more specific areas of research. However, unlike quantitative questions, qualitative research questions are adaptable, non-directional and more flexible. Different types of qualitative research questions are: i. Exploratory questions ii. Predictive questions iii. Interpretive questions 2. Quantitative Research Question: Quantitative questions prove or disprove a researcher’s hypothesis through descriptions, comparisons, and relationships. These questions are beneficial when choosing a research topic or when posing follow-up questions that garner more information. Different types of quantitative research questions are: i. Descriptive questions ii. Comparative questions iii. Relationship-based questions

Qualitative research questions aim to explore the richness and depth of participants' experiences and perspectives. They should guide your research and allow for in-depth exploration of the phenomenon under investigation. After identifying the research topic and the purpose of your research: • Begin with Broad Inquiry: Start with a general research question that captures the main focus of your study. This question should be open-ended and allow for exploration. • Break Down the Main Question: Identify specific aspects or dimensions related to the main research question that you want to investigate. • Formulate Sub-questions: Create sub-questions that delve deeper into each specific aspect or dimension identified in the previous step. • Ensure Open-endedness: Make sure your research questions are open-ended and allow for varied responses and perspectives. Avoid questions that can be answered with a simple "yes" or "no." Encourage participants to share their experiences, opinions, and perceptions in their own words. • Refine and Review: Review your research questions to ensure they align with your research purpose, topic, and objectives. Seek feedback from your research advisor or peers to refine and improve your research questions.

Developing research questions requires careful consideration of the research topic, objectives, and the type of study you intend to conduct. Here are the steps to help you develop effective research questions: 1. Select a Topic 2. Conduct Preliminary Research 3. Consider Your Audience 4. Generate Potential Questions 5. Review Your Questions 6. Construct Your Research Question Based on PICOT or PEO Framework

There are two frameworks to construct your research question. The first one being PICOT framework, which stands for: • Population or problem • Intervention or indicator being studied • Comparison group • Outcome of interest • Time frame of the study The second framework is PEO, which stands for: • Population being studied • Exposure to preexisting conditions • Outcome of interest

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Research Aims, Objectives & Questions

The “Golden Thread” Explained Simply (+ Examples)

By: David Phair (PhD) and Alexandra Shaeffer (PhD) | June 2022

The research aims , objectives and research questions (collectively called the “golden thread”) are arguably the most important thing you need to get right when you’re crafting a research proposal , dissertation or thesis . We receive questions almost every day about this “holy trinity” of research and there’s certainly a lot of confusion out there, so we’ve crafted this post to help you navigate your way through the fog.

Overview: The Golden Thread

• What is the golden thread
• What are research aims ( examples )
• What are research objectives ( examples )
• What are research questions ( examples )
• The importance of alignment in the golden thread

What is the “golden thread”?  

The golden thread simply refers to the collective research aims , research objectives , and research questions for any given project (i.e., a dissertation, thesis, or research paper ). These three elements are bundled together because it’s extremely important that they align with each other, and that the entire research project aligns with them.

Importantly, the golden thread needs to weave its way through the entirety of any research project , from start to end. In other words, it needs to be very clearly defined right at the beginning of the project (the topic ideation and proposal stage) and it needs to inform almost every decision throughout the rest of the project. For example, your research design and methodology will be heavily influenced by the golden thread (we’ll explain this in more detail later), as well as your literature review.

The research aims, objectives and research questions (the golden thread) define the focus and scope ( the delimitations ) of your research project. In other words, they help ringfence your dissertation or thesis to a relatively narrow domain, so that you can “go deep” and really dig into a specific problem or opportunity. They also help keep you on track , as they act as a litmus test for relevance. In other words, if you’re ever unsure whether to include something in your document, simply ask yourself the question, “does this contribute toward my research aims, objectives or questions?”. If it doesn’t, chances are you can drop it.

Alright, enough of the fluffy, conceptual stuff. Let’s get down to business and look at what exactly the research aims, objectives and questions are and outline a few examples to bring these concepts to life.

Research Aims: What are they?

Simply put, the research aim(s) is a statement that reflects the broad overarching goal (s) of the research project. Research aims are fairly high-level (low resolution) as they outline the general direction of the research and what it’s trying to achieve .

Research Aims: Examples  

True to the name, research aims usually start with the wording “this research aims to…”, “this research seeks to…”, and so on. For example:

“This research aims to explore employee experiences of digital transformation in retail HR.”   “This study sets out to assess the interaction between student support and self-care on well-being in engineering graduate students”  

As you can see, these research aims provide a high-level description of what the study is about and what it seeks to achieve. They’re not hyper-specific or action-oriented, but they’re clear about what the study’s focus is and what is being investigated.

Need a helping hand?

Research Objectives: What are they?

The research objectives take the research aims and make them more practical and actionable . In other words, the research objectives showcase the steps that the researcher will take to achieve the research aims.

The research objectives need to be far more specific (higher resolution) and actionable than the research aims. In fact, it’s always a good idea to craft your research objectives using the “SMART” criteria. In other words, they should be specific, measurable, achievable, relevant and time-bound”.

Research Objectives: Examples  

Let’s look at two examples of research objectives. We’ll stick with the topic and research aims we mentioned previously.  

For the digital transformation topic:

To observe the retail HR employees throughout the digital transformation. To assess employee perceptions of digital transformation in retail HR. To identify the barriers and facilitators of digital transformation in retail HR.

And for the student wellness topic:

To determine whether student self-care predicts the well-being score of engineering graduate students. To determine whether student support predicts the well-being score of engineering students. To assess the interaction between student self-care and student support when predicting well-being in engineering graduate students.

  As you can see, these research objectives clearly align with the previously mentioned research aims and effectively translate the low-resolution aims into (comparatively) higher-resolution objectives and action points . They give the research project a clear focus and present something that resembles a research-based “to-do” list.

Research Questions: What are they?

Finally, we arrive at the all-important research questions. The research questions are, as the name suggests, the key questions that your study will seek to answer . Simply put, they are the core purpose of your dissertation, thesis, or research project. You’ll present them at the beginning of your document (either in the introduction chapter or literature review chapter) and you’ll answer them at the end of your document (typically in the discussion and conclusion chapters).  

The research questions will be the driving force throughout the research process. For example, in the literature review chapter, you’ll assess the relevance of any given resource based on whether it helps you move towards answering your research questions. Similarly, your methodology and research design will be heavily influenced by the nature of your research questions. For instance, research questions that are exploratory in nature will usually make use of a qualitative approach, whereas questions that relate to measurement or relationship testing will make use of a quantitative approach.  

Let’s look at some examples of research questions to make this more tangible.

Research Questions: Examples  

Again, we’ll stick with the research aims and research objectives we mentioned previously.  

For the digital transformation topic (which would be qualitative in nature):

How do employees perceive digital transformation in retail HR? What are the barriers and facilitators of digital transformation in retail HR?  

And for the student wellness topic (which would be quantitative in nature):

Does student self-care predict the well-being scores of engineering graduate students? Does student support predict the well-being scores of engineering students? Do student self-care and student support interact when predicting well-being in engineering graduate students?  

You’ll probably notice that there’s quite a formulaic approach to this. In other words, the research questions are basically the research objectives “converted” into question format. While that is true most of the time, it’s not always the case. For example, the first research objective for the digital transformation topic was more or less a step on the path toward the other objectives, and as such, it didn’t warrant its own research question.  

So, don’t rush your research questions and sloppily reword your objectives as questions. Carefully think about what exactly you’re trying to achieve (i.e. your research aim) and the objectives you’ve set out, then craft a set of well-aligned research questions . Also, keep in mind that this can be a somewhat iterative process , where you go back and tweak research objectives and aims to ensure tight alignment throughout the golden thread.

The importance of strong alignment 

Alignment is the keyword here and we have to stress its importance . Simply put, you need to make sure that there is a very tight alignment between all three pieces of the golden thread. If your research aims and research questions don’t align, for example, your project will be pulling in different directions and will lack focus . This is a common problem students face and can cause many headaches (and tears), so be warned.

Take the time to carefully craft your research aims, objectives and research questions before you run off down the research path. Ideally, get your research supervisor/advisor to review and comment on your golden thread before you invest significant time into your project, and certainly before you start collecting data .  

Recap: The golden thread

In this post, we unpacked the golden thread of research, consisting of the research aims , research objectives and research questions . You can jump back to any section using the links below.

As always, feel free to leave a comment below – we always love to hear from you. Also, if you’re interested in 1-on-1 support, take a look at our private coaching service here.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

41 Comments

Thank you very much for your great effort put. As an Undergraduate taking Demographic Research & Methodology, I’ve been trying so hard to understand clearly what is a Research Question, Research Aim and the Objectives in a research and the relationship between them etc. But as for now I’m thankful that you’ve solved my problem.

Well appreciated. This has helped me greatly in doing my dissertation.

An so delighted with this wonderful information thank you a lot.

so impressive i have benefited a lot looking forward to learn more on research.

I am very happy to have carefully gone through this well researched article.

Infact,I used to be phobia about anything research, because of my poor understanding of the concepts.

Now,I get to know that my research question is the same as my research objective(s) rephrased in question format.

I please I would need a follow up on the subject,as I intends to join the team of researchers. Thanks once again.

Thanks so much. This was really helpful.

I know you pepole have tried to break things into more understandable and easy format. And God bless you. Keep it up

i found this document so useful towards my study in research methods. thanks so much.

This is my 2nd read topic in your course and I should commend the simplified explanations of each part. I’m beginning to understand and absorb the use of each part of a dissertation/thesis. I’ll keep on reading your free course and might be able to avail the training course! Kudos!

Thank you! Better put that my lecture and helped to easily understand the basics which I feel often get brushed over when beginning dissertation work.

This is quite helpful. I like how the Golden thread has been explained and the needed alignment.

This is quite helpful. I really appreciate!

The article made it simple for researcher students to differentiate between three concepts.

Very innovative and educational in approach to conducting research.

I am very impressed with all these terminology, as I am a fresh student for post graduate, I am highly guided and I promised to continue making consultation when the need arise. Thanks a lot.

A very helpful piece. thanks, I really appreciate it .

Very well explained, and it might be helpful to many people like me.

Wish i had found this (and other) resource(s) at the beginning of my PhD journey… not in my writing up year… 😩 Anyways… just a quick question as i’m having some issues ordering my “golden thread”…. does it matter in what order you mention them? i.e., is it always first aims, then objectives, and finally the questions? or can you first mention the research questions and then the aims and objectives?

Thank you for a very simple explanation that builds upon the concepts in a very logical manner. Just prior to this, I read the research hypothesis article, which was equally very good. This met my primary objective.

My secondary objective was to understand the difference between research questions and research hypothesis, and in which context to use which one. However, I am still not clear on this. Can you kindly please guide?

In research, a research question is a clear and specific inquiry that the researcher wants to answer, while a research hypothesis is a tentative statement or prediction about the relationship between variables or the expected outcome of the study. Research questions are broader and guide the overall study, while hypotheses are specific and testable statements used in quantitative research. Research questions identify the problem, while hypotheses provide a focus for testing in the study.

Exactly what I need in this research journey, I look forward to more of your coaching videos.

This helped a lot. Thanks so much for the effort put into explaining it.

What data source in writing dissertation/Thesis requires?

What is data source covers when writing dessertation/thesis

This is quite useful thanks

I’m excited and thankful. I got so much value which will help me progress in my thesis.

where are the locations of the reserch statement, research objective and research question in a reserach paper? Can you write an ouline that defines their places in the researh paper?

Very helpful and important tips on Aims, Objectives and Questions.

Thank you so much for making research aim, research objectives and research question so clear. This will be helpful to me as i continue with my thesis.

Thanks much for this content. I learned a lot. And I am inspired to learn more. I am still struggling with my preparation for dissertation outline/proposal. But I consistently follow contents and tutorials and the new FB of GRAD Coach. Hope to really become confident in writing my dissertation and successfully defend it.

As a researcher and lecturer, I find splitting research goals into research aims, objectives, and questions is unnecessarily bureaucratic and confusing for students. For most biomedical research projects, including ‘real research’, 1-3 research questions will suffice (numbers may differ by discipline).

Awesome! Very important resources and presented in an informative way to easily understand the golden thread. Indeed, thank you so much.

Well explained

The blog article on research aims, objectives, and questions by Grad Coach is a clear and insightful guide that aligns with my experiences in academic research. The article effectively breaks down the often complex concepts of research aims and objectives, providing a straightforward and accessible explanation. Drawing from my own research endeavors, I appreciate the practical tips offered, such as the need for specificity and clarity when formulating research questions. The article serves as a valuable resource for students and researchers, offering a concise roadmap for crafting well-defined research goals and objectives. Whether you’re a novice or an experienced researcher, this article provides practical insights that contribute to the foundational aspects of a successful research endeavor.

A great thanks for you. it is really amazing explanation. I grasp a lot and one step up to research knowledge.

I really found these tips helpful. Thank you very much Grad Coach.

I found this article helpful. Thanks for sharing this.

thank you so much, the explanation and examples are really helpful

This is a well researched and superbly written article for learners of research methods at all levels in the research topic from conceptualization to research findings and conclusions. I highly recommend this material to university graduate students. As an instructor of advanced research methods for PhD students, I have confirmed that I was giving the right guidelines for the degree they are undertaking.

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Matthew DeCarlo

Chapter Outline

• Empirical vs. ethical questions (4 minute read)
• Characteristics of a good research question (4 minute read)
• Quantitative research questions (7 minute read)
• Qualitative research questions (3 minute read)
• Evaluating and updating your research questions (4 minute read)

Content warning: examples in this chapter include references to sexual violence, sexism, substance use disorders, homelessness, domestic violence, the child welfare system, cissexism and heterosexism, and truancy and school discipline.

9.1 Empirical vs. ethical questions

Learning objectives.

Learners will be able to…

• Define empirical questions and provide an example
• Define ethical questions and provide an example

Writing a good research question is an art and a science. It is a science because you have to make sure it is clear, concise, and well-developed. It is an art because often your language needs “wordsmithing” to perfect and clarify the meaning. This is an exciting part of the research process; however, it can also be one of the most stressful.

Creating a good research question begins by identifying a topic you are interested in studying. At this point, you already have a working question. You’ve been applying it to the exercises in each chapter, and after reading more about your topic in the scholarly literature, you’ve probably gone back and revised your working question a few times. We’re going to continue that process in more detail in this chapter. Keep in mind that writing research questions is an iterative process, with revisions happening week after week until you are ready to start your project.

Empirical vs. ethical questions

When it comes to research questions, social science is best equipped to answer empirical questions —those that can be answered by real experience in the real world—as opposed to  ethical questions —questions about which people have moral opinions and that may not be answerable in reference to the real world. While social workers have explicit ethical obligations (e.g., service, social justice), research projects ask empirical questions to help actualize and support the work of upholding those ethical principles.

In order to help you better understand the difference between ethical and empirical questions, let’s consider a topic about which people have moral opinions. How about SpongeBob SquarePants? [1] In early 2005, members of the conservative Christian group Focus on the Family (2005) [2] denounced this seemingly innocuous cartoon character as “morally offensive” because they perceived his character to be one that promotes a “pro-gay agenda.” Focus on the Family supported their claim that SpongeBob is immoral by citing his appearance in a children’s video designed to promote tolerance of all family forms (BBC News, 2005). [3] They also cited SpongeBob’s regular hand-holding with his male sidekick Patrick as further evidence of his immorality.

So, can we now conclude that SpongeBob SquarePants is immoral? Not so fast. While your mother or a newspaper or television reporter may provide an answer, a social science researcher cannot. Questions of morality are ethical, not empirical. Of course, this doesn’t mean that social science researchers cannot study opinions about or social meanings surrounding SpongeBob SquarePants (Carter, 2010). [4] We study humans after all, and as you will discover in the following chapters of this textbook, we are trained to utilize a variety of scientific data-collection techniques to understand patterns of human beliefs and behaviors. Using these techniques, we could find out how many people in the United States find SpongeBob morally reprehensible, but we could never learn, empirically, whether SpongeBob is in fact morally reprehensible.

Let’s consider an example from a recent MSW research class I taught. A student group wanted to research the penalties for sexual assault. Their original research question was: “How can prison sentences for sexual assault be so much lower than the penalty for drug possession?” Outside of the research context, that is a darn good question! It speaks to how the War on Drugs and the patriarchy have distorted the criminal justice system towards policing of drug crimes over gender-based violence.

Unfortunately, it is an ethical question, not an empirical one. To answer that question, you would have to draw on philosophy and morality, answering what it is about human nature and society that allows such unjust outcomes. However, you could not answer that question by gathering data about people in the real world. If I asked people that question, they would likely give me their opinions about drugs, gender-based violence, and the criminal justice system. But I wouldn’t get the real answer about why our society tolerates such an imbalance in punishment.

As the students worked on the project through the semester, they continued to focus on the topic of sexual assault in the criminal justice system. Their research question became more empirical because they read more empirical articles about their topic. One option that they considered was to evaluate intervention programs for perpetrators of sexual assault to see if they reduced the likelihood of committing sexual assault again. Another option they considered was seeing if counties or states with higher than average jail sentences for sexual assault perpetrators had lower rates of re-offense for sexual assault. These projects addressed the ethical question of punishing perpetrators of sexual violence but did so in a way that gathered and analyzed empirical real-world data. Our job as social work researchers is to gather social facts about social work issues, not to judge or determine morality.

Key Takeaways

• Empirical questions are distinct from ethical questions.
• There are usually a number of ethical questions and a number of empirical questions that could be asked about any single topic.
• While social workers may research topics about which people have moral opinions, a researcher’s job is to gather and analyze empirical data.
• Take a look at your working question. Make sure you have an empirical question, not an ethical one. To perform this check, describe how you could find an answer to your question by conducting a study, like a survey or focus group, with real people.

9.2 Characteristics of a good research question

• Identify and explain the key features of a good research question
• Explain why it is important for social workers to be focused and clear with the language they use in their research questions

Now that you’ve made sure your working question is empirical, you need to revise that working question into a formal research question. So, what makes a good research question? First, it is generally written in the form of a question. To say that your research question is “the opioid epidemic” or “animal assisted therapy” or “oppression” would not be correct. You need to frame your topic as a question, not a statement. A good research question is also one that is well-focused. A well-focused question helps you tune out irrelevant information and not try to answer everything about the world all at once. You could be the most eloquent writer in your class, or even in the world, but if the research question about which you are writing is unclear, your work will ultimately lack direction.

In addition to being written in the form of a question and being well-focused, a good research question is one that cannot be answered with a simple yes or no. For example, if your interest is in gender norms, you could ask, “Does gender affect a person’s performance of household tasks?” but you will have nothing left to say once you discover your yes or no answer. Instead, why not ask, about the relationship between gender and household tasks. Alternatively, maybe we are interested in how or to what extent gender affects a person’s contributions to housework in a marriage? By tweaking your question in this small way, you suddenly have a much more fascinating question and more to say as you attempt to answer it.

A good research question should also have more than one plausible answer. In the example above, the student who studied the relationship between gender and household tasks had a specific interest in the impact of gender, but she also knew that preferences might be impacted by other factors. For example, she knew from her own experience that her more traditional and socially conservative friends were more likely to see household tasks as part of the female domain, and were less likely to expect their male partners to contribute to those tasks. Thinking through the possible relationships between gender, culture, and household tasks led that student to realize that there were many plausible answers to her questions about how  gender affects a person’s contribution to household tasks. Because gender doesn’t exist in a vacuum, she wisely felt that she needed to consider other characteristics that work together with gender to shape people’s behaviors, likes, and dislikes. By doing this, the student considered the third feature of a good research question–she thought about relationships between several concepts. While she began with an interest in a single concept—household tasks—by asking herself what other concepts (such as gender or political orientation) might be related to her original interest, she was able to form a question that considered the relationships  among  those concepts.

This student had one final component to consider. Social work research questions must contain a target population. Her study would be very different if she were to conduct it on older adults or immigrants who just arrived in a new country. The target population is the group of people whose needs your study addresses. Maybe the student noticed issues with household tasks as part of her social work practice with first-generation immigrants, and so she made it her target population. Maybe she wants to address the needs of another community. Whatever the case, the target population should be chosen while keeping in mind social work’s responsibility to work on behalf of marginalized and oppressed groups.

In sum, a good research question generally has the following features:

• It is written in the form of a question
• It is clearly written
• It cannot be answered with “yes” or “no”
• It has more than one plausible answer
• It considers relationships among multiple variables
• It is specific and clear about the concepts it addresses
• It includes a target population
• A poorly focused research question can lead to the demise of an otherwise well-executed study.
• Research questions should be clearly worded, consider relationships between multiple variables, have more than one plausible answer, and address the needs of a target population.

Okay, it’s time to write out your first draft of a research question.

• Once you’ve done so, take a look at the checklist in this chapter and see if your research question meets the criteria to be a good one.

Brainstorm whether your research question might be better suited to quantitative or qualitative methods.

• Describe why your question fits better with quantitative or qualitative methods.
• Provide an alternative research question that fits with the other type of research method.

9.3 Quantitative research questions

• Describe how research questions for exploratory, descriptive, and explanatory quantitative questions differ and how to phrase them
• Identify the differences between and provide examples of strong and weak explanatory research questions

Quantitative descriptive questions

The type of research you are conducting will impact the research question that you ask. Probably the easiest questions to think of are quantitative descriptive questions. For example, “What is the average student debt load of MSW students?” is a descriptive question—and an important one. We aren’t trying to build a causal relationship here. We’re simply trying to describe how much debt MSW students carry. Quantitative descriptive questions like this one are helpful in social work practice as part of community scans, in which human service agencies survey the various needs of the community they serve. If the scan reveals that the community requires more services related to housing, child care, or day treatment for people with disabilities, a nonprofit office can use the community scan to create new programs that meet a defined community need.

Quantitative descriptive questions will often ask for percentage, count the number of instances of a phenomenon, or determine an average. Descriptive questions may only include one variable, such as ours about student debt load, or they may include multiple variables. Because these are descriptive questions, our purpose is not to investigate causal relationships between variables. To do that, we need to use a quantitative explanatory question.

Quantitative explanatory questions

Most studies you read in the academic literature will be quantitative and explanatory. Why is that? If you recall from Chapter 2 , explanatory research tries to build nomothetic causal relationships. They are generalizable across space and time, so they are applicable to a wide audience. The editorial board of a journal wants to make sure their content will be useful to as many people as possible, so it’s not surprising that quantitative research dominates the academic literature.

Structurally, quantitative explanatory questions must contain an independent variable and dependent variable. Questions should ask about the relationship between these variables. The standard format I was taught in graduate school for an explanatory quantitative research question is: “What is the relationship between [independent variable] and [dependent variable] for [target population]?” You should play with the wording for your research question, revising that standard format to match what you really want to know about your topic.

Let’s take a look at a few more examples of possible research questions and consider the relative strengths and weaknesses of each. Table 9.1 does just that. While reading the table, keep in mind that I have only noted what I view to be the most relevant strengths and weaknesses of each question. Certainly each question may have additional strengths and weaknesses not noted in the table. Each of these questions is drawn from student projects in my research methods classes and reflects the work of many students on their research question over many weeks.

Making it more specific

A good research question should also be specific and clear about the concepts it addresses. A student investigating gender and household tasks knows what they mean by “household tasks.” You likely also have an impression of what “household tasks” means. But are your definition and the student’s definition the same? A participant in their study may think that managing finances and performing home maintenance are household tasks, but the researcher may be interested in other tasks like childcare or cleaning. The only way to ensure your study stays focused and clear is to be specific about what you mean by a concept. The student in our example could pick a specific household task that was interesting to them or that the literature indicated was important—for example, childcare. Or, the student could have a broader view of household tasks, one that encompasses childcare, food preparation, financial management, home repair, and care for relatives. Any option is probably okay, as long as the researcher is clear on what they mean by “household tasks.” Clarifying these distinctions is important as we look ahead to specifying how your variables will be measured in Chapter 11 .

Table 9.2 contains some “watch words” that indicate you may need to be more specific about the concepts in your research question.

It can be challenging to be this specific in social work research, particularly when you are just starting out your project and still reading the literature. If you’ve only read one or two articles on your topic, it can be hard to know what you are interested in studying. Broad questions like “What are the causes of chronic homelessness, and what can be done to prevent it?” are common at the beginning stages of a research project as working questions. However, moving from working questions to research questions in your research proposal requires that you examine the literature on the topic and refine your question over time to be more specific and clear. Perhaps you want to study the effect of a specific anti-homelessness program that you found in the literature. Maybe there is a particular model to fighting homelessness, like Housing First or transitional housing, that you want to investigate further. You may want to focus on a potential cause of homelessness such as LGBTQ+ discrimination that you find interesting or relevant to your practice. As you can see, the possibilities for making your question more specific are almost infinite.

Quantitative exploratory questions

In exploratory research, the researcher doesn’t quite know the lay of the land yet. If someone is proposing to conduct an exploratory quantitative project, the watch words highlighted in Table 9.2 are not problematic at all. In fact, questions such as “What factors influence the removal of children in child welfare cases?” are good because they will explore a variety of factors or causes. In this question, the independent variable is less clearly written, but the dependent variable, family preservation outcomes, is quite clearly written. The inverse can also be true. If we were to ask, “What outcomes are associated with family preservation services in child welfare?”, we would have a clear independent variable, family preservation services, but an unclear dependent variable, outcomes. Because we are only conducting exploratory research on a topic, we may not have an idea of what concepts may comprise our “outcomes” or “factors.” Only after interacting with our participants will we be able to understand which concepts are important.

Remember that exploratory research is appropriate only when the researcher does not know much about topic because there is very little scholarly research. In our examples above, there is extensive literature on the outcomes in family reunification programs and risk factors for child removal in child welfare. Make sure you’ve done a thorough literature review to ensure there is little relevant research to guide you towards a more explanatory question.

• Descriptive quantitative research questions are helpful for community scans but cannot investigate causal relationships between variables.
• Explanatory quantitative research questions must include an independent and dependent variable.
• Exploratory quantitative research questions should only be considered when there is very little previous research on your topic.
• Identify the type of research you are engaged in (descriptive, explanatory, or exploratory).
• Create a quantitative research question for your project that matches with the type of research you are engaged in.

Preferably, you should be creating an explanatory research question for quantitative research.

9.4 Qualitative research questions

• List the key terms associated with qualitative research questions
• Distinguish between qualitative and quantitative research questions

Qualitative research questions differ from quantitative research questions. Because qualitative research questions seek to explore or describe phenomena, not provide a neat nomothetic explanation, they are often more general and openly worded. They may include only one concept, though many include more than one. Instead of asking how one variable causes changes in another, we are instead trying to understand the experiences ,  understandings , and  meanings that people have about the concepts in our research question. These keywords often make an appearance in qualitative research questions.

Let’s work through an example from our last section. In Table 9.1, a student asked, “What is the relationship between sexual orientation or gender identity and homelessness for late adolescents in foster care?” In this question, it is pretty clear that the student believes that adolescents in foster care who identify as LGBTQ+ may be at greater risk for homelessness. This is a nomothetic causal relationship—LGBTQ+ status causes changes in homelessness.

However, what if the student were less interested in  predicting  homelessness based on LGBTQ+ status and more interested in  understanding  the stories of foster care youth who identify as LGBTQ+ and may be at risk for homelessness? In that case, the researcher would be building an idiographic causal explanation . The youths whom the researcher interviews may share stories of how their foster families, caseworkers, and others treated them. They may share stories about how they thought of their own sexuality or gender identity and how it changed over time. They may have different ideas about what it means to transition out of foster care.

Because qualitative questions usually center on idiographic causal relationships, they look different than quantitative questions. Table 9.3 below takes the final research questions from Table 9.1 and adapts them for qualitative research. The guidelines for research questions previously described in this chapter still apply, but there are some new elements to qualitative research questions that are not present in quantitative questions.

• Qualitative research questions often ask about lived experience, personal experience, understanding, meaning, and stories.
• Qualitative research questions may be more general and less specific.
• Qualitative research questions may also contain only one variable, rather than asking about relationships between multiple variables.

Qualitative research questions have one final feature that distinguishes them from quantitative research questions: they can change over the course of a study. Qualitative research is a reflexive process, one in which the researcher adapts their approach based on what participants say and do. The researcher must constantly evaluate whether their question is important and relevant to the participants. As the researcher gains information from participants, it is normal for the focus of the inquiry to shift.

For example, a qualitative researcher may want to study how a new truancy rule impacts youth at risk of expulsion. However, after interviewing some of the youth in their community, a researcher might find that the rule is actually irrelevant to their behavior and thoughts. Instead, their participants will direct the discussion to their frustration with the school administrators or the lack of job opportunities in the area. This is a natural part of qualitative research, and it is normal for research questions and hypothesis to evolve based on information gleaned from participants.

However, this reflexivity and openness unacceptable in quantitative research for good reasons. Researchers using quantitative methods are testing a hypothesis, and if they could revise that hypothesis to match what they found, they could never be wrong! Indeed, an important component of open science and reproducability is the preregistration of a researcher’s hypotheses and data analysis plan in a central repository that can be verified and replicated by reviewers and other researchers. This interactive graphic from 538 shows how an unscrupulous research could come up with a hypothesis and theoretical explanation  after collecting data by hunting for a combination of factors that results in a statistically significant relationship. This is an excellent example of how the positivist assumptions behind quantitative research and intepretivist assumptions behind qualitative research result in different approaches to social science.

• Qualitative research questions often contain words or phrases like “lived experience,” “personal experience,” “understanding,” “meaning,” and “stories.”
• Qualitative research questions can change and evolve over the course of the study.
• Using the guidance in this chapter, write a qualitative research question. You may want to use some of the keywords mentioned above.

9.5 Evaluating and updating your research questions

• Evaluate the feasibility and importance of your research questions
• Begin to match your research questions to specific designs that determine what the participants in your study will do

Feasibility and importance

As you are getting ready to finalize your research question and move into designing your research study, it is important to check whether your research question is feasible for you to answer and what importance your results will have in the community, among your participants, and in the scientific literature

Key questions to consider when evaluating your question’s feasibility include:

• Do you have access to the data you need?
• Will you be able to get consent from stakeholders, gatekeepers, and others?
• Does your project pose risk to individuals through direct harm, dual relationships, or breaches in confidentiality? (see Chapter 6 for more ethical considerations)
• Are you competent enough to complete the study?
• Do you have the resources and time needed to carry out the project?

Key questions to consider when evaluating the importance of your question include:

• Can we answer your research question simply by looking at the literature on your topic?
• How does your question add something new to the scholarly literature? (raises a new issue, addresses a controversy, studies a new population, etc.)
• How will your target population benefit, once you answer your research question?
• How will the community, social work practice, and the broader social world benefit, once you answer your research question?
• Using the questions above, check whether you think your project is feasible for you to complete, given the constrains that student projects face.
• Realistically, explore the potential impact of your project on the community and in the scientific literature. Make sure your question cannot be answered by simply reading more about your topic.

Matching your research question and study design

This chapter described how to create a good quantitative and qualitative research question. In Parts 3 and 4 of this textbook, we will detail some of the basic designs like surveys and interviews that social scientists use to answer their research questions. But which design should you choose?

As with most things, it all depends on your research question. If your research question involves, for example, testing a new intervention, you will likely want to use an experimental design. On the other hand, if you want to know the lived experience of people in a public housing building, you probably want to use an interview or focus group design.

We will learn more about each one of these designs in the remainder of this textbook. We will also learn about using data that already exists, studying an individual client inside clinical practice, and evaluating programs, which are other examples of designs. Below is a list of designs we will cover in this textbook:

• Surveys: online, phone, mail, in-person
• Experiments: classic, pre-experiments, quasi-experiments
• Interviews: in-person or via phone or videoconference
• Focus groups: in-person or via videoconference
• Content analysis of existing data
• Secondary data analysis of another researcher’s data
• Program evaluation

The design of your research study determines what you and your participants will do. In an experiment, for example, the researcher will introduce a stimulus or treatment to participants and measure their responses. In contrast, a content analysis may not have participants at all, and the researcher may simply read the marketing materials for a corporation or look at a politician’s speeches to conduct the data analysis for the study.

I imagine that a content analysis probably seems easier to accomplish than an experiment. However, as a researcher, you have to choose a research design that makes sense for your question and that is feasible to complete with the resources you have. All research projects require some resources to accomplish. Make sure your design is one you can carry out with the resources (time, money, staff, etc.) that you have.

There are so many different designs that exist in the social science literature that it would be impossible to include them all in this textbook. The purpose of the subsequent chapters is to help you understand the basic designs upon which these more advanced designs are built. As you learn more about research design, you will likely find yourself revising your research question to make sure it fits with the design. At the same time, your research question as it exists now should influence the design you end up choosing. There is no set order in which these should happen. Instead, your research project should be guided by whether you can feasibly carry it out and contribute new and important knowledge to the world.

• Research questions must be feasible and important.
• Research questions must match study design.
• Based on what you know about designs like surveys, experiments, and interviews, describe how you might use one of them to answer your research question.
• You may want to refer back to Chapter 2 which discusses how to get raw data about your topic and the common designs used in student research projects.
• Not familiar with SpongeBob SquarePants? You can learn more about him on Nickelodeon’s site dedicated to all things SpongeBob:  http://www.nick.com/spongebob-squarepants/ ↵
• Focus on the Family. (2005, January 26). Focus on SpongeBob.  Christianity Today . Retrieved from  http://www.christianitytoday.com/ct/2005/januaryweb-only/34.0c.html ↵
• BBC News. (2005, January 20). US right attacks SpongeBob video. Retrieved from:  http://news.bbc.co.uk/2/hi/americas/4190699.stm ↵
• In fact, an MA thesis examines representations of gender and relationships in the cartoon: Carter, A. C. (2010).  Constructing gender and   relationships in “SpongeBob SquarePants”: Who lives in a pineapple under the sea . MA thesis, Department of Communication, University of South Alabama, Mobile, AL. ↵
• Writing from an outline (10 minute read plus an 8 minute video, and then a 15 minute video)
• Writing your literature review (30 minute read)

Content warning: TBA

6.1: Writing from an outline

Learners will be able to...

• Integrate facts from the literature into scholarly writing
• Experiment with different approaches to integrating information that do not involve direct quotations from other authors

Congratulations! By now, you should have discovered, retrieved, evaluated, synthesized, and organized the information you need for your literature review. It’s now time to turn that stack of articles, papers, and notes into a literature review–it’s time to start writing!

The first step in research writing is outlining. In Chapter 4, we reviewed how to build a topical outline using quotations and facts from other authors. Use that outline (or one you write now) as a way to organize your thoughts.

Watch this video from Nicholas Cifuentes-Goodbody on Outlining . As he highlights, outlining is like building a mise en place before a meal--arranging your ingredients in an orderly way so you can create your masterpiece.

From quotations to original writing

Much like combining ingredients on a kitchen countertop, you will need to mix your ingredients together. That means you will not be relying extensively on quotations from other authors in your literature review. In moving from an outline to a literature review, the key intellectual move is relying on your own ideas about the literature, rather than quoting extensively from other sources.

Integrating ideas from other authors

Watch this video from Nicholas Cifuentes-Goodbody on using quotations in academic writing . In the video, he reviews a few different techniques to integrate quotations or ideas from other authors into your writing. All literature reviews use the ideas from other authors, but it's important not to overuse others' words. Your literature review is evaluated by your professor based on how well it shows  you are able to make connections between different facts in the scientific literature. The examples in this section should highlight how to get other people's words out of the way of your own. Use these strategies to diversify your writing and show your readers how your sources contributed to your work.

1. Make a claim without a quote

Claim ( Citation )

Some view cities as the storehouse of culture and creativity, and propose that urbanization is a consequence of the attractiveness of these social benefits ( Mumford, 1961 ).

More information

Oftentimes you do not need to directly quote a source to convey its conclusions or arguments – and some disciplines discourage quoting directly! Rather you can paraphrase the main point of a paper in your own words and provide an in-text citation. A benefit of using this strategy is that you can offer support for a claim without using a whole paragraph to introduce and frame a quote. You should make sure that you fully understand the paper's argument and that you are following university citation guidelines before attempting to paraphrase something from a paper.

2. Make a claim that is supported by two or more sources:

Claim ( Citation 1 ; Citation 2 ).

Reviews of this literature concede difficulty in making direct comparisons of emission levels across different sets of analysis ( Bader and Bleischwitz, 2009 ; Kennedy et al., 2009 ; Ramaswami et al., 2012 ).

Sometimes multiple sources support your claim, or there are two major publications that deserve credit for providing evidence on a topic. This is a perfect time to use multiple citations. You can cite two, three, or more sources in a single sentence!

Make a claim that has been supported in multiple contexts:

Context 1 ( Citation ), Context 2 ( Citation ), Context 3 ( Citation ).

These results are supported by more recent research on transportation energy consumption ( Liddle, 2014 ), electricity consumption in buildings ( Lariviere and Lafrance, 1999 ), and overall urban GHG emissions ( Marcotullio et al., 2013b ).

More information:

Use this citation strategy when you want to show that a body of research has found support for some claim across several different contexts. This can show the robustness of an effect or phenomenon and can give your claim some added validity

3. Quote important or unique terms

Claim " Term " ( Citation ).

The spatial implications of this thinking are manifest in the " concentric ring model " of urban expansion and its variants ( Harris and Ullman, 1945 ).

While block or even whole-sentence citations are rare in most research papers in the science and social science disciplines, there is often a need to quote specific terms or phrases that were first coined by a certain source or that were well-explained in a specific paper.

4. Quoting definitions

Contextualize quote , " important word or phrase ."

Role conflict is defined as "A situation in which contradictory, competing, or incompatible expectations are placed on an individual by two or more roles held at the same time" (Open Sociology Dictionary, 2023); whereas, role strain is defined as "a situation caused by higher-than-expected demands placed on an individual performing a specific role that leads to difficulty or stress" (Open Sociology Dictionary, 2023). In our study, we hypothesize that caregivers who reenter higher education experience role conflict between school work, paid work, and care work. Further, we hypothesize that this conflict is greater in individuals who had experienced role strain in employment or caregiving prior to entering college.

A direct quotation can bring attention to specific language in your source. When someone puts something perfectly, you can use a quotation to convey the identical meaning in your work. Definitions are an excellent example of when to use a quotation. In other cases, there may be quotations from important thinkers, clients or community members, and others whose specific wording is important.

I encourage you to use few, if any, direct quotations in your literature review. Personally, I think most students are scared of looking stupid and would rather use a good quotation than risk not getting it right. If you are a student who considers themselves a strong writer, this may not sound relevant to you. However, I'm willing to bet that there are many of your peers for whom this describes a particular bit of research anxiety.

When using quotations, make sure to only include the parts of the quotation that are necessary. You do not need to use quotation marks for statistics you use. And I encourage you to find ways to put others' statistics in  your sentences.

Why share information from other sources?

Now that you know some different sentence structures using APA citations, let's examine the purpose behind why you are sharing information from another source. Cited evidence can serve a wide range of purposes in academic papers. These examples will give you an idea of the different ways that you can use citations in your paper.

1. Summarize your source

The studies of Newman and Kenworthy ( 1989, 1999 ) demonstrate a negative relationship between population density and transportation fuel use .

You will help your reader understand your points better if you summarize the key points of a study. Describe the strengths or weaknesses a specific source that has been pivotal in your field. Describe the source's specific methodology, theory, or approach. Be sure to still include a citation. If you mention the name of the author in your text, you still need to provide the date of the study in a parenthetical citation.

2. Cite a method

Despite the popularity of the WUP indicators , they have been routinely criticized because the methodology relies on local- and country-specific definitions of bounding urban areas, resulting in of ten incomparable and widely divergent definitions of the population, density thresholds, or administrative/political units designated ( Satterthwaite, 2007 ).

This is an easy way to give credit to a source that has provided some evidence for the validity of a method or questionnaire. Readers can reference your citation if they are interested in knowing more about the method and its standing in the current literature.

3. Compare sources

Some evidence for this scaling relationship suggests that urban areas with larger population sizes have proportionally smaller energy infrastructures than smaller cities ( Bettencourt et al., 2007 ; Fragkias et al., 2013 ). Other evidence suggests that GHG emissions may increase more than proportionally to population size, such that larger cities exhibit proportionally higher energy demand as they grow than do smaller cities ( Marcotullio et al., 2013 ).

This is one of the most important techniques for creating an effective literature review. This allows you and your readers to consider controversies and discrepancies among the current literature, revealing gaps in the literature or points of contention for further study.

The examples in this guide come from:

Marcotullio, P. J., Hughes, S., Sarzynski, A., Pincetl, S., Sanchez Peña, L., Romero-Lankao, P., Runfola, D. and Seto, K. C. (2014), Urbanization and the carbon cycle: Contributions from social science. Earth's Future, 2: 496–514. doi:10.1002/2014EF000257

Avoiding plagiarism

The most difficult thing about avoiding plagiarism is that reading so much of other people's ideas can make them seem like your own after a while. We recommend you work through this interactive activity on determining how and when to cite other authors.

• Research writing requires outlining, which helps you arrange your facts neatly before writing. It's similar to arranging all of your ingredients before you start cooking.
• Eliminate quotations from your writing as much as possible. Your literature review needs to be your analysis of the literature, not just a summary of other people's good ideas.
• Experiment with the prompts in this chapter as you begin to write your research question. 

6.2 Writing your literature review

• Describe the components of a literature review
• Begin to write your literature review
• Identify the purpose of a problem statement
• Apply the components of a formal argument to your topic
• Use elements of formal writing style, including signposting and transitions
• Recognize commons errors in literature reviews

Writing about research is different than other types of writing. Research writing is not like a journal entry or opinion paper. The goal here is not to apply your research question to your life or growth as a practitioner. Research writing is about the provision and interpretation of facts. The tone should be objective and unbiased, and personal experiences and opinions are excluded. Particularly for students who are used to writing case notes, research writing can be a challenge. That's why its important to normalize getting help! If your professor has not built in peer review, consider setting up a peer review group among your peers. You should also reach out to your academic advisor to see if there are writing services on your campus available to graduate students. No one should feel bad for needing help with something they haven't done before, haven't done in a while, or were never taught how to do. 

If you’ve followed the steps in this chapter, you likely have an outline, summary table, and concept map from which you can begin the writing process. But what do you need to include in your literature review? We’ve mentioned it before, but to summarize, a literature review should:

• Introduce the topic and define its key terms.
• Establish the importance of the topic.
• Provide an overview of the important literature related to the concepts found in the research question.
• Identify gaps or controversies in the literature.
• Point out consistent findings across studies.
• Synthesize that which is known about a topic, rather than just provide a summary of the articles you read.
• Discuss possible implications and directions for future research.

Do you have enough facts and sources to accomplish these tasks? It’s a good time to consult your outlines and notes on each article you plan to include in your literature review. You may also want to consult with your professor on what is expected of you. If there is something you are missing, you may want to jump back to section 2.3 where we discussed how to search for literature. While you can always fill in material, there is the danger that you will start writing without really knowing what you are talking about or what you want to say. For example, if you don’t have a solid definition of your key concepts or a sense of how the literature has developed over time, it will be difficult to make coherent scholarly claims about your topic.

There is no magical point at which one is ready to write. As you consider whether you are ready, it may be useful to ask yourself these questions:

• How will my literature review be organized?
• What section headings will I be using?
• How do the various studies relate to each other?
• What contributions do they make to the field?
• Where are the gaps or limitations in existing research?
• And finally, but most importantly, how does my own research fit into what has already been done?

The problem statement

Scholarly works often begin with a problem statement, which serves two functions. First, it establishes why your topic is a social problem worth studying. Second, it pulls your reader into the literature review. Who would want to read about something unimportant?

A problem statement generally answers the following questions, though these are far from exhaustive:

• Why is this an important problem to study?
• How many people are affected by this problem?
• How does this problem impact other social issues relevant to social work?
• Why is your target population an important one to study?

A strong problem statement, like the rest of your literature review, should be filled with empirical results, theory, and arguments based on the extant literature. A research proposal differs significantly from other more reflective essays you’ve likely completed during your social work studies. If your topic were domestic violence in rural Appalachia, I’m sure you could come up with answers to the above questions without looking at a single source. However, the purpose of the literature review is not to test your intuition, personal experience, or empathy. Instead, research methods are about gaining specific and articulable knowledge to inform action. With a problem statement, you can take a “boring” topic like the color of rooms used in an inpatient psychiatric facility, transportation patterns in major cities, or the materials used to manufacture baby bottles, and help others see the topic as you see it—an important part of the social world that impacts social work practice.

The structure of a literature review

In general, the problem statement belongs at the beginning of the literature review. We usually advise students to spend no more than a paragraph or two for a problem statement. For the rest of your literature review, there is no set formula by which it needs to be organized. However, a literature review generally follows the format of any other essay—Introduction, Body, and Conclusion.

The introduction to the literature review contains a statement or statements about the overall topic. At a minimum, the introduction should define or identify the general topic, issue, or area of concern. You might consider presenting historical background, mentioning the results of a seminal study, and providing definitions of important terms. The introduction may also point to overall trends in what has been previously published on the topic or on conflicts in theory, methodology, evidence, conclusions, or gaps in research and scholarship. We also suggest putting in a few sentences that walk the reader through the rest of the literature review. Highlight your main arguments from the body of the literature review and preview your conclusion. An introduction should let the reader know what to expect from the rest of your review.

The body of your literature review is where you demonstrate your synthesis and analysis of the literature. Again, do not just summarize the literature. We would also caution against organizing your literature review by source—that is, one paragraph for source A, one paragraph for source B, etc. That structure will likely provide an adequate summary of the literature you’ve found, but it would give you almost no synthesis of the literature. That approach doesn’t tell your reader how to put those facts together, it doesn't highlight points of agreement or contention, or how each study builds on the work of others. In short, it does not demonstrate critical thinking.

Organize your review by argument

Instead, use your outlines and notes as a guide what you have to say about the important topics you need to cover. Literature reviews are written from the perspective of an expert in that field. After an exhaustive literature review, you should feel as though you are able to make strong claims about what is true—so make them! There is no need to hide behind “I believe” or “I think.” Put your voice out in front, loud and proud! But make sure you have facts and sources that back up your claims.

I’ve used the term “ argument ” here in a specific way. An argument in writing means more than simply disagreeing with what someone else said, as this classic Monty Python sketch demonstrates. Toulman, Rieke, and Janik (1984) identify six elements of an argument:

• Claim: the thesis statement—what you are trying to prove
• Grounds: theoretical or empirical evidence that supports your claim
• Warrant: your reasoning (rule or principle) connecting the claim and its grounds
• Backing: further facts used to support or legitimize the warrant
• Qualifier: acknowledging that the argument may not be true for all cases
• Rebuttal: considering both sides (as cited in Burnette, 2012) [1]

Let’s walk through an example. If I were writing a literature review on a negative income tax, a policy in which people in poverty receive an unconditional cash stipend from the government each month equal to the federal poverty level, I would want to lay out the following:

• Claim: the negative income tax is superior to other forms of anti-poverty assistance.
• Grounds: data comparing negative income tax recipients to people receiving anti-poverty assistance in existing programs, theory supporting a negative income tax, data from evaluations of existing anti-poverty programs, etc.
• Warrant: cash-based programs like the negative income tax are superior to existing anti-poverty programs because they allow the recipient greater self-determination over how to spend their money.
• Backing: data demonstrating the beneficial effects of self-determination on people in poverty.
• Qualifier: the negative income tax does not provide taxpayers and voters with enough control to make sure people in poverty are not wasting financial assistance on frivolous items.
• Rebuttal: policy should be about empowering the oppressed, not protecting the taxpayer, and there are ways of addressing taxpayer spending concerns through policy design.

Like any effective argument, your literature review must have some kind of structure. For example, it might begin by describing a phenomenon in a general way along with several studies that provide some detail, then describing two or more competing theories of the phenomenon, and finally presenting a hypothesis to test one or more of the theories. Or, it might describe one phenomenon, then describe another that seems inconsistent with the first, then propose a theory that resolves the inconsistency, and finally present a hypothesis to test that theory. In applied research, it might describe a phenomenon or theory, then describe how that phenomenon or theory applies to some important real-world situation, and finally, may suggest a way to test whether it does, in fact, apply to that situation.

Use signposts

Another important issue is  signposting . It may not be a term you are familiar with, but you are likely familiar with the concept. Signposting refers to the words used to identify the organization and structure of your literature review to your reader. The most basic form of signposting is using a topic sentence at the beginning of each paragraph. A topic sentence introduces the argument you plan to make in that paragraph. For example, you might start a paragraph stating, “There is strong disagreement in the literature as to whether psychedelic drugs cause people to develop psychotic disorders, or whether psychotic disorders cause people to use psychedelic drugs.” Within that paragraph, your reader would likely assume you will present evidence for both arguments. The concluding sentence of your paragraph should address the topic sentence, discussing how the facts and arguments from the paragraph you've written support a specific conclusion. To continue with our example, I might say, “There is likely a reciprocal effect in which both the use of psychedelic drugs worsens pre-psychotic symptoms and worsening psychosis increases the desire to use psychedelic drugs.”

Signposting also involves using headings and subheadings. Your literature review will use APA formatting, which means you need to follow their rules for bolding, capitalization, italicization, and indentation of headings. Headings help your reader understand the structure of your literature review. They can also help if the reader gets lost and needs to re-orient themselves within the document. We often tell our students to assume we know nothing (they don’t mind) and need to be shown exactly where they are addressing each part of the literature review. It’s like walking a small child around, telling them “First we’ll do this, then we’ll do that, and when we’re done, we’ll know this!”

Another way to use signposting is to open each paragraph with a sentence that links the topic of the paragraph with the one before it. Alternatively, one could end each paragraph with a sentence that links it with the next paragraph. For example, imagine we wanted to link a paragraph about barriers to accessing healthcare with one about the relationship between the patient and physician. We could use a transition sentence like this: “Even if patients overcome these barriers to accessing care, the physician-patient relationship can create new barriers to positive health outcomes.” A transition sentence like this builds a connection between two distinct topics. Transition sentences are also useful within paragraphs. They tell the reader how to consider one piece of information in light of previous information. Even simple transitional words like 'however' and 'similarly' can help demonstrate critical thinking and link each building block of your argument together.

Many beginning researchers have difficulty incorporating transitions into their writing. Let’s look at an example. Instead of beginning a sentence or paragraph by launching into a description of a study, such as “Williams (2004) found that…,” it is better to start by indicating something about why you are describing this particular study. Here are some simple examples:

• Another example of this phenomenon comes from the work of Williams (2004)...
• Williams (2004) offers one explanation of this phenomenon...
• An alternative perspective has been provided by Williams (2004)...

Now that we know to use signposts, the natural question is “What goes on the signposts?” First, it is important to start with an outline of the main points that you want to make, organized in the order you want to make them. The basic structure of your argument should then be apparent from the outline itself. Unfortunately, there is no formula we can give you that will work for everyone, but we can provide some general pointers on structuring your literature review.

The literature review tends to move from general to more specific ideas. You can build a review by identifying areas of consensus and areas of disagreement. You may choose to present historical studies—preferably seminal studies that are of significant importance—and close with the most recent research. Another approach is to start with the most distantly related facts and literature and then report on those most closely related to your research question. You could also compare and contrast valid approaches, features, characteristics, theories – that is, one approach, then a second approach, followed by a third approach.

Here are some additional tips for writing the body of your literature review:

• Start broad and then narrow down to more specific information.
• When appropriate, cite two or more sources for a single point, but avoid long strings of references for a single idea.
• Use quotes sparingly. Quotations for definitions are okay, but reserve quotes for when something is said so well you couldn’t possible phrase it differently. Never use quotes for statistics.
• Paraphrase when you need to relay the specific details within an article
• Include only the aspects of the study that are relevant to your literature review. Don’t insert extra facts about a study just to take up space.
• Avoid reflective, personal writing. It is traditional to avoid using first-person language (I, we, us, etc.).
• Avoid informal language like contractions, idioms, and rhetorical questions.
• Note any sections of your review that lack citations from the literature. Your arguments need to be based in empirical or theoretical facts. Do not approach this like a reflective journal entry.
• Point out consistent findings and emphasize stronger studies over weaker ones.
• Point out important strengths and weaknesses of research studies, as well as contradictions and inconsistent findings.
• Implications and suggestions for further research (where there are gaps in the current literature) should be specific.

The conclusion should summarize your literature review, discuss implications, and create a space for further research needed in this area. Your conclusion, like the rest of your literature review, should make a point. What are the important implications of your literature review? How do they inform the question you are trying to answer?

You should consult with your professor and the course syllabus about the final structure your literature review should take. Here is an example of one possible structure:

• Establish the importance of the topic
• Number and type of people affected
• Seriousness of the impact
• Physical, psychological, economic, social, or spiritual consequences of the problem
• Definitions of key terms
• Supporting evidence
• Common findings across studies, gaps in the literature
• Research question(s) and hypothesis(es)

Editing your literature review

Literature reviews are more than a summary of the publications you find on a topic. As you have seen in this brief introduction, literature reviews represent a very specific type of research, analysis, and writing. We will explore these topics further in upcoming chapters. As you begin your literature review, here are some common errors to avoid:

• Accepting a researcher’s finding as valid without evaluating methodology and data
• Ignoring contrary findings and alternative interpretations
• Using findings that are not clearly related to your own study or using findings that are too general
• Dedicating insufficient time to literature searching
• Reporting statistical results from a single study, rather than synthesizing the results of multiple studies to provide a comprehensive view of the literature on a topic
• Relying too heavily on secondary sources
• Overusing quotations
• Not justifying arguments using specific facts or theories from the literature

For your literature review, remember that your goal is to construct an argument for the importance of your research question. As you start editing your literature review, make sure it is balanced. Accurately report common findings, areas where studies contradict each other, new theories or perspectives, and how studies cause us to reaffirm or challenge our understanding of your topic.

It is acceptable to argue that the balance of the research supports the existence of a phenomenon or is consistent with a theory (and that is usually the best that researchers in social work can hope for), but it is not acceptable to ignore contradictory evidence. A large part of what makes a research question interesting is uncertainty about its answer (University of Minnesota, 2016). [2]

In addition to subjectivity and bias, writer's block can obstruct the completion of your literature review. Often times, writer’s block can stem from confusing the creating and editing parts of the writing process. Many writers often start by simply trying to type out what they want to say, regardless of how good it is. Author Anne Lamott (1995) [3] terms these “shitty first drafts,” and we all write them. They are a natural and important part of the writing process.

Even if you have a detailed outline from which to work, the words are not going to fall into place perfectly the first time you start writing. You should consider turning off the editing and critiquing part of your brain for a while and allow your thoughts to flow. Don’t worry about putting a correctly formatted internal citation (as long as  you know which source you used there) when you first write. Just get the information out. Only after you’ve reached a natural stopping point might you go back and edit your draft for grammar, APA style, organization, flow, and more. Divorcing the writing and editing process can go a long way to addressing writer’s block—as can picking a topic about which you have something to say!

As you are editing, keep in mind these questions adapted from Green (2012): [4]

• Content: Have I clearly stated the main idea or purpose of the paper? Is the thesis or focus clearly presented and appropriate for the reader?
• Organization: How well is it structured? Is the organization spelled out and easy to follow for the reader ?
• Flow: Is there a logical flow from section to section, paragraph to paragraph, sentence to sentence? Are there transitions between and within paragraphs that link ideas together?
• Development: Have I validated the main idea with supporting material? Are supporting data sufficient? Does the conclusion match the introduction?
• Form: Are there any APA style issues, redundancy, problematic wording and terminology (always know the definition of any word you use!), flawed sentence constructions and selection, spelling, and punctuation?

Social workers use the APA style guide to format and structure their literature reviews. Most students know APA style only as it relates to internal and external citations. If you are confused about them, consult this amazing APA style guide from the University of Texas-Arlington library. Your university's library likely has resources they created to help you with APA style, and you can meet with a librarian or your professor to talk about formatting questions you have. Make sure you budget in a few hours at the end of each project to build a correctly formatted references page and check your internal citations. The highest quality online source of information on APA style is the APA style blog, where you can search questions and answers from the

Of course, APA style is about much more than knowing there is a period after "et al." or citing the location a book was published. APA style is also about what the profession considers to be good writing. If you haven't picked up an APA publication manual because you use citation generators, know that I did the same thing when I was in school. Purchasing the APA manual can help you with a common problem we hear about from students. Every professor (and every website about APA style) seems to have their own peculiar idea of "correct" APA style that you can, if needed, demonstrate is not accurate.

• A literature review is not a book report. Do not organize it by article, with one paragraph for each source in your references. Instead, organize it based on the key ideas and arguments.
• The problem statement draws the reader into your topic by highlighting the importance of the topic to social work and to society overall.
• Signposting is an important component of academic writing that helps your reader follow the structure of your argument and of your literature review.
• Transitions demonstrate critical thinking and help guide your reader through your arguments.
• Editing and writing are separate processes.
• Consult with an APA style guide or a librarian to help you format your paper.

Look at your professor's prompt for the literature review component of your research proposal (or if you don't have one, use the example question provided in this section).

• Write 2-3 facts you would use to address each question or component in the prompt.
• Reflect on which questions you have a lot of information about and which you need to gather more information about in order to answer adequately.

Outline the structure of your literature review using your concept map from Section 5.2 as a guide.

• Identify the key arguments you will make and how they are related to each other.
• Reflect on topic sentences and concluding sentences you would use for each argument.
• Human subjects research (19 minute read)
• Specific ethical issues to consider (12 minute read)
• Benefits and harms of research across the ecosystem (7 minute read)
• Being an ethical researcher (8 minute read)

Content warning: examples in this chapter contain references to numerous incidents of unethical medical experimentation (e.g. intentionally injecting diseases into unknowing participants, withholding proven treatments), social experimentation under extreme conditions (e.g. being directed to deliver electric shocks to test obedience), violations of privacy, gender and racial inequality, research with people who are incarcerated or on parole, experimentation on animals, abuse of people with Autism, community interactions with law enforcement, WWII, the Holocaust, and Nazi activities (especially related to research on humans).

With your literature review underway, you are ready to begin thinking in more concrete terms about your research topic. Recall our discussion in Chapter 2 on practical and ethical considerations that emerge as part of the research process. In this chapter, we will expand on the ethical boundaries that social scientists must abide by when conducting human subjects research. As a result of reading this chapter, you should have a better sense of what is possible and ethical for the research project you create.

6.1 Human subjects research

• Understand what we mean by ethical research and why it is important
• Understand some of the egregious ethical violations that have occurred throughout history

While all research comes with its own set of ethical concerns, those associated with research conducted on human subjects vary dramatically from those of research conducted on nonliving entities. The US Department of Health and Human Services (USDHHS) defines a human subject as “a living individual about whom an investigator (whether professional or student) conducting research obtains (1) data through intervention or interaction with the individual, or (2) identifiable private information” (USDHHS, 1993, para. 1). [5] Some researchers prefer the term "participants" to "subjects'" as it acknowledges the agency of people who participate in the study. For our purposes, we will use the two terms interchangeably.

In some states, human subjects also include deceased individuals and human fetal materials. Nonhuman research subjects, on the other hand, are objects or entities that investigators manipulate or analyze in the process of conducting research. Nonhuman research subjects typically include sources such as newspapers, historical documents, pieces of clothing, television shows, buildings, and even garbage (to name just a few), that are analyzed for unobtrusive research projects. Unsurprisingly, research on human subjects is regulated much more heavily than research on nonhuman subjects. This is why many student research projects use data that is publicly available, rather than recruiting their own study participants. However, there are ethical considerations that all researchers must take into account, regardless of their research subject. We’ll discuss those considerations in addition to concerns that are unique to human subject research.

Why do research participants need protection?

First and foremost, we are professionally bound to engage in the ethical practice of research. This chapter discusses ethical research and will show you how to engage in research that is consistent with the NASW Code of Ethics as well as national and international ethical standards all researchers are accountable to. Before we begin, we need to understand the historical occurrences that were the catalyst for the formation of the current ethical standards . This chapter will enable you to view ethics from a micro, mezzo, and macro perspective.

The research process has led to many life-changing discoveries; these have improved life expectancy, improved living conditions, and helped us understand what contributes to certain social problems. That said, not all research has been conducted in respectful, responsible, or humane ways. Unfortunately, some research projects have dramatically marginalized, oppressed, and harmed participants and whole communities.

Would you believe that the following actions have been carried out in the name of research? I realize there was a content warning at the beginning of the chapter, but it is worth mentioning that the list below of research atrocities may be particularly upsetting or triggering.

• intentionally froze healthy body parts of prisoners to see if they could develop a treatment for freezing [6]
• scaled the body parts of prisoners to how best to treat soldiers who had injuries from being exposed to high temperatures [7]
• intentionally infected healthy individuals to see if they could design effective methods of treatment for infections [8]
• gave healthy people TB to see if they could treat it [9]
• attempted to transplant limbs, bones, and muscles to another person to see if this was possible [10]
• castrated and irradiated genitals to see if they could develop a faster method of sterilization [11]
• starved people and only allowed them to drink seawater to see if they could make saline water drinkable [12]
• artificially inseminated women with animal sperm to see what would happen [13]
• gassed living people to document how they would die [14]
• conducted cruel experiments on people and if they did not die, would kill them so they could undergo an autopsy [15]
• refused to treat syphilis in African American men (when treatment was available) because they wanted to track the progression of the illness [16]
• vivisected humans without anesthesia to see how illnesses that researches gave prisoners impacted their bodies [17]
• intentionally tried to infect prisoners with the Bubonic Plague [18]
• intentionally infected prisoners, prostitutes, soldiers, and children with syphilis to study the disease's progression [19]
• performed gynecological experiments on female slaves without anesthesia to investigate new surgical methods [20]

The sad fact is that not only did all of these occur, in many instances, these travesties continued for years until exposed and halted. Additionally, these examples have contributed to the formation of a legacy of distrust toward research. Specifically, many underrepresented groups have a deep distrust of agencies that implement research and are often skeptical of research findings. This has made it difficult for groups to support and have confidence in medical treatments, advances in social service programs, and evidence-informed policy changes. While the aforementioned unethical examples may have ended, this deep and painful wound on the public's trust remains. Consequently, we must be vigilant in our commitment to ethical research.

Many of the situations described may seem like extreme historical cases of misuse of power as researchers. However, ethical problems in research don't just happen in these extreme occurrences. None of us are immune to making unethical choices and the ethical practice of research requires conscientious mindful attention to what we are asking of our research participants. A few examples of less noticeable ethical issues might include: failing to fully explain to someone in advance what their participation might involve because you are in a rush to recruit a large enough sample; or only presenting findings that support your ideas to help secure a grant that is relevant to your research area. Remember, any time research is conducted with human beings, there is the chance that ethical violations may occur that pose social, emotional, and even physical risks for groups, and this is especially true when vulnerable or oppressed groups are involved.

A brief history of unethical social science research

Research on humans hasn’t always been regulated in the way it is today. The earliest documented cases of research using human subjects are of medical vaccination trials (Rothman, 1987). [21] One such case took place in the late 1700s, when scientist Edward Jenner exposed an 8-year-old boy to smallpox in order to identify a vaccine for the devastating disease. Medical research on human subjects continued without much law or policy intervention until the mid-1900s when, at the end of World War II, a number of Nazi doctors and scientists were put on trial for conducting human experimentation during the course of which they tortured and murdered many concentration camp inmates (Faden & Beauchamp, 1986). [22] The trials, conducted in Nuremberg, Germany, resulted in the creation of the Nuremberg Code , a 10-point set of research principles designed to guide doctors and scientists who conduct research on human subjects. Today, the Nuremberg Code guides medical and other research conducted on human subjects, including social scientific research.

Medical scientists are not the only researchers who have conducted questionable research on humans. In the 1960s, psychologist Stanley Milgram (1974) [23] conducted a series of experiments designed to understand obedience to authority in which he tricked subjects into believing they were administering an electric shock to other subjects. In fact, the shocks weren’t real at all, but some, though not many, of Milgram’s research participants experienced extreme emotional distress after the experiment (Ogden, 2008). [24] A reaction of emotional distress is understandable. The realization that one is willing to administer painful shocks to another human being just because someone who looks authoritative has told you to do so might indeed be traumatizing—even if you later learn that the shocks weren’t real.

Around the same time that Milgram conducted his experiments, sociology graduate student Laud Humphreys (1970) [25] was collecting data for his dissertation on the tearoom trade, which was the practice of men engaging in anonymous sexual encounters in public restrooms. Humphreys wished to understand who these men were and why they participated in the trade. To conduct his research, Humphreys offered to serve as a “watch queen,” in a local park restroom where the tearoom trade was known to occur. His role would be to keep an eye out for police while also getting the benefit of being able to watch the sexual encounters. What Humphreys did not do was identify himself as a researcher to his research subjects. Instead, he watched his subjects for several months, getting to know several of them, learning more about the tearoom trade practice and, without the knowledge of his research subjects, jotting down their license plate numbers as they pulled into or out of the parking lot near the restroom.

Sometime after participating as a watch queen, with the help of several insiders who had access to motor vehicle registration information, Humphreys used those license plate numbers to obtain the names and home addresses of his research subjects. Then, disguised as a public health researcher, Humphreys visited his subjects in their homes and interviewed them about their lives and their health. Humphreys’ research dispelled a good number of myths and stereotypes about the tearoom trade and its participants. He learned, for example, that over half of his subjects were married to women and many of them did not identify as gay or bisexual. [26]

Once Humphreys’ work became public, there was some major controversy at his home university (e.g., the chancellor tried to have his degree revoked), among scientists in general, and among members of the public, as it raised public concerns about the purpose and conduct of social science research. In addition, the Washington   Post  journalist Nicholas von Hoffman wrote the following warning about “sociological snoopers”:

We’re so preoccupied with defending our privacy against insurance investigators, dope sleuths, counterespionage men, divorce detectives and credit checkers, that we overlook the social scientists behind the hunting blinds who’re also peeping into what we thought were our most private and secret lives. But they are there, studying us, taking notes, getting to know us, as indifferent as everybody else to the feeling that to be a complete human involves having an aspect of ourselves that’s unknown (von Hoffman, 1970). [27]

In the original version of his report, Humphreys defended the ethics of his actions. In 2008 [28] , years after Humphreys’ death, his book was reprinted with the addition of a retrospect on the ethical implications of his work. In his written reflections on his research and the fallout from it, Humphreys maintained that his tearoom observations constituted ethical research on the grounds that those interactions occurred in public places. But Humphreys added that he would conduct the second part of his research differently. Rather than trace license numbers and interview unwitting tearoom participants in their homes under the guise of public health research, Humphreys instead would spend more time in the field and work to cultivate a pool of informants. Those informants would know that he was a researcher and would be able to fully consent to being interviewed. In the end, Humphreys concluded “there is no reason to believe that any research subjects have suffered because of my efforts, or that the resultant demystification of impersonal sex has harmed society” (Humphreys, 2008, p. 231). [29]

Today, given increasing regulation of social scientific research, chances are slim that a researcher would be allowed to conduct a project similar to Humphreys’. Some argue that Humphreys’ research was deceptive, put his subjects at risk of losing their families and their positions in society, and was therefore unethical (Warwick, 1973; Warwick, 1982). [30] Others suggest that Humphreys’ research “did not violate any premise of either beneficence or the sociological interest in social justice” and that the benefits of Humphreys’ research, namely the dissolution of myths about the tearoom trade specifically and human sexual practice more generally, outweigh the potential risks associated with the work (Lenza, 2004, p. 23). [31] What do you think, and why?

These and other studies (Reverby, 2009) [32] led to increasing public awareness of and concern about research on human subjects. In 1974, the US Congress enacted the National Research Act , which created the National Commission for the Protection of Human Subjects in Biomedical and Behavioral Research. The commission produced  The Belmont Report , a document outlining basic ethical principles for research on human subjects (National Commission for the Protection of Human Subjects in Biomedical and Behavioral Research, 1979). [33] The National Research Act (1974) [34] also required that all institutions receiving federal support establish institutional review boards (IRBs) to protect the rights of human research subjects. Since that time, many organizations that do not receive federal support but where research is conducted have also established review boards to evaluate the ethics of the research that they conduct. IRBs are overseen by the federal Office of Human Research Protections .

The Belmont Report

As mentioned above, The Belmont Report is a federal document that outlines the foundational principles that guide the ethical practice of research in the United States. These ethical principles include: respect for persons, beneficence, and justice. Each of these terms has specific implications as they are applied to the practice of research. These three principles arose as a response to many of the mistreatment and abuses that have been previously discussed and provide important guidance as researchers consider how they will construct and conduct their research studies. As you are crafting your research proposal, makes sure you are mindful of these important ethical guidelines.

Respect for Persons

As social workers, our professional code of ethics requires that we recognize and respect the "inherent dignity and worth of the person." [35] This is very similar to the ethical research principle of r espect for persons . According to this principle, as researchers, we need to treat all research participants with respect, dignity and inherent autonomy. This is reflected by ensuring that participants have self-determination to make informed decisions about their participation in research, that they have a clear understanding of what they will be asked to do and any risks involved, and that their participation is voluntary and can be stopped at any time. Furthermore, for those persons who may have diminished autonomy (e.g. children, people who are incarcerated), extra protections must be built in to these research studies to ensure that respect for persons continues to be demonstrated towards these groups, as they may be especially vulnerable to exploitation and coercion through the research process. A critical tool in establishing respect for persons in your research is the informed consent process, which will be discussed in more detail below.

Beneficence

You may not be familiar with this word yet, but the concept is pretty straightforward. The main idea with beneficence is that the intent of research is to do good. As researchers, to accomplish this, we seek to maximize benefits and minimize risks. Benefits may be something good or advantageous directly received by the research participant, or they may represent a broader good to a wider group of people or the scientific community at large (such as increasing knowledge about the topic or social problem that you are studying). Risks are potential physical, social, or emotional harm that may come about as a response to participation in a study. These risks may be more immediate (e.g. risk of identifying information about a participant being shared, or a participant being upset or triggered by a particular question), or long-term (e.g. some aspect about the person could be shared that could lead to long-term stigmatization). As researchers, we need to think about risk that might be experienced by the individual, but also risks that might be directed towards the community or population(s) the individual may represent. For instance, if our study is specifically focused on surveying single parents, we need to consider how the sharing of our findings might impact this group and how they are perceived. It is a very rare study in which there is no risk to participants. However, a well-designed and ethically sound study will seek to minimize these risks, provide resources to anticipate and address them, and maximize the benefits that are gained through the study.

The final ethical principle we need to cover is justice. While you likely have some idea what justice is, for the purposes of research, justice is the idea that the benefits and the burdens of research are distributed fairly across populations and groups. To help illustrate the concept of justice in research, research in the area of mental health and psychology has historically been critiqued as failing to adequately represent women and people of diverse racial and ethnic groups in their samples (Cundiff, 2012). [36] This has created a body of knowledge that is overly representative of the white male experience, further reinforcing systems of power and privilege. In addition, consider the influence of language as it relates to research justice. If we create studies that only recruit participants fluent in English, which many studies do, we are often failing to satisfy the ethical principle of justice as it applies to people who don't speak English. It is unrealistic to think that we can represent all people in all studies. However, we do need to thoughtfully acknowledge voices that might not be reflected in our samples and attempt to recruit diverse and representative samples whenever possible.

These three principles provide the foundation for the oversight work that is carried out by Institutional Review Boards, our next topic.

Institutional review boards

Institutional review boards, or IRBs, are tasked with ensuring that the rights and welfare of human research subjects will be protected at all institutions, including universities, hospitals, nonprofit research institutions, and other organizations, that receive federal support for research. IRBs typically consist of members from a variety of disciplines, such as sociology, economics, education, social work, and communications (to name a few). Most IRBs also include representatives from the community in which they reside. For example, representatives from nearby prisons, hospitals, or treatment centers might sit on the IRBs of university campuses near them. The diversity of membership helps to ensure that the many and complex ethical issues that may arise from human subjects research will be considered fully and by a knowledgeable and experienced panel. Investigators conducting research on human subjects are required to submit proposals outlining their research plans to IRBs for review and approval prior to beginning their research. Even students who conduct research on human subjects must have their proposed work reviewed and approved by the IRB before beginning any research (though, on some campuses, exceptions are made for student projects that will not be shared outside of the classroom).

The IRB has three levels of review, defined in statute by the USDHHS.

Exempt review is the lowest level of review. Studies that are considered exempt expose participants to the least potential for harm and often involve little participation by human subjects. In social work, exempt studies often examine data that is publicly available or secondary data from another researcher that has been de-identified by the person who collected it.

Expedited review is the middle level of review. Studies considered under expedited review do not have to go before the full IRB board because they expose participants to minimal risk. However, the studies must be thoroughly reviewed by a member of the IRB committee. While there are many types of studies that qualify for expedited review, the most relevant to social workers include the use of existing medical records, recordings (such as interviews) gathered for research purposes, and research on individual group characteristics or behavior.

Finally, the highest level of review is called a  full board review . A full board review will involve multiple members of the IRB evaluating your proposal. When researchers submit a proposal under full board review, the full IRB board will meet, discuss any questions or concerns with the study, invite the researcher to answer questions and defend their proposal, and vote to approve the study or send it back for revision. Full board proposals pose greater than minimal risk to participants. They may also involve the participation of  vulnerable populations , or people who need additional protection from the IRB. Vulnerable populations include prisoners, children, people with cognitive impairments, people with physical disabilities, employees, and students. While some of these populations can fall under expedited review in some cases, they will often require the full IRB to approve their study.

It may surprise you to hear that IRBs are not always popular or appreciated by researchers. Who wouldn’t want to conduct ethical research, you ask? In some cases, the concern is that IRBs are most well-versed in reviewing biomedical and experimental research, neither of which is particularly common within social work. Much social work research, especially qualitative research, is open-ended in nature, a fact that can be problematic for IRBs. The members of IRBs often want to know in advance exactly who will be observed, where, when, and for how long, whether and how they will be approached, exactly what questions they will be asked, and what predictions the researcher has for their findings. Providing this level of detail for a year-long participant observation within an activist group of 200-plus members, for example, would be extraordinarily frustrating for the researcher in the best case and most likely would prove to be impossible. Of course, IRBs do not intend to have researchers avoid studying controversial topics or avoid using certain methodologically sound data collection techniques, but unfortunately, that is sometimes the result. The solution is not to eradicate review boards, which serve a necessary and important function, but instead to help educate IRB members about the variety of social scientific research methods and topics covered by social workers and other social scientists.

What we have provided here is only a short summary of federal regulations and international agreements that provide the boundaries between ethical and unethical research.

Here are a few more detailed guides for continued learning about research ethics and human research protections.

• University of California, San Francisco: Levels of IRB Review
• United States Department of Health and Human Services: The Belmont Report
• NIH, National Institute of Environmental Health Sciences: What is Ethics in Research & Why is it important 
• NIH: Guiding Principles for Ethical Research
• Council on Social Work Education: National Statement on Research Integrity in Social Work
• Butler, I. (2002). A code of ethics for social work and social care research.  British Journal of Social Work ,  32 (2), 239-248
• Research on human subjects presents a unique set of challenges and opportunities when it comes to conducting ethical research.
• Research on human subjects has not always been regulated to the extent that it is today.
• All institutions receiving federal support for research must have an IRB. Organizations that do not receive federal support but where research is conducted also often include IRBs as part of their organizational structure.
• Researchers submit studies for IRB review at one of three different levels, depending on the level of harm the study may cause.
• Recall whether your project will gather data from human subjects and sketch out what the data collection process might look like.
• Identify which level of IRB review is most appropriate for your project.
• For many students, your professors may have existing agreements with your university's IRB that allow students to conduct research projects outside the supervision of the IRB. Make sure that your project falls squarely within those parameters. If you feel you may be outside of such an agreement, consult with your professor to see if you will need to submit your study for IRB review before starting your project.

6.2 Specific ethical issues to consider

• Define informed consent, and describe how it works
• Identify the unique concerns related to the study of vulnerable populations
• Differentiate between anonymity and confidentiality
• Explain the ethical responsibilities of social workers conducting research

As should be clear by now, conducting research on humans presents a number of unique ethical considerations. Human research subjects must be given the opportunity to consent to their participation in research, and be fully informed of the study’s risks, benefits, and purpose. Further, subjects’ identities and the information they share should be protected by researchers. Of course, how consent and identity protection are defined may vary by individual researcher, institution, or academic discipline. In this section, we’ll take a look at a few specific topics that individual researchers must consider before embarking on research with human subjects.

Informed consent

An expectation of voluntary participation is presumed in all social work research projects. In other words, we cannot force anyone to participate in our research without that person’s knowledge or consent. Researchers must therefore design procedures to obtain subjects’ informed consent to participate in their research. This specifically relates back to the ethical principle of respect for persons outlined in The Belmont Report . Informed consent  is defined as a subject’s voluntary agreement to participate in research based on a full understanding of the research and of the possible risks and benefits involved. Although it sounds simple, ensuring that one has actually obtained informed consent is a much more complex process than you might initially presume.

The first requirement is that, in giving their informed consent, subjects may neither waive nor even  appear  to waive any of their legal rights. Subjects also cannot release a researcher, her sponsor, or institution from any legal liability should something go wrong during the course of their participation in the research (USDHHS,2009). [37] Because social work research does not typically involve asking subjects to place themselves at risk of physical harm by, for example, taking untested drugs or consenting to new medical procedures, social work researchers do not often worry about potential liability associated with their research projects. However, their research may involve other types of risks.

For example, what if a social work researcher fails to sufficiently conceal the identity of a subject who admits to participating in a local swinger’s club? In this case, a violation of confidentiality may negatively affect the participant’s social standing, marriage, custody rights, or employment. Social work research may also involve asking about intimately personal topics that may be difficult for participants to discuss, such as trauma or suicide. Participants may re-experience traumatic events and symptoms when they participate in your study. Even if you are careful to fully inform your participants of all risks before they consent to the research process, I’m sure you can empathize with thinking you could bear talking about a difficult topic and then finding it too overwhelming once you start. In cases like these, it is important for a social work researcher to have a plan to provide supports. This may mean providing referrals to counseling supports in the community or even calling the police if the participant is an imminent danger to himself or others.

It is vital that social work researchers explain their mandatory reporting duties in the consent form and ensure participants understand them before they participate. Researchers should also emphasize to participants that they can stop the research process at any time or decide to withdraw from the research study for any reason. Importantly, it is not the job of the social work researcher to act as a clinician to the participant. While a supportive role is certainly appropriate for someone experiencing a mental health crisis, social workers must ethically avoid dual roles. Referring a participant in crisis to other mental health professionals who may be better able to help them is the expectation.

Beyond the legal issues, most IRBs require researchers to share some details about the purpose of the research, possible benefits of participation, and, most importantly, possible risks associated with participating in that research with their subjects. In addition, researchers must describe how they will protect subjects’ identities, how, where, and for how long any data collected will be stored, how findings may be shared, and whom to contact for additional information about the study or about subjects’ rights. All this information is typically shared in an informed consent form that researchers provide to subjects. In some cases, subjects are asked to sign the consent form indicating that they have read it and fully understand its contents. In other cases, subjects are simply provided a copy of the consent form and researchers are responsible for making sure that subjects have read and understand the form before proceeding with any kind of data collection. Your IRB will often provide guidance or even templates for what they expect to see included in an informed consent form. This is a document that they will inspect very closely. Table 6.1 outlines elements to include in your informed consent. While these offer a guideline for you, you should always visit your schools, IRB website to see what guidance they offer. They often provide a template that they prefer researchers to use. Using these templates ensures that you are using the language that the IRB reviewers expect to see and this can also save you time.

One last point to consider when preparing to obtain informed consent is that not all potential research subjects are considered equally competent or legally allowed to consent to participate in research. Subjects from vulnerable populations may be at risk of experiencing undue influence or coercion (USDHHS, 2009). [38] The rules for consent are more stringent for vulnerable populations. For example, minors must have the consent of a legal guardian in order to participate in research. In some cases, the minors themselves are also asked to participate in the consent process by signing special, age-appropriate assent forms designed specifically for them. Prisoners and parolees also qualify as vulnerable populations. Concern about the vulnerability of these subjects comes from the very real possibility that prisoners and parolees could perceive that they will receive some highly desired reward, such as early release, if they participate in research or that there could be punitive consequences if they choose not to participate. When a participant faces undue or excess pressure to participate by either favorable or unfavorable means, this is known as coercion and must be avoided by researchers.

Another potential concern regarding vulnerable populations is that they may be underrepresented or left out of research opportunities, specifically because of concerns about their ability to consent. So, on the one hand, researchers must take extra care to ensure that their procedures for obtaining consent from vulnerable populations are not coercive. The procedures for receiving approval to conduct research with these groups may be more rigorous than that for non-vulnerable populations. On the other hand, researchers must work to avoid excluding members of vulnerable populations from participation simply on the grounds that they are vulnerable or that obtaining their consent may be more complex. While there is no easy solution to this ethical research dilemma, an awareness of the potential concerns associated with research on vulnerable populations is important for identifying whatever solution is most appropriate for a specific case.

Protection of identities

As mentioned earlier, the informed consent process includes the requirement that researchers outline how they will protect the identities of subjects. This aspect of the research process, however, is one of the most commonly misunderstood. Furthermore, failing to protect identities is one of the greatest risks to participants in social work research studies.

In protecting subjects’ identities, researchers typically promise to maintain either the anonymity or confidentiality of their research subjects. These are two distinctly different terms and they are NOT interchangeable. Anonymity is the more stringent of the two and is very hard to guarantee in most research studies. When a researcher promises anonymity to participants, not even the researcher is able to link participants’ data with their identities. Anonymity may be impossible for some social work researchers to promise due to the modes of data collection many social workers employ. Face-to-face interviewing means that subjects will be visible to researchers and will hold a conversation, making anonymity impossible. In other cases, the researcher may have a signed consent form or obtain personal information on a survey and will therefore know the identities of their research participants. In these cases, a researcher should be able to at least promise confidentiality to participants.

Offering  confidentiality means that some identifying information is known at some time by the research team, but only the research team has access to this identifying information and this information will not be linked with their data in any publicly accessible way. Confidentiality in research is quite similar to confidentiality in clinical practice. You know who your clients are, but others do not. You agree to keep their information and identity private. As you can see under the “Risks” section of the consent form in Figure 5.1, sometimes it is not even possible to promise that a subject’s confidentiality will be maintained. This is the case if data are collected in public or in the presence of other research participants in the course of a focus group, for example. Participants who social work researchers deem to be of imminent danger to self or others or those that disclose abuse of children and other vulnerable populations fall under a social worker’s duty to report. Researchers must then violate confidentiality to fulfill their legal obligations.

There are a number of steps that researchers can take to protect the identities of research participants. These include, but are not limited to:

• Collecting data in private spaces
• Not requesting information that will uniquely identify or "out" that person as a participant
• Assigning study identification codes or pseudonyms
• Keeping signed informed consent forms separate from other data provided by the participant
• Making sure that physical data is kept in a locked and secured location, and the virtual data is encrypted or password-protected
• Reporting data in aggregate (only discussing the data collectively, not by individual responses)

Protecting research participants’ identities is not always a simple prospect, especially for those conducting research on stigmatized groups or illegal behaviors. Sociologist Scott DeMuth learned that all too well when conducting his dissertation research on a group of animal rights activists. As a participant observer, DeMuth knew the identities of his research subjects. So when some of his research subjects vandalized facilities and removed animals from several research labs at the University of Iowa, a grand jury called on Mr. DeMuth to reveal the identities of the participants in the raid. When DeMuth refused to do so, he was jailed briefly and then charged with conspiracy to commit animal enterprise terrorism and cause damage to the animal enterprise (Jaschik, 2009). [39]

Publicly, DeMuth’s case raised many of the same questions as Laud Humphreys’ work 40 years earlier. What do social scientists owe the public? Is DeMuth, by protecting his research subjects, harming those whose labs were vandalized? Is he harming the taxpayers who funded those labs? Or is it more important that DeMuth emphasize what he owes his research subjects, who were told their identities would be protected? DeMuth’s case also sparked controversy among academics, some of whom thought that as an academic himself, DeMuth should have been more sympathetic to the plight of the faculty and students who lost years of research as a result of the attack on their labs. Many others stood by DeMuth, arguing that the personal and academic freedom of scholars must be protected whether we support their research topics and subjects or not. DeMuth’s academic adviser even created a new group, Scholars for Academic Justice , to support DeMuth and other academics who face persecution or prosecution as a result of the research they conduct. What do you think? Should DeMuth have revealed the identities of his research subjects? Why or why not?

Discipline-specific considerations

Often times, specific disciplines will provide their own set of guidelines for protecting research subjects and, more generally, for conducting ethical research. For social workers, the National Association of Social Workers (NASW) Code of Ethics section 5.02 describes the responsibilities of social workers in conducting research. Summarized below, these responsibilities are framed as part of a social worker’s responsibility to the profession. As representative of the social work profession, it is your responsibility to conduct and use research in an ethical manner.

A social worker should:

• Monitor and evaluate policies, programs, and practice interventions
• Contribute to the development of knowledge through research
• Keep current with the best available research evidence to inform practice
• Ensure voluntary and fully informed consent of all participants
• Not engage in any deception in the research process
• Allow participants to withdraw from the study at any time
• Provide access to appropriate supportive services for participants
• Protect research participants from harm
• Maintain confidentiality
• Report findings accurately
• Disclose any conflicts of interest
• Researchers must obtain the informed consent of research participants.
• Social workers must take steps to minimize the harms that could arise during the research process.
• If anonymity is promised, individual participants cannot be linked with their data.
• If confidentiality is promised, the identities of research participants cannot be revealed, even if individual participants can be linked with their data.
• The NASW Code of Ethics includes specific responsibilities for social work researchers.
• Talk with your professor to see if an informed consent form is required for your research project. If documentation is required, customize the template provided by your professor or the IRB at your school, using the details of your study. If documentation on consent is not required, for example if consent is given verbally, use the templates as guides to create a guide for what you will say to participants regarding informed consent.
• Identify whether your data will be confidential or anonymous. Describe the measures you will take to protect the identities of individuals in your study. How will you store the data? How will you ensure that no one can identify participants based on what you report in papers and presentations? Be sure to think carefully. People can be identified by characteristics such as age, gender, disability status, location, etc.

6.3 Benefits and harms of research across the ecosystem

• Identify and distinguish between micro-, mezzo-, and macro-level considerations with respect to the ethical conduct of social scientific research

This chapter began with a long list of harmful acts that researchers engaged in while conducting studies on human subjects. Indeed, even the last section on informed consent and protection of confidential information can be seen in light of minimizing harm and maximizing benefits. The benefits of your study should be greater than the harms. But who benefits from your research study, and who might be harmed? The first person who benefits is, most clearly, you as the researcher. You need a project to complete, be it for a grade, a grant, an academic responsibility, etc. However you need to make sure that your benefit does not come at the expense of harming others. Furthermore, research requires resources, including resources from the communities we work with. Part of being good stewards of these resources as social work researchers means that we need to engage in research that benefits the people we serve in meaningful and relevant ways. We need to consider how others are impacted by our research.

Micro-, mezzo-, and macro-level concerns

One useful way to think about the breadth of ethical questions that might arise out of any research project is to think about potential issues from the perspective of different analytical levels that are familiar to us as social workers. In Chapter 1 , you learned about the micro-, mezzo-, and macro-levels of inquiry and how a researcher’s specific point of focus might vary depending on her level of inquiry. Here we’ll apply this ecological framework to a discussion of research ethics. Within most research projects, there are specific questions that arise for researchers at each of these three levels.

At the micro-level, researchers must consider their own conduct and the impact on individual research participants. For example, did Stanley Milgram behave ethically when he allowed research participants to think that they were administering electric shocks to fellow participants? Did Laud Humphreys behave ethically when he deceived his research subjects about his own identity? Were the rights of individuals in these studies protected? How did these participants benefit themselves from the research that was conducted? While not social workers by trade, would the actions of these two researchers hold up against our professional NASW Code of Ethics? The questions posed here are the sort that you will want to ask yourself as a researcher when considering ethics at the micro-level.

At the mezzo-level, researchers should think about their duty to the community. How will the results of your study impact your target population? Ideally, your results will benefit your target population by identifying important areas for social workers to intervene and to better understand the experiences of the communities they serve. However, it is possible that your study may perpetuate negative stereotypes about your target population or damage its reputation. Indigenous people in particular have highlighted how historically social science has furthered marginalization of indigenous peoples (Smith, 2013). [40] Mezzo-level concerns should also address other groups or organizations that are connected to your target population. This may include the human service agencies with whom you've partnered for your study as well as the communities and peoples they serve. If your study reflected negatively on a particular housing project in your area, for example, will community members seek to remove it from their community? Or might it draw increased law enforcement presence that is unwanted by participants or community members? Research is a powerful tool and can be used for many purposes, not all of them altruistic. In addition, research findings can have many implications, intended and unintended. As responsible researchers, we need to do our best to thoughtfully anticipate these consequences.

Finally, at the macro-level, a researcher should consider duty to, and the expectations of, society. Perhaps the most high-profile case involving macro-level questions of research ethics comes from debates over whether to use data gathered by, or cite published studies based on data gathered from, the Nazis in the course of their unethical and horrendous experiments on humans during World War II (Moe, 1984). [41] Some argue that because the data were gathered in such an unquestionably unethical manner, they should never be used. The data, say these people, are neither valid nor reliable and should therefore not be used in any current scientific investigation (Berger, 1990). [42]

On the other hand, some people argue that data themselves are neutral; that “information gathered is independent of the ethics of the methods and that the two are not linked together” (Pozos, 1992, p. 104). [43] Others point out that not using the data could inadvertently strengthen the claims of those who deny that the Holocaust ever happened. In his striking statement in support of publishing the data, medical ethics professor Velvl Greene (1992) says,

Instead of banning the Nazi data or assigning it to some archivist or custodial committee, I maintain that it be exhumed, printed, and disseminated to every medical school in the world along with the details of methodology and the names of the doctors who did it, whether or not they were indicted, acquitted, or hanged.…Let the students and the residents and the young doctors know that this was not ancient history or an episode from a horror movie where the actors get up after filming and prepare for another role. It was real. It happened yesterday (p. 169–170). [44]

While debates about the use of data collected by the Nazis are typically centered on medical scientists’ use of them, there are conceivable circumstances under which these data might be used by social scientists. Perhaps, for example, a social scientist might wish to examine contemporary reactions to the experiments. Or perhaps the data could be used in a study of the sociology of science. What do you think? Should data gathered by the Nazis be used or cited today? What arguments can you make in support of your position, and how would you respond to those who disagree?

Additionally at the macro-level, you must also consider your responsibilities to the profession of social work. When you engage in social work research, you stand on the reputation the profession has built for over a century. Since research is public-facing, meaning that research findings are intended to be shared publicly, you are an ambassador for the profession. How you conduct yourself as a social work researcher has potential implications for how the public perceives both social work and research. As a social worker, you have a responsibility to work towards greater social, environmental, and economic justice and human rights. Your research should reflect this responsibility. Attending to research ethics helps to fulfill your responsibilities to the profession, in addition to your target population.

Table 6.2 summarizes the key questions that researchers might ask themselves about the ethics of their research at each level of inquiry.

• At the micro-level, researchers should consider their own conduct and the rights of individual research participants.
• At the mezzo-level, researchers should consider the expectations of their profession, any organizations that may have funded their research, and the communities affected by their research.
• At the macro-level, researchers should consider their duty to and the expectations of society with respect to social science research.
• Summarize the benefits and harms at the micro-, mezzo-, and macro-level of inquiry. At which level of inquiry is your research project?
• In a few sentences, identify whether the benefits of your study outweigh the potential harms.

6.4 Being an ethical researcher

• Identify why researchers must provide a detailed description of methodology
• Describe what it means to use science in an ethical way

Research ethics has to do with both how research is conducted and how findings from that research are used. In this section, we’ll consider research ethics from both angles.

Doing science the ethical way

As you should now be aware, researchers must consider their own personal ethical principles in addition to following those of their institution, their discipline, and their community. We’ve already considered many of the ways that social workers strive to ensure the ethical practice of research, such as informing and protecting subjects. But the practice of ethical research doesn’t end once subjects have been identified and data have been collected. Social workers must also fully disclose their research procedures and findings. This means being honest about how research subjects were identified and recruited, how exactly data were collected and analyzed, and ultimately, what findings were reached.

If researchers fully disclose how they conducted their research, then those who use their work to build research projects, create social policies, or make treatment decisions can have greater confidence in the work. By sharing how research was conducted, a researcher helps assure readers they have conducted legitimate research and didn’t simply come to whatever conclusions they wanted   to find. A description or presentation of research findings that is not accompanied by information about research methodology is missing relevant information. Sometimes methodological details are left out because there isn’t time or space to share them. This is often the case with news reports of research findings. Other times, there may be a more insidious reason that important information is missing. This may be the case if sharing methodological details would call the legitimacy of a study into question. As researchers, it is our ethical responsibility to fully disclose our research procedures. As consumers of research, it is our ethical responsibility to pay attention to such details. We’ll discuss this more in the next section.

There’s a New Yorker cartoon that depicts a set of filing cabinets that aptly demonstrates what we don’t want to see happen with research. Each filing cabinet drawer in the cartoon is labeled differently. The labels include such headings as, “Our Facts,” “Their Facts,” “Neutral Facts,” “Disputable Facts,” “Absolute Facts,” “Bare Facts,” “Unsubstantiated Facts,” and “Indisputable Facts.” The implication of this cartoon is that one might just choose to open the file drawer of her choice and pick whichever facts one likes best. While this may occur if we use some of the unscientific ways of knowing described in Chapter 1 , it is fortunately not how the discovery of knowledge in social work, or in any other science for that matter, takes place. There actually is a method to this madness we call research. At its best, research reflects a systematic, transparent, informative process.

Honesty in research is facilitated by the scientific principle of replication . Ideally, this means that one scientist could repeat another’s study with relative ease. By replicating a study, we may become more (or less) confident in the original study’s findings. Replication is far more difficult (perhaps impossible) to achieve in the case of many qualitative studies, as our purpose is often a deep understanding of very specific circumstances, rather than the broad, generalizable knowledge we traditionally seek in quantitative studies. Nevertheless, transparency in the research process is an important standard for all social scientific researchers—that we provide as much detail as possible about the processes by which we reach our conclusions. This allows the quality of our research to be evaluated. Along with replication, peer review is another important principle of the scientific process. Peer review involves other knowledgeable researchers in our field of study to evaluate our research and to determine if it is of sufficient quality to share with the public. There are valid critiques of the peer review process: that it is biased towards studies with positive findings, that it may reinforce systemic barriers to oppressed groups accessing and leveraging knowledge, that it is far more subjective and/or unreliable than it claims to be. Despite these critiques, peer review remains a foundational concept for how scientific knowledge is generated.

Full disclosure also includes the need to be honest about a study’s strengths and weaknesses, both with oneself and with others. Being aware of the strengths and weaknesses of your own work can help a researcher make reasonable recommendations about the next steps other researchers might consider taking in their inquiries. Awareness and disclosure of a study’s strengths and weaknesses can also help highlight the theoretical or policy implications of one’s work. In addition, openness about strengths and weaknesses helps those reading the research better evaluate the work and decide for themselves how or whether to rely on its findings. Finally, openness about a study’s sponsors is crucial. How can we effectively evaluate research without knowing who paid the bills? This allows us to assess for potential conflicts of interest that may compromise the integrity of the research.

The standard of replicability, the peer-review process, and openness about a study’s strengths, weaknesses, and funding sources enables those who read the research to evaluate it fairly and completely. Knowledge of funding sources is often raised as an issue in medical research. Understandably, independent studies of new drugs may be more compelling to the Food and Drug Administration (FDA) than studies touting the virtues of a new drug that happen to have been funded by the company who created that drug. But medical researchers aren’t the only ones who need to be honest about their funding. If we know, for example, that a political think tank with ties to a particular party has funded some research, we can take that knowledge into consideration when reviewing the study’s findings and stated policy implications. Lastly, and related to this point, we must consider how, by whom, and for what purpose research may be used.

Using science the ethical way

Science has many uses. By “use” I mean the ways that science is understood and applied (as opposed to the way it is conducted). Some use science to create laws and social policies; others use it to understand themselves and those around them. Some people rely on science to improve their life conditions or those of other people, while still others use it to improve their businesses or other undertakings. In each case, the most ethical way for us to use science is to educate ourselves about the design and purpose of any studies we may wish to use. This helps us to more adequately critique the value of this research, to recognize its strengths and limitations.

As part of my research course, students are asked to critique a research article. I often find in this assignment that students often have very lofty expectations for everything that 'should' be included in the journal article they are reviewing. While I appreciate the high standards, I often give them feedback that it is perhaps unrealistic (even unattainable) for a research study to be perfectly designed and described for public consumption. All research has limitations; this may be a consequence of limited resources, issues related to feasibility, and unanticipated roadblocks or problems as we are carrying out our research. Furthermore, the ways we disseminate or share our research often has restrictions on what and how we can share our findings. This doesn't mean that a study with limitations has no value—every study has limitations! However, as we are reviewing research, we should look for an open discussion about methodology , strengths, and weaknesses of the study that helps us to interpret what took place and in what ways it may be important.

For instance, this can be especially important to think about in terms of a study's sample. It can be challenging to recruit a diverse and representative sample for your study (however, that doesn't mean we shouldn't try!). The next time you are reading research studies that were used to help establish an evidence based practice (EBP), make sure to look at the description of the sample. We cannot assume that what works for one group of people will uniformly work with all groups of people with very different life experiences; however, historically much of our intervention repertoire has been both created by and evaluated on white men. If research studies don't obtain a diverse sample, for whatever reason, we would expect that the authors would identify this as a limitation and an area requiring further study. We need to challenge our profession to provide practices, strategies, models, interventions, and policies that have been evaluated and tested for their efficacy with the diverse range of people that we work with as social workers.

Social scientists who conduct research on behalf of organizations and agencies may face additional ethical questions about the use of their research, particularly when the organization for which a study is conducted controls the final report and the publicity it receives. There is a potential conflict of interest for evaluation researchers who are employees of the agency being evaluated. A similar conflict of interest might exist between independent researchers whose work is being funded by some government agency or private foundation.

So who decides what constitutes ethical conduct or use of research? Perhaps we all do. What qualifies as ethical research may shift over time and across cultures as individual researchers, disciplinary organizations, members of society, and regulatory entities, such as institutional review boards, courts, and lawmakers, all work to define the boundaries between ethical and unethical research.

• Conducting research ethically requires that researchers be ethical not only in their data collection procedures but also in reporting their methods and findings.
• The ethical use of research requires an effort to understand research, an awareness of your own limitations in terms of knowledge and understanding, and the honest application of research findings.
• Think about your research hypothesis at this point. What would happen if your results revealed information that could harm the population you are studying? What are your ethical responsibilities as far as reporting about your research?
• Ultimately, we cannot control how others will use the results of our research. What are the implications of this for how you report on your research?
• Reading the results of empirical studies (16 minute read)
• Annotating empirical journal articles (15 minute read)
• Generalizability and transferability of empirical results (15 minute read)

Content warning: examples in this chapter contain references to domestic violence and details on types of abuse, drug use, poverty, mental health, sexual harassment and details on harassing behaviors, children’s mental health, LGBTQ+ oppression and suicide, obesity, anti-poverty stigma, and psychotic disorders.

5.1 Reading the results of empirical studies

• Describe how statistical significance and confidence intervals demonstrate which results are most important
• Differentiate between qualitative and quantitative results in an empirical journal article

If you recall from section 3.1 , empirical journal articles are those that report the results of quantitative or qualitative data analyzed by the author. They follow a set structure—introduction, methods, results, discussion/conclusions. This section is about reading the most challenging section: results.

I want to normalize not understanding statistics terms and symbols. However, a basic understanding of a results section goes a very long way to understanding the key results in an article. This will take you beyond the two or three sentences in the abstract that summarize the study's results and into the nitty-gritty of what they found for each concept they studied.

Read beyond the abstract

At this point, I have read hundreds of literature reviews written by students. One of the challenges I have noted is that students will report the results as summarized in the abstract, rather than the detailed findings laid out in the results section of the article. This poses a problem when you are writing a literature review because you need to provide specific and clear facts that support your reading of the literature. The abstract may say something like: “we found that poverty is associated with mental health status.” For your literature review, you want the details, not the summary. In the results section of the article, you may find a sentence that states: “children living in households experiencing poverty are three times more likely to have a mental health diagnosis.” This more specific statistical information provides a stronger basis on which to build the arguments in your literature review.

Using the summarized results in an abstract is an understandable mistake to make. The results section often contains figures and tables that may be challenging to understand. Often, without having completed more advanced coursework on statistical or qualitative analysis, some of the terminology, symbols, or diagrams may be difficult to comprehend. This section is all about how to read and interpret the results of an empirical (quantitative or qualitative) journal article. Our discussion here will be basic, and in parts three and four of the textbook, you will learn more about how to interpret results from statistical tests and qualitative data analysis.

Remember, this section only addresses empirical articles. Non-empirical articles (e.g., theoretical articles, literature reviews) don't have results. They cite the analysis of raw data completed by other authors, not the person writing the journal article who is merely summarizing others' work.

Quantitative results

Quantitative articles often contain tables, and scanning them is a good way to begin reading the results. A table usually provides a quick, condensed summary of the report’s key findings. Tables are a concise way to report large amounts of data. Some tables present descriptive information about a researcher’s sample (often the first table in a results section). These tables will likely contain frequencies (N) and percentages (%). For example, if gender happened to be an important variable for the researcher’s analysis, a descriptive table would show how many and what percent of all study participants are of a particular gender. Frequencies or “how many” will probably be listed as N, while the percent symbol (%) might be used to indicate percentages.

In a table presenting a causal relationship, two sets of variables are represented. The independent variable , or cause, and the dependent variable , the effect. We will discuss these further when we review quantitative conceptualization and measurement. Independent variable attributes are typically presented in the table’s columns, while dependent variable attributes are presented in rows. This allows the reader to scan a table’s rows to see how values on the dependent variable change as the independent variable values change (i.e., changes in the dependent variable depend on changes in the independent variable). Tables displaying results of quantitative analysis will also likely include some information about which relationships are significant or not. We will discuss the details of significance and p-values later in this section.

Let’s look at a specific example: Table 5.1. It presents the causal relationship between gender and experiencing harassing behaviors at work. In this example, gender is the independent variable (the cause) and the harassing behaviors listed are the dependent variables (the effects). [46] Therefore, we place gender in the table’s columns and harassing behaviors in the table’s rows.

Reading across the table’s top row, we see that 2.9% of women in the sample reported experiencing subtle or obvious threats to their safety at work, while 4.7% of men in the sample reported the same. We can read across each of the rows of the table in this way. Reading across the bottom row, we see that 9.4% of women in the sample reported experiencing staring or invasion of their personal space at work while just 2.3% of men in the sample reported having the same experience. We’ll discuss  p values later in this section.

While you can certainly scan tables for key results, they are often difficult to understand without reading the text of the article. The article and table were meant to complement each other, and the text should provide information on how the authors interpret their findings. The table is not redundant with the text of the results section. Additionally, the first table in most results sections is a summary of the study's sample, which provides more background information on the study than information about hypotheses and findings. It is also a good idea to look back at the methods section of the article as the data analysis plan the authors outline should walk you through the steps they took to analyze their data which will inform how they report them in the results section.

Statistical significance

The statistics reported in Table 5.1 represent what the researchers found in their sample. The purpose of statistical analysis is usually to generalize from a the small number of people in a study's sample to a larger population of people. Thus, the researchers intend to make causal arguments about harassing behaviors at workplaces beyond those covered in the sample.

Generalizing is key to understanding statistical significance . According to Cassidy and colleagues, (2019) [47] 89% of research methods textbooks in psychology define statistical significance incorrectly. This includes an early draft of this textbook which defined statistical significance as "the likelihood that the relationships we observe could be caused by something other than chance." If you have previously had a research methods class, this might sound familiar to you. It certainly did to me!

But statistical significance is less about "random chance" than more about the null hypothesis . Basically, at the beginning of a study a researcher develops a hypothesis about what they expect to find, usually that there is a statistical relationship between two or more variables . The null hypothesis is the opposite. It is the hypothesis that there is no relationship between the variables in a research study. Researchers then can hopefully reject the null hypothesis because they find a relationship between the variables.

For example, in Table 5.1 researchers were examining whether gender impacts harassment. Of course, researchers assumed that women were more likely to experience harassment than men. The null hypothesis, then, would be that gender has no impact on harassment. Once we conduct the study, our results will hopefully lead us to reject the null hypothesis because we find that gender impacts harassment. We would then generalize from our study's sample to the larger population of people in the workplace.

Statistical significance is calculated using a p-value which is obtained by comparing the statistical results with a hypothetical set of results if the researchers re-ran their study a large number of times. Keeping with our example, imagine we re-ran our study with different men and women from different workplaces hundreds and hundred of times and we assume that the null hypothesis is true that gender has no impact on harassment. If results like ours come up pretty often when the null hypothesis is true, our results probably don't mean much. "The smaller the p-value, the greater the statistical incompatibility with the null hypothesis" (Wasserstein & Lazar, 2016, p. 131). [48] Generally, researchers in the social sciences have used 0.05 as the value at which a result is significant (p is less than 0.05) or not significant (p is greater than 0.05). The p-value 0.05 refers to if 5% of those hypothetical results from re-running our study show the same or more extreme relationships when the null hypothesis is true. Researchers, however, may choose a stricter standard such as 0.01 in which only 1% of those hypothetical results are more extreme or a more lenient standard like 0.1 in which 10% of those hypothetical results are more extreme than what was found in the study.

Let's look back at Table 5.1. Which one of the relationships between gender and harassing behaviors is statistically significant? It's the last one in the table, "staring or invasion of personal space," whose p-value is 0.039 (under the p<0.05 standard to establish statistical significance). Again, this indicates that if we re-ran our study over and over again and gender did not  impact staring/invasion of space (i.e., the null hypothesis was true), only 3.9% of the time would we find similar or more extreme differences between men and women than what we observed in our study. Thus, we conclude that for staring or invasion of space only , there is a statistically significant relationship.

For contrast, let's look at "being pushed, hit, or grabbed" and run through the same analysis to see if it is statistically significant. If we re-ran our study over and over again and the null hypothesis was true, 48% of the time (p=.48) we would find similar or more extreme differences between men and women. That means these results are not statistically significant.

This discussion should also highlight a point we discussed previously: that it is important to read the full results section, rather than simply relying on the summary in the abstract. If the abstract stated that most tests revealed no statistically significant relationships between gender and harassment, you would have missed the detail on which behaviors were and were not associated with gender. Read the full results section! And don't be afraid to ask for help from a professor in understanding what you are reading, as results sections are often not written to be easily understood.

Statistical significance and p-values have been critiqued recently for a number of reasons, including that they are misused and misinterpreted (Wasserstein & Lazar, 2016) [49] , that researchers deliberately manipulate their analyses to have significant results (Head et al., 2015) [50] , and factor into the difficulty scientists have today in reproducing many of the results of previous social science studies (Peng, 2015). [51] For this reason, we share these principles, adapted from those put forth by the American Statistical Association, [52]  for understanding and using p-values in social science:

• P-values provide evidence against a null hypothesis.
• P-values do not indicate whether the results were produced by random chance alone or if the researcher's hypothesis is true, though both are common misconceptions.
• Statistical significance can be detected in minuscule differences that have very little effect on the real world.
• Nuance is needed to interpret scientific findings, as a conclusion does not become true or false when the p-value passes from p=0.051 to p=0.049.
• Real-world decision-making must use more than reported p-values. It's easy to run analyses of large datasets and only report the significant findings.
• Greater confidence can be placed in studies that pre-register their hypotheses and share their data and methods openly with the public.
• "By itself, a p-value does not provide a good measure of evidence regarding a model or hypothesis. For example, a p-value near 0.05 taken by itself offers only weak evidence against the null hypothesis. Likewise, a relatively large p-value does not imply evidence in favor of the null hypothesis; many other hypotheses may be equally or more consistent with the observed data" (Wasserstein & Lazar, 2016, p. 132).

Confidence intervals

Because of the limitations of p-values, scientists can use other methods to determine whether their models of the world are true. One common approach is to use a confidence interval , or a range of values in which the true value is likely to be found. Confidence intervals are helpful because, as principal #5 above points out, p-values do not measure the size of an effect (Greenland et al., 2016). [53] Remember, something that has very little impact on the world can be statistically significant, and the values in a confidence interval would be helpful. In our example from Table 5.1, imagine our analysis produced a confidence interval that women are 1.2-3.4x more likely to experience "staring or invasion of personal space" than men. As with p-values, calculation for a confidence interval compares what was found in one study with a hypothetical set of results if we repeated the study over and over again. If we calculated 95% confidence intervals for all of the hypothetical set of hundreds and hundreds of studies, that would be our confidence interval. 

Confidence intervals are pretty intuitive. As of this writing, my wife and are expecting our second child. The doctor told us our due date was December 11th. But the doctor also told us that December 11th was only their best estimate. They were actually 95% sure our baby might be born any time in the 30-day period between November 27th and December 25th. Confidence intervals are often listed with a percentage, like 90% or 95%, and a range of values, such as between November 27th and December 25th. You can read that as: "we are 95% sure your baby will be born between November 27th and December 25th because we've studied hundreds of thousands of fetuses and mothers, and we're 95% sure your baby will be within these two dates."

Notice that we're hedging our bets here by using words like "best estimate." When testing hypotheses, social scientists generally phrase their findings in a tentative way, talking about what results "indicate" or "support," rather than making bold statements about what their results "prove." Social scientists have humility because they understand the limitations of their knowledge. In a literature review, using a single study or fact to "prove" an argument right or wrong is often a signal to the person reading your literature review (usually your professor) that you may not have appreciated the limitations of that study or its place in the broader literature on the topic. Strong arguments in a literature review include multiple facts and ideas that span across multiple studies.

You can learn more about creating tables, reading tables, and tests of statistical significance in a class focused exclusively on statistical analysis. We provide links to many free and openly licensed resources on statistics in Chapter 16 . For now, we hope this brief introduction to reading tables will improve your confidence in reading and understanding the results sections in quantitative empirical articles.

Qualitative results

Quantitative articles will contain a lot of numbers and the results of statistical tests demonstrating associations between those numbers. Qualitative articles, on the other hand, will consist mostly of quotations from participants. For most qualitative articles, the authors want to put their results in the words of their participants, as they are the experts. Articles that lack quotations make it difficult to assess whether the researcher interpreted the data in a trustworthy, unbiased manner. These types of articles may also indicate how often particular themes or ideas came up in the data, potentially reflective of how important they were to participants.

Authors often organize qualitative results by themes and subthemes. For example, see this snippet from the results section in Bonanno and Veselak (2019) [54] discussion parents' attitudes towards child mental health information sources.

Data analysis revealed four themes related to participants’ abilities to access mental health help and information for their children, and parents’ levels of trust in these sources. These themes are: others’ firsthand experiences family and friends with professional experience, protecting privacy, and uncertainty about schools as information sources. Trust emerged as an overarching and unifying concept for all of these themes. Others’ firsthand experiences. Several participants reported seeking information from other parents who had experienced mental health struggles similar to their own children. They often referenced friends or family members who had been or would be good sources of information due to their own personal experiences. The following quote from Adrienne demonstrates the importance of firsthand experience: [I would only feel comfortable sharing concerns or asking for advice] if I knew that they had been in the same situation. (Adrienne) Similarly, Michelle said: And I talked to a friend of mine who has kids who have IEPs in the district to see, kind of, how did she go about it. (Michelle) ... Friends/family with professional experience . Several respondents referred to friends or family members who had professional experience with or knowledge of child mental health and suggested that these individuals would be good sources of information. For example, Hannah said: Well, what happened with me was I have an uncle who’s a psychiatrist. Sometimes if he’s up in (a city to the north), he’s retired, I can call him sometimes and get information. (Hannah) Michelle, who was in nursing school, echoed this sentiment: At this point, [if my child’s behavioral difficulties continued], I would probably call one of my [nursing] professors. That’s what I’ve done in the past when I’ve needed help with certain things...I have a professor who I would probably consider a friend who I would probably talk to first. She has a big adolescent practice. (Michelle) (p. 402-403)

The terms in bold above refer to the key themes (i.e., qualitative results) that were present in the data. Researchers will state the process by which they interpret each theme, providing a definition and usually some quotations from research participants. Researchers will also draw connections between themes, note consensus or conflict over themes, and situate the themes within the study context.

Qualitative results are specific to the time, place, and culture in which they arise, so you will have to use your best judgment to determine whether these results are relevant to your study. For example, students in my class at Radford University in Southwest Virginia may be studying rural populations. Would a study on group homes in a large urban city transfer well to group homes in a rural area?

Maybe. But even if you were using data from a qualitative study in another rural area, are all rural areas the same? How is the client population and sociocultural context in the article similar or different to the one in your study? Qualitative studies have tremendous depth, but researchers must be intentional about drawing conclusions about one context based on a study in another context. To make conclusions about how a study applies in another context, researchers need to examine each component of an empirical journal article--they need to annotate!

• The results section of empirical articles are often the most difficult to understand.
• To understand a quantitative results section, look for results that were statistically significant and examine the confidence interval, if provided.
• To understand a qualitative results section, look for definitions of themes or codes and use the quotations provided to understand the participants’ perspective.

Select a quantitative empirical article related to your topic.

• Write down the results the authors identify as statistically significant in the results section.
• How do the authors interpret their results in the discussion section?
• Do the authors provide enough information in the introduction for you to understand their results?

Select a qualitative empirical article relevant to your topic.

• Write down the key themes the authors identify and how they were defined by the participants.

5.2 Annotating empirical journal articles

• Define annotation and describe how to use it to identify, extract, and reflect on the information you need from an article

Annotation refers to the process of writing notes on an article. There are many ways to do this. The most basic technique is to print out the article and build a binder related to your topic. Raul Pacheco-Vega's excellent blog has a post on his approach to taking physical notes. Honestly, while you are there, browse around that website. It is full of amazing tips for students conducting a literature review and graduate research projects. I see a lot of benefits to the paper, pen, and highlighter approach to annotating articles. Personally though, I prefer to use a computer to write notes on an article because my handwriting is terrible and typing notes allows me search for keywords. For other students, electronic notes work best because they cannot afford to print every article that they will use in their paper. No matter what you use, the point is that you need to write notes when you're reading. Reading is research!

There are a number of free software tools you can use to help you annotate a journal article. Most PDF readers like Adobe Acrobat have a commenting and highlighting feature, though the PDF readers included with internet browsers like Google Chrome, Microsoft Edge, and Safari do not have this feature. The best approach may be to use a citation manager like Zotero. Using a citation manager, you can build a library of articles, save your annotations, and link annotations across PDFs using keywords. They also provide integration with word processing programs to help with citations in a reference list

Of course, I don't follow this advice because I have a system that works well for me. I have a PDF open in one computer window and a Word document open in a window next to it. I type notes and copy quotes, listing the page number for each note I take. It's a bit low-tech, but it does make my notes searchable. This way, when I am looking for a concept or quote, I can simply search my notes using the Find feature in Word and get to the information I need.

Annotation and reviewing literature does not have to be a solo project. If are working in a group, you can use the Hypothes.is web browser extension to annotate articles collaboratively. You can also use Google Docs to collaboratively annotate a shared PDF using the commenting feature and write collaborative notes in a shared document. By sharing your highlights and comments, you can split the work of getting the most out of each article you read and build off one another's ideas.

Common annotations

In this section, we present common annotations people make when reading journal articles. These annotations are adapted from Craig Whippo and Raul Pacheco-Vega . If you are annotating on paper, I suggest using different color highlighters for each type of annotation listed below. If you are annotating electronically, you can use the names below as tags to easily find information later. For example, if you are searching for definitions of key concepts, you can either click on the tag for [definitions] in your PDF reader or thumb through a printed copy of article for whatever color or tag you used to indicate definitions of key terms. Most of all, you want to avoid reading through all of your sources again just to find that one thing you know you read somewhere . Time is a graduate student's most valuable resource, so our goal here is to help you spend your time reading the literature wisely.

Personal reflections

Personal reflections are all about you. What do you think? Are there any areas you are confused about? Any new ideas or reflections come to mind while you're reading? Treat these annotations as a means of capturing your first reflections about an article. Write down any questions or thoughts that come to mind as you read. If you think the author says something inaccurate or unsubstantiated, write that down. If you don't understand something, make a note about it and ask your professor. Don't feel bad! Journal articles are hard to understand sometimes, even for professors. Your goal is to critically read the literature, so write down what you think while reading! Table 4.2 contains some questions that might stimulate your thoughts.

Definitions

Note definitions of key terms for your topic. At minimum, you should include a scholarly definition for the concepts represented in your working question. If your working question asks about the process of leaving a relationship with domestic violence, your research proposal will have to explain how you define domestic violence, as well as how you define "leaving" an abusive relationship. While you may already know what you mean by domestic violence, the person reading your research proposal does not.

Annotating definitions also helps you engage with the scholarly debate around your topic. Definitions are often contested among scholars. Some definitions of domestic violence will be more comprehensive, including things such economic abuse or forcing the victim to problematically use substances. Other definitions will be less comprehensive, covering only physical, verbal, and sexual abuse. Often, how someone defines something conceptually is highly related to how they measure it in their study. Since you will have to do both of these things, find a definition that feels right to you or create your own, noting the ways in which it is similar or different from those in the literature.

Definitions are also an important way of dealing with jargon. Becoming familiar with a new content area involves learning the jargon experts use. For example, in the last paragraph I used the term economic abuse, but that's probably not a term you've heard before. If you were conducting a literature review on domestic violence, you would want to search for keywords like economic abuse if they are relevant to your working question. You will also want to know what they mean so you can use them appropriately in designing your study and writing your literature review.

Theoretical perspective

Noting the theoretical perspective of the article can help you interpret the data in the same manner as the author. For example, articles on supervised injection facilities for people who use intravenous drugs most likely come from a harm reduction perspective, and understanding the theory behind harm reduction is important to make sense of empirical results. Articles should be grounded in a theoretical perspective that helps the author conceptualize and understand the data. As we discussed in Chapter 3 , some journal articles are entirely theoretical and help you understand the theories or conceptual models related to your topic. We will help you determine a theoretical perspective for your project in Chapter 7 . For now, it's a good idea to note what theories authors mention when talking about your topic area. Some articles are better about this than others, and many authors make it a bit challenging to find theory (if mentioned at all). In other articles, it may help to note which social work theories are missing  from the literature. For example, a study's findings might address issues of oppression and discrimination, but the authors may not use critical theory to make sense of what happened.

Background knowledge

It's a good idea to note any relevant information the author relies on for background. When an author cites facts or opinions from others, you are subsequently able to get information from multiple articles simultaneously. For example, if we were looking at this meta-analysis about domestic violence , in the introduction section, the authors provide facts from many other sources. These facts will likely be relevant to your inquiry on domestic violence, as well.

As you are looking at background information, you should also note any subtopics or concepts about which there is controversy or consensus. The author may present one viewpoint and then an opposing viewpoint, something you may do in your literature review as well. Similarly, they may present facts that scholars in the field have come to consensus on and describe the ways in which different sources support these conclusions.

Sources of interest

Note any relevant sources the author cites. If there is any background information you plan to use, note the original source of that information. When you write your literature review, cite the original source of a piece of information you are using, which may not be where you initially read it . Remember that you should read and refer to the primary source . If you are reading Article A and the author cites a fact from Article B, you should note Article B in your annotations and use Article B when you cite the fact in your paper. You should also make sure Article A interpreted Article B correctly and scan Article B for any other useful facts.

Research question/Purpose

Authors should be clear about the purpose of their article. Charitable authors will give you a sentence that starts with something like this:

• "The purpose of this research project was..."
• "Our research question was..."
• "The research project was designed to test the following hypothesis..."

Unfortunately, not all authors are so clear, and you may to hunt around for the research question or hypothesis. Generally, in an empirical article, the research question or hypothesis is at the end of the introduction. In non-empirical articles, the author will likely discuss the purpose of the article in the abstract or introduction.

We will discuss in greater detail how to read the results of empirical articles in Chapter 5 . For now, just know that you should highlight any of the key findings of an article. They will be described very briefly in the abstract, and in much more detail in the article itself. In an empirical article, you should look at both the 'Results' and 'Discussion' sections. For a non-empirical article, the key findings will likely be in the conclusion. You can also find them in the topic or concluding sentences in a paragraph within the body of the article.

How do researchers know something when they see it? Found in the 'Methods' section of empirical articles, the measures section is where researchers spell out the tools, or measures, they used to gather data. For quantitative studies, you will want to get familiar with the questions researchers typically use to measure key variables. For example, to measure domestic violence, researchers often use the Conflict Tactics Scale . The more frequently used and cited a measure is, the more we know about how well it works (or not). Qualitative studies will often provide at least some of the interview or focus group questions they used with research participants. They will also include information about how their inquiry and hypotheses may have evolved over time. Keep in mind however, sometimes important information is cut out of an article during editing. If you need more information, consider reaching out to the author directly. Before you do so, check if the author provided an appendix with the information you need or if the article links to a their data and measures as part open data sharing practices.

Who exactly were the study participants and how were they recruited? In quantitative studies, you will want to pay attention to the sample size. Generally, the larger the sample, the greater the study's explanatory power. Additionally, randomly drawn samples are desirable because they leave any variation up to chance. Samples that are conducted out of convenience can be biased and non-representative of the larger population. In qualitative studies, non-random sampling is appropriate but consider this: how well does what we find for this group of people transfer to the people who will be in your study? For qualitative studies and quantitative studies, look for how well the sample is described and whether there are important characteristics missing from the article that you would need to determine the quality of the sample.

Limitations

Honest authors will include these at the end of each article. But you should also note any additional limitations you find with their work as well.

Your annotations

These are just a few suggested annotations, but you can come up with your own. For example, maybe there are annotations you would use for different assignments or for the problem statement in your research proposal. If you have an argument or idea that keeps coming to mind when you read, consider creating an annotation for it so you can remember which part of each article supports your ideas. Whatever works for you. The goal with annotation is to extract as much information from each article while reading, so you don't have to go back through everything again. It's useless to read an article and forget most of what you read. Annotate!

• Begin your search by reading thorough and cohesive literature reviews. Review articles are great sources of information to get a broad perspective of your topic.
• Don’t read an article just to say you’ve read it. Annotate and take notes so you don’t have to re-read it later.
• Use software or paper-and-pencil approaches to write notes on articles.
• Annotation is best used when closely reading an empirical study highly similar to your research project.
• Select an empirical article highly related to the study you would like to conduct.
• Annotate the article using the aforementioned annotations and create some of your own.
• Create the first draft of a summary table with key information from this empirical study that you would like to compare to other empirical studies you closely read.

5.3 Generalizability and transferability of empirical results

• Define generalizability and transferability.
• Assess the generalizability and transferability to how researchers use the results from empirical research studies to make arguments about what is objectively true.
• Relate both concepts to the hierarchy of evidence and the types of articles in the scholarly literature

Now that you have read an empirical article in detail, it's important to put its results in conversation with the broader literature on your topic. In this chapter we discuss two important concepts-- generalizability and   transferability --and the interrelationship between the two. We also explain how these two properties of empirical data impact your literature review and evidence-based practice.

Generalizability

The figure below provides a common approach to assessing empirical evidence. As you move up the pyramid below, you can be more sure that the data contained in those studies generalizes to all people who experience the issue.

As we reviewed in Chapter 1, objective truth is true for everyone, regardless of context. In other words, objective truths generalize beyond the sample of people from whom data were collected to the larger population of people who experience the issue under examination. You can be much more sure that information from a systematic review or meta-analysis will generalize than something from a case study of a single person, pilot projects, and other studies that do not seek to establish generalizability.

The type of article listed here is also related to the types of research methods the authors used. While we cover many of these approaches in this textbook, some of them (like cohort studies) are somewhat less common in social work. Additionally, there is one important research method, survey design, that does not appear in this diagram. Finally, social work research uses many different types of qualitative research--some of which generates more generalizable data than others.

For a refresher on the different types of evidence available in each type of article, refer back to section 4.1. You'll recall the hierarchy of evidence as described by McNeese & Thyer (2004) [55]

• Systematic reviews and meta-analyses
• Randomized controlled trials
• Quasi-experimental studies
• Case-control and cohort studies
• Pre-experimental (or non-experimental) group studies
• Qualitative studies

Because there is further variation in the types of studies used by social work researchers, I expanded the hierarchy of evidence to cover a greater breadth of research methods in Figure 5.3.

Refined information from multiple sources

The top of the hierarchy represents refined scientific information or meta-research . Meta-research uses the scientific method to analyze and improve the scientific production of knowledge. For example, meta-analyses pull together samples of people from all high-quality studies on a given topic area creating a super-study with far more people than any single researcher could feasibly collect data from. Because scientists (and clinical experts) refine data across multiple studies, these represent the most generalizable research findings.

Of course, not all meta-analyses or systematic reviews are of good quality. As a peer reviewer for a scholarly journal, I have seen poor quality systematic reviews that make methodological mistakes—like not including relevant keywords—that lead to incorrect conclusions. Unfortunately, not all errors are caught in the peer review process, and not all limitations are acknowledged by the authors. Just because you are looking at a systematic review does not mean you are looking at THE OBJECTIVE TRUTH. Nevertheless, you can be pretty sure that results from these studies are generalizable to the population in the study’s research question.

A good way to visualize the process of sampling is by examining the procedure used for systematic reviews and meta-analyses to scientifically search for articles. In Figure 5.4 below, you can see how researchers conducting a systematic review identified a large pool of potentially relevant articles, downloaded and analyzed them for relevance, and in the end, analyzed only 71 articles in their systematic review out of a total of 1,589 potentially relevant articles. Because systematic reviews or meta-analyses are intended to make strong, generalizable conclusions, they often exclude studies that still contain good information.

In the process of selecting articles for a meta-analysis and systematic review, researchers may exclude articles with important information for a number of good reasons. No study is perfect, and all research methods decisions come with limitations--including meta-research. Authors conducting a meta-analysis cannot include a study unless researchers provide data for the authors to include in their meta-analysis, and many empirical journal articles do not make their data available. Additionally, a study’s intervention or measures may be a bit different than what researchers want to make conclusions about. This is a key truth applicable across all articles you read—who or what gets selected for analysis in a research project determines how well the project’s results generalize to everyone.

We will talk about this in future chapters as sampling, and in those chapters, we will learn which sampling approaches are intended to support generalizability and which are used for other purposes. For example, availability or convenience sampling is often used to get quick information while random sampling approaches are intended to support generalizability. It is impossible to know everything about your article right now, but by the end of this course, you will have the information you need to critically examine the generalizability of a sample.

Primary sources (empirical studies)

Because refined sources like systematic reviews exclude good studies, they are only a first step in getting to know a topic area. You will need to examine primary sources--the reports of researchers who conducted empirical studies--to make evidence-based conclusions about your topic. Figure 5.3 describes three different types of data and ranks them vertically based on how well you can be sure the information generalizes.

As we will discuss further in our chapter on causal explanations, a key factor in scientifically assessing what happened first. Researchers conducting intervention studies are causing change by providing therapy, housing, or whatever the intervention is and measuring the outcomes of that intervention after they happen. This is unlike survey researchers, who do not introduce an intervention but ask people to self-report information on a questionnaire. Longitudinal surveys are particularly helpful because they can provide a clearer picture of whether the cause came before the effect in a causal relationship, but because they are expensive and time-consuming to conduct, longitudinal studies are relatively rare in the literature and most surveys measure people at only one point in time. Thus, because researchers cannot tightly control the causal variable (an intervention, an experience of abuse, etc.) we can be somewhat less certain of the conclusions of surveys than experiments. At the same time, because surveys measure people in their naturalistic environment rather than in a laboratory or artificial setting, they may do a better job at reducing the potential for the researcher to influence the data a participant provides. Surveys also provide descriptive information--like the number of people with a diagnosis or risk factor--that experiments cannot provide.

Surveys and experiments are commonly used in social work, and we will describe the methods they use in future chapters. When assessing the generalizability of a given survey or experiment, you are looking at whether the methods used by the researchers improve generalizability (or, at least that those methods are intended to improve generalizability). Specifically, there are sampling, measurement, and design decisions that researchers make that can improve generalizability. And once the study is conducted, whether those methods worked as intended also impact generalizability.

We address sampling, measurement, and design in the coming chapters, and you will need more in-depth knowledge of research methods to assess the generalizability of the results you are reading. In the meantime, Figure 5.3 is organized by design, and this is a good starting point for your inquiry since it only requires you to identify the design in each empirical article--which should be included in the abstract and described in detail in the methods section. For more information on how to conduct sampling, measurement, and design in a way that maximizes generalizability, read Part 2 of this textbook.

When searching for design of a study, look for specific keywords that indicate the researcher used methods that do not generalize well like pilot study, pre-experiment, non-experiment, convenience sample, availability sample, and exploratory study. When researchers are seeking to perform a pilot study, they are optimizing for time, not generalizability. Their results may still be useful to you! But, you should not generalize from their study to all people with the issue under analysis without a lot of caution and additional supporting evidence. Instead, you should see whether the lessons from this study might transfer to the context in which you are researching--our next topic.

Qualitative studies use sampling, measures, and designs that do not try to optimize generalizability. Thus, if the results of a qualitative study indicate 10 out of 50 students who participated in the focus group found the mandatory training on harassment to be unhelpful, does that mean 20% of all college students at this university find it unhelpful? Because focus groups and interviews (and other qualitative methods we will discuss) use qualitative methods, they are not concerned with generalizability. It would not make sense to generalize from focus groups to all people in a population. Instead, focus groups methods optimize for trustworthy and authentic research projects that make sure, for example, all themes and quotes in the researcher's report are traceable to quotes from focus group participants. Instead of providing what is generally true, qualitative research provides a thick description of people's experiences so you can understand them. S ubjective inquiry is less generalizable but provides greater depth in understanding people's feelings, beliefs, and decision-making processes within their context. 

In Figure 5.3, you will note that some qualitative studies are ranked higher than others in terms of generalizability. Meta-syntheses are ranked highest because they are meta-research, pooling together the themes and raw data from multiple qualitative studies into a super-study. A meta-synthesis is the qualitative equivalent of a meta-analysis, which analyzes quantitative data. Because the researchers conducting the meta-syntheses aim to make more broad generalizations across research studies, even though generalizability is not strictly the goal. In a similar way, grounded theory studies (a type of qualitative design) aim to produce a testable hypothesis that could generalize. At the bottom of the hierarchy are individual case studies, which report what happens with a single person, organization, or event. It's best not to think too long about the generalizability of qualitative results. When examining qualitative articles, you should be examining their transferability, our topic for the next subsection.

Transferability

Generalizability asks one question: How well does the sample of people in this study represent everyone with this issue? If you read in a study that 50% of people in the sample experienced depression, does that mean 50% of everyone experiences depression? We previewed future discussions in this textbook that will discuss the specific quantitative research methods used to optimize the generalizability of results. By adhering strictly to best practices in sampling, measurement, and design, researchers can provide you with good evidence for the generalizability of their study's results.

Of course, generalizability is not the only question worth asking. Just because a study's sample represents a broader population does not mean it is helpful for making conclusions about your working question. In assessing a study's transferability, you are making a weaker but compelling argument that the conclusions of one study can be applied to understanding the people in your working question and research project. Generalizable results may be applicable because they are broadly transferable across situations, and you can be confident in that when they follow the best practices in this textbook for improving generalizability. However, there may be aspects of a study that make its results difficult to transfer to your topic area.

When evaluating the transferability of a research result to your working question, consider the sample, measures, and design. That is, how data was collected from individuals, who those individuals are, and what researchers did with them. You may find that the samples in generalizable studies do not talk about the specific ethnic, cultural, or geographic group that is in your working question. Similarly, studies that measure the outcomes of substance use treatment by measuring sobriety may not match your working question on moderation, medication adherence, or substitution as an outcome in substance use treatment. Evaluating the transferability of designs may help you identify whether the methods the authors used would be similar to those you might use if you were to conduct a study gathering and collecting your own raw data.

Assessing transferability is more subjective. You are using your knowledge of your topic area and research methods (which are always improving!) to make a reasonable argument about why a given piece of evidence from a primary source helps you understand something. Look back at Table 5.2, your annotations, and the researchers' sampling, data analysis, results, and design. Using your critical thinking (and the knowledge you can in Part 2 and Part 3 of this textbook) you will need to make a reasonable argument that these results transfer to the people, places, and culture that you are talking about in your working question.

In the final chapter of Part 1, we will discuss how to assemble the facts you have taken from journal articles into a literature review that represents what  you think about the topic.

• Developing your theoretical framework
• Conceptual definitions
• Inductive & deductive reasoning

Nomothetic causal explanations

Content warning: examples in this chapter include references to sexual harassment, domestic violence, gender-based violence, the child welfare system, substance use disorders, neonatal abstinence syndrome, child abuse, racism, and sexism.

11.1 Developing your theoretical framework

• Differentiate between theories that explain specific parts of the social world versus those that are more broad and sweeping in their conclusions
• Identify the theoretical perspectives that are relevant to your project and inform your thinking about it
• Define key concepts in your working question and develop a theoretical framework for how you understand your topic.

Theories provide a way of looking at the world and of understanding human interaction. Paradigms are grounded in big assumptions about the world—what is real, how do we create knowledge—whereas theories describe more specific phenomena. Well, we are still oversimplifying a bit. Some theories try to explain the whole world, while others only try to explain a small part. Some theories can be grouped together based on common ideas but retain their own individual and unique features. Our goal is to help you find a theoretical framework that helps you understand your topic more deeply and answer your working question.

Theories: Big and small

In your human behavior and the social environment (HBSE) class, you were introduced to the major theoretical perspectives that are commonly used in social work. These are what we like to call big-T 'T'heories. When you read about systems theory, you are actually reading a synthesis of decades of distinct, overlapping, and conflicting theories that can be broadly classified within systems theory. For example, within systems theory, some approaches focus more on family systems while others focus on environmental systems, though the core concepts remain similar.

Different theorists define concepts in their own way, and as a result, their theories may explore different relationships with those concepts. For example, Deci and Ryan's (1985) [56] self-determination theory discusses motivation and establishes that it is contingent on meeting one's needs for autonomy, competency, and relatedness. By contrast, ecological self-determination theory, as written by Abery & Stancliffe (1996), [57] argues that self-determination is the amount of control exercised by an individual over aspects of their lives they deem important across the micro, meso, and macro levels. If self-determination were an important concept in your study, you would need to figure out which of the many theories related to self-determination helps you address your working question.

Theories can provide a broad perspective on the key concepts and relationships in the world or more specific and applied concepts and perspectives. Table 7.2 summarizes two commonly used lists of big-T Theoretical perspectives in social work. See if you can locate some of the theories that might inform your project.

Competing theoretical explanations

Within each area of specialization in social work, there are many other theories that aim to explain more specific types of interactions. For example, within the study of sexual harassment, different theories posit different explanations for why harassment occurs.

One theory, first developed by criminologists, is called routine activities theory. It posits that sexual harassment is most likely to occur when a workplace lacks unified groups and when potentially vulnerable targets and motivated offenders are both present (DeCoster, Estes, & Mueller, 1999). [60]

Other theories of sexual harassment, called relational theories, suggest that one's existing relationships are the key to understanding why and how workplace sexual harassment occurs and how people will respond when it does occur (Morgan, 1999). [61] Relational theories focus on the power that different social relationships provide (e.g., married people who have supportive partners at home might be more likely than those who lack support at home to report sexual harassment when it occurs).

Finally, feminist theories of sexual harassment take a different stance. These theories posit that the organization of our current gender system, wherein those who are the most masculine have the most power, best explains the occurrence of workplace sexual harassment (MacKinnon, 1979). [62] As you might imagine, which theory a researcher uses to examine the topic of sexual harassment will shape the questions asked about harassment. It will also shape the explanations the researcher provides for why harassment occurs.

For a graduate student beginning their study of a new topic, it may be intimidating to learn that there are so many theories beyond what you’ve learned in your theory classes. What’s worse is that there is no central database of theories on your topic. However, as you review the literature in your area, you will learn more about the theories scientists have created to explain how your topic works in the real world. There are other good sources for theories, in addition to journal articles. Books often contain works of theoretical and philosophical importance that are beyond the scope of an academic journal. Do a search in your university library for books on your topic, and you are likely to find theorists talking about how to make sense of your topic. You don't necessarily have to agree with the prevailing theories about your topic, but you do need to be aware of them so you can apply theoretical ideas to your project.

Applying big-T theories to your topic

The key to applying theories to your topic is learning the key concepts associated with that theory and the relationships between those concepts, or propositions . Again, your HBSE class should have prepared you with some of the most important concepts from the theoretical perspectives listed in Table 7.2. For example, the conflict perspective sees the world as divided into dominant and oppressed groups who engage in conflict over resources. If you were applying these theoretical ideas to your project, you would need to identify which groups in your project are considered dominant or oppressed groups, and which resources they were struggling over. This is a very general example. Challenge yourself to find small-t theories about your topic that will help you understand it in much greater detail and specificity. If you have chosen a topic that is relevant to your life and future practice, you will be doing valuable work shaping your ideas towards social work practice.

Integrating theory into your project can be easy, or it can take a bit more effort. Some people have a strong and explicit theoretical perspective that they carry with them at all times. For me, you'll probably see my work drawing from exchange and choice, social constructionist, and critical theory. Maybe you have theoretical perspectives you naturally employ, like Afrocentric theory or person-centered practice. If so, that's a great place to start since you might already be using that theory (even subconsciously) to inform your understanding of your topic. But if you aren't aware of whether you are using a theoretical perspective when you think about your topic, try writing a paragraph off the top of your head or talking with a friend explaining what you think about that topic. Try matching it with some of the ideas from the broad theoretical perspectives from Table 7.2. This can ground you as you search for more specific theories. Some studies are designed to test whether theories apply the real world while others are designed to create new theories or variations on existing theories. Consider which feels more appropriate for your project and what you want to know.

Another way to easily identify the theories associated with your topic is to look at the concepts in your working question. Are these concepts commonly found in any of the theoretical perspectives in Table 7.2? Take a look at the Payne and Hutchison texts and see if any of those look like the concepts and relationships in your working question or if any of them match with how you think about your topic. Even if they don't possess the exact same wording, similar theories can help serve as a starting point to finding other theories that can inform your project. Remember, HBSE textbooks will give you not only the broad statements of theories but also sources from specific theorists and sub-theories that might be more applicable to your topic. Skim the references and suggestions for further reading once you find something that applies well.

Choose a theoretical perspective from Hutchison, Payne, or another theory textbook that is relevant to your project. Using their textbooks or other reputable sources, identify :

• At least five important concepts from the theory
• What relationships the theory establishes between these important concepts (e.g., as x increases, the y decreases)
• How you can use this theory to better understand the concepts and variables in your project?

Developing your own theoretical framework

Hutchison's and Payne's frameworks are helpful for surveying the whole body of literature relevant to social work, which is why they are so widely used. They are one framework, or way of thinking, about all of the theories social workers will encounter that are relevant to practice. Social work researchers should delve further and develop a theoretical or conceptual framework of their own based on their reading of the literature. In Chapter 8 , we will develop your theoretical framework further, identifying the cause-and-effect relationships that answer your working question. Developing a theoretical framework is also instructive for revising and clarifying your working question and identifying concepts that serve as keywords for additional literature searching. The greater clarity you have with your theoretical perspective, the easier each subsequent step in the research process will be.

Getting acquainted with the important theoretical concepts in a new area can be challenging. While social work education provides a broad overview of social theory, you will find much greater fulfillment out of reading about the theories related to your topic area. We discussed some strategies for finding theoretical information in Chapter 3 as part of literature searching. To extend that conversation a bit, some strategies for searching for theories in the literature include:

• Consider searching for these keywords in the title or abstract, specifically
• Looking at the references and cited by links within theoretical articles and textbooks
• Looking at books, edited volumes, and textbooks that discuss theory
• Talking with a scholar on your topic, or asking a professor if they can help connect you to someone
• Nice authors are clear about how they use theory to inform their research project, usually in the introduction and discussion section.
• For example, from the broad umbrella of systems theory, you might pick out family systems theory if you want to understand the effectiveness of a family counseling program.

It's important to remember that knowledge arises within disciplines, and that disciplines have different theoretical frameworks for explaining the same topic. While it is certainly important for the social work perspective to be a part of your analysis, social workers benefit from searching across disciplines to come to a more comprehensive understanding of the topic. Reaching across disciplines can provide uncommon insights during conceptualization, and once the study is completed, a multidisciplinary researcher will be able to share results in a way that speaks to a variety of audiences. A study by An and colleagues (2015) [63] uses game theory from the discipline of economics to understand problems in the Temporary Assistance for Needy Families (TANF) program. In order to receive TANF benefits, mothers must cooperate with paternity and child support requirements unless they have "good cause," as in cases of domestic violence, in which providing that information would put the mother at greater risk of violence. Game theory can help us understand how TANF recipients and caseworkers respond to the incentives in their environment, and highlight why the design of the "good cause" waiver program may not achieve its intended outcome of increasing access to benefits for survivors of family abuse.

Of course, there are natural limits on the depth with which student researchers can and should engage in a search for theory about their topic. At minimum, you should be able to draw connections across studies and be able to assess the relative importance of each theory within the literature. Just because you found one article applying your theory (like game theory, in our example above) does not mean it is important or often used in the domestic violence literature. Indeed, it would be much more common in the family violence literature to find psychological theories of trauma, feminist theories of power and control, and similar theoretical perspectives used to inform research projects rather than game theory, which is equally applicable to survivors of family violence as workers and bosses at a corporation. Consider using the Cited By feature to identify articles, books, and other sources of theoretical information that are seminal or well-cited in the literature. Similarly, by using the name of a theory in the keywords of a search query (along with keywords related to your topic), you can get a sense of how often the theory is used in your topic area. You should have a sense of what theories are commonly used to analyze your topic, even if you end up choosing a different one to inform your project.

Theories that are not cited or used as often are still immensely valuable. As we saw before with TANF and "good cause" waivers, using theories from other disciplines can produce uncommon insights and help you make a new contribution to the social work literature. Given the privileged position that the social work curriculum places on theories developed by white men, students may want to explore Afrocentricity as a social work practice theory (Pellebon, 2007) [64] or abolitionist social work (Jacobs et al., 2021) [65] when deciding on a theoretical framework for their research project that addresses concepts of racial justice. Start with your working question, and explain how each theory helps you answer your question. Some explanations are going to feel right, and some concepts will feel more salient to you than others. Keep in mind that this is an iterative process. Your theoretical framework will likely change as you continue to conceptualize your research project, revise your research question, and design your study.

By trying on many different theoretical explanations for your topic area, you can better clarify your own theoretical framework. Some of you may be fortunate enough to find theories that match perfectly with how you think about your topic, are used often in the literature, and are therefore relatively straightforward to apply. However, many of you may find that a combination of theoretical perspectives is most helpful for you to investigate your project. For example, maybe the group counseling program for which you are evaluating client outcomes draws from both motivational interviewing and cognitive behavioral therapy. In order to understand the change happening in the client population, you would need to know each theory separately as well as how they work in tandem with one another. Because theoretical explanations and even the definitions of concepts are debated by scientists, it may be helpful to find a specific social scientist or group of scientists whose perspective on the topic you find matches with your understanding of the topic. Of course, it is also perfectly acceptable to develop your own theoretical framework, though you should be able to articulate how your framework fills a gap within the literature.

If you are adapting theoretical perspectives in your study, it is important to clarify the original authors' definitions of each concept. Jabareen (2009) [66] offers that conceptual frameworks are not merely collections of concepts but, rather, constructs in which each concept plays an integral role. [67] A conceptual framework is a network of linked concepts that together provide a comprehensive understanding of a phenomenon. Each concept in a conceptual framework plays an ontological or epistemological role in the framework, and it is important to assess whether the concepts and relationships in your framework make sense together. As your framework takes shape, you will find yourself integrating and grouping together concepts, thinking about the most important or least important concepts, and how each concept is causally related to others.

Much like paradigm, theory plays a supporting role for the conceptualization of your research project. Recall the ice float from Figure 7.1. Theoretical explanations support the design and methods you use to answer your research question. In student projects that lack a theoretical framework, I often see the biases and errors in reasoning that we discussed in Chapter 1 that get in the way of good social science. That's because theories mark which concepts are important, provide a framework for understanding them, and measure their interrelationships. If you are missing this foundation, you will operate on informal observation, messages from authority, and other forms of unsystematic and unscientific thinking we reviewed in Chapter 1 .

Theory-informed inquiry is incredibly helpful for identifying key concepts and how to measure them in your research project, but there is a risk in aligning research too closely with theory. The theory-ladenness of facts and observations produced by social science research means that we may be making our ideas real through research. This is a potential source of confirmation bias in social science. Moreover, as Tan (2016) [68] demonstrates, social science often proceeds by adopting as true the perspective of Western and Global North countries, and cross-cultural research is often when ethnocentric and biased ideas are most visible . In her example, a researcher from the West studying teacher-centric classrooms in China that rely partially on rote memorization may view them as less advanced than student-centered classrooms developed in a Western country simply because of Western philosophical assumptions about the importance of individualism and self-determination. Developing a clear theoretical framework is a way to guard against biased research, and it will establish a firm foundation on which you will develop the design and methods for your study.

• Just as empirical evidence is important for conceptualizing a research project, so too are the key concepts and relationships identified by social work theory.
• Using theory your theory textbook will provide you with a sense of the broad theoretical perspectives in social work that might be relevant to your project.
• Try to find small-t theories that are more specific to your topic area and relevant to your working question.
• In Chapter 2 , you developed a concept map for your proposal. Take a moment to revisit your concept map now as your theoretical framework is taking shape. Make any updates to the key concepts and relationships in your concept map. . If you need a refresher, we have embedded a short how-to video from the University of Guelph Library (CC-BY-NC-SA 4.0) that we also used in Chapter 2 .

11.2 Conceptual definitions

• Define measurement and conceptualization
• Apply Kaplan’s three categories to determine the complexity of measuring a given variable
• Identify the role previous research and theory play in defining concepts
• Distinguish between unidimensional and multidimensional concepts
• Critically apply reification to how you conceptualize the key variables in your research project

In social science, when we use the term  measurement , we mean the process by which we describe and ascribe meaning to the key facts, concepts, or other phenomena that we are investigating. At its core, measurement is about defining one’s terms in as clear and precise a way as possible. Of course, measurement in social science isn’t quite as simple as using a measuring cup or spoon, but there are some basic tenets on which most social scientists agree when it comes to measurement. We’ll explore those, as well as some of the ways that measurement might vary depending on your unique approach to the study of your topic.

An important point here is that measurement does not require any particular instruments or procedures. What it does require is a systematic procedure for assigning scores, meanings, and descriptions to individuals or objects so that those scores represent the characteristic of interest. You can measure phenomena in many different ways, but you must be sure that how you choose to measure gives you information and data that lets you answer your research question. If you're looking for information about a person's income, but your main points of measurement have to do with the money they have in the bank, you're not really going to find the information you're looking for!

The question of what social scientists measure can be answered by asking yourself what social scientists study. Think about the topics you’ve learned about in other social work classes you’ve taken or the topics you’ve considered investigating yourself. Let’s consider Melissa Milkie and Catharine Warner’s study (2011) [69] of first graders’ mental health. In order to conduct that study, Milkie and Warner needed to have some idea about how they were going to measure mental health. What does mental health mean, exactly? And how do we know when we’re observing someone whose mental health is good and when we see someone whose mental health is compromised? Understanding how measurement works in research methods helps us answer these sorts of questions.

As you might have guessed, social scientists will measure just about anything that they have an interest in investigating. For example, those who are interested in learning something about the correlation between social class and levels of happiness must develop some way to measure both social class and happiness. Those who wish to understand how well immigrants cope in their new locations must measure immigrant status and coping. Those who wish to understand how a person’s gender shapes their workplace experiences must measure gender and workplace experiences (and get more specific about which experiences are under examination). You get the idea. Social scientists can and do measure just about anything you can imagine observing or wanting to study. Of course, some things are easier to observe or measure than others.

Observing your variables

In 1964, philosopher Abraham Kaplan (1964) [70] wrote The   Conduct of Inquiry,  which has since become a classic work in research methodology (Babbie, 2010). [71] In his text, Kaplan describes different categories of things that behavioral scientists observe. One of those categories, which Kaplan called “observational terms,” is probably the simplest to measure in social science. Observational terms are the sorts of things that we can see with the naked eye simply by looking at them. Kaplan roughly defines them as conditions that are easy to identify and verify through direct observation. If, for example, we wanted to know how the conditions of playgrounds differ across different neighborhoods, we could directly observe the variety, amount, and condition of equipment at various playgrounds.

Indirect observables , on the other hand, are less straightforward to assess. In Kaplan's framework, they are conditions that are subtle and complex that we must use existing knowledge and intuition to define. If we conducted a study for which we wished to know a person’s income, we’d probably have to ask them their income, perhaps in an interview or a survey. Thus, we have observed income, even if it has only been observed indirectly. Birthplace might be another indirect observable. We can ask study participants where they were born, but chances are good we won’t have directly observed any of those people being born in the locations they report.

Sometimes the measures that we are interested in are more complex and more abstract than observational terms or indirect observables. Think about some of the concepts you’ve learned about in other social work classes—for example, ethnocentrism. What is ethnocentrism? Well, from completing an introduction to social work class you might know that it has something to do with the way a person judges another’s culture. But how would you  measure  it? Here’s another construct: bureaucracy. We know this term has something to do with organizations and how they operate but measuring such a construct is trickier than measuring something like a person’s income. The theoretical concepts of ethnocentrism and bureaucracy represent ideas whose meanings we have come to agree on. Though we may not be able to observe these abstractions directly, we can observe their components.

Kaplan referred to these more abstract things that behavioral scientists measure as constructs.  Constructs  are “not observational either directly or indirectly” (Kaplan, 1964, p. 55), [72] but they can be defined based on observables. For example, the construct of bureaucracy could be measured by counting the number of supervisors that need to approve routine spending by public administrators. The greater the number of administrators that must sign off on routine matters, the greater the degree of bureaucracy. Similarly, we might be able to ask a person the degree to which they trust people from different cultures around the world and then assess the ethnocentrism inherent in their answers. We can measure constructs like bureaucracy and ethnocentrism by defining them in terms of what we can observe. [73]

The idea of coming up with your own measurement tool might sound pretty intimidating at this point. The good news is that if you find something in the literature that works for you, you can use it (with proper attribution, of course). If there are only pieces of it that you like, you can reuse those pieces (with proper attribution and describing/justifying any changes). You don't always have to start from scratch!

Look at the variables in your research question.

• Classify them as direct observables, indirect observables, or constructs.
• Do you think measuring them will be easy or hard?
• What are your first thoughts about how to measure each variable? No wrong answers here, just write down a thought about each variable.

Measurement starts with conceptualization

In order to measure the concepts in your research question, we first have to understand what we think about them. As an aside, the word concept  has come up quite a bit, and it is important to be sure we have a shared understanding of that term. A  concept is the notion or image that we conjure up when we think of some cluster of related observations or ideas. For example, masculinity is a concept. What do you think of when you hear that word? Presumably, you imagine some set of behaviors and perhaps even a particular style of self-presentation. Of course, we can’t necessarily assume that everyone conjures up the same set of ideas or images when they hear the word  masculinity . While there are many possible ways to define the term and some may be more common or have more support than others, there is no universal definition of masculinity. What counts as masculine may shift over time, from culture to culture, and even from individual to individual (Kimmel, 2008). This is why defining our concepts is so important.\

Not all researchers clearly explain their theoretical or conceptual framework for their study, but they should! Without understanding how a researcher has defined their key concepts, it would be nearly impossible to understand the meaning of that researcher’s findings and conclusions. Back in Chapter 7 , you developed a theoretical framework for your study based on a survey of the theoretical literature in your topic area. If you haven't done that yet, consider flipping back to that section to familiarize yourself with some of the techniques for finding and using theories relevant to your research question. Continuing with our example on masculinity, we would need to survey the literature on theories of masculinity. After a few queries on masculinity, I found a wonderful article by Wong (2010) [74] that analyzed eight years of the journal Psychology of Men & Masculinity and analyzed how often different theories of masculinity were used . Not only can I get a sense of which theories are more accepted and which are more marginal in the social science on masculinity, I am able to identify a range of options from which I can find the theory or theories that will inform my project. 

Identify a specific theory (or more than one theory) and how it helps you understand...

• Your independent variable(s).
• Your dependent variable(s).
• The relationship between your independent and dependent variables.

Rather than completing this exercise from scratch, build from your theoretical or conceptual framework developed in previous chapters.

In quantitative methods, conceptualization involves writing out clear, concise definitions for our key concepts. These are the kind of definitions you are used to, like the ones in a dictionary. A conceptual definition involves defining a concept in terms of other concepts, usually by making reference to how other social scientists and theorists have defined those concepts in the past. Of course, new conceptual definitions are created all the time because our conceptual understanding of the world is always evolving.

Conceptualization is deceptively challenging—spelling out exactly what the concepts in your research question mean to you. Following along with our example, think about what comes to mind when you read the term masculinity. How do you know masculinity when you see it? Does it have something to do with men or with social norms? If so, perhaps we could define masculinity as the social norms that men are expected to follow. That seems like a reasonable start, and at this early stage of conceptualization, brainstorming about the images conjured up by concepts and playing around with possible definitions is appropriate. However, this is just the first step. At this point, you should be beyond brainstorming for your key variables because you have read a good amount of research about them

In addition, we should consult previous research and theory to understand the definitions that other scholars have already given for the concepts we are interested in. This doesn’t mean we must use their definitions, but understanding how concepts have been defined in the past will help us to compare our conceptualizations with how other scholars define and relate concepts. Understanding prior definitions of our key concepts will also help us decide whether we plan to challenge those conceptualizations or rely on them for our own work. Finally, working on conceptualization is likely to help in the process of refining your research question to one that is specific and clear in what it asks. Conceptualization and operationalization (next section) are where "the rubber meets the road," so to speak, and you have to specify what you mean by the question you are asking. As your conceptualization deepens, you will often find that your research question becomes more specific and clear.

If we turn to the literature on masculinity, we will surely come across work by Michael Kimmel , one of the preeminent masculinity scholars in the United States. After consulting Kimmel’s prior work (2000; 2008), [75] we might tweak our initial definition of masculinity. Rather than defining masculinity as “the social norms that men are expected to follow,” perhaps instead we’ll define it as “the social roles, behaviors, and meanings prescribed for men in any given society at any one time” (Kimmel & Aronson, 2004, p. 503). [76] Our revised definition is more precise and complex because it goes beyond addressing one aspect of men’s lives (norms), and addresses three aspects: roles, behaviors, and meanings. It also implies that roles, behaviors, and meanings may vary across societies and over time. Using definitions developed by theorists and scholars is a good idea, though you may find that you want to define things your own way.

As you can see, conceptualization isn’t as simple as applying any random definition that we come up with to a term. Defining our terms may involve some brainstorming at the very beginning. But conceptualization must go beyond that, to engage with or critique existing definitions and conceptualizations in the literature. Once we’ve brainstormed about the images associated with a particular word, we should also consult prior work to understand how others define the term in question. After we’ve identified a clear definition that we’re happy with, we should make sure that every term used in our definition will make sense to others. Are there terms used within our definition that also need to be defined? If so, our conceptualization is not yet complete. Our definition includes the concept of "social roles," so we should have a definition for what those mean and become familiar with role theory to help us with our conceptualization. If we don't know what roles are, how can we study them?

Let's say we do all of that. We have a clear definition of the term masculinity with reference to previous literature and we also have a good understanding of the terms in our conceptual definition...then we're done, right? Not so fast. You’ve likely met more than one man in your life, and you’ve probably noticed that they are not the same, even if they live in the same society during the same historical time period. This could mean there are dimensions of masculinity. In terms of social scientific measurement, concepts can be said to have multiple dimensions  when there are multiple elements that make up a single concept. With respect to the term  masculinity , dimensions could based on gender identity, gender performance, sexual orientation, etc.. In any of these cases, the concept of masculinity would be considered to have multiple dimensions.

While you do not need to spell out every possible dimension of the concepts you wish to measure, it is important to identify whether your concepts are unidimensional (and therefore relatively easy to define and measure) or multidimensional (and therefore require multi-part definitions and measures). In this way, how you conceptualize your variables determines how you will measure them in your study. Unidimensional concepts are those that are expected to have a single underlying dimension. These concepts can be measured using a single measure or test. Examples include simple concepts such as a person’s weight, time spent sleeping, and so forth. 

One frustrating this is that there is no clear demarcation between concepts that are inherently unidimensional or multidimensional. Even something as simple as age could be broken down into multiple dimensions including mental age and chronological age, so where does conceptualization stop? How far down the dimensional rabbit hole do we have to go? Researchers should consider two things. First, how important is this variable in your study? If age is not important in your study (maybe it is a control variable), it seems like a waste of time to do a lot of work drawing from developmental theory to conceptualize this variable. A unidimensional measure from zero to dead is all the detail we need. On the other hand, if we were measuring the impact of age on masculinity, conceptualizing our independent variable (age) as multidimensional may provide a richer understanding of its impact on masculinity. Finally, your conceptualization will lead directly to your operationalization of the variable, and once your operationalization is complete, make sure someone reading your study could follow how your conceptual definitions informed the measures you chose for your variables. 

Write a conceptual definition for your independent and dependent variables.

• Cite and attribute definitions to other scholars, if you use their words.
• Describe how your definitions are informed by your theoretical framework.
• Place your definition in conversation with other theories and conceptual definitions commonly used in the literature.
• Are there multiple dimensions of your variables?
• Are any of these dimensions important for you to measure?

Do researchers actually know what we're talking about?

Conceptualization proceeds differently in qualitative research compared to quantitative research. Since qualitative researchers are interested in the understandings and experiences of their participants, it is less important for them to find one fixed definition for a concept before starting to interview or interact with participants. The researcher’s job is to accurately and completely represent how their participants understand a concept, not to test their own definition of that concept.

If you were conducting qualitative research on masculinity, you would likely consult previous literature like Kimmel’s work mentioned above. From your literature review, you may come up with a  working definition  for the terms you plan to use in your study, which can change over the course of the investigation. However, the definition that matters is the definition that your participants share during data collection. A working definition is merely a place to start, and researchers should take care not to think it is the only or best definition out there.

In qualitative inquiry, your participants are the experts (sound familiar, social workers?) on the concepts that arise during the research study. Your job as the researcher is to accurately and reliably collect and interpret their understanding of the concepts they describe while answering your questions. Conceptualization of concepts is likely to change over the course of qualitative inquiry, as you learn more information from your participants. Indeed, getting participants to comment on, extend, or challenge the definitions and understandings of other participants is a hallmark of qualitative research. This is the opposite of quantitative research, in which definitions must be completely set in stone before the inquiry can begin.

The contrast between qualitative and quantitative conceptualization is instructive for understanding how quantitative methods (and positivist research in general) privilege the knowledge of the researcher over the knowledge of study participants and community members. Positivism holds that the researcher is the "expert," and can define concepts based on their expert knowledge of the scientific literature. This knowledge is in contrast to the lived experience that participants possess from experiencing the topic under examination day-in, day-out. For this reason, it would be wise to remind ourselves not to take our definitions too seriously and be critical about the limitations of our knowledge.

Conceptualization must be open to revisions, even radical revisions, as scientific knowledge progresses. While I’ve suggested consulting prior scholarly definitions of our concepts, you should not assume that prior, scholarly definitions are more real than the definitions we create. Likewise, we should not think that our own made-up definitions are any more real than any other definition. It would also be wrong to assume that just because definitions exist for some concept that the concept itself exists beyond some abstract idea in our heads. Building on the paradigmatic ideas behind interpretivism and the critical paradigm, researchers call the assumption that our abstract concepts exist in some concrete, tangible way is known as reification . It explores the power dynamics behind how we can create reality by how we define it.

Returning again to our example of masculinity. Think about our how our notions of masculinity have developed over the past few decades, and how different and yet so similar they are to patriarchal definitions throughout history. Conceptual definitions become more or less popular based on the power arrangements inside of social science the broader world. Western knowledge systems are privileged, while others are viewed as unscientific and marginal. The historical domination of social science by white men from WEIRD countries meant that definitions of masculinity were imbued their cultural biases and were designed explicitly and implicitly to preserve their power. This has inspired movements for cognitive justice as we seek to use social science to achieve global development.

• Measurement is the process by which we describe and ascribe meaning to the key facts, concepts, or other phenomena that we are investigating.
• Kaplan identified three categories of things that social scientists measure including observational terms, indirect observables, and constructs.
• Some concepts have multiple elements or dimensions.
• Researchers often use measures previously developed and studied by other researchers.
• Conceptualization is a process that involves coming up with clear, concise definitions.
• Conceptual definitions are based on the theoretical framework you are using for your study (and the paradigmatic assumptions underlying those theories).
• Whether your conceptual definitions come from your own ideas or the literature, you should be able to situate them in terms of other commonly used conceptual definitions.
• Researchers should acknowledge the limited explanatory power of their definitions for concepts and how oppression can shape what explanations are considered true or scientific.

Think historically about the variables in your research question.

• How has our conceptual definition of your topic changed over time?
• What scholars or social forces were responsible for this change?

Take a critical look at your conceptual definitions.

• How participants might define terms for themselves differently, in terms of their daily experience?
• On what cultural assumptions are your conceptual definitions based?
• Are your conceptual definitions applicable across all cultures that will be represented in your sample?

11.3 Inductive and deductive reasoning

• Describe inductive and deductive reasoning and provide examples of each
• Identify how inductive and deductive reasoning are complementary

Congratulations! You survived the chapter on theories and paradigms. My experience has been that many students have a difficult time thinking about theories and paradigms because they perceive them as "intangible" and thereby hard to connect to social work research. I even had one student who said she got frustrated just reading the word "philosophy."

Rest assured, you do not need to become a theorist or philosopher to be an effective social worker or researcher. However, you should have a good sense of what theory or theories will be relevant to your project, as well as how this theory, along with your working question, fit within the three broad research paradigms we reviewed. If you don't have a good idea about those at this point, it may be a good opportunity to pause and read more about the theories related to your topic area.

Theories structure and inform social work research. The converse is also true: research can structure and inform theory. The reciprocal relationship between theory and research often becomes evident to students when they consider the relationships between theory and research in inductive and deductive approaches to research. In both cases, theory is crucial. But the relationship between theory and research differs for each approach.

While inductive and deductive approaches to research are quite different, they can also be complementary. Let’s start by looking at each one and how they differ from one another. Then we’ll move on to thinking about how they complement one another.

Inductive reasoning

A researcher using inductive reasoning begins by collecting data that is relevant to their topic of interest. Once a substantial amount of data have been collected, the researcher will then step back from data collection to get a bird’s eye view of their data. At this stage, the researcher looks for patterns in the data, working to develop a theory that could explain those patterns. Thus, when researchers take an inductive approach, they start with a particular set of observations and move to a more general set of propositions about those experiences. In other words, they move from data to theory, or from the specific to the general. Figure 8.1 outlines the steps involved with an inductive approach to research.

There are many good examples of inductive research, but we’ll look at just a few here. One fascinating study in which the researchers took an inductive approach is Katherine Allen, Christine Kaestle, and Abbie Goldberg’s (2011) [77] study of how boys and young men learn about menstruation. To understand this process, Allen and her colleagues analyzed the written narratives of 23 young cisgender men in which the men described how they learned about menstruation, what they thought of it when they first learned about it, and what they think of it now. By looking for patterns across all 23 cisgender men’s narratives, the researchers were able to develop a general theory of how boys and young men learn about this aspect of girls’ and women’s biology. They conclude that sisters play an important role in boys’ early understanding of menstruation, that menstruation makes boys feel somewhat separated from girls, and that as they enter young adulthood and form romantic relationships, young men develop more mature attitudes about menstruation. Note how this study began with the data—men’s narratives of learning about menstruation—and worked to develop a theory.

In another inductive study, Kristin Ferguson and colleagues (Ferguson, Kim, & McCoy, 2011) [78] analyzed empirical data to better understand how to meet the needs of young people who are homeless. The authors analyzed focus group data from 20 youth at a homeless shelter. From these data they developed a set of recommendations for those interested in applied interventions that serve homeless youth. The researchers also developed hypotheses for others who might wish to conduct further investigation of the topic. Though Ferguson and her colleagues did not test their hypotheses, their study ends where most deductive investigations begin: with a theory and a hypothesis derived from that theory. Section 8.4 discusses the use of mixed methods research as a way for researchers to test hypotheses created in a previous component of the same research project.

You will notice from both of these examples that inductive reasoning is most commonly found in studies using qualitative methods, such as focus groups and interviews. Because inductive reasoning involves the creation of a new theory, researchers need very nuanced data on how the key concepts in their working question operate in the real world. Qualitative data is often drawn from lengthy interactions and observations with the individuals and phenomena under examination. For this reason, inductive reasoning is most often associated with qualitative methods, though it is used in both quantitative and qualitative research.

Deductive reasoning

If inductive reasoning is about creating theories from raw data, deductive reasoning is about testing theories using data. Researchers using deductive reasoning take the steps described earlier for inductive research and reverse their order. They start with a compelling social theory, create a hypothesis about how the world should work, collect raw data, and analyze whether their hypothesis was confirmed or not. That is, deductive approaches move from a more general level (theory) to a more specific (data); whereas inductive approaches move from the specific (data) to general (theory).

A deductive approach to research is the one that people typically associate with scientific investigation. Students in English-dominant countries that may be confused by inductive vs. deductive research can rest part of the blame on Sir Arthur Conan Doyle, creator of the Sherlock Holmes character. As Craig Vasey points out in his breezy introduction to logic book chapter , Sherlock Holmes more often used inductive rather than deductive reasoning (despite claiming to use the powers of deduction to solve crimes). By noticing subtle details in how people act, behave, and dress, Holmes finds patterns that others miss. Using those patterns, he creates a theory of how the crime occurred, dramatically revealed to the authorities just in time to arrest the suspect. Indeed, it is these flashes of insight into the patterns of data that make Holmes such a keen inductive reasoner. In social work practice, rather than detective work, inductive reasoning is supported by the intuitions and practice wisdom of social workers, just as Holmes' reasoning is sharpened by his experience as a detective.

So, if deductive reasoning isn't Sherlock Holmes' observation and pattern-finding, how does it work? It starts with what you have already done in Chapters 3 and 4, reading and evaluating what others have done to study your topic. It continued with Chapter 5, discovering what theories already try to explain how the concepts in your working question operate in the real world. Tapping into this foundation of knowledge on their topic, the researcher studies what others have done, reads existing theories of whatever phenomenon they are studying, and then tests hypotheses that emerge from those theories. Figure 8.2 outlines the steps involved with a deductive approach to research.

While not all researchers follow a deductive approach, many do. We’ll now take a look at a couple excellent recent examples of deductive research. 

In a study of US law enforcement responses to hate crimes, Ryan King and colleagues (King, Messner, & Baller, 2009) [79] hypothesized that law enforcement’s response would be less vigorous in areas of the country that had a stronger history of racial violence. The authors developed their hypothesis from prior research and theories on the topic. They tested the hypothesis by analyzing data on states’ lynching histories and hate crime responses. Overall, the authors found support for their hypothesis and illustrated an important application of critical race theory.

In another recent deductive study, Melissa Milkie and Catharine Warner (2011) [80] studied the effects of different classroom environments on first graders’ mental health. Based on prior research and theory, Milkie and Warner hypothesized that negative classroom features, such as a lack of basic supplies and heat, would be associated with emotional and behavioral problems in children. One might associate this research with Maslow's hierarchy of needs or systems theory. The researchers found support for their hypothesis, demonstrating that policymakers should be paying more attention to the mental health outcomes of children’s school experiences, just as they track academic outcomes (American Sociological Association, 2011). [81]

Complementary approaches

While inductive and deductive approaches to research seem quite different, they can actually be rather complementary. In some cases, researchers will plan for their study to include multiple components, one inductive and the other deductive. In other cases, a researcher might begin a study with the plan to conduct either inductive or deductive research, but then discovers along the way that the other approach is needed to help illuminate findings. Here is an example of each such case.

Dr. Amy Blackstone (n.d.), author of Principles of sociological inquiry: Qualitative and quantitative methods , relates a story about her mixed methods research on sexual harassment.

We began the study knowing that we would like to take both a deductive and an inductive approach in our work. We therefore administered a quantitative survey, the responses to which we could analyze in order to test hypotheses, and also conducted qualitative interviews with a number of the survey participants. The survey data were well suited to a deductive approach; we could analyze those data to test hypotheses that were generated based on theories of harassment. The interview data were well suited to an inductive approach; we looked for patterns across the interviews and then tried to make sense of those patterns by theorizing about them. For one paper (Uggen & Blackstone, 2004) [82] , we began with a prominent feminist theory of the sexual harassment of adult women and developed a set of hypotheses outlining how we expected the theory to apply in the case of younger women’s and men’s harassment experiences. We then tested our hypotheses by analyzing the survey data. In general, we found support for the theory that posited that the current gender system, in which heteronormative men wield the most power in the workplace, explained workplace sexual harassment—not just of adult women but of younger women and men as well. In a more recent paper (Blackstone, Houle, & Uggen, 2006), [83] we did not hypothesize about what we might find but instead inductively analyzed interview data, looking for patterns that might tell us something about how or whether workers’ perceptions of harassment change as they age and gain workplace experience. From this analysis, we determined that workers’ perceptions of harassment did indeed shift as they gained experience and that their later definitions of harassment were more stringent than those they held during adolescence. Overall, our desire to understand young workers’ harassment experiences fully—in terms of their objective workplace experiences, their perceptions of those experiences, and their stories of their experiences—led us to adopt both deductive and inductive approaches in the work. (Blackstone, n.d., p. 21) [84]

Researchers may not always set out to employ both approaches in their work but sometimes find that their use of one approach leads them to the other. One such example is described eloquently in Russell Schutt’s  Investigating the Social World (2006). [85] As Schutt describes, researchers Sherman and Berk (1984) [86] conducted an experiment to test two competing theories of the effects of punishment on deterring deviance (in this case, domestic violence).Specifically, Sherman and Berk hypothesized that deterrence   theory (see Williams, 2005 [87] for more information on that theory) would provide a better explanation of the effects of arresting accused batterers than labeling theory . Deterrence theory predicts that arresting an accused spouse batterer will  reduce  future incidents of violence. Conversely, labeling theory predicts that arresting accused spouse batterers will  increase  future incidents (see Policastro & Payne, 2013 [88] for more information on that theory). Figure 8.3 summarizes the two competing theories and the hypotheses Sherman and Berk set out to test.

Research from these follow-up studies were mixed. In some cases, arrest deterred future incidents of violence. In other cases, it did not. This left the researchers with new data that they needed to explain. The researchers therefore took an inductive approach in an effort to make sense of their latest empirical observations. The new studies revealed that arrest seemed to have a deterrent effect for those who were married and employed, but that it led to increased offenses for those who were unmarried and unemployed. Researchers thus turned to control theory, which posits that having some stake in conformity through the social ties provided by marriage and employment, as the better explanation (see Davis et al., 2000 [90] for more information on this theory).

What the original Sherman and Berk study, along with the follow-up studies, show us is that we might start with a deductive approach to research, but then, if confronted by new data we must make sense of, we may move to an inductive approach. We will expand on these possibilities in section 8.4 when we discuss mixed methods research.

Ethical and critical considerations

Deductive and inductive reasoning, just like other components of the research process comes with ethical and cultural considerations for researchers. Specifically, deductive research is limited by existing theory. Because scientific inquiry has been shaped by oppressive forces such as sexism, racism, and colonialism, what is considered theory is largely based in Western, white-male-dominant culture. Thus, researchers doing deductive research may artificially limit themselves to ideas that were derived from this context. Non-Western researchers, international social workers, and practitioners working with non-dominant groups may find deductive reasoning of limited help if theories do not adequately describe other cultures.

While these flaws in deductive research may make inductive reasoning seem more appealing, on closer inspection you'll find similar issues apply. A researcher using inductive reasoning applies their intuition and lived experience when analyzing participant data. They will take note of particular themes, conceptualize their definition, and frame the project using their unique psychology. Since everyone's internal world is shaped by their cultural and environmental context, inductive reasoning conducted by Western researchers may unintentionally reinforcing lines of inquiry that derive from cultural oppression.

Inductive reasoning is also shaped by those invited to provide the data to be analyzed. For example, I recently worked with a student who wanted to understand the impact of child welfare supervision on children born dependent on opiates and methamphetamine. Due to the potential harm that could come from interviewing families and children who are in foster care or under child welfare supervision, the researcher decided to use inductive reasoning and to only interview child welfare workers.

Talking to practitioners is a good idea for feasibility, as they are less vulnerable than clients. However, any theory that emerges out of these observations will be substantially limited, as it would be devoid of the perspectives of parents, children, and other community members who could provide a more comprehensive picture of the impact of child welfare involvement on children. Notice that each of these groups has less power than child welfare workers in the service relationship. Attending to which groups were used to inform the creation of a theory and the power of those groups is an important critical consideration for social work researchers.

As you can see, when researchers apply theory to research they must wrestle with the history and hierarchy around knowledge creation in that area. In deductive studies, the researcher is positioned as the expert, similar to the positivist paradigm presented in Chapter 5. We've discussed a few of the limitations on the knowledge of researchers in this subsection, but the position of the "researcher as expert" is inherently problematic. However, it should also not be taken to an extreme. A researcher who approaches inductive inquiry as a naïve learner is also inherently problematic. Just as competence in social work practice requires a baseline of knowledge prior to entering practice, so does competence in social work research. Because a truly naïve intellectual position is impossible—we all have preexisting ways we view the world and are not fully aware of how they may impact our thoughts—researchers should be well-read in the topic area of their research study but humble enough to know that there is always much more to learn.

• Inductive reasoning begins with a set of empirical observations, seeking patterns in those observations, and then theorizing about those patterns.
• Deductive reasoning begins with a theory, developing hypotheses from that theory, and then collecting and analyzing data to test the truth of those hypotheses.
• Inductive and deductive reasoning can be employed together for a more complete understanding of the research topic.
• Though researchers don’t always set out to use both inductive and deductive reasoning in their work, they sometimes find that new questions arise in the course of an investigation that can best be answered by employing both approaches.
• Identify one theory and how it helps you understand your topic and working question.

I encourage you to find a specific theory from your topic area, rather than relying only on the broad theoretical perspectives like systems theory or the strengths perspective. Those broad theoretical perspectives are okay...but I promise that searching for theories about your topic will help you conceptualize and design your research project.

• Using the theory you identified, describe what you expect the answer to be to your working question.
• Define and provide an example of idiographic causal relationships
• Describe the role of causality in quantitative research as compared to qualitative research
• Identify, define, and describe each of the main criteria for nomothetic causal relationships
• Describe the difference between and provide examples of independent, dependent, and control variables
• Define hypothesis, state a clear hypothesis, and discuss the respective roles of quantitative and qualitative research when it comes to hypotheses

Causality  refers to the idea that one event, behavior, or belief will result in the occurrence of another, subsequent event, behavior, or belief. In other words, it is about cause and effect. It seems simple, but you may be surprised to learn there is more than one way to explain how one thing causes another. How can that be? How could there be many ways to understand causality?

Think back to our discussion in Section 5.3 on paradigms [insert chapter link plus link to section 1.2]. You’ll remember the positivist paradigm as the one that believes in objectivity. Positivists look for causal explanations that are universally true for everyone, everywhere  because they seek objective truth. Interpretivists, on the other hand, look for causal explanations that are true for individuals or groups in a specific time and place because they seek subjective truths. Remember that for interpretivists, there is not one singular truth that is true for everyone, but many truths created and shared by others.

"Are you trying to generalize or nah?"

One of my favorite classroom moments occurred in the early days of my teaching career. Students were providing peer feedback on their working questions. I overheard one group who was helping someone rephrase their research question. A student asked, “Are you trying to generalize or nah?” Teaching is full of fun moments like that one. Answering that one question can help you understand how to conceptualize and design your research project.

Nomothetic causal explanations are incredibly powerful. They allow scientists to make predictions about what will happen in the future, with a certain margin of error. Moreover, they allow scientists to generalize —that is, make claims about a large population based on a smaller sample of people or items. Generalizing is important. We clearly do not have time to ask everyone their opinion on a topic or test a new intervention on every person. We need a type of causal explanation that helps us predict and estimate truth in all situations.

Generally, nomothetic causal relationships work best for explanatory research projects [INSERT SECTION LINK]. They also tend to use quantitative research: by boiling things down to numbers, one can use the universal language of mathematics to use statistics to explore those relationships. On the other hand, descriptive and exploratory projects often fit better with idiographic causality. These projects do not usually try to generalize, but instead investigate what is true for individuals, small groups, or communities at a specific point in time. You will learn about this type of causality in the next section. Here, we will assume you have an explanatory working question. For example, you may want to know about the risk and protective factors for a specific diagnosis or how a specific therapy impacts client outcomes.

What do nomothetic causal explanations look like?

Nomothetic causal explanations express relationships between variables . The term variable has a scientific definition. This one from Gillespie & Wagner (2018) "a logical grouping of attributes that can be observed and measured and is expected to vary from person to person in a population" (p. 9). [91] More practically, variables are the key concepts in your working question. You know, the things you plan to observe when you actually do your research project, conduct your surveys, complete your interviews, etc. These things have two key properties. First, they vary , as in they do not remain constant. "Age" varies by number. "Gender" varies by category. But they both vary. Second, they have attributes . So the variable "health professions" has attributes or categories, such as social worker, nurse, counselor, etc.

It's also worth reviewing what is  not a variable. Well, things that don't change (or vary) aren't variables. If you planned to do a study on how gender impacts earnings but your study only contained women, that concept would not vary . Instead, it would be a constant . Another common mistake I see in students' explanatory questions is mistaking an attribute for a variable. "Men" is not a variable. "Gender" is a variable. "Virginia" is not a variable. The variable is the "state or territory" in which someone or something is physically located.

When one variable causes another, we have what researchers call independent and dependent variables. For example, in a study investigating the impact of spanking on aggressive behavior, spanking would be the independent variable and aggressive behavior would be the dependent variable. An independent variable is the cause, and a  dependent variable  is the effect. Why are they called that? Dependent variables  depend on independent variables. If all of that gets confusing, just remember the graphical relationship in Figure 8.5.

Write out your working question, as it exists now. As we said previously in the subsection, we assume you have an explanatory research question for learning this section.

• Write out a diagram similar to Figure 8.5.
• Put your independent variable on the left and the dependent variable on the right.
• Can your variables vary?
• Do they have different attributes or categories that vary from person to person?
• How does the theory you identified in section 8.1 help you understand this causal relationship?

If the theory you've identified isn't much help to you or seems unrelated, it's a good indication that you need to read more literature about the theories related to your topic.

For some students, your working question may not be specific enough to list an independent or dependent variable clearly. You may have "risk factors" in place of an independent variable, for example. Or "effects" as a dependent variable. If that applies to your research question, get specific for a minute even if you have to revise this later. Think about which specific risk factors or effects you are interested in. Consider a few options for your independent and dependent variable and create diagrams similar to Figure 8.5.

Finally, you are likely to revisit your working question so you may have to come back to this exercise to clarify the causal relationship you want to investigate.

For a ten-cent word like "nomothetic," these causal relationships should look pretty basic to you. They should look like "x causes y." Indeed, you may be looking at your causal explanation and thinking, "wow, there are so many other things I'm missing in here." In fact, maybe my dependent variable sometimes causes changes in my independent variable! For example, a working question asking about poverty and education might ask how poverty makes it more difficult to graduate college or how high college debt impacts income inequality after graduation. Nomothetic causal relationships are slices of reality. They boil things down to two (or often more) key variables and assert a one-way causal explanation between them. This is by design, as they are trying to generalize across all people to all situations. The more complicated, circular, and often contradictory causal explanations are idiographic, which we will cover in the next section of this chapter.

Developing a hypothesis

A hypothesis   is a statement describing a researcher’s expectation regarding what they anticipate finding. Hypotheses in quantitative research are a nomothetic causal relationship that the researcher expects to determine is true or false. A hypothesis is written to describe the expected relationship between the independent and dependent variables. In other words, write the answer to your working question using your variables. That's your hypothesis! Make sure you haven't introduced new variables into your hypothesis that are not in your research question. If you have, write out your hypothesis as in Figure 8.5.

A good hypothesis should be testable using social science research methods. That is, you can use a social science research project (like a survey or experiment) to test whether it is true or not. A good hypothesis is also  specific about the relationship it explores. For example, a student project that hypothesizes, "families involved with child welfare agencies will benefit from Early Intervention programs," is not specific about what benefits it plans to investigate. For this student, I advised her to take a look at the empirical literature and theory about Early Intervention and see what outcomes are associated with these programs. This way, she could  more clearly state the dependent variable in her hypothesis, perhaps looking at reunification, attachment, or developmental milestone achievement in children and families under child welfare supervision.

Your hypothesis should be an informed prediction based on a theory or model of the social world. For example, you may hypothesize that treating mental health clients with warmth and positive regard is likely to help them achieve their therapeutic goals. That hypothesis would be based on the humanistic practice models of Carl Rogers. Using previous theories to generate hypotheses is an example of deductive research. If Rogers’ theory of unconditional positive regard is accurate, a study comparing clinicians who used it versus those who did not would show more favorable treatment outcomes for clients receiving unconditional positive regard.

Let’s consider a couple of examples. In research on sexual harassment (Uggen & Blackstone, 2004), [92] one might hypothesize, based on feminist theories of sexual harassment, that more females than males will experience specific sexually harassing behaviors. What is the causal relationship being predicted here? Which is the independent and which is the dependent variable? In this case, researchers hypothesized that a person’s sex (independent variable) would predict their likelihood to experience sexual harassment (dependent variable).

Sometimes researchers will hypothesize that a relationship will take a specific direction. As a result, an increase or decrease in one area might be said to cause an increase or decrease in another. For example, you might choose to study the relationship between age and support for legalization of marijuana. Perhaps you’ve taken a sociology class and, based on the theories you’ve read, you hypothesize that age is negatively related to support for marijuana legalization. [93] What have you just hypothesized?

You have hypothesized that as people get older, the likelihood of their supporting marijuana legalization decreases. Thus, as age (your independent variable) moves in one direction (up), support for marijuana legalization (your dependent variable) moves in another direction (down). So, a direct relationship (or positive correlation) involve two variables going in the same direction and an inverse relationship (or negative correlation) involve two variables going in opposite directions. If writing hypotheses feels tricky, it is sometimes helpful to draw them out and depict each of the two hypotheses we have just discussed.

It’s important to note that once a study starts, it is unethical to change your hypothesis to match the data you find. For example, what happens if you conduct a study to test the hypothesis from Figure 8.7 on support for marijuana legalization, but you find no relationship between age and support for legalization? It means that your hypothesis was incorrect, but that’s still valuable information. It would challenge what the existing literature says on your topic, demonstrating that more research needs to be done to figure out the factors that impact support for marijuana legalization. Don’t be embarrassed by negative results, and definitely don’t change your hypothesis to make it appear correct all along!

Criteria for establishing a nomothetic causal relationship

Let’s say you conduct your study and you find evidence that supports your hypothesis, as age increases, support for marijuana legalization decreases. Success! Causal explanation complete, right? Not quite.

You’ve only established one of the criteria for causality. The criteria for causality must include all of the following: covariation, plausibility, temporality, and nonspuriousness. In our example from Figure 8.7, we have established only one criteria—covariation. When variables covary , they vary together. Both age and support for marijuana legalization vary in our study. Our sample contains people of varying ages and varying levels of support for marijuana legalization. If, for example, we only included 16-year-olds in our study, age would be a  constant , not a variable.

Just because there might be some correlation between two variables does not mean that a causal relationship between the two is really plausible. Plausibility means that in order to make the claim that one event, behavior, or belief causes another, the claim has to make sense. It makes sense that people from previous generations would have different attitudes towards marijuana than younger generations. People who grew up in the time of Reefer Madness or the hippies may hold different views than those raised in an era of legalized medicinal and recreational use of marijuana. Plausibility is of course helped by basing your causal explanation in existing theoretical and empirical findings.

Once we’ve established that there is a plausible relationship between the two variables, we also need to establish whether the cause occurred before the effect, the criterion of temporality . A person’s age is a quality that appears long before any opinions on drug policy, so temporally the cause comes before the effect. It wouldn’t make any sense to say that support for marijuana legalization makes a person’s age increase. Even if you could predict someone’s age based on their support for marijuana legalization, you couldn’t say someone’s age was caused by their support for legalization of marijuana.

Finally, scientists must establish nonspuriousness. A spurious relationship is one in which an association between two variables appears to be causal but can in fact be explained by some third variable. This third variable is often called a confound or confounding variable because it clouds and confuses the relationship between your independent and dependent variable, making it difficult to discern the true causal relationship is.

Continuing with our example, we could point to the fact that older adults are less likely to have used marijuana recreationally. Maybe it is actually recreational use of marijuana that leads people to be more open to legalization, not their age. In this case, our confounding variable would be recreational marijuana use. Perhaps the relationship between age and attitudes towards legalization is a spurious relationship that is accounted for by previous use. This is also referred to as the third variable problem , where a seemingly true causal relationship is actually caused by a third variable not in the hypothesis. In this example, the relationship between age and support for legalization could be more about having tried marijuana than the age of the person.

Quantitative researchers are sensitive to the effects of potentially spurious relationships. As a result, they will often measure these third variables in their study, so they can control for their effects in their statistical analysis. These are called  control variables , and they refer to potentially confounding variables whose effects are controlled for mathematically in the data analysis process. Control variables can be a bit confusing, and we will discuss them more in Chapter 10, but think about it as an argument between you, the researcher, and a critic.

Researcher: “The older a person is, the less likely they are to support marijuana legalization.” Critic: “Actually, it’s more about whether a person has used marijuana before. That is what truly determines whether someone supports marijuana legalization.” Researcher: “Well, I measured previous marijuana use in my study and mathematically controlled for its effects in my analysis. Age explains most of the variation in attitudes towards marijuana legalization.”

Let’s consider a few additional, real-world examples of spuriousness. Did you know, for example, that high rates of ice cream sales have been shown to cause drowning? Of course, that’s not really true, but there is a positive relationship between the two. In this case, the third variable that causes both high ice cream sales and increased deaths by drowning is time of year, as the summer season sees increases in both (Babbie, 2010). [94]

Here’s another good one: it is true that as the salaries of Presbyterian ministers in Massachusetts rise, so too does the price of rum in Havana, Cuba. Well, duh, you might be saying to yourself. Everyone knows how much ministers in Massachusetts love their rum, right? Not so fast. Both salaries and rum prices have increased, true, but so has the price of just about everything else (Huff & Geis, 1993). [95]

Finally, research shows that the more firefighters present at a fire, the more damage is done at the scene. What this statement leaves out, of course, is that as the size of a fire increases so too does the amount of damage caused as does the number of firefighters called on to help (Frankfort-Nachmias & Leon-Guerrero, 2011). [96] In each of these examples, it is the presence of a confounding variable that explains the apparent relationship between the two original variables.

In sum, the following criteria must be met for a nomothetic causal relationship:

• The two variables must vary together.
• The relationship must be plausible.
• The cause must precede the effect in time.
• The relationship must be nonspurious (not due to a confounding variable).

The hypothetico-dedutive method

The primary way that researchers in the positivist paradigm use theories is sometimes called the hypothetico-deductive method (although this term is much more likely to be used by philosophers of science than by scientists themselves). Researchers choose an existing theory. Then, they make a prediction about some new phenomenon that should be observed if the theory is correct. Again, this prediction is called a hypothesis. The researchers then conduct an empirical study to test the hypothesis. Finally, they reevaluate the theory in light of the new results and revise it if necessary.

This process is usually conceptualized as a cycle because the researchers can then derive a new hypothesis from the revised theory, conduct a new empirical study to test the hypothesis, and so on. As Figure 8.8 shows, this approach meshes nicely with the process of conducting a research project—creating a more detailed model of “theoretically motivated” or “theory-driven” research. Together, they form a model of theoretically motivated research. 

Keep in mind the hypothetico-deductive method is only one way of using social theory to inform social science research. It starts with describing one or more existing theories, deriving a hypothesis from one of those theories, testing your hypothesis in a new study, and finally reevaluating the theory based on the results data analyses. This format works well when there is an existing theory that addresses the research question—especially if the resulting hypothesis is surprising or conflicts with a hypothesis derived from a different theory.

But what if your research question is more interpretive? What if it is less about theory-testing and more about theory-building? This is what our next chapters will cover: the process of inductively deriving theory from people's stories and experiences. This process looks different than that depicted in Figure 8.8. It still starts with your research question and answering that question by conducting a research study. But instead of testing a hypothesis you created based on a theory, you will create a theory of your own that explain the data you collected. This format works well for qualitative research questions and for research questions that existing theories do not address.

• In positivist and quantitative studies, the goal is often to understand the more general causes of some phenomenon rather than the idiosyncrasies of one particular instance, as in an idiographic causal relationship.
• Nomothetic causal explanations focus on objectivity, prediction, and generalization.
• Criteria for nomothetic causal relationships require the relationship be plausible and nonspurious; and that the cause must precede the effect in time.
• In a nomothetic causal relationship, the independent variable causes changes in the dependent variable.
• Hypotheses are statements, drawn from theory, which describe a researcher’s expectation about a relationship between two or more variables.
• Write out your working question and hypothesis.
• Defend your hypothesis in a short paragraph, using arguments based on the theory you identified in section 8.1.
• Review the criteria for a nomothetic causal relationship. Critique your short paragraph about your hypothesis using these criteria.
• Are there potentially confounding variables, issues with time order, or other problems you can identify in your reasoning?

Inductive & deductive (deductive focus)

9. Writing your research question Copyright © 2020 by Matthew DeCarlo is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Frequently asked questions

What makes a good research question.

Research questions anchor your whole project, so it’s important to spend some time refining them.

In general, they should be:

• Focused and researchable
• Answerable using credible sources
• Complex and arguable
• Feasible and specific
• Relevant and original

Frequently asked questions: Writing a research paper

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.

The best way to remember the difference between a research plan and a research proposal is that they have fundamentally different audiences. A research plan helps you, the researcher, organize your thoughts. On the other hand, a dissertation proposal or research proposal aims to convince others (e.g., a supervisor, a funding body, or a dissertation committee) that your research topic is relevant and worthy of being conducted.

Formulating a main research question can be a difficult task. Overall, your question should contribute to solving the problem that you have defined in your problem statement .

However, it should also fulfill criteria in three main areas:

• Researchability
• Feasibility and specificity
• Relevance and originality

All research questions should be:

• Focused on a single problem or issue
• Researchable using primary and/or secondary sources
• Feasible to answer within the timeframe and practical constraints
• Specific enough to answer thoroughly
• Complex enough to develop the answer over the space of a paper or thesis
• Relevant to your field of study and/or society more broadly

A research aim is a broad statement indicating the general purpose of your research project. It should appear in your introduction at the end of your problem statement , before your research objectives.

Research objectives are more specific than your research aim. They indicate the specific ways you’ll address the overarching aim.

Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement .

Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.

I will compare …

Your research objectives indicate how you’ll try to address your research problem and should be specific:

Research objectives describe what you intend your research project to accomplish.

They summarize the approach and purpose of the project and help to focus your research.

Your objectives should appear in the introduction of your research paper , at the end of your problem statement .

The main guidelines for formatting a paper in Chicago style are to:

• Use a standard font like 12 pt Times New Roman
• Use 1 inch margins or larger
• Apply double line spacing
• Indent every new paragraph ½ inch
• Include a title page
• Place page numbers in the top right or bottom center
• Cite your sources with author-date citations or Chicago footnotes
• Include a bibliography or reference list

To automatically generate accurate Chicago references, you can use Scribbr’s free Chicago reference generator .

The main guidelines for formatting a paper in MLA style are as follows:

• Use an easily readable font like 12 pt Times New Roman
• Set 1 inch page margins
• Include a four-line MLA heading on the first page
• Center the paper’s title
• Use title case capitalization for headings
• Cite your sources with MLA in-text citations
• List all sources cited on a Works Cited page at the end

To format a paper in APA Style , follow these guidelines:

• Use a standard font like 12 pt Times New Roman or 11 pt Arial
• If submitting for publication, insert a running head on every page
• Apply APA heading styles
• Cite your sources with APA in-text citations
• List all sources cited on a reference page at the end

No, it’s not appropriate to present new arguments or evidence in the conclusion . While you might be tempted to save a striking argument for last, research papers follow a more formal structure than this.

All your findings and arguments should be presented in the body of the text (more specifically in the results and discussion sections if you are following a scientific structure). The conclusion is meant to summarize and reflect on the evidence and arguments you have already presented, not introduce new ones.

The conclusion of a research paper has several key elements you should make sure to include:

• A restatement of the research problem
• A summary of your key arguments and/or findings
• A short discussion of the implications of your research

Don’t feel that you have to write the introduction first. The introduction is often one of the last parts of the research paper you’ll write, along with the conclusion.

This is because it can be easier to introduce your paper once you’ve already written the body ; you may not have the clearest idea of your arguments until you’ve written them, and things can change during the writing process .

The way you present your research problem in your introduction varies depending on the nature of your research paper . A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement .

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• Published: 13 September 2024

Understanding disciplinary perspectives: a framework to develop skills for interdisciplinary research collaborations of medical experts and engineers

• Sophie van Baalen   ORCID: orcid.org/0000-0002-1592-3276 1 , 2 &
• Mieke Boon   ORCID: orcid.org/0000-0003-2492-2854 1  

BMC Medical Education volume  24 , Article number:  1000 ( 2024 ) Cite this article

Metrics details

Health professionals need to be prepared for interdisciplinary research collaborations aimed at the development and implementation of medical technology. Expertise is highly domain-specific, and learned by being immersed in professional practice. Therefore, the approaches and results from one domain are not easily understood by experts from another domain. Interdisciplinary collaboration in medical research faces not only institutional, but also cognitive and epistemological barriers. This is one of the reasons why interdisciplinary and interprofessional research collaborations are so difficult. To explain the cognitive and epistemological barriers, we introduce the concept of disciplinary perspectives . Making explicit the disciplinary perspectives of experts participating in interdisciplinary collaborations helps to clarify the specific approach of each expert, thereby improving mutual understanding.

We developed a framework for making disciplinary perspectives of experts participating in an interdisciplinary research collaboration explicit. The applicability of the framework has been tested in an interdisciplinary medical research project aimed at the development and implementation of diffusion MRI for the diagnosis of kidney cancer, where the framework was applied to analyse and articulate the disciplinary perspectives of the experts involved.

We propose a general framework, in the form of a series of questions, based on new insights from the philosophy of science into the epistemology of interdisciplinary research. We explain these philosophical underpinnings in order to clarify the cognitive and epistemological barriers of interdisciplinary research collaborations. In addition, we present a detailed example of the use of the framework in a concrete interdisciplinary research project aimed at developing a diagnostic technology. This case study demonstrates the applicability of the framework in interdisciplinary research projects.

Interdisciplinary research collaborations can be facilitated by a better understanding of how an expert’s disciplinary perspectives enables and guides their specific approach to a problem. Implicit disciplinary perspectives can and should be made explicit in a systematic manner, for which we propose a framework that can be used by disciplinary experts participating in interdisciplinary research project. Furthermore, we suggest that educators can explore how the framework and philosophical underpinning can be implemented in HPE to support the development of students’ interdisciplinary expertise.

Peer Review reports

Expertise is highly domain-specific, and learned by being immersed in professional practice [ 1 ]. However, today’s rapidly evolving health care systems require clinicians who are capable of meeting complex challenges [ 2 ], which often requires interdisciplinary and interprofessional collaborations between experts from distinct disciplines. Footnote 1 With the increasingly central role of innovative medical technologies in many medical specialties [ 3 ], health professionals will presumable participate in interdisciplinary and interprofessional research collaborations. But interprofessional and interdisciplinary research collaborations are notoriously difficult (e.g., [ 4 , 5 , 6 , 7 ]). Boon et al. (2019) argue that the complexity of current medical practices requires interdisciplinary expertise , which is an extension of adaptive expertise [ 8 ]. Interdisciplinary expertise involves the ability to understand the role of disciplinary perspectives .

In this paper, we combine insights from the philosophy of science on disciplinary perspectives and practice experience from an interdisciplinary medical research project aimed at the development and implementation of diffusion MRI for the diagnosis of kidney cancer. Based on these insights and practice experience, we propose a framework for mitigating cognitive and epistemological barriers caused by different disciplinary perspectives. In addition, we present a detailed example of the use of the framework to analyse and explain the experts’ disciplinary perspectives in the aforementioned interdisciplinary research project aimed at developing a diagnostic technology. This case study demonstrates the use of the framework in interdisciplinary research projects. The framework can be used by health professionals to facilitate their interdisciplinary research projects, by analysing and explaining their disciplinary perspectives.

Interdisciplinary research

To address the barriers to interdisciplinary research, various authors have developed analytical frameworks to guide the research process and help disciplinary experts understand what it takes to execute projects together with experts from other disciplines [ 9 , 10 , 11 , 12 ]. Menken et al. (2016), for example, provide a method for interdisciplinary research that is much similar to the traditional empirical cycle, including steps such as “identify problem or topic,” “formulate preliminary research questions,” “data collection” and “draw conclusions” [ 11 ]. Other frameworks describe which steps need to be taken in the interdisciplinary research process . In the literature on team science , several authors also aim to provide a better understanding of the process of interdisciplinary research. For example, Hasan et al. (2023) focuses on the ‘micro’ layers of the team science ecosystem proposed by Stokols et al. (2019) – the layer of individual team members collaborating in interdisciplinary research projects [ 13 , 14 ]. From their analysis of an online collaborations between early academics from different fields, they provide insights into common issues in interdisciplinary research and methods for dealing with them. By applying their framework from the start of the interdisciplinary research process, they argue, interdisciplinary capture [ 15 ] can be avoided.

Although the aforementioned frameworks provide valuable guidance on the process of interdisciplinary collaboration, they do not address the deeper cognitive and epistemological challenges of interdisciplinary research collaboration [ 5 , 16 ], which is the objective of our contribution. A crucial assumption in current frameworks seems to be that interdisciplinary research collaboration is learned by doing, and that the integration of different disciplines will automatically follow. Footnote 2 In our view, however, the integration of different disciplines is both crucial and one of the most challenging aspects of interdisciplinary research collaboration. In previous work we have argued that the inherent cognitive and epistemological (knowledge-theoretical) challenges of integration have been neglected by most authors providing models for interdisciplinary research [ 8 ]. In this paper, our focus is therefore on challenges of using and producing knowledge in interdisciplinary research collaborations that aim at solving complex real-world problems. Examples are collaborations between distinct medical specialists in the diagnosis and treatment of a specific patient (e.g., an oncologist and radiologist), but also collaborations between medical experts and biomedical engineers aimed at innovative medical technology for clinical uses. In this paper, we focus on inter disciplinary research projects, in which two or more academic fields are integrated to solve real-world problems, and not on trans disciplinary projects in which one or more academic fields are integrated with expertise from outside of academia such as policy-making or practice. Footnote 3

The challenge of interdisciplinary research collaborations aimed at solving a shared problem is that each expert is guided by his/her own disciplinary perspective. However, the results produced by experts from different disciplines, although internally coherent, are not mutually coherent, so that they are not easily integrated. Furthermore, approaches and results understood within a contributing disciplinary perspective are not easily understood by experts specialised in other disciplinary perspectives, even though each expert aims to contribute to the same problem.

In short, the way in which experts use and produce knowledge is guided by the disciplinary perspective typical of their own practice. But experts are often unaware of having a disciplinary perspective. We argue that this is an obstacle to participating in interdisciplinary research collaborations focused on using and producing knowledge for complex problem-solving . Moreover, disciplinary perspectives are often considered impenetrable —as they are acquired by doing — which makes dealing with the disciplinary perspective of other experts a difficult learning objective. In this paper, we defend that disciplinary perspectives can be made explicit in a systematic manner, and that their role in ‘how experts in a specific discipline use and produce knowledge’ can thus be made understandable for experts and students in both their own and other disciplines.

To this end, we have developed a framework, based on new insights in the philosophy of science and on practice experience of interdisciplinary research collaboration aimed at the development of a medical technology, which can be used by experts in a particular discipline to analyse different elements of their discipline and, together with collaborators, to analyse the same elements from other disciplines. We believe that this systematic approach to understanding disciplinary perspectives will facilitate interdisciplinary research collaborations between experts from different fields. It will create awareness of one’s own disciplinary perspective and the ability to understand the disciplinary perspective of other experts at a sufficient level. Our framework thus aims to alleviate the challenge of integration in a collaborative research project by providing a tool for analysing disciplinary perspectives . We suggest that the concrete descriptions of disciplinary perspectives that result from the application of the framework, clarify the approaches of experts in a multi-disciplinary team. It thus enables effective communication through improved understanding of how each discipline contributes. Once researchers sufficiently understand each other’s discipline, they will be able to construct so-called conceptual models that integrate content relevant to the problems at hand. Footnote 4

Education in interdisciplinary research

In addition to professionals using our framework to facilitate collaboration in interdisciplinary research projects, we suggest that this framework can also be implemented in medical education. It can be used to teach students what it means to have a disciplinary perspective, and to explicate the role of disciplinary perspectives of disciplinary experts participating in an interdisciplinary research collaboration. We have implemented this framework in an innovative, challenge-based educational design that explicitly aims to support and promote the development of interdisciplinary research skills [ 22 ]. Research into the intended learning objectives has not yet been completed, but our initial findings indicate that the proposed framework effectively supports students in their ability to develop crucial skills for conducting interdisciplinary research projects. We suggest therefore that the framework can also be implemented in HPE as a scaffold for teaching and learning metacognitive skills needed in interdisciplinary research collaborations, for example between medical experts and engineers.

Research has shown that interprofessional education courses for healthcare students can have a positive effect on the knowledge, skills and attitudes required for interprofessional collaboration, but that organising such interventions is challenging [ 23 , 24 ]. In the HPE literature, it is generally assumed that the limitations of interprofessional and interdisciplinary teamwork are due to problems of communication, collaboration and cooperation [ 25 , 26 ], which are linked to barriers and enablers at institutional, organizational, infrastructural, professional and individual levels (e.g., [ 27 , 28 ]). Therefore, interprofessional and interdisciplinary collaborations are discussed extensively in the HPE literature – our focus is challenges of interdisciplinary research collaboration.

The ability to use and produce knowledge and methods in solving (novel) problems is covered in the HPE literature by the notion of adaptive expertise , which encompasses clinical reasoning, integrating basic and clinical sciences, and the transfer of previously learned knowledge, concepts and methods to solve new problems in another context (e.g., [ 1 , 29 , 30 , 31 , 32 , 33 , 34 ]). In previous work, we introduced the concept of interdisciplinary expertise, which expands on the notion of adaptive expertise by including the ability to understand, analyse and communicate disciplinary perspectives [ 8 ]. In this paper, we address the challenge posed by how this ability to understand, analyse and communicate disciplinary perspectives can be learned. The framework that we propose can be implemented in HPE to function as a tool to scaffold metacognitive skills of health professions students, facilitating the development of interdisciplinary expertise.

Aims and contributions of this paper

Our first objective is to show that interdisciplinary collaboration in (medical) research faces not only institutional, but also cognitive and epistemological barriers. Therefore, we first provide a theoretical explanation of the concept of ‘disciplinary perspective’ as developed in the philosophy of science, in order to make it plausible that the cognitive barriers experienced by experts in interdisciplinary collaboration are the result of different disciplinary perspectives on a problem and its solution.

Our second objective is to provide a systematic approach to improve interdisciplinary research, for which we propose a framework, in the form of a series of questions, based on new insights from the philosophy of science into the epistemology of interdisciplinary research. We provide a detailed explanation of the application of the proposed framework in an interdisciplinary medical research project to illustrate its applicability in a multidisciplinary research collaborations, by showing that the different disciplinary perspectives that inform researchers and technicians within a multidisciplinary research team can be made transparent in a systematic way.

In short, our intended contribution is (i) to explain cognitive and epistemological barriers by introducing the concept of disciplinary perspectives in medical research collaborations, (ii) to offer a framework that enables the mitigation of these barriers within interdisciplinary research projects that are caused by different disciplinary perspectives, and (iii) to illustrate the applicability of this framework by a concrete case of an interdisciplinary research collaboration in a medical-technical research setting.

We developed a framework for making disciplinary perspectives of experts participating in an interdisciplinary research collaboration explicit, by combining insights from the philosophy of science with practical experience from a medical research project. Philosophy of science provided the theoretical basis for our concept of disciplinary perspectives. Our detailed case-description stems from an interdisciplinary medical research project to develop and implement a new imaging tool for the diagnosis of kidney cancer, in which the first author participated. We then applied the framework to analyze and articulate the disciplinary perspectives of experts involved in this interdisciplinary medical research project.

The usefulness and applicability of the proposed framework was tested by the first author who, in her role as PI, was able to use it successfully in coordinating an interdisciplinary research project aimed at developing a biomedical technology for clinical practice [ 35 , 36 ]. Below, we illustrate how the framework was systematically applied to this specific case, providing initial evidence of its applicability. However, to test whether the proposed framework reduces the cognitive and epistemological barriers caused by different disciplinary perspectives, experts need to be trained in its use. We suggest that training in the use of this framework requires, among other things, some insight into the philosophical underpinnings of the concept of ‘disciplinary perspective’. Our explanation of the so-called epistemology of disciplinary perspectives in this paper aims to provide such insight.

Developing a framework for analysing and articulating a disciplinary perspective

The framework proposed here is based on insights about disciplinary perspectives in the philosophy of science. These insights concern an epistemology (a theory of knowledge) of scientific disciplines. In other words, the framework is based on an account of the knowledge-theoretical (epistemic) and pragmatic aspects that guide the production of knowledge and scientific understanding by a discipline [ 21 ].

The epistemology of scientific disciplines developed in our previous work is based on the philosophical work of Thomas Kuhn [ 37 ]. Building on his seminal ideas, we understand disciplinary perspectives as analysable in terms of a coherent set of epistemic and pragmatic aspects related to the way in which experts trained in the discipline (and who have thus, albeit implicitly, acquired the disciplinary perspective) apply and produce knowledge [ 38 ]. In our approach, the epistemic and pragmatic aspects that generally characterize a discipline, are made explicit through a set of questions that form the basis of the proposed framework (see Table 1 , and the first column of Table  2 ). The disciplinary perspective can thus be revealed through this framework. In turn, when used in educational settings, this framework can be used to foster interdisciplinary expertise by acting as a scaffold for teaching and learning metacognitive skills for interdisciplinary research collaborations. Footnote 5

The general aspects indicated by italics in each question in Table 1 are interdependent, so that analysis using this framework results in a coherent description of the disciplinary perspective in terms of these aspects. The framework can be used by experts in an interdisciplinary research project not only to make explicit their disciplinary perspective in a general sense, but to also to specify in a systematic way how these aspects relate to the interdisciplinary research problem from their disciplinary discipline (see Table  2 , which contains both the general and problem-specific descriptions for each aspect per discipline). In our view, this approach is productive in overcoming the cognitive and epistemological barriers. It thus contributes to productive interdisciplinary collaboration.

Applying the framework in an interdisciplinary medical research project

To test the applicability of this framework, we applied it to an interdisciplinary medical research project. The interdisciplinary medical research project aimed at developing a new clinical imaging tool, namely, diffusion magnetic resonance imaging (i.e., diffusion MRI) to characterize the micro-structural makeup of kidney tumours, running from early 2014 to mid-2018. The first author was involved in this project as a principle investigator (PI). As an interdisciplinary expert with a background in technical medicine , which combines medical training with technological expertise [ 41 ], she coordinated and integrated contributions from experts with medical and engineering backgrounds. In her role as PI, she applied the proposed framework to analyse and articulate the disciplinary perspectives of other experts involved in the medical research project.

The aim of the interdisciplinary medical research project was to develop a new imaging tool for the characterization of renal tumours, i.e., diffusion MRI. Diffusion MRI allows for visualization and quantification of water diffusion without administration of exogenous contrast materials and is, therefore, a promising technique for imaging kidney tumours. In earlier studies, several parameters derived from diffusion MRI studies were found to differentiate between different tumour types in the kidney [ 42 , 43 , 44 ]. Existing imaging methods in clinical practice can detect the size and location of kidney tumours, but the tumour type and malignancy can only be determined histologically after surgery. The purpose of the medical research project was to assess whether more advanced parameters that can be obtained from diffusion MRI [ 35 , 45 ] can differentiate between malignant and benign kidney tumours [ 36 ]. Being able to make this distinction could potentially prevent unnecessary surgery in patients with non-malignant tumours.

The interdisciplinary medical research project needed to bring together expertise (knowledge and skills) from different professionals, academic researchers as well as clinicians. Therefore, the research team consisted of a physicist, a biomedical engineer, a radiologist, a urologist and the principle investigator. The complex, interdisciplinary research object can be thought of as a system that encompasses several elements: the MRI-machine, the software necessary to produce images, the patient with a (suspected) kidney tumour, and the wider practice of care in which the clinical tool should function. In developing the clinical tool, these elements must be considered interrelated, whereas usually each expert focuses on one of these elements.

The PI utilized the framework to coordinate and integrate the contributions from different experts in the following manner. Throughout the project, she had meetings with each of the team members, where she probed them to explain their specific expertise in regard of the research object, as well as their expert contribution to the development of the imaging tool. Her approach in these meetings was guided by the general questions of the framework (Table 1 ). In this manner, she succeeded in getting a clear insight in aspects of each discipline relevant to the research object, and also in the specific contribution that needed to be made by each expert (as illustrated in Table  2 below). The level of understanding gained by this approach enabled her to, firstly, facilitate interdisciplinary team meetings in which disciplinary interpretations and questions from the experts about the target system could be aligned, and secondly, integrate their contributions towards the development of the new imaging tool [ 36 ].

In the presented approach, the framework was exclusively used by the PI, enabling her to acquire relevant information and understanding about the contributions of the disciplines involved. The other team members in the medical research project were not explicitly involved in applying the framework, nor in articulating their own disciplinary perspective or that of others. Hence, the resulting articulation of the disciplinary perspectives and of the contributions per discipline to the research object (in Table  2 ) is crafted by the PI. The level of understanding of the role of each discipline that the PI has acquired thereby appears to be sufficient to enable her coordinating task in this complex medical research project. Our suggestion for other research and educational practices, though, is that clinicians (as well as) other medical experts can develop this metacognitive skill by using the scaffold (in Table  1 ) in order to participate more effectively in these kinds of complex medical research projects.

In the results  section we will first present our explanation and justification of the idea that disciplinary perspectives determine the specific approaches of experts (who have been trained in a specific discipline in using and producing knowledge) when faced with a complex problem. In this explanation and justification, we will use insights from the philosophy of science. Next, we will explain and illustrate the systematic use of the proposed framework (Table 1 ) by showing the results of applying it to the interdisciplinary medical research project.

The insights from philosophy of science on which the proposed framework for the explication of disciplinary perspectives is rooted in insights of the philosophers Immanuel Kant (1794–1804) and Thomas Kuhn (1922–1996). Their important epistemological insight was that ‘objective’ knowledge of reality does not arise from some kind of imprint in the mind, such as on a photographic plate, but is partly formed by the concepts and theories that scientists hold. These concepts and theories therefore shape the way they perceive the world and produce knowledge about reality. This philosophical insight provides an important explanation for the cognitive and epistemological barriers between disciplines. After all, scientific experts learn these concepts and theories by being trained within a certain discipline. In this way, they develop a disciplinary perspective that determines their view and understanding of reality. Based on this philosophical insight, we can imagine how these barriers can be bridged, namely by developing the metacognitive ability to think about their own cognition and how their scientific view of reality is shaped by their specific disciplinary perspective. In order to facilitate this ability, we develop a framework that can be used as a metacognitive scaffold. Finally, we apply this framework to an example interdisciplinary medical-technical research project, to illustrate it’s use in practice.

Insights from the philosophy of science: disciplinary perspectives

Boon et al. (2019) refer to the notion of disciplinary perspectives and their indelible role in how experts approach problems —in particular, the ways in which experts use and produce knowledge in regard of the problem they aim to solve— and provide a philosophical account of this notion based on so-called constructivist (Kantian) epistemology (i.e., knowledge-theory, [ 38 , 46 ]). On a Kantian view, ‘the world does not speak for itself,’ i.e., knowledge of (aspects of) the external world is not acquired passively on the basis of impressions in the mind (physically) caused by the external world (e.g., similar to how pictures of the world are physically imprinted on a photographic plate). Instead, the way in which people produce and use knowledge results from an interaction between the external world, the human senses and the human cognitive system. Crucially, neither our concepts nor our perceptions stem from passive impressions. Instead, ‘pre-given’ concepts ‘in the mind’ are needed in order to be able to perceive something at all and thus to produce knowledge about reality. Conversely, according to Kant, the imaginative (i.e. creative) capacity of the mind is then able to generate new concepts and to draw new connections of which the adequacy and usability must be tested against our experiences of reality. When new concepts (invented by the creative capacity of the human mind) have been tested against experience, they allow us to see new things in the external world, which we would not see without those concepts. This theoretical insight by Kant is crucial to get past naïve conceptions of knowledge, in particular, by understanding the indelible role of concepts in generating knowledge from observations and experiences.

This philosophical insight already makes it clear, for instance, that ‘descriptions of facts’ in a research project involve discipline-specific concepts, making these descriptions not easy to understand for someone who is not trained in that discipline. After Kant, this role of concepts has been expanded to the role of perspectives . For, Kuhn [ 37 ] created awareness that the human mind plays ‘unconsciously’ and ‘unintentionally’ a much greater role in the way scientific knowledge is created than usually assumed in the view that scientific knowledge is objective . Kuhn has introduced the concept of scientific paradigm to indicate in what sense the mind contributes. His idea was revolutionary because the notion of true and objective knowledge, which is the aim of science, became deeply problematic, as knowledge is only true and objective within the scientific paradigm, whereas it may even be meaningless in another.

Our notion of disciplinary perspectives is in many respects comparable to Kuhn’s idea of scientific paradigm, and is certainly indebted to Kuhn’s invention, particularly, with regard to the idea that it is a more or less coherent, usually implicit ‘background picture’ or ‘conceptual framework,’ which constitutes an inherent part of the cognitive system of an expert, and which forms the basis from which an expert thinks, sees and investigates in a scientific or professional practice. Furthermore, the scientific paradigm is not ‘innate,’ nor individually acquired, but maintained and transferred in scientific or professional practices, usually by being immersed in it. The same can be said about disciplinary perspectives. Yet, there are also important differences.

First, Kuhn believed that the paradigm is so deeply rooted in the cognitive structure of individual scientists, and, moreover, is embedded in how the scientific community functions, that it takes a scientific revolution and a new generation of scientists to shift into another paradigm, which is called a paradigm-shift (sometimes explained as a Gestalt-switch ). Kuhn’s belief suggests that humans lack the capacity to reflect on their own paradigm. Footnote 6 Conversely, we argue that humans can develop the metacognitive ability to perform this kind of reflection by which the structure and content of the paradigm or disciplinary perspective is made explicit. We take this as an important part of interdisciplinary expertise . Our suggestion, however, should not be confused with the idea that we can think without any paradigm or disciplinary perspective – we can’t, but we can explicate its workings (and adapt it), which is what we will illustrate in the case-description below.

Second, Kuhn’s focus was science , i.e., the production of objectively true scientific knowledge, in particular, theories. Instead, our focus is on experts trained in specific disciplines, who use and produce knowledge with regard to (practical) problems that have to be solved. Nonetheless, the Kuhnean insight explains why knowledge generated in distinct disciplines often cannot be combined in a straightforward manner (e.g., as in a jigsaw puzzle), which is due to the fact that knowledge is only fully meaningful and understandable relative to the disciplinary perspective in which it has been produced.

Our notion of disciplinary perspectives is similar to Kuhn’s idea of paradigm (which he specified later on as disciplinary matrices ) in the sense that a paradigm functions as a perspective or a conceptual framework , i.e., a background picture within which a scientific or professional practice of a specific discipline is embedded and which guides and enables this practice. But instead of considering them as replacing each other in a serial historical order as Kuhn did, we assume that disciplinary perspectives co-exist, that is, exist in parallel instead of serial. This view on disciplinary perspectives can be elaborated somewhat further by harking back to Ludwik Fleck [ 47 ], a microbiologist, who already in the 1930s developed a historical philosophy and sociology of science that is very similar to Kuhn’s (also see [ 48 ]). Footnote 7 Similar to and deeply affected by Kant, Fleck draws a close connection between human knowledge (e.g., facts) and cognition. Hence, Fleck disputes that facts are descriptions of things in reality discovered through properly passive observation of aspects in reality – which is why, according to Fleck, facts are invented , not discovered . Similar to Kuhn, Fleck expands on Kant by also including the role of the community in which scientists and experts are trained. Instead of paradigms , however, Fleck uses the terms thought styles and thought collectives to describe how experts in a certain professional or academic community adopt similar ways of perceiving and thinking that differ between disciplines: “The expert [trained in the discipline] is already a specially moulded individual who can no longer escape the bonds of tradition and of the collective; otherwise he would not be an expert” ([ 47 ], p. 54). But while Kuhn strove to explain radical changes in science, Fleck’s focus is on ‘normal science,’ that is, on communities ( thought collectives each having their own thought style ) that co-exist and gradually, rather than radically, change, which is closer to our take on disciplines. Importantly, according to Fleck, the community guides which problems members of that communities find relevant and how they approach these problems. Translated to our vocabulary, in scientific and professional practices, experts trained in different disciplines each have different disciplinary perspective, by means of which they recognize different aspects and problems of the same so-called research object , which they approach in accordance with their own discipline.

We propose that disciplinary perspectives can be analysed and made explicit, which we consider a crucial metacognitive skill of interdisciplinary experts. Our proposal for the framework to analyse disciplinary perspectives (in Table 1 ) takes its cue in Kuhn’s notion of disciplinary matrices. Kuhn’s original notion presents a matrix by which historians and philosophers can analyse the paradigm in hindsight, specifying aspects such as the metaphysical background beliefs and basic concepts, core theories, epistemic values, and methods, which all play a role in how knowledge is generated (also see [ 8 , 50 ]). Our framework includes some of these aspects, but also adds others, thereby generating a scaffold that facilitates interdisciplinary collaborations aimed at applying and producing knowledge for complex problem-solving in professional research practices aimed at ‘real-world’ practices, such as medical research practice. Below, we will illustrate the application of this framework in a concrete case.

Interdisciplinary research project: diffusion MRI for the diagnosis of kidney tumour

We will illustrate the applicability of the proposed framework (Table 1 ) for the analysis of disciplinary perspectives using the example of a research project that aims to develop a new clinical imaging tool, namely, diffusion MRI to characterize the microstructure of renal tumours. In our analysis, we focus on experts from four different disciplines: (I) clinical practice, (II) medical biology, (III) MRI physics, and (IV) signal and image processing. As indicated in the methods section, the complex, interdisciplinary research object that these experts have to deal with concerns a system consisting of the MRI-machine, the software necessary to produce images, and the patient with a (suspected) renal tumour, including the broader care practice in which the clinical tool should function.

In the following paragraphs we will first present a general explanation of the four disciplines involved in the project, and next, illustrate how the proposed framework can be applied to analyse and articulate each disciplinary perspective as well as the specific contribution of each discipline to the research object (in Table  2 ). It is not our intention to provide comprehensive descriptions of the fields that are involved, but rather to provide insight into how the fields differ from each other across the elements of our framework. In addition, we do not believe that all (disciplinary) experts only adhere to one disciplinary perspective. For example, clinicians usually combine both a clinical and biomedical perspective to fit together a complete picture of a patient for clinical decision-making concerning diagnosis and treatment [ 51 , 52 , 53 ]. Moreover, MRI engineers will usually need to combine insights from MRI physics and signal processing.

I. Clinical practice concerning patients with renal tumours

Clinical practice concerns the patient with a renal tumour. This practice differs from the other disciplines in our example, because it is not primarily a scientific discipline. Nonetheless, to develop a diagnostic tool, the disciplinary perspective of clinicians specialized in patients with kidney tumours is crucial, for example, to determine the conditions that the technology needs to meet in order to be useful for their clinical practice. The knowledge-base of clinical experts is rooted in biomedical sciences, which means that clinical experts often understand their patient’s signs and symptoms from a biomedical perspective (i.e., in terms of tumour formation of healthy renal physiology). Yet, clinicians will usually focus on their patient’s clinical presentation and possible diagnostic and clinical pathways. In clinical practice, several kidney tumour types are distinguished, each with its own histological presentation (visible under the microscope), tumour growth rate and chance of metastases. Unfortunately, all kidney tumour types, including non-malignant types, appear the same on standard imaging modalities, namely, as solid lesions. When the tumour is not metastasized, treatment consists of surgery removing the whole kidney or the part of the kidney that contains the tumour (i.e., ‘radical’ or ‘partial’ nephrectomy). If surgery is not possible, other treatments include chemotherapy or radiation. After surgery, a pathologist examines the tumour tissue to determine the tumour type. Occasionally, the pathologist concludes that the removed tumour was non-malignant, which is a situation that may be prevented if diffusion MRI can be used to distinguish between malignant and non-malignant tumours prior to surgery.

II. Medical biology

In biology, the structure and working of the body is studied at several levels, from the interaction of proteins and other macromolecules within cells to the functioning of organs. In the case at hand, the organ of interest is the kidney. Functions of the kidneys are excretion of waste materials, control of blood pressure via hormone excretion, balancing the body fluid, acid-base balance and balancing salts by excretion or resorption of ions. Understanding these functions requires insights into the anatomy, tissue architecture and physiology of the kidneys. The main functional structures of the kidney are: (1) the nephron, consisting of a tuft of capillaries (the glomerulus) surrounded by membranes that are shaped like a cup (Bowman’s capsule), responsible for the first filtration of water and small ions, and (2) the renal tubule that is responsible for more specific resorption and excretion of ions and water. The arrangement of small tubes that fan from the centre towards the outside (or cortex) of the kidneys allows maintaining variation in concentrations of ions, which helps to regulate resorption and excretion. The contribution of medical biology to the development of the diagnostic tool is important because knowledge about kidneys such as just sketched provides an understanding of the properties (i.e., microstructural of physiological properties) by which different tumour types can be distinguished from each other, which is crucial to interpreting the novel diagnostic imaging technology.

III. MRI physics & diffusion MRI

Magnetic resonance imaging is based on the physics of magnetism and the interaction of tissue components with radio magnetic fields. The main component of the human body that clinical MRI machines are sensitive to is (the amount of) water molecules or, more specifically, hydrogen nuclei (protons). These protons can be thought of as rotating or spinning , producing (tiny) magnetic fields. By placing tissue in a relatively strong magnetic field (usually 1.5 or 3 Tesla emitted by a large coil that surrounds the body), the tiny magnetic fields of protons (in the water-phase of the tissue) will align themselves with the direction of the strong magnetic field. By then applying a series of radiofrequency pulses, protons will be pushed out of balance and rotate back to their original state, causing a magnetic flux that causes a change in voltage which is picked up by receiver coils in the MRI machine. The rate with which protons return to their original state, the relaxation time, is influenced by the makeup of their environment, and will, therefore, differ for different tissues, resulting in image contrasts between tissues. To be able to form images of the signal, magnetic field gradients are applied, spatially varying the field which enables to differentiate between signals from different locations. Computer software using mathematical formulas ‘translate’ the signal into a series of images.

Diffusion MRI is a subfield of MR imaging, that is based on a contrast between ‘diffusion rates’ of water molecules in different tissues. Diffusion is based on the random (‘Brownian’) motion of water molecules in tissue. This motion is restricted by tissue components such as membranes and macromolecules and therefore water molecules move (or ‘diffuse’) at different rates in different tissues, depending on the microstructure of tissues. To measure this, additional magnetic field gradients are applied, which results in a signal attenuation proportional to the diffusion rate, as water molecules move (‘or diffuse’) out of their original voxel due to diffusion.

The method for acquiring diffusion-weighted images with an MRI machine (i.e., the ‘acquisition sequence’ of applying radiofrequency pulses and switching gradients on and off) is designed to gain sensitivity to the water molecules diffusing from their original location. The measured diffusion coefficient is considered to be related to microstructural properties of the tissue, namely the density of tissue structures such as macromolecules and membranes that restrict water diffusion. Together with other diffusion parameters that can be obtained by fitting the signal to other functions or ‘models’, the diffusion coefficient can be used to characterise and distinguish between different (tumour) tissue types, which is the aim of this new imaging tool.

IV. Signal and image processing

The signal acquired by MRI machines undergoes many processing steps before they appear as images on the screen. Some of these steps are performed automatically by the MRI system while others require standardized operations in the software package supplied by the manufacturer, and yet other, more advanced, manipulations are performed in custom-made programs or software packages developed for specific research purposes. In the field of diffusion MRI, software packages that perform the most common fitting procedures are available but often custom-made algorithms are required. The reason for this is that diffusion MRI is originally developed for brain imaging, while investigating its feasibility in other organs has started more recently and only makes up a small part of the field. New applications generate new challenges. For example, unlike the brain, kidneys (and other abdominal organs) move up and down as a consequence of breathing. Therefore, specific algorithms manipulating the scan to correct for this respiratory motion are required for diffusion MRI of the kidneys. Furthermore, as tissue structure and physiology in the kidneys differ from that in the brain, existing models need to be adjusted to that of the kidney.

In this paper, we have argued that interdisciplinary collaboration is difficult because of the role of experts’ disciplinary perspective, which shapes their view and approach to a problem and creates cognitive and epistemological barriers when collaborating with other disciplines. To overcome these barriers, disciplinary experts involved in interdisciplinary research projects need to be able to explicate their own disciplinary perspective. This ability is part of what is known as interdisciplinary expertise [ 8 ]. We defend that interdisciplinary expertise begins with creating awareness of the role of disciplinary perspectives in how experts view a problem, interpret it, formulate questions and develop solutions.

Analytical frameworks to guide interdisciplinary research processes previously developed by other authors typically focus on the process of interdisciplinary collaboration [ 9 , 10 , 11 , 12 , 13 , 14 , 15 ]. The approach we propose here contributes to this literature by addressing the deeper cognitive and epistemological challenges of interdisciplinary research collaboration on the role of the disciplinary perspective as an inherent part of one’s expertise [ 5 , 16 ]. Several authors have already used the concept of ‘disciplinary perspectives’ to point out the challenges of interdisciplinary research (e.g., [ 9 , 15 ]). Our contribution to this literature is the idea, based on philosophical insights into the epistemology of interdisciplinary research, that disciplinary perspectives can be made explicit, and next, to provide an analytical framework with which disciplinary perspectives within an interdisciplinary research context can be systematically described (as in Table 1 ) with the aim of facilitating interdisciplinary communication within such research projects.

Our further contribution is that we have applied this framework to a concrete case, thereby demonstrating that disciplinary perspectives within a concrete interdisciplinary research project can actually be analyzed and explicated in terms of a coherent set of elements that make up the proposed framework. The result of this analysis (in Table  2 ) shows a coherent description of the discipline in question per column, with an explanation per aspect of what this aspect means for the interdisciplinary research project. It can also be seen that the horizontal comparison (in Table  2 ) results in very different descriptions per aspect for each discipline. We believe that this example demonstrates that it is possible to explain the nature of a specific discipline in a way that is accessible to experts from other disciplines. We do not claim, therefore, that this table is an exhaustive description of the four disciplines involved. Instead, our aim is to show that the approach outlined in this table reduces cognitive and epistemological barriers in interdisciplinary research by enabling communication about the content and nature of the disciplines involved.

We suggest that educators can explore how the framework and philosophical underpinning can be implemented in HPE to support the development of students’ interdisciplinary expertise. Much has been written, especially in the engineering education literature, about the importance of interdisciplinarity and how to teach it. A recent systematic review article shows that the focus of education aimed at interdisciplinarity is on so-called soft skills such as communication and teamwork. Project-based learning is often used to teach the necessary skills, but without specific support to promote these skills [ 7 ]. In our literature review on education for interdisciplinarity [ 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 ], we did not find any authors who specifically address the cognitive and epistemological barriers to interdisciplinary collaboration as described in our article. One possible reason for this is that current epistemological views on the application of science in real-world problem-solving contexts, such as the research project presented here, do not recognise the inherent cognitive and epistemological barriers philosophically explained in this article [ 78 ]. The novelty of our approach is therefore our emphasis on the epistemological and cognitive barriers between disciplines that result from the ineradicable role of disciplinary perspectives in the discipline-bound way in which researchers frame and interpret the common problem. This makes interdisciplinary communication and integration particularly difficult. Specific scaffolds are needed to overcome these barriers. The framework proposed here, which systematically makes the disciplinary perspective explicit, aims to be such a scaffold. We therefore argue that much more attention should be paid to this specific challenge of interdisciplinary collaboration in academic HPE education. This requires both an in-depth philosophical explanation that offers a new view of scientific knowledge that makes clear why interdisciplinary research is difficult, and learning how to make disciplinary perspectives explicit, for which the proposed framework provides a metacognitive scaffold.

We have implemented this framework in a newly designed minor programme that uses challenge-based learning and aims to develop interdisciplinary research skills. In this minor, small groups of students from different disciplines work on the (interdisciplinary) analysis and solution of a complex real-world problem. A number of other scaffolds focused on the overarching learning objective have been included in the educational design, which means that the framework proposed here cannot be tested in isolation. Although our research into whether this new educational design achieves the intended learning goal is not yet complete, our initial experience of using the framework is positive. Students, guided by the teacher, are able to use the framework in their interdisciplinary communication - first in a general sense to get to know each other’s disciplines and then within their research project. This implies that the framework is useful in education aimed at learning to conduct interdisciplinary research.

This example, where the framework has been implemented in education aimed at developing interdisciplinary research skills, also shows that although it was developed in the context of a medical-technical research project, it is in fact very general and well suited for any interdisciplinary research.

A critical comment should be made regarding our preliminary evidence of the framework’s usefulness. The first author, who was PI of the interdisciplinary medical research project, in which she applied this framework in her role as coordinator, was also involved in the development of the framework [ 35 , 36 ]. She, therefore has a detailed insight into the theoretical underpinnings of the framework in relation to its intended application. The lack of such a theoretical background may make it more difficult to apply the framework in interdisciplinary research. Footnote 8 Which is why we have provided an extensive elaboration of these underpinnings in this paper.

Further research should address the question of whether this scaffold can facilitate interdisciplinary collaboration between disciplinary experts.

Further research is also needed to systematically analyse the value of this framework in HPE education. This starts with the question of what type of educational design it can be successfully implemented in. Other important questions are: Can interdisciplinary expertise be acquired without knowledge of the other discipline (e.g., biomedical engineering)? In other words, how much education in other disciplines should HPE provide to prepare experts to participate in specific interdisciplinary collaborations?

Furthermore, we emphasize that in addition to learning to use this framework as a metacognitive scaffold to gain a deeper understanding of the epistemological and cognitive barriers, students also need to develop other skills necessary for interdisciplinary research collaboration and working in interdisciplinary teams. The frameworks discussed in our introduction that analyse and guide the interdisciplinary research process provide insights into these skills (e.g. [ 9 , 10 , 11 , 12 ] and [ 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 ]).

We suggest that the article as a whole can be used in such educational settings to achieve several goals, provided that students are guided and coached by educators. First, to foster student’s understanding of the epistemological challenges of interdisciplinary collaboration and to recognize that these challenges are usually underestimated and not addressed in most approaches. Second, by providing insights into the epistemological challenges by outlining the philosophical underpinnings, students will be made aware of having a disciplinary perspective and how it guides their work. Finally, by providing a framework that can be used to analyse these disciplinary perspectives and by providing an example from the case description. When successful, this approach encourages students to developing transferrable skills that can be used in research projects beyond the initial educational project.

Conclusions

Interdisciplinary research collaborations can be facilitated by a better understanding of how an expert’s disciplinary perspectives enables and guides their specific approach to a problem. Implicit disciplinary perspectives can and should be made explicit in a systematic manner, for which we propose a framework that can be used by disciplinary experts participating in interdisciplinary research projects. With this framework, and its philosophical underpinning, we contribute to a fundamental aspect of interdisciplinary collaborations.

Availability of data and materials

All data generated or analysed during this study are included in this published.

In this article, we use ‘disciplines,’ ‘fields’ and ‘specialisms’ interchangeably.

Bridle (2013), Klein (1990), Newell (2007) and Szostak (2002) provide activities that are important for interdisciplinary collaborations, such as communication, negotiation and evaluating assumptions. In order to be able to perform such activities, students need to develop the appropriate skills [ 9 , 17 , 18 , 19 ].

Roux et al. (2017) provide a clear characterization of transdisciplinary research: “A key aim of transdisciplinary research is for actors from science, policy and practice to co-evolve their understanding of a social–ecological issue, reconcile their diverse perspectives and co-produce appropriate knowledge to serve a common purpose.” ([ 20 ], p. 1).

Boon (2020, 2023) explains the notion of conceptual modelling in application oriented research [ 21 , 22 ].

i.e., a framework that enables us to think analytically and systematically about our cognitive processes when we use and produce knowledge [ 39 , 40 ].

Yet, we recognize that this belief was plausible in Kuhn’s era, where the idea that humans (including scientists) are inevitably and indelibly guided by paradigms and perspectives was revolutionary and devastating with regard to the rational view of man. But nowadays we have become familiar with this idea, which offers an opening for the metacognitive abilities that we suggest.

To scholars in HPE, we recommend the entry on Ludwik Fleck in the Stanford Encyclopedia of Philosophy [ 49 ].

The point made here touches on a more fundamental issue that is beyond the scope of this article. Namely, that resistance of students, but also of teachers, to the described approach may have to do with more traditional epistemological beliefs about science that do not fit well with the way scientific research works in practice [ 78 , 79 ]. The philosophical underpinnings of the proposed framework explained in this article suggest alternative epistemological beliefs that are more appropriate for interdisciplinary research aimed at (complex) ‘real-world’ problems.

Abbreviations

Health professions education

Magnetic Resonance Imaging

Principle investigator

Mylopoulos M, Regehr G. Cognitive metaphors of expertise and knowledge: prospects and limitations for medical education. Med Educ. 2007. https://doi.org/10.1111/j.1365-2923.2007.02912.x .

Mylopoulos M, Kulasegaram K, Woods NN. Developing the experts we need: fostering adaptive expertise through education. J Eval Clin Pract. 2018. https://doi.org/10.1111/jep.12905 .

World Health Organization (WHO). Medical devices: managing the Mismatch. An outcome of the Priority Medical devices project. WHO; 2010. https://www.who.int/publications/i/item/9789241564045 .

Gilbert JH, Yan J, Hoffman SJ. A WHO report: framework for action on interprofessional education and collaborative practice. J Allied Health. 2010;39(Suppl 1):196–7.

Google Scholar  

MacLeod M. What makes interdisciplinarity difficult? Some consequences of domain specificity in interdisciplinary practice. Synthese. 2016. https://doi.org/10.1007/s11229-016-1236-4 .

Hudson JN, Croker A. Educating for collaborative practice: an interpretation of current achievements and thoughts for future directions. Med Educ. 2018. https://doi.org/10.1111/medu.13455 .

Van der Beemt A, MacLeod M, van der Veen JT, van de Ven A, van Baalen S, Klaassen RG, Boon M. Interdisciplinary engineering education: a review of vision, teaching and support. J Eng Educ. 2020;109(1). https://doi.org/10.1002/jee.20347 .

Boon M, Van Baalen SJ, Groenier M. Interdisciplinary expertise in medical practice: challenges of using and producing knowledge in complex problem-solving. Med Teach. 2019. https://doi.org/10.1080/0142159X.2018.1544417 .

Klein J. Interdisciplinarity: history, theory and practice. Detroit, MI: Wayne State University; 1990.

Repko A, Navakas F, Fiscella J. Integrating interdisciplinarity: how the theories of common ground and Cognitive_Interdisciplinarity are informing the debate on interdisciplinary integration. Issues Interdisciplinary Stud. 2007;25:1–31.

Menken S, Keestra M, Rutting L, Post G, de Roo M, Blad S, de Greef L. An introduction to interdisciplinary research: theory and practice. Amsterdam: Amsterdam University; 2016.

Book   Google Scholar  

Repko AF, Szostak R. Interdisciplinary research. Process and theory. 3rd ed. Los Angeles: Sage; 2017.

Hasan MN, Koksal C, Montel L, Le Gouais A, Barnfield A, Bates G, Kwon HR. Developing shared understanding through online interdisciplinary collaboration: reflections from a research project on better integration of health outcomes in future urban. Futures. 2023. https://doi.org/10.1016/j.futures.2023.103176 .

Stokols D, Olson JS, Salazar M, Olson GM. Strengthening the ecosystem for effective team science: a case study from University of California, Irvine, USA. 2019. https://i2insights.org/2019/02/19/team-science-ecosystem/ . Accessed 2 Feb 2024 .

Brister E. Disciplinary capture and epistemological obstacles to interdisciplinary research: lessons from Central African conservation disputes. Stud History Philos Sci part C: Stud History Philos Biol Biomedical Sci. 2016. https://doi.org/10.1016/j.shpsc.2015.11.001 .

Boon M, Orozco M, Sivakumar K. Epistemological and educational issues in teaching practice-oriented scientific research: roles for philosophers of science. Eur J Philos Sci. 2022;12(1):16. https://doi.org/10.1007/s13194-022-00447-z .

Article   Google Scholar  

Bridle H, Vrieling A, Cardillo M, Araya Y, Hinojosa L. Preparing for an interdisciplinary future: a perspective from early-career researchers. Futures. 2013. https://doi.org/10.1016/j.futures.2013.09.003 .

Newell WH. Decision-making in Interdisciplinary studies. In: Morcol G, editor. Handbook of decision making. New York: CRC Press/Taylor & Francis Group; 2007. p. 245–65.

Szostak R. How to do interdisciplinarity. Integrating the debate. Issues Integr Stud. 2002;20:103–22.

Roux DJ, Nel JL, Cundill G, O’farrell P, Fabricius C. Transdisciplinary research for systemic change: who to learn with, what to learn about and how to learn. Sustain Sci. 2017. https://doi.org/10.1007/s11625-017-0446-0 .

Boon M. The role of disciplinary perspectives in an epistemology of models. Eur J Philos Sci. 2020. https://doi.org/10.1007/s13194-020-00295-9 .

Boon M, Conceptual modelling as an overarching research skill in engineering education. SEFI2023 2023;  https://doi.org/10.21427/ZDX4-VV41 accessed through https://arrow.tudublin.ie/cgi/viewcontent.cgi?article=1074&context=sefi2023_prapap .

Guraya SY, Barr H. The effectiveness of interprofessional education in healthcare: a systematic review and meta-analysis. Kaohsiung J Med Sci. 2018. https://doi.org/10.1016/j.kjms.2017.12.009 .

Darlow B, Brown M, McKinlay E, Gray L, Purdie G, Pullen S. Longitudinal impact of preregistration interprofessional education on the attitudes and skills of health professionals during their early careers: a non-randomised trial with 4-year outcomes. BMJ Open. 2022;12(7):e060066. https://doi.org/10.1136/bmjopen-2021-060066 .

Clark G. Institutionalizing interdisciplinary health professions programs in higher education: the implications of one story and two laws. J Interprof Care. 2004. https://doi.org/10.1080/13561820410001731296 .

O’Keefe M, Henderson A, Chick R. Defining a set of common interprofessional learning competencies for health profession students. Med Teach. 2017. https://doi.org/10.1080/0142159X.2017.1300246 .

Choi BC, Pak AW. Multidisciplinarity, interdisciplinarity, and transdisciplinarity in health research, services, education and policy: 2. Promotors, barriers, and strategies of enhancement. Clin Invest Med. 2007. https://doi.org/10.25011/cim.v30i6.2950 .

Lawlis TR, Anson J, Greenfield D. Barriers and enablers that influence sustainable interprofessional education: a literature review. J Interprof Care. 2014. https://doi.org/10.3109/13561820.2014.895977 .

Schwartz DL, Bransford JD, Sears D. Efficiency and innovation in transfer. In transfer of learning from a modern multidisciplinary perspective . Charlotte, NC: Information age publishing. 2005; 3:1–51. Edited by JP Mestre JP.

Mylopoulos M, Regehr G. Putting the expert together again. Med Educ. 2011. https://doi.org/10.1111/j.1365-2923.2011.04032.x .

Carbonell KB, Stalmeijer RE, Könings KD, Segers M, van Merriënboer JJ. How experts deal with novel situations: a review of adaptive expertise. Educ Res Rev. 2014. https://doi.org/10.1016/j.edurev.2014.03.001 .

Kulasegaram K, Min C, Howey E, Neville A, Woods N, Dore K, et al. The mediating effect of context variation in mixed practice for transfer of basic science. Adv Health Sci Educ. 2015. https://doi.org/10.1007/s10459-014-9574-9 .

Castillo JM, Park YS, Harris I, Cheung JJH, Sood L, Clark MD, et al. A critical narrative review of transfer of basic science knowledge in health professions education. Med Educ. 2018. https://doi.org/10.1111/medu.13519 .

Dyre L, Tolsgaard MG. The gap in transfer research. Med Educ. 2018. https://doi.org/10.1111/medu.13591 .

Van Baalen S, Leemans A, Dik P, Lilien MR, Ten Haken B, Froeling M. Intravoxel incoherent motion modeling in the kidneys: comparison of mono-, bi-, and triexponential fit. J Magn Reson Imaging. 2017. https://doi.org/10.1002/jmri.25519 .

Van Baalen S, Froeling M, Asselman M, Klazen C, Jeltes C, Van Dijk L, et al. Mono, bi-and tri-exponential diffusion MRI modelling for renal solid masses and comparison with histopathological findings. Cancer Imaging. 2018. https://doi.org/10.1186/s40644-018-0178-0 .

Kuhn TS. The Structure of Scientific Revolutions. 2nd ed. Chicago: The University of Chicago Press; 1970.

Boon M, Van Baalen S. Epistemology for interdisciplinary research–shifting philosophical paradigms of science. Eur J Philos Sci. 2019. https://doi.org/10.1007/s13194-018-0242-4 .

Flavell JH. Metacognition and cognitive monitoring: a new area of cognitive–developmental inquiry. Am Psychol. 1979. https://doi.org/10.1037/0003-066X.34.10.906 .

Pintrich P P.R. The role of metacognitive knowledge in learning, teaching, and assessing. Theory into Pract. 2002. https://doi.org/10.1207/s15430421tip4104_3 .

Groenier M, Pieters JM, Miedema HAT. Technical medicine: designing medical technological solutions for improved health care. Med Sci Educ 2017, https://doi.org/10.1007/s40670-017-0443-z

Chandarana H, Kang SK, Wong S, Rusinek H, Zhang JL, Arizono S et al. Diffusion-Weighted Intravoxel Incoherent Motion Imaging of Renal Tumors with Histopathologic Correlation. Invest Radiol 2012. https://doi.org/10.1097/RLI.0b013e31826a0a49 .

Feng Q, Ma Z, Zhang S, Wu J. Usefulness of diffusion tensor imaging for the differentiation between low-fat angiomyolipoma and clear cell carcinoma of the kidney. SpringerPlus. 2016. https://doi.org/10.1186/s40064-015-1628-x .

Rheinheimer S, Stieltjes B, Schneider F, Simon D, Pahernik S, Kauczor HU, et al. Investigation of renal lesions by diffusion-weighted magnetic resonance imaging applying intravoxel incoherent motion-derived parameters–initial experience. Eur J Radiol. 2012. https://doi.org/10.1016/j.ejrad.2011.10.016 .

Van der Bel R, Gurney-Champion OJ, Froeling M, Stroues ESG, Nederveen AJ, Krediet CTP. A tri-exponential model for intravoxel incoherent motion analysis of the human kidney: in silico and during pharmacological renal perfusion modulation. Eur J Radiol. 2017. https://doi.org/10.1016/j.ejrad.2017.03.008 .

Boon M: Philosophy of science in practice: a proposal for epistemological constructivism. 2015; Helsinki (Finland). Edited by Leitgeb H, Niiniluoto I, Seppälä P, Sober E. Helsinki (Finland): College publications. 2017a:289–310. 2017a.

Fleck L. Genesis and development of a scientific fact. Chicago: University of Chicago Press; 1935/1979.

Mößner N. Thought styles and paradigms—a comparative study of Ludwik Fleck and Thomas S. Kuhn. Stud Hist Philos Sci Part A. 2011. https://doi.org/10.1016/j.shpsa.2010.12.002 .

Sady W. Ludwik Fleck. In: the stanford encyclopedia of philosophy. Zalta EN, editor. 2017. https://plato.stanford.edu/archives/fall2017/entries/fleck/ . Accessed 30 Jul 2020.

Boon M. An engineering paradigm in the biomedical sciences: knowledge as epistemic tool. Prog Biophys Mol Biol. 2017b. doi:j.pbiomolbio.2017.04.001.

Van Baalen S, Boon M. An epistemological shift: from evidence-based medicine to epistemological responsibility. J Eval Clin Pract. 2015. https://doi.org/10.1111/jep.12282 .

Woods NN, Brooks LR, Norman GR. The role of biomedical knowledge in diagnosis of difficult clinical cases. Adv Health Sci Educ. 2007;12:417–26.

Schmidt HG, Rikers RMJP. How expertise develops in medicine: knowledge encapsulation and illness script formation. Med Educ. 2007. https://doi.org/10.1111/j.1365-2923.2007.02915.x .

Newell WH. A theory of interdisciplinary studies. Issues Integr Stud. 2001;19:1–25.

Ivanitskaya L, Clark D, Montgomery G, Primeau R. Interdisciplinary learning: process and outcomes. Innov High Educ. 2002. https://doi.org/10.1023/A:1021105309984 .

Nikitina S. Three strategies for interdisciplinary teaching: contextualizing, conceptualizing, and problem-centring. J Curric stud. 2006. https://doi.org/10.1080/00220270500422632 .

Aram JD. Concepts of interdisciplinarity: configurations of knowledge and action. Hum Relat. 2004. https://doi.org/10.1177/0018726704043893 .

Aboelela SW, Larson E, Bakken S, Carrasquillo O, Formicola A, Glied SA, et al. Defining interdisciplinary research: conclusions from a critical review of the literature. Health Serv Res. 2007. https://doi.org/10.1111/j.1475-6773.2006.00621.x .

Mansilla VB, Duraisingh ED, Wolfe CR, Haynes C. Targeted assessment rubric: an empirically grounded rubric for interdisciplinary writing. J High Educ. 2009;80(3):334–53.

Spelt EJ, Biemans HJ, Tobi H, Luning PA, Mulder M. Teaching and learning in interdisciplinary higher education: a systematic review. Educ Psychol Rev. 2009. https://doi.org/10.1007/s10648-009-9113-z .

Klein JA. A Taxonomy of interdisciplinarity. In: Frodeman R, editor. In the oxford handbook of interdisciplinarity. Oxford: Oxford University press; 2010. p. 15–30.

Terpstra JL, Best A, Abrams DB, Moor G. Health sciences and health services. In: Frodeman R, editor. The Oxford Handbook of Interdisciplinarity. Oxford: Oxford University Press; 2010.

DeZure D. Interdisciplinary pedagogies in higher education. In: Frodeman R, editor. In the oxford handbook of interdisciplinarity. Oxford: Oxford University press; 2010. p. 372–87.

Frenk J, Chen L, Bhutta ZA, Cohen J, Crisp N, Evans T. Health professionals for a new century: transforming education to strengthen health systems in an interdependent world. Lancet. 2010. https://doi.org/10.1016/S0140-6736(10)61854-5 .

Haynes C, Brown-Leonard J. From surprise parties to mapmaking: undergraduate journeys toward interdisciplinary understanding. J High Educ. 2010. https://doi.org/10.1080/00221546.2010.11779070 .

Hirsch-Hadorn G, Pohl C, Bammer G. Solving problems through transdisciplinary research. In: Frodeman R, editor. In the oxford handbook of interdisciplinarity. Oxford: Oxford University press; 2010. p. 431–52.

Szostak R. The interdisciplinary research process. In: Repko AF, Newell WH, Szostak R, editors. In Interdisciplinary research: case studies of integrative understandings of complex problems. Thousand Oaks, CA: Sage; 2011. p. 3–19.

McNair LD, Newswander C, Boden D, Borrego M. Student and faculty interdisciplinary identities in self-managed teams. J Eng Educ. 2011. https://doi.org/10.1002/j.2168-9830.2011.tb00018.x .

Liu SY, Lin CS, Tsai CC. College Students’ scientific epistemological views and thinking patterns in Socioscientific decision making. Sci Educ. 2011. https://doi.org/10.1002/sce.20422 .

Abu-Rish E, Kim S, Choe L, Varpio L, Malik E, White AA, et al. Current trends in interprofessional education of health sciences students: a literature review. J Interprof Care. 2012. https://doi.org/10.3109/13561820.2012.715604 .

Bammer G. Disciplining interdisciplinarity - integration and implementation sciences for researching Complex real-world problems. Canberra: Australian National University E-Press; 2013.

Holbrook JB. What is interdisciplinary communication? Reflections on the very idea of disciplinary integration. Synthese. 2013. https://doi.org/10.1007/s11229-012-0179-7 .

Andersen H. The second essential tension: on tradition and innovation in interdisciplinary research. Topoi. 2013. https://doi.org/10.1007/s11245-012-9133-z .

Andersen H. Collaboration, interdisciplinarity, and the epistemology of contemporary science. Stud Hist Philos Sci Part A. 2016. https://doi.org/10.1016/j.shpsa.2015.10.006 .

Lattuca LR, Knight DB, Bergom IM. Developing a measure of interdisciplinary competence for engineers. Paper presented at the American Society for Engineering Education 2012 Annual Conference & Exposition, San Antonio, Texas, USA; 2013.

Acquavita SP, Lewis MA, Aparicio E, Pecukonis E. Student perspectives on interprofessional education and experiences. J Allied Health. 2014;43(2):e31–6.

Pharo E, Davison A, McGregor H, Warr K, Brown P. Using communities of practice to enhance interdisciplinary teaching: lessons from four Australian institutions. High Educ Res Dev. 2014. https://doi.org/10.1080/07294360.2013.832168 .

Boon M. How philosophical beliefs about science affect science education in academic engineering programs: the context of construction. Eng Stud. 2022. https://doi.org/10.1080/19378629.2022.2125398 .

Bromme R, Pieschl S, Stahl E. Epistemological beliefs are standards for adaptive learning: a functional theory about epistemological beliefs and metacognition. Metacognition Learn. 2010. https://doi.org/10.1007/s11409-009-9053-5 .

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Acknowledgements

We are very grateful to three anonymous reviewers who have provided valuable feedback and suggestions that have helped us improve the paper.

This work is financed by an Aspasia grant (409.40216) of the Dutch National Science Foundation (NWO) for the project Philosophy of Science for the Engineering Sciences , and by the work package Interdisciplinary Engineering Education at the 4TU-CEE (Centre Engineering Education https://www.4tu.nl/cee/en/ ) in The Netherlands.

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SvB and MB have co-authored the manuscript and have contributed equally to the article.

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Mieke Boon (PhD) graduated in chemical engineering (cum laude) and is a full professor in philosophy of science in practice . Her research aims at a philosophy of science for the engineering sciences , addressing topics such as methodology, technological instruments, scientific modeling, paradigms of science, interdisciplinarity, and science teaching. Sophie van Baalen (PhD) graduated in technical medicine and in philosophy of science technology and society , both cum laude. She recently finished her PhD project in which she aimed to understand epistemological aspects of technical medicine from a philosophy of science perspective, such as evidence-based medicine, expertise, interdisciplinarity and technological instruments.

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van Baalen, S., Boon, M. Understanding disciplinary perspectives: a framework to develop skills for interdisciplinary research collaborations of medical experts and engineers. BMC Med Educ 24 , 1000 (2024). https://doi.org/10.1186/s12909-024-05913-1

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Received : 14 July 2023

Accepted : 14 August 2024

Published : 13 September 2024

DOI : https://doi.org/10.1186/s12909-024-05913-1

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