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• Writing Strong Research Questions | Criteria & Examples

Writing Strong Research Questions | Criteria & Examples

Published on October 26, 2022 by Shona McCombes . Revised on November 21, 2023.

A research question pinpoints exactly what you want to find out in your work. A good research question is essential to guide your research paper , dissertation , or thesis .

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

Table of contents

How to write a research question, what makes a strong research question, using sub-questions to strengthen your main research question, research questions quiz, other interesting articles, frequently asked questions about research questions.

You can follow these steps to develop a strong research question:

• Choose your topic
• Do some preliminary reading about the current state of the field
• Narrow your focus to a specific niche
• Identify the research problem that you will address

The way you frame your question depends on what your research aims to achieve. The table below shows some examples of how you might formulate questions for different purposes.

Using your research problem to develop your research question

Note that while most research questions can be answered with various types of research , the way you frame your question should help determine your choices.

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Research questions anchor your whole project, so it’s important to spend some time refining them. The criteria below can help you evaluate the strength of your research question.

Focused and researchable

Feasible and specific

Complex and arguable

Relevant and original

Chances are that your main research question likely can’t be answered all at once. That’s why sub-questions are important: they allow you to answer your main question in a step-by-step manner.

Good sub-questions should be:

• Less complex than the main question
• Focused only on 1 type of research
• Presented in a logical order

Here are a few examples of descriptive and framing questions:

• Descriptive: According to current government arguments, how should a European bank tax be implemented?
• Descriptive: Which countries have a bank tax/levy on financial transactions?
• Framing: How should a bank tax/levy on financial transactions look at a European level?

Keep in mind that sub-questions are by no means mandatory. They should only be asked if you need the findings to answer your main question. If your main question is simple enough to stand on its own, it’s okay to skip the sub-question part. As a rule of thumb, the more complex your subject, the more sub-questions you’ll need.

Try to limit yourself to 4 or 5 sub-questions, maximum. If you feel you need more than this, it may be indication that your main research question is not sufficiently specific. In this case, it’s is better to revisit your problem statement and try to tighten your main question up.

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

Methodology

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

 Statistics

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

Research bias

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

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 .

A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis —a prediction that will be confirmed or disproved by your research.

As you cannot possibly read every source related to your topic, it’s important to evaluate sources to assess their relevance. Use preliminary evaluation to determine whether a source is worth examining in more depth.

This involves:

• Reading abstracts , prefaces, introductions , and conclusions
• Looking at the table of contents to determine the scope of the work
• Consulting the index for key terms or the names of important scholars

A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (“ x affects y because …”).

A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses . In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.

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

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• Cookies & Privacy
• GETTING STARTED
• Introduction
• FUNDAMENTALS
• Acknowledgements
• Research questions & hypotheses
• Concepts, constructs & variables
• Research limitations
• Getting started
• Sampling Strategy
• Research Quality
• Research Ethics
• Data Analysis

FUTURE RESEARCH

Types of future research suggestion.

The Future Research section of your dissertation is often combined with the Research Limitations section of your final, Conclusions chapter. This is because your future research suggestions generally arise out of the research limitations you have identified in your own dissertation. In this article, we discuss six types of future research suggestion. These include: (1) building on a particular finding in your research; (2) addressing a flaw in your research; examining (or testing) a theory (framework or model) either (3) for the first time or (4) in a new context, location and/or culture; (5) re-evaluating and (6) expanding a theory (framework or model). The goal of the article is to help you think about the potential types of future research suggestion that you may want to include in your dissertation.

Before we discuss each of these types of future research suggestion, we should explain why we use the word examining and then put or testing in brackets. This is simply because the word examining may be considered more appropriate when students use a qualitative research design; whereas the word testing fits better with dissertations drawing on a quantitative research design. We also put the words framework or model in brackets after the word theory . We do this because a theory , framework and model are not the same things. In the sections that follow, we discuss six types of future research suggestion.

Addressing research limitations in your dissertation

Building on a particular finding or aspect of your research, examining a conceptual framework (or testing a theoretical model) for the first time, examining a conceptual framework (or testing a theoretical model) in a new context, location and/or culture.

• Expanding a conceptual framework (or testing a theoretical model)

Re-evaluating a conceptual framework (or theoretical model)

In the Research Limitations section of your Conclusions chapter, you will have inevitably detailed the potential flaws (i.e., research limitations) of your dissertation. These may include:

An inability to answer your research questions

Theoretical and conceptual problems

Limitations of your research strategy

Problems of research quality

Identifying what these research limitations were and proposing future research suggestions that address them is arguably the easiest and quickest ways to complete the Future Research section of your Conclusions chapter.

Often, the findings from your dissertation research will highlight a number of new avenues that could be explored in future studies. These can be grouped into two categories:

Your dissertation will inevitably lead to findings that you did not anticipate from the start. These are useful when making future research suggestions because they can lead to entirely new avenues to explore in future studies. If this was the case, it is worth (a) briefly describing what these unanticipated findings were and (b) suggesting a research strategy that could be used to explore such findings in future.

Sometimes, dissertations manage to address all aspects of the research questions that were set. However, this is seldom the case. Typically, there will be aspects of your research questions that could not be answered. This is not necessarily a flaw in your research strategy, but may simply reflect that fact that the findings did not provide all the answers you hoped for. If this was the case, it is worth (a) briefly describing what aspects of your research questions were not answered and (b) suggesting a research strategy that could be used to explore such aspects in future.

You may want to recommend that future research examines the conceptual framework (or tests the theoretical model) that you developed. This is based on the assumption that the primary goal of your dissertation was to set out a conceptual framework (or build a theoretical model). It is also based on the assumption that whilst such a conceptual framework (or theoretical model) was presented, your dissertation did not attempt to examine (or test) it in the field . The focus of your dissertations was most likely a review of the literature rather than something that involved you conducting primary research.

Whilst it is quite rare for dissertations at the undergraduate and master's level to be primarily theoretical in nature like this, it is not unknown. If this was the case, you should think about how the conceptual framework (or theoretical model) that you have presented could be best examined (or tested) in the field . In understanding the how , you should think about two factors in particular:

What is the context, location and/or culture that would best lend itself to my conceptual framework (or theoretical model) if it were to be examined (or tested) in the field?

What research strategy is most appropriate to examine my conceptual framework (or test my theoretical model)?

If the future research suggestion that you want to make is based on examining your conceptual framework (or testing your theoretical model) in the field , you need to suggest the best scenario for doing so.

More often than not, you will not only have set out a conceptual framework (or theoretical model), as described in the previous section, but you will also have examined (or tested) it in the field . When you do this, focus is typically placed on a specific context, location and/or culture.

If this is the case, the obvious future research suggestion that you could propose would be to examine your conceptual framework (or test the theoretical model) in a new context, location and/or culture. For example, perhaps you focused on consumers (rather than businesses), or Canada (rather than the United Kingdom), or a more individualistic culture like the United States (rather than a more collectivist culture like China).

When you propose a new context, location and/or culture as your future research suggestion, make sure you justify the choice that you make. For example, there may be little value in future studies looking at different cultures if culture is not an important component underlying your conceptual framework (or theoretical model). If you are not sure whether a new context, location or culture is more appropriate, or what new context, location or culture you should select, a review the literature will often help clarify where you focus should be.

Expanding a conceptual framework (or theoretical model)

Assuming that you have set out a conceptual framework (or theoretical model) and examined (or tested) it in the field , another series of future research suggestions comes out of expanding that conceptual framework (or theoretical model).

We talk about a series of future research suggestions because there are so many ways that you can expand on your conceptual framework (or theoretical model). For example, you can do this by:

Examining constructs (or variables) that were included in your conceptual framework (or theoretical model) but were not focused.

Looking at a particular relationship aspect of your conceptual framework (or theoretical model) further.

Adding new constructs (or variables) to the conceptual framework (or theoretical model) you set out (if justified by the literature).

It would be possible to include one or a number of these as future research suggestions. Again, make sure that any suggestions you make have are justified , either by your findings or the literature.

With the dissertation process at the undergraduate and master's level lasting between 3 and 9 months, a lot a can happen in between. For example, a specific event (e.g., 9/11, the economic crisis) or some new theory or evidence that undermines (or questions) the literature (theory) and assumptions underpinning your conceptual framework (or theoretical model). Clearly, there is little you can do about this. However, if this happens, reflecting on it and re-evaluating your conceptual framework (or theoretical model), as well as your findings, is an obvious source of future research suggestions.

Research Question Examples 🧑🏻‍🏫

25+ Practical Examples & Ideas To Help You Get Started 

By: Derek Jansen (MBA) | October 2023

A well-crafted research question (or set of questions) sets the stage for a robust study and meaningful insights.  But, if you’re new to research, it’s not always clear what exactly constitutes a good research question. In this post, we’ll provide you with clear examples of quality research questions across various disciplines, so that you can approach your research project with confidence!

Research Question Examples

• Psychology research questions
• Business research questions
• Education research questions
• Healthcare research questions
• Computer science research questions

Examples: Psychology

Let’s start by looking at some examples of research questions that you might encounter within the discipline of psychology.

How does sleep quality affect academic performance in university students?

This question is specific to a population (university students) and looks at a direct relationship between sleep and academic performance, both of which are quantifiable and measurable variables.

What factors contribute to the onset of anxiety disorders in adolescents?

The question narrows down the age group and focuses on identifying multiple contributing factors. There are various ways in which it could be approached from a methodological standpoint, including both qualitatively and quantitatively.

Do mindfulness techniques improve emotional well-being?

This is a focused research question aiming to evaluate the effectiveness of a specific intervention.

How does early childhood trauma impact adult relationships?

This research question targets a clear cause-and-effect relationship over a long timescale, making it focused but comprehensive.

Is there a correlation between screen time and depression in teenagers?

This research question focuses on an in-demand current issue and a specific demographic, allowing for a focused investigation. The key variables are clearly stated within the question and can be measured and analysed (i.e., high feasibility).

Examples: Business/Management

Next, let’s look at some examples of well-articulated research questions within the business and management realm.

How do leadership styles impact employee retention?

This is an example of a strong research question because it directly looks at the effect of one variable (leadership styles) on another (employee retention), allowing from a strongly aligned methodological approach.

What role does corporate social responsibility play in consumer choice?

Current and precise, this research question can reveal how social concerns are influencing buying behaviour by way of a qualitative exploration.

Does remote work increase or decrease productivity in tech companies?

Focused on a particular industry and a hot topic, this research question could yield timely, actionable insights that would have high practical value in the real world.

How do economic downturns affect small businesses in the homebuilding industry?

Vital for policy-making, this highly specific research question aims to uncover the challenges faced by small businesses within a certain industry.

Which employee benefits have the greatest impact on job satisfaction?

By being straightforward and specific, answering this research question could provide tangible insights to employers.

Examples: Education

Next, let’s look at some potential research questions within the education, training and development domain.

How does class size affect students’ academic performance in primary schools?

This example research question targets two clearly defined variables, which can be measured and analysed relatively easily.

Do online courses result in better retention of material than traditional courses?

Timely, specific and focused, answering this research question can help inform educational policy and personal choices about learning formats.

What impact do US public school lunches have on student health?

Targeting a specific, well-defined context, the research could lead to direct changes in public health policies.

To what degree does parental involvement improve academic outcomes in secondary education in the Midwest?

This research question focuses on a specific context (secondary education in the Midwest) and has clearly defined constructs.

What are the negative effects of standardised tests on student learning within Oklahoma primary schools?

This research question has a clear focus (negative outcomes) and is narrowed into a very specific context.

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Examples: Healthcare

Shifting to a different field, let’s look at some examples of research questions within the healthcare space.

What are the most effective treatments for chronic back pain amongst UK senior males?

Specific and solution-oriented, this research question focuses on clear variables and a well-defined context (senior males within the UK).

How do different healthcare policies affect patient satisfaction in public hospitals in South Africa?

This question is has clearly defined variables and is narrowly focused in terms of context.

Which factors contribute to obesity rates in urban areas within California?

This question is focused yet broad, aiming to reveal several contributing factors for targeted interventions.

Does telemedicine provide the same perceived quality of care as in-person visits for diabetes patients?

Ideal for a qualitative study, this research question explores a single construct (perceived quality of care) within a well-defined sample (diabetes patients).

Which lifestyle factors have the greatest affect on the risk of heart disease?

This research question aims to uncover modifiable factors, offering preventive health recommendations.

Examples: Computer Science

Last but certainly not least, let’s look at a few examples of research questions within the computer science world.

What are the perceived risks of cloud-based storage systems?

Highly relevant in our digital age, this research question would align well with a qualitative interview approach to better understand what users feel the key risks of cloud storage are.

Which factors affect the energy efficiency of data centres in Ohio?

With a clear focus, this research question lays a firm foundation for a quantitative study.

How do TikTok algorithms impact user behaviour amongst new graduates?

While this research question is more open-ended, it could form the basis for a qualitative investigation.

What are the perceived risk and benefits of open-source software software within the web design industry?

Practical and straightforward, the results could guide both developers and end-users in their choices.

Remember, these are just examples…

In this post, we’ve tried to provide a wide range of research question examples to help you get a feel for what research questions look like in practice. That said, it’s important to remember that these are just examples and don’t necessarily equate to good research topics . If you’re still trying to find a topic, check out our topic megalist for inspiration.

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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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Educational resources and simple solutions for your research journey

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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How to Write a Research Question in 2024: Types, Steps, and Examples

by Imed Bouchrika, Phd

Co-Founder and Chief Data Scientist

A note from the author, Imed Bouchrika, PhD, career planning and academic research expert:

From conducting preliminary literature reviews to collecting data, every part of the research process relies on a research question. As an expert with more than 10 years of experience in academic research and writing, I know well that identifying a research question can be challenging even with primary and secondary research sources as the literature body continues to expand. Given this challenge, I have created this guide on how to create a good research question based on actual practices in the academe. Through this guide, I hope to impart knowledge that can help you in identifying a research question and also in creating a study that can significantly impact your field.

How to Write a Research Question Table of Contents

What is a research question, types of research questions, steps to developing a good research question, examples of good and bad research questions, important points to keep in mind in creating a research question.

A research question is a question that a study or research project, through its thesis statement , aims to answer. This question often addresses an issue or a problem, which, through analysis and interpretation of data, is answered in the study’s conclusion. In most studies, the research question is written so that it outlines various aspects of the study, including the population and variables to be studied and the problem the study addresses.

As their name implies, a research question is often grounded on research. As a result, these questions are dynamic; this means researchers can change or refine the research question as they review related literature and develop a framework for the study. While many research projects will focus on a single research question, larger studies often use more than one research question.

Importance of the research question

The primary importance of developing a research question is that it narrows down a broad topic of interest into a specific area of study (Creswell, 2014). Research questions, along with hypotheses, also serve as a guiding framework for research. These questions also specifically reveal the boundaries of the study, setting its limits, and ensuring cohesion.

Moreover, the research question has a domino effect on the rest of the study. These questions influence factors, such as the research methodology, sample size, data collection, and data analysis (Lipowski, 2008).

Research questions can be classified into different categories, depending on the type of research to be done. Knowing what type of research one wants to do—quantitative, qualitative, or mixed-methods studies—can help in writing effective research questions.

Doody and Bailey (2016) suggest a number of common types of research questions, as outlined below.

Quantitative research questions

Quantitative research questions are precise. These questions typically include the population to be studied, dependent and independent variables, and the research design to be used. They are usually framed and finalized at the start of the study (Berger, 2015).

Quantitative research questions also establish a link between the research question and the research design. Moreover, these questions are not answerable with “yes" or “no" responses. As a result, quantitative research questions don’t use words such as “is," “are," “do," or “does."

Quantitative research questions usually seek to understand particular social, familial, or educational experiences or processes that occur in a particular context and/or location (Marshall & Rossman, 2011). They can be further categorized into three types: descriptive, comparative, and relationship.

• Descriptive research questions aim to measure the responses of a study’s population to one or more variables or describe variables that the research will measure. These questions typically begin with “what". Students aim for a what is research question to uncover particular processes.
• Comparative research questions aim to discover the differences between two or more groups for an outcome variable. These questions can be causal, as well. For instance, the researcher may compare a group where a certain variable is involved and another group where that variable is not present.
• Relationship research questions seek to explore and define trends and interactions between two or more variables. This research question design often includes both dependent and independent variables and use words such as “association" or “trends."

Qualitative research questions

Qualitative research questions may concern broad areas of research or more specific areas of study. Similar to quantitative research questions, qualitative research questions are linked to research design. Unlike their quantitative counterparts, though, qualitative research questions are usually adaptable, non-directional, and more flexible (Creswell, 2013). As a result, studies using these questions generally aim to “discover," “explain," or “explore."

Ritchie et al. (2014) and Marshall and Rossman (2011) have also further categorized qualitative research questions into a number of types, as listed below:

• Contextual research questions seek to describe the nature of what already exists.
• Descriptive research questions attempt to describe a phenomenon.
• Emancipatory research questions aim to produce knowledge that allows for engagement in social action, especially for the benefit of disadvantaged people.
• Evaluative research questions assess the effectiveness of existing methods or paradigms.
• Explanatory research questions seek to expound on a phenomenon or examine reasons for and associations between what exists.
• Exploratory research questions investigate little-known areas of a particular topic.
• Generative research questions aim to provide new ideas for the development of theories and actions.
• Ideological research questions are used in research that aims to advance specific ideologies of a position.

The following table illustrates the differences between quantitative and qualitative research questions.

Mixed-methods studies

Mixed-methods studies typically require a set of both quantitative and qualitative research questions. Separate questions are appropriate when the mixed-methods study focuses on the significance and differences in quantitative and qualitative methods and not on the study’s integrative component (Tashakkori & Teddlie, 2010).

Researchers also have the option to develop a single mixed-methods research question. According to Tashakkori and Teddlie (2010), this suggests an integrative process or component between the study’s quantitative and qualitative research methods.

Before learning how to write a research paper , you must first learn how to create a research question. Based on the research question definition provided, formulate your query. If you are looking for criteria for a good research question, Stone (2002) says that a good research question should be relevant, decided, and meaningful. Creating a research question can be a tricky process, but there is a specific method you can follow to ease the process.

The following steps will guide you on how to formulate a research question:

1. Start with a broad topic.

A broad topic provides writers with plenty of avenues to explore in their search for a viable research question. Techniques to help you develop a topic into subtopics and potential research questions include brainstorming and concept mapping. For example, you can raise thought-provoking questions with your friends and flesh out ideas from your discussions. These techniques can organize your thoughts so you can identify connections and relevant themes within a broad topic.

When searching for a topic, it’s wise to choose an area of study that you are genuinely interested in, since your interest in a topic will affect your motivation levels throughout your research. It’s also wise to consider the interests being addressed recently by the research community, as this may affect your paper’s chances of getting published.

2. Do preliminary research to learn about topical issues.

Once you have picked a topic, you can start doing preliminary research. This initial stage of research accomplishes two goals. First, a preliminary review of related literature allows you to discover issues that are currently being discussed by scholars and fellow researchers. This way, you get up-to-date, relevant knowledge on your topic.

Second, a preliminary review of related literature allows you to spot existing gaps or limitations in existing knowledge of your topic. With a certain amount of fine-tuning, you can later use these gaps as the focus of your research question.

Moreover, according to Farrugia et al. (2010), certain institutions that provide grants encourage applicants to conduct a systematic review of available studies and evidence to see if a similar, recent study doesn’t already exist, before applying for a grant.

3. Narrow down your topic and determine potential research questions.

Once you have gathered enough knowledge on the topic you want to pursue, you can start focusing on a more specific area of study and narrowing down a research question. One option is to focus on gaps in existing knowledge or recent literature. Referred to by Sandberg and Alvesson (2011) as “gap-spotting," this method involves constructing research questions out of identified limitations in literature and overlooked areas of study. Similarly, researchers can choose research questions that extend or complement the findings of existing literature.

Another way of identifying and constructing research questions: problematization (Sandberg & Alvesson, 2011). As a research question methodology, problematization aims to challenge and scrutinize assumptions that support others’ and the researcher’s theoretical position. This means constructing research questions that challenge your views or knowledge of the area of study.

Lipowski (2008), on the other hand, emphasizes the importance of taking into consideration the researcher’s personal experiences in the process of developing a research question. Researchers who are also practitioners, for instance, can reflect on problematic areas of their practice. Patterns and trends in practice may also provide new insights and potential research question examples.

4. Evaluate the soundness of your research question.

At this point, you should have a list of potential research questions to choose from. To narrow them down, you have to evaluate each potential option based on their soundness, which can mean a number of things. Aside from being clear or specific, a good research question will also need to be relevant. There are other factors to consider when choosing which research question to investigate. To create a better play-by-play, here are the most crucial characteristics of the research question that you are looking for according to Hulley et al. (2007) known as the “FINER" criteria to find out if you have a good research question. The FINER criteria are outlined below:

F Feasible A good research question is feasible, which means that the question is well within the researcher’s ability to investigate. Researchers should be realistic about the scale of their research as well as their ability to collect data and complete the research with their skills and the resources available to them. It’s also wise to have a contingency plan in place in case problems arise.

I Interesting The ideal research question is interesting not only to the researcher but also to their peers and community. This interest boosts the researcher’s motivation to see the question answered. For instance, you can do research on student housing trends if it is right up your alley, as they do change often.

N Novel Your research question should be developed to bring new insights to the field of study you are investigating. The question may confirm or extend previous findings on the topic you are researching, for instance.

E Ethical This is one of the more important considerations of making a research question. Your research question and your subsequent study must be something that review boards and the appropriate authorities will approve.

R Relevant Aside from being interesting and novel, the research question should be relevant to the scientific community and people involved in your area of study. If possible, your research question should also be relevant to the public’s interest.

5. Construct your research question properly.

Considering research question importance, research questions should be structured properly to ensure clarity. Look for good research questions examples. There are a number of frameworks that you can use for properly constructing a research question. The two most commonly used frameworks are explained below.

PICOT framework

The PICOT research question framework was first introduced in 1995 by Richardson et al. Using the PICOT framework, research questions can be constructed to address important elements of the study, including the population to be studied, the expected outcomes, and the time it takes to achieve the outcome. With these elements, the framework is more commonly used in clinical research and evidence-based studies.

• P population, patients, or problem
• I intervention or indicator being studied
• C comparison group
• O outcome of interest
• T timeframe of the study

The sample research question below illustrates how to write research questions based on the PICOT framework and its elements:

PEO framework

Like the PICOT framework, the PEO framework is commonly used in clinical studies as well. However, this framework is more useful for qualitative research questions. This framework includes these elements:

• P population being studied
• E exposure to preexisting conditions

Below is an example of research question in the PEO framework:

Other commonly used frameworks for research questions include the SPIDER (Sample, Phenomenon of Interest, Design, Evaluation, Research type) and CLIP (Client group, Location of provided service, Improvement/Information/Innovation, Professionals) frameworks. Aside from helping researchers properly structure research questions, these frameworks also help refine research results and improve the focus of data analysis.

The following research question examples can further guide researchers on properly constructing a research question.

Example no. 1

Bad: How does social media affect people’s behavior? Good: What effect does the daily use of YouTube have on the attention span of children aged under 16?

The first research question is considered bad because of the vagueness of “social media" as a concept and the question’s lack of specificity. A good research question should be specific and focused, and its answer should be discovered through data collection and analysis. You can also hone your ability to construct well-worded and specific research questions by improving reading skills .

Example no. 2

Bad: Has there been an increase in childhood obesity in the US in the past 10 years? Good: How have school intervention programs and parental education levels affected the rate of childhood obesity among 1st to 6th-grade students?

In the second example, the first research question is not ideal because it’s too simple, and it’s easily answerable by a “yes" or “no." The second research question is more complicated; to answer it, the researcher must collect data, perform in-depth data analysis, and form an argument that leads to further discussion.

Developing the right research question is a critical first step in the research process. The examples of research questions provided in this guide have illustrated what good research questions look like. The key points outlined below should help researchers in the pursuit:

• The development of a research question is an iterative process that involves continuously updating one’s knowledge on the topic and refining ideas at all stages (Maxwell, 2013).
• Remain updated on current trends, state-of-the-art research studies, and technological advances in the field of study you are pursuing.
• Make the research question as specific and concise as possible to ensure clarity. Avoid using words or terms that don’t add to the meaning of the research question.
• Aside from doing a literature review, seek the input of experts in the field, mentors, and colleagues. Such inputs can prove beneficial not only for the research question but also for creating the rest of the study.
• Finally, refrain from committing the two most common mistakes in framing research questions: posing a question as an anticipated contribution and framing a question as a method (Mayo et al., 2013).

Key Insights

• Central Role of Research Questions: A research question is foundational to the entire research process, guiding the scope, methodology, and analysis of a study.
• Types of Research Questions: Research questions can be categorized into quantitative, qualitative, and mixed-methods, each requiring different approaches and designs.
• Quantitative Research Questions: These are precise and structured, often exploring relationships, comparisons, or descriptions within a study.
• Qualitative Research Questions: These are flexible and exploratory, aiming to discover, explain, or describe phenomena.
• Mixed-Methods Research Questions: These incorporate both quantitative and qualitative elements, requiring comprehensive and integrative approaches.
• Steps to Developing Research Questions: The process involves starting with a broad topic, conducting preliminary research, narrowing down the topic, evaluating the soundness of potential questions, and properly constructing the final research question.
• Criteria for Good Research Questions: Good research questions should be feasible, interesting, novel, ethical, and relevant (FINER criteria).
• Frameworks for Constructing Research Questions: Common frameworks include PICOT for quantitative research and PEO for qualitative research, helping to ensure clarity and focus.
• Examples of Research Questions: Clear examples illustrate the difference between poorly constructed and well-formulated research questions, highlighting the importance of specificity and focus.

1. What is a research question?

A research question is a query that a study aims to answer, often addressing an issue or problem. It outlines the study's focus, including the population, variables, and problem being investigated.

2. Why is developing a research question important?

Developing a research question is crucial because it narrows down a broad topic into a specific area of study. It also guides the research framework, methodology, and analysis, ensuring the study's cohesion and relevance.

3. What are the different types of research questions?

Research questions can be categorized into quantitative, qualitative, and mixed-methods. Quantitative questions are precise and structured, qualitative questions are flexible and exploratory, and mixed-methods questions combine both approaches.

4. How do you start developing a research question?

Start by choosing a broad topic of interest. Conduct preliminary research to learn about current issues and gaps in existing literature. Narrow down the topic to a specific area of study and identify potential research questions.

5. What criteria should a good research question meet?

A good research question should be feasible, interesting, novel, ethical, and relevant. This means it should be realistically investigable, engaging, provide new insights, be ethically sound, and pertinent to the field of study.

6. How can frameworks help in constructing research questions?

Frameworks like PICOT for quantitative research and PEO for qualitative research help ensure that research questions are structured clearly and address essential elements such as population, intervention, and outcome, improving the study's focus and clarity.

7. Can you provide examples of good and bad research questions?

Yes. A bad question might be vague or too simple, such as "How does social media affect people’s behavior?" A good question is specific and focused, like "What effect does the daily use of YouTube have on the attention span of children aged under 16?"

8. What are some common mistakes to avoid when framing research questions?

Avoid posing a question as an anticipated contribution or framing a question as a method. Ensure the question is clear, specific, and avoids terms that don't add meaningful context or clarity to the research focus.

References:

• Berger, R. (2015). Now I see it, now I don’t: Researcher’s position and reflexivity in qualitative research. Qualitative Research, 15 (2), 219-234. https://doi.org/10.1177/1468794112468475
• Creswell, J.W. (2013). Qualitative Inquiry and Research Design: Choosing Among Five Approaches, 3rd ed . Thousand Oaks, CA: Sage.
• Creswell, J.W. (2014). Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research,   5th ed . Upper Saddle River, NJ: Pearson Education.
• Doody, O., & Bailey, M. E. (2016). Setting a research question, aim, and objective.  Nurse Researcher ,  23  (4). https://journals.rcni.com/doi/pdfplus/10.7748/nr.23.4.19.s5
• Farrugia, P., Petrisor, B. A., Farrokhyar, F., & Bhandari, M. (2010). Research questions, hypotheses, and objectives. Canadian Journal of Surgery , 53 (4), 278. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2912019/
• Lipowski, E. E. (2008). Developing great research questions.  American Journal of Health-System Pharmacy ,  65  (17), 1667-1670.  https://academic.oup.com/ajhp/article-abstract/65/17/1667/5128061
• Marshall, C., & Rossman, G. B. (2014).  Designing qualitative research . Sage publications. Google Books
• Mayo, N., Asano, M., & Barbic, S.P. (2013). When is a research question not a research question? Journal of Rehabilitation Medicine, 45 (6), 513-518. https://doi.org/10.2340/16501977-1150
• Patnaik, S., & Swaroop, S. (2019). Hypothesizing the research question. Indian Journal of Public Health Research & Development , 10  (11).  http://www.indianjournals.com/ijor.aspx?target=ijor:ijphrd&volume=10&issue=11&article=097
• Richardson, W. S., Wilson, M. C., Nishikawa, J., & Hayward, R. S. (1995). The well-built clinical question: a key to evidence-based decisions.  Acp j club ,  123  (3), A12-3. https://doi.org/10.7326/ACPJC-1995-123-3-A12
• Ritchie, J., Lewis, J., Nicholls, C. M., & Ormston, R. (Eds.). (2013).  Qualitative Research Practice: A Guide for Social Science Students and Researchers . Thousand Oaks, CA: Sage.   http://jbposgrado.org/icuali/Qualitative%20Research%20practice.pdf
• Sandberg, J., & Alvesson, M. (2011). Ways of constructing research questions: gap-spotting or problematization?  Organization ,  18  (1), 23-44. https://journals.sagepub.com/doi/abs/10.1177/1350508410372151
• Stone, P. (2002). Deciding upon and refining a research question. Palliative Medicine , 16, 265267.  https://doi.org/10.1191/0269216302pm562xx
• Tashakkori, A., & Teddlie, C. (Eds.). (2010).  Sage Handbook of Mixed Methods in Social & Behavioral Research . Thousand Oaks, CA: Sage.  https://doi.org/10.4135/9781506335193

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Home » Research Questions – Types, Examples and Writing Guide

Research Questions – Types, Examples and Writing Guide

Table of Contents

Research Questions

Definition:

Research questions are the specific questions that guide a research study or inquiry. These questions help to define the scope of the research and provide a clear focus for the study. Research questions are usually developed at the beginning of a research project and are designed to address a particular research problem or objective.

Types of Research Questions

Types of Research Questions are as follows:

Descriptive Research Questions

These aim to describe a particular phenomenon, group, or situation. For example:

• What are the characteristics of the target population?
• What is the prevalence of a particular disease in a specific region?

Exploratory Research Questions

These aim to explore a new area of research or generate new ideas or hypotheses. For example:

• What are the potential causes of a particular phenomenon?
• What are the possible outcomes of a specific intervention?

Explanatory Research Questions

These aim to understand the relationship between two or more variables or to explain why a particular phenomenon occurs. For example:

• What is the effect of a specific drug on the symptoms of a particular disease?
• What are the factors that contribute to employee turnover in a particular industry?

Predictive Research Questions

These aim to predict a future outcome or trend based on existing data or trends. For example :

• What will be the future demand for a particular product or service?
• What will be the future prevalence of a particular disease?

Evaluative Research Questions

These aim to evaluate the effectiveness of a particular intervention or program. For example:

• What is the impact of a specific educational program on student learning outcomes?
• What is the effectiveness of a particular policy or program in achieving its intended goals?

How to Choose Research Questions

Choosing research questions is an essential part of the research process and involves careful consideration of the research problem, objectives, and design. Here are some steps to consider when choosing research questions:

• Identify the research problem: Start by identifying the problem or issue that you want to study. This could be a gap in the literature, a social or economic issue, or a practical problem that needs to be addressed.
• Conduct a literature review: Conducting a literature review can help you identify existing research in your area of interest and can help you formulate research questions that address gaps or limitations in the existing literature.
• Define the research objectives : Clearly define the objectives of your research. What do you want to achieve with your study? What specific questions do you want to answer?
• Consider the research design : Consider the research design that you plan to use. This will help you determine the appropriate types of research questions to ask. For example, if you plan to use a qualitative approach, you may want to focus on exploratory or descriptive research questions.
• Ensure that the research questions are clear and answerable: Your research questions should be clear and specific, and should be answerable with the data that you plan to collect. Avoid asking questions that are too broad or vague.
• Get feedback : Get feedback from your supervisor, colleagues, or peers to ensure that your research questions are relevant, feasible, and meaningful.

How to Write Research Questions

Guide for Writing Research Questions:

• Start with a clear statement of the research problem: Begin by stating the problem or issue that your research aims to address. This will help you to formulate focused research questions.
• Use clear language : Write your research questions in clear and concise language that is easy to understand. Avoid using jargon or technical terms that may be unfamiliar to your readers.
• Be specific: Your research questions should be specific and focused. Avoid broad questions that are difficult to answer. For example, instead of asking “What is the impact of climate change on the environment?” ask “What are the effects of rising sea levels on coastal ecosystems?”
• Use appropriate question types: Choose the appropriate question types based on the research design and objectives. For example, if you are conducting a qualitative study, you may want to use open-ended questions that allow participants to provide detailed responses.
• Consider the feasibility of your questions : Ensure that your research questions are feasible and can be answered with the resources available. Consider the data sources and methods of data collection when writing your questions.
• Seek feedback: Get feedback from your supervisor, colleagues, or peers to ensure that your research questions are relevant, appropriate, and meaningful.

Examples of Research Questions

Some Examples of Research Questions with Research Titles:

Research Title: The Impact of Social Media on Mental Health

• Research Question : What is the relationship between social media use and mental health, and how does this impact individuals’ well-being?

Research Title: Factors Influencing Academic Success in High School

• Research Question: What are the primary factors that influence academic success in high school, and how do they contribute to student achievement?

Research Title: The Effects of Exercise on Physical and Mental Health

• Research Question: What is the relationship between exercise and physical and mental health, and how can exercise be used as a tool to improve overall well-being?

Research Title: Understanding the Factors that Influence Consumer Purchasing Decisions

• Research Question : What are the key factors that influence consumer purchasing decisions, and how do these factors vary across different demographics and products?

Research Title: The Impact of Technology on Communication

• Research Question : How has technology impacted communication patterns, and what are the effects of these changes on interpersonal relationships and society as a whole?

Research Title: Investigating the Relationship between Parenting Styles and Child Development

• Research Question: What is the relationship between different parenting styles and child development outcomes, and how do these outcomes vary across different ages and developmental stages?

Research Title: The Effectiveness of Cognitive-Behavioral Therapy in Treating Anxiety Disorders

• Research Question: How effective is cognitive-behavioral therapy in treating anxiety disorders, and what factors contribute to its success or failure in different patients?

Research Title: The Impact of Climate Change on Biodiversity

• Research Question : How is climate change affecting global biodiversity, and what can be done to mitigate the negative effects on natural ecosystems?

Research Title: Exploring the Relationship between Cultural Diversity and Workplace Productivity

• Research Question : How does cultural diversity impact workplace productivity, and what strategies can be employed to maximize the benefits of a diverse workforce?

Research Title: The Role of Artificial Intelligence in Healthcare

• Research Question: How can artificial intelligence be leveraged to improve healthcare outcomes, and what are the potential risks and ethical concerns associated with its use?

Applications of Research Questions

Here are some of the key applications of research questions:

• Defining the scope of the study : Research questions help researchers to narrow down the scope of their study and identify the specific issues they want to investigate.
• Developing hypotheses: Research questions often lead to the development of hypotheses, which are testable predictions about the relationship between variables. Hypotheses provide a clear and focused direction for the study.
• Designing the study : Research questions guide the design of the study, including the selection of participants, the collection of data, and the analysis of results.
• Collecting data : Research questions inform the selection of appropriate methods for collecting data, such as surveys, interviews, or experiments.
• Analyzing data : Research questions guide the analysis of data, including the selection of appropriate statistical tests and the interpretation of results.
• Communicating results : Research questions help researchers to communicate the results of their study in a clear and concise manner. The research questions provide a framework for discussing the findings and drawing conclusions.

Characteristics of Research Questions

Characteristics of Research Questions are as follows:

• Clear and Specific : A good research question should be clear and specific. It should clearly state what the research is trying to investigate and what kind of data is required.
• Relevant : The research question should be relevant to the study and should address a current issue or problem in the field of research.
• Testable : The research question should be testable through empirical evidence. It should be possible to collect data to answer the research question.
• Concise : The research question should be concise and focused. It should not be too broad or too narrow.
• Feasible : The research question should be feasible to answer within the constraints of the research design, time frame, and available resources.
• Original : The research question should be original and should contribute to the existing knowledge in the field of research.
• Significant : The research question should have significance and importance to the field of research. It should have the potential to provide new insights and knowledge to the field.
• Ethical : The research question should be ethical and should not cause harm to any individuals or groups involved in the study.

Purpose of Research Questions

Research questions are the foundation of any research study as they guide the research process and provide a clear direction to the researcher. The purpose of research questions is to identify the scope and boundaries of the study, and to establish the goals and objectives of the research.

The main purpose of research questions is to help the researcher to focus on the specific area or problem that needs to be investigated. They enable the researcher to develop a research design, select the appropriate methods and tools for data collection and analysis, and to organize the results in a meaningful way.

Research questions also help to establish the relevance and significance of the study. They define the research problem, and determine the research methodology that will be used to address the problem. Research questions also help to determine the type of data that will be collected, and how it will be analyzed and interpreted.

Finally, research questions provide a framework for evaluating the results of the research. They help to establish the validity and reliability of the data, and provide a basis for drawing conclusions and making recommendations based on the findings of the study.

Advantages of Research Questions

There are several advantages of research questions in the research process, including:

• Focus : Research questions help to focus the research by providing a clear direction for the study. They define the specific area of investigation and provide a framework for the research design.
• Clarity : Research questions help to clarify the purpose and objectives of the study, which can make it easier for the researcher to communicate the research aims to others.
• Relevance : Research questions help to ensure that the study is relevant and meaningful. By asking relevant and important questions, the researcher can ensure that the study will contribute to the existing body of knowledge and address important issues.
• Consistency : Research questions help to ensure consistency in the research process by providing a framework for the development of the research design, data collection, and analysis.
• Measurability : Research questions help to ensure that the study is measurable by defining the specific variables and outcomes that will be measured.
• Replication : Research questions help to ensure that the study can be replicated by providing a clear and detailed description of the research aims, methods, and outcomes. This makes it easier for other researchers to replicate the study and verify the results.

Limitations of Research Questions

Limitations of Research Questions are as follows:

• Subjectivity : Research questions are often subjective and can be influenced by personal biases and perspectives of the researcher. This can lead to a limited understanding of the research problem and may affect the validity and reliability of the study.
• Inadequate scope : Research questions that are too narrow in scope may limit the breadth of the study, while questions that are too broad may make it difficult to focus on specific research objectives.
• Unanswerable questions : Some research questions may not be answerable due to the lack of available data or limitations in research methods. In such cases, the research question may need to be rephrased or modified to make it more answerable.
• Lack of clarity : Research questions that are poorly worded or ambiguous can lead to confusion and misinterpretation. This can result in incomplete or inaccurate data, which may compromise the validity of the study.
• Difficulty in measuring variables : Some research questions may involve variables that are difficult to measure or quantify, making it challenging to draw meaningful conclusions from the data.
• Lack of generalizability: Research questions that are too specific or limited in scope may not be generalizable to other contexts or populations. This can limit the applicability of the study’s findings and restrict its broader implications.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Research questions that could have a big social impact, organised by discipline

On this page:.

• Introduction
• 1.1 What are these lists based on?
• 2 Biology and genetics
• 3 Business and organisational development
• 4 China studies
• 5 Climate studies and earth sciences
• 6 Cognitive science and neuroscience
• 7 Economics
• 8 Epidemiology, synthetic biology, and medicine
• 9 Global Priorities Research
• 12 Machine learning, artificial intelligence, and computer science
• 13 Philosophy
• 14 Physics and astronomy
• 15 Political science, international relations, and security studies
• 16 Psychology
• 17 Public policy
• 18 Science policy/infrastructure and metascience
• 19 Sociology
• 20 Statistics and mathematics
• 21.1 Want to work on one of the research questions above?
• 21.2 Thinking of going into academia?

About these research questions

People frequently ask us what high-impact research in different disciplines might look like. This might be because they’re already working in a field and want to shift their research in a more impactful direction. Or maybe they’re thinking of pursuing an academic research career and they aren’t sure which discipline is right for them.

Below you will find a list of disciplines and a handful of research questions and project ideas for each one.

They are meant to be illustrative, in order to help people who are working or considering working in these disciplines get a sense of what some attempts to approach them from a longtermist perspective might look like. They also represent projects that we think would be useful to pursue from a longtermist perspective.

These lists are not meant to be exhaustive; nor are they meant to express a considered view on what we think the most valuable questions and projects in each area are.

We’ve categorised the entries by discipline, though even if you’re already a researcher in one discipline we’d encourage you to consider questions and projects from others as well. Working at the intersection of two fields, and using the tools from one to tackle questions from another, can be good ways to increase your impact, as these interfaces are often more neglected.

There is some overlap between the disciplines listed below, and some repetition of questions that seemed like particularly good examples of research in more than one field.

This article is a work in progress — we hope to add and refine entries to these lists over time.

Note February 2022: A new list of questions that seem particularly high impact to us has just come out: Important, actionable research questions for the most important century . They don’t all fit neatly into the categories below, as many are interdisciplinary and somewhat different from the kind of work done in most academic departments, so we haven’t integrated them below. But check them out, and if you think you might be a good fit for working on one of them we encourage you to explore it!

What are these lists based on?

Our primary strategy in compiling these lists was to look through formal and informal collections of high-impact research questions put together by others in the effective altruism community or by people working on our priority problems . We’ve linked to these sources throughout, as well as at the end of this article. One reason we’ve used informal sources is that we’re interested in questions and projects that seem high-impact in part because they’re less well-researched by established academics.

When choosing between a question or project that seemed higher impact from a longtermist perspective and one that struck us as more illustrative, we often chose the latter.

We’ve lightly edited or changed many of the questions and project descriptions we got from other sources, which we note in parentheses. If there is no adaptation or change indicated, the entry is an exact quote. Often you can find more context for these questions and projects — including existing literature and additional questions — in the linked sources. If there is no source indicated, we wrote the entry ourselves.

Table of Contents

Biology and genetics

• How are average welfare levels distributed across different species (in the wild or in captivity)?
• What’s the average lifespan of the most common species of wild animals? What percent die via various means and how slow and painful is it? (Adapted from Lewis Bollard, EA summit project ideas )
• How do our best AI systems so far compare to animals and humans, both in terms of performance and in terms of brain size? What do we know from animals about how cognitive abilities scale with brain size, learning time, environmental complexity, etc.? (Richard Ngo, Technical AGI safety research outside AI )
• Research and develop methods for genetically engineering or breeding crops that could thrive in the tropics during a nuclear winter scenario (Adapted from ALLFED, Effective Theses Topic Ideas )
• What future possibilities are there for brain-computer interfacing and how does this interact with issues in AI safety? (Ryan Carey, comment on Concrete projects list )
• Research the genetic basis of hedonic set point, e.g. develop a model to predict hedonic set point using SNPs available on 23andme. Some researchers think promising candidates for such a study include the SCN9A and FAAH and FAAH-OUT genes. (Adapted from Qualia Research Institute, Volunteer page )
• What’s the minimum viable human population (from the perspective of genetic diversity)? (Michael Aird, Crucial questions for longtermists )

Business and organisational development

• How should altruistic/philanthropic actors coordinate when there are projects they’d both like to see happen but would both prefer that the other do/fund? (Adapted from Luke Muehlhauser (writing for Open Philanthropy), Technical and Philosophical Questions That Might Affect our Grantmaking )
• What forecasting methods used by private corporations can be adapted for use by altruistic actors?
• What is the state of the art for making crucial data and information visible and salient to leaders at large private corporations? Can these techniques be adapted into interfaces that keep relevant decision makers up to date with the most important information about deployed AI? (Inspired by Richard Ngo, Technical AGI safety research outside AI )

China studies

• What are Chinese computer scientists’ views on AI progress and the importance of work on safety? (You might try running a survey similar to this one from 2016 , but focusing on AI experts in China.) (Adapted from Ben Todd, A new recommend career path for effective altruists: China specialist )
• How does the Chinese government shape its technology policy? What attitudes does it have towards AI (including AI safety), synthetic biology, and regulation of emerging technology? (Adapted from Ben Todd, A new recommend career path for effective altruists: China specialist )
• How does Chinese nuclear no first-use policy affect global stability and potential strategic doctrines for emerging technologies? (Adapted from personal correspondence with an expert)
• Why has Mohism almost died out in China, relative to other schools of thought? (Adapted from personal correspondence with an expert)
• Why have certain aspects of Chinese civilisation been so long-lasting? Are there any lessons we can draw from this about what makes for highly resilient institutions, cultures, or schools of thought? (Inspired by personal correspondence with an expert)

Climate studies and earth sciences

• Under what scenarios could climate change be an existential catastrophe? E.g. through runaway or moist greenhouse effects, permafrost, methane clathrate, or cloud feedbacks? How likely are these scenarios? (Toby Ord, The Precipice , Appendix F )
• More generally, what environmental problems — if any — pose existential risks? (Adapted from Effective Thesis )
• How frequent are supervolcanic eruptions and what size of eruption could cause a volcanic winter scenario? (Adapted from Toby Ord, The Precipice, Appendix F )
• Improve modeling on nuclear winter and climate effect of asteroids, comets, and supervolcanoes ( The Precipice , Appendix F )
• What are potential risks from geoengineering technologies and which of these technologies — if any — might be promising for mitigating climate change?

Cognitive science and neuroscience

• What traits are the best indicators of sentience in different animal species? What do these measurements suggest about the distribution of sentience across species?
• What are the best and cheapest underexplored treatments for cluster headaches and other extremely painful conditions? What does this imply about the causes of extreme suffering? (Adapted from Qualia Research Institute, Volunteer page )
• Which features of the human brain are most important for intelligence? How important is computational power vs. brain architecture vs. accumulated knowledge?
• What potential nootropics or other cognitive enhancement tools are most promising? E.g. does creatine actually increase IQ in vegetarians?

What is the effect of economic growth on existential risk? How desirable is economic growth after accounting for this and any other side effects that might be important from a longtermist perspective? (See a recent paper by Leopold Aschenbrenner for some initial work on this question.)

What’s the best way to measure individual wellbeing? What’s the best way to measure aggregate wellbeing for groups?

What determines the long-term rate of expropriation of financial investments? How does this vary as investments grow larger? (Michael Aird, Crucial questions for longtermists )

• What can economic models — especially models of economic growth — tell us about recursive self improvement in advanced AI systems? (Adapted from AI Impacts, Promising research projects )
• Can concerns about unaligned artificial intelligence or economic dominance by influence-seeking agents be reformulated in terms of standard economic ideas, such as principal-agent problems and the effects of automation? (Adapted from Richard Ngo, Technical AI Safety research outside AI )
• Of the comprehensive macroeconomic indices already available to us, which serve best as proxies for long-term expected global welfare (including but not limited to considerations of existential risks)? What would be the broad policy implications of targeting such indices instead of GDP per capita? (Global Priorities Institute, Research Agenda )
• What is the optimal design of international institutions that are formed to increase global public goods or decrease global public bads? (Global Priorities Institute, Research Agenda )
• Economists may also be interested in working on questions in the global priorities research section, below .

Epidemiology, synthetic biology, and medicine

Research and development of techniques for screening DNA synthesis requests for dangerous pathogens (especially techniques that won’t create infohazards by being reverse engineered).

Research and development into platforms that might decrease the time it takes to go from novel pathogen to vaccine. (Cassidy Nelson, 80,000 Hours podcast interview )

What broad-spectrum drugs, especially antivirals, are most promising for tackling novel pathogens? (Cassidy Nelson, 80,000 Hours podcast interview )

Roll out genetic sequencing-based diagnostics that let you test someone for all known and unknown pathogens in one go. (Cassidy Nelson, 80,000 Hours podcast interview )

Is extreme human life extension possible? If so, what research is most promising for reaching that goal? (Adapted from Effective Thesis )

Global Priorities Research

• How likely would catastrophic long-term outcomes be if everyone in the future acts for their own self-interest alone? (Adapted from Michael Aird, Crucial questions for longtermists )

How should altruistic/philanthropic actors coordinate when there are projects they’d both like to see happen but would both prefer that the other do/fund? (Inspired by Luke Muehlhauser (writing for Open Philanthropy), Technical and Philosophical Questions That Might Affect our Grantmaking )

What is the expected value of the continued existence of the human race? Might this expected value be negative, or just unclear? How do our answers to these questions vary if we (i) assume utilitarianism; (ii) assume a non-utilitarian axiology; (iii) fully take axiological uncertainty into account? (Global Priorities Institute, Research Agenda )

• Assuming that there is a single, context-independent welfare level corresponding to a life’s having zero contributive value to social welfare, what kinds of lives have zero welfare in this contributive sense? (Global Priorities Institute, Research Agenda )
• Could advances in AI lead to risks of very bad outcomes, like suffering on a massive scale ? Is it the most likely source of such risks? (Adapted from Michael Aird, Crucial questions for longtermists )
• One common view is that we should favour interventions that have more evidential support, all else being equal. On the face of it, this conflicts with the maximisation of expected value if one would prefer an intervention with much stronger evidence but a (possibly infinitesimally) small reduction in expected value (if ‘all else being equal’ means: ‘expected value being equal’). On the other hand, it also seems reasonable to place some value on the uncertainty of an intervention. What is the correct response to this mean-variance tradeoff? (Global Priorities Institute, Research Agenda )
• How much do global issues differ in how cost-effective the most cost-effective interventions within them are?
• Many of the questions under economics , philosophy , history , and other disciplines could also be considered global priorities research.

What were the biggest and most long-lasting changes in cultural value systems throughout history? How did they happen and why? (Inspired by Effective Thesis )

• How frequently and to what extent have technologies caused discontinuous progress on relevant metrics? What are some technologies that have caused these discontinuities? (AI Impacts, Promising research projects )
• How many — if any — significant historical successes have come from people explicitly trying to address challenges 30+ years away? What about in the distant future? (Adapted from Nick Beckstead, How to Compare Broad and Targeted Attempts to Shape the Far Future , slide 36)
• What factors have encouraged companies and countries to engage in risk-taking behaviour and arms races? (Center on Long-Term Risk, Open Research Questions )
• Generate case studies of successes and failures in the history of technological regulation and governance (Adapted from Michael Aird, Some history topics it might be very valuable to investigate ). See Katja Grace’s research on the Asilomar Conference and Leó Szilárd for examples of doing this kind of research outside of history academia.
• What case studies are there for legal rights or other protections being won for beings that didn’t and wouldn’t ever have the right to vote, and what lessons do these have for animal welfare?
• What lessons for AI can be drawn from the regulation of other dual-use technologies? ( Effective Thesis )
• What legal obstacles are there to setting up a stable long-term financial investment fund that will not be appropriated for centuries or longer?
• What legal strategies might help make prediction markets more viable?
• What rights might digital minds have under current law? What characteristics would affect this?
• What legal tools could states use to close and/or exert control over AI companies? (Adapted from Allan Dafoe, AI Governance: A Research Agenda )

Machine learning, artificial intelligence, and computer science

• Analyze the performance of different versions of software for benchmark problems, like SAT solving or chess, and determine the extent to which hardware and software progress facilitated improvement. (AI Impacts, Possible Empirical Investigations )
• How can we make AI systems more robust to distributional shifts (i.e. how do we make sure they fail gracefully if they encounter a context that differs radically from their training environment)? For example, can we develop reinforcement learning agents that consistently notice when they are out of distribution and ask for guidance? (Adapted from Amodei et al., Concrete Problems in AI Safety )
• Designing techniques to avoid reward hacking. For example, using an adversarial reward-checking agent to try to find scenarios that the ML system claimed were high reward but a human labels as low reward (Amodei et al., Concrete Problems in AI Safety )
• Improving ML systems’ ability to avoid negative side effects without having to hard code them into the system’s loss function. For example, one could try to define an ‘impact regularizer’ that would penalise making big ‘changes to the environment.’ How might such an idea be formalised? (Adapted from Amodei et al., Concrete Problems in AI Safety )

How can we design ML systems that are more transparent and whose models are more easily interpretable by humans? For example, see Chris Olah’s research into designing better visual representations of deep learning. (Evan Hubinger, Chris Olah’s Views on AGI Safety )

If you have a system that can make decisions as well as a human can, how can you use that system to build more powerful systems which make much better decisions than humans while still preserving its alignment with human values? Answering this question means that it’s more likely that we’ll be able to use powerful general-purpose ML to make decisions that are actually good for us, rather than just seeming good. (Personal correspondence with Buck Shlegeris). For more information, see OpenAI’s blog post on “AI Safety via Debate” and/or Paul Christiano’s work on iterated distillation and amplification , which is discussed in our interview with Paul .

Currently, formal models of agents and decision making are based on clearly false simplifying assumptions about the world; for example, that the agent itself has a mind that isn’t part of the physical universe. These limitations of our models sometimes mean that they suggest absurd things about what rational agents would do in various situations. If we want to be able to reason carefully about the behaviour of artificially constructed intelligent agents, it might be helpful to have more usable formal models. (Not everyone thinks that it’s important for us to be able to reason formally about agents this way.) (Personal correspondence with Buck Shlegeris). See the Machine Intelligence Research Institute (MIRI)’s work on embedded agency for more.

What types of AI (in terms of architecture, subfield, application, etc.) are most likely to contribute to reaching artificial general intelligence ? What AI capabilities would be necessary or sufficient, individually or collectively? (Adapted from Future of Life Institute, A survey of research topics for robust and beneficial AI )

How quickly might those capabilities arise?

How can “progress” in AI research effectively be tracked and measured? What progress points would signal important technological milestones or the need for a change in approach? (CNAS, Artificial Intelligence and Global Security Initiative Research Agenda ) (See also: the “Assessing AI Progress” section of Centre for the Governance of AI’s research agenda (page 21))

• Assuming we are uncertain about what moral theory to believe, is there anything wrong with some views with very high stakes dominating our uncertainty-adjusted moral conclusions (‘fanaticism’)? For example, if you think theory A is very unlikely to be true, but it says action X is extremely valuable, while all other theories think X is just slightly bad, is there anything wrong with concluding you should do X? If so, what plausible view of moral uncertainty would allow us to avoid this conclusion? (Adapted from Global Priorities research agenda )
• What concerns are there with representing people as having utility functions? What alternatives are there?
• What sorts of entities have moral status? Controversial categories include nonhuman animals (including insects), the dead, the natural environment, and current or potential artificial intelligence. (Adapted from Will MacAskill, The most important unsolved problems in ethics )
• Although it has been frequently argued that advanced AI goals should reflect ‘human values’, which particular values should be preserved (given that there is a broad spectrum of inconsistent views across the globe and across time about what these values should be)? (Adapted from Future of Life Institute, A survey of research topics for robust and beneficial AI )

What are the best heuristics for reliably identifying experts on a topic, or choosing what to believe when apparent experts disagree?

What’s the chance that the people making the decision in the future about how to use our ‘cosmic endowment’ are such that we would be happy, now, to defer to them? (Global Priorities Institute, Research Agenda )

• How can we distinguish between AIs helping us better understand what we want and AIs changing what we want (both as individuals and as a civilisation)? How easy is the latter to do; and how easy is it for us to identify? (Richard Ngo, Technical AGI safety research outside AI )
• Philosophers may also be interested in working on questions in the global priorities research section, above .

Physics and astronomy

• Research the deflection of 1 km+ asteroids and comets, perhaps restricted to methods that couldn’t be weaponised (such as those that don’t lead to accurate changes in trajectory). (Toby Ord, The Precipice , Appendix F )
• Improve our understanding of the risks from long-period comets. (Toby Ord, The Precipice , Appendix F )
• Improve our modelling of impact winter scenarios, especially for 1–10 km asteroids. Work with experts in climate modelling and nuclear winter modelling to see what modern models say. (Toby Ord, The Precipice , Appendix F )
• What would be required for humans to settle other planets or to use resources from outside Earth?
• How likely is the existence of extraterrestrial life? (Center on Long-Term Risk, Open Research Questions )

Political science, international relations, and security studies

• What types or features of institutions could help enable the representation of the interests of future generations and/or sentient nonhumans in political processes?
• How feasible is an eventual rise of a global and potentially long-lasting totalitarian regime? What are potential predictors of such a regime? (Such as, perhaps, improved surveillance technologies or genetic engineering?) (Adapted from Michael Aird, Crucial questions for longtermists )
• How could AI transform domestic and mass politics? E.g. will AI-enabled surveillance, persuasion, and robotics make totalitarian systems more capable and resilient? (Allan Dafoe, AI Governance: A Research Agenda )
• How will geopolitical, bureaucratic, cultural, or other factors affect how actors choose to adopt AI technology for military or security purposes? (CNAS, Artificial Intelligence and Global Security Initiative Research Agenda )

Will AI come to be seen as the one of the most strategically important parts of the modern economy, warranting massive state support and intervention? If so, what policies might this cause countries to adopt, and how will this AI nationalism interact with global free trade institutions and commitments? (Adapted from Allan Dafoe, AI Governance: A Research Agenda )

What are the conditions that could spark and fuel an international AI race? How great are the dangers from such a race, how can those dangers be communicated and understood, and what factors could reduce or exacerbate them? What routes exist for avoiding or escaping the race, such as norms, agreements, or institutions regarding standards, verification, enforcement, or international control? (Allan Dafoe, AI Governance: A Research Agenda )

• How well does good forecasting ability transfer across domains? (Inspired by Scott Alexander, answer to What are the open problems in human rationality? )
• What’s the best way to measure individual wellbeing — across people, and for different kinds of sentient beings? (Adapted from Happier Lives Institute, Research agenda )

What are the best ways to encourage compliance with safety and security norms and/or create a culture of safety and security among scientists who work with dangerous pathogens or other dual-use technologies? (Adapted from Effective Thesis )

• Develop more reliable and tamper-proof measures for so-called ‘dark tetrad’ traits — psychopathy, Machiavellianism, sadism, and narcissism. (Adapted from David Althaus and Tobias Baumann, Reducing long-term risks from malevolent actors )
• Some expect that as AI advances it might engage in behaviour that we experience as manipulative. What are the best defenses against these new possible sorts of manipulation? (Adapted from Future of Life Institute, A survey of research topics for robust and beneficial AI )

Public policy

• What are the best methodologies for evaluating policy options for unprecedented future scenarios? (Inspired by Max Stauffer et al., Research Directions on Improving Policy-making )
• What regulatory and other government approaches can prevent AI technologies from being misused? For example, how — if at all — could compliance with a treaty agreeing to restrictions on the development of lethal autonomous weapons be reliably verified? (Adapted from CNAS, Artificial Intelligence and Global Security Initiative Research Agenda )
• Public policy considerations are relevant to many of the questions on this list. See especially political science and international relations .

Science policy/infrastructure and metascience

• The replication crisis has cast into doubt important research findings, such as the Stanford prison experiment. What other socially important findings have been undermined? How should we interpret scientific literature post-crisis? (Inspired by Scott Alexander, answer to What are the open problems in human rationality? )
• What are the best existing methods for estimating the long-term benefit of past investments in scientific research, and what have they found? What new estimates should be conducted? (Adapted from Luke Muehlhauser (writing for Open Philanthropy), Technical and Philosophical Questions That Might Affect our Grantmaking )
• What disciplinary norms from across different disciplines and traditions lead to the most — and most socially responsible — scientific progress? (Inspired by Richard Ngo, Technical AGI safety research outside AI )
• What are the best policies for handling ‘ information hazards ’ from dual-use research?
• How does the current state of openness among the AI research community affect prospects for cooperation or competition? How would a change in openness affect incentives among various actors? (CNAS, Artificial Intelligence and Global Security Initiative Research Agenda )

Generate case studies of successes and failures by social movements (e.g. the anti-GMO movement, the anti-nuclear weapons movement, or the LGBTQ movement) — what happened and how? (Inspired by Sentience Institute, Research agenda )

• Why are some values, institutions, and organisations extremely durable — lasting hundreds of years (e.g. academia) — whereas others change frequently? What are the social mechanisms that explain this? ( Effective Thesis )
• Case studies into how institutions and organisations make big, important decisions, or respond to catastrophes.

Statistics and mathematics

• When estimating the chance that now (or any given time) is a particularly pivotal moment in history, what is the best uninformative prior to update from? For example, see our podcast with Will MacAskill and this thread between Will MacAskill and Toby Ord for a discussion of the relative merits of using a uniform prior v. a Jeffreys prior.

Toby Ord has argued that because the human species has survived for a long time, we can conclude the natural per-century human existential risk is low (or else it’d be extremely unlikely that we’d be here). Does this argument still hold if we assume there are millions of potentially intelligent species evolving throughout the history of the universe, and only those that survive about as long as we have become advanced enough to ask questions about how high natural extinction risk is? ( Some experts believe this issue has been adequately resolved.)

• Many statisticians may also be interested in the ML questions we list above .

Thank you to everyone who put together lists of research questions — original or compiled from elsewhere — that they thought could be promising for people to work on. This article relied on their efforts more than our own. Michael Aird’s Effective Altruism Forum post A Central directory for open research questions was particularly helpful in putting this article together.

Here are all the other cited sources (in order of appearance):

• Lewis Bollard’s EA Summit project ideas
• Richard Ngo, Technical AGI safety research outside AI
• ALLFED, Effective Theses Topic Ideas
• Ryan Carey, comment on Concrete projects list
• Qualia Research Institute’s Volunteer page
• Michael Aird, Crucial questions for longtermists
• Luke Muehlhauser (writing for Open Philanthropy), Technical and Philosophical Questions That Might Affect our Grantmaking
• Ben Todd, A new recommend career path for effective altruists: China specialist
• Toby Ord, The Precipice , Appendix F
• Effective Thesis (various disciplines)
• AI Impacts, Promising research projects
• Global Priorities Institute, Research Agenda
• Cassidy Nelson, 80,000 Hours podcast interview on how to stop pandemics
• Nick Beckstead, How to Compare Broad and Targeted Attempts to Shape the Far Future
• Center on Long-Term Risk, Open Research Questions
• Michael Aird, Some history topics it might be very valuable to investigate
• AI Impacts, Possible Empirical Investigations
• Amodei et al., Concrete Problems in AI Safety
• Evan Hubinger, Chris Olah’s Views on AGI Safety
• Future of Life Institute, A survey of research topics for robust and beneficial AI
• CNAS, Artificial Intelligence and Global Security Initiative Research Agenda
• Will MacAskill, The most important unsolved problems in ethics
• Allan Dafoe, AI Governance: A Research Agenda
• Scott Alexander, answer to What are the open problems in human rationality?
• Happier Lives Institute, Research agenda
• David Althaus and Tobias Baumann, Reducing long-term risks from malevolent actors
• Max Stauffer et al., Research Directions on Improving Policy-making
• Sentience Institute, Research agenda

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Suggestions for Future Research

Your dissertation needs to include suggestions for future research. Depending on requirements of your university, suggestions for future research can be either integrated into Research Limitations section or it can be a separate section.

You will need to propose 4-5 suggestions for future studies and these can include the following:

1. Building upon findings of your research . These may relate to findings of your study that you did not anticipate. Moreover, you may suggest future research to address unanswered aspects of your research problem.

2. Addressing limitations of your research . Your research will not be free from limitations and these may relate to formulation of research aim and objectives, application of data collection method, sample size, scope of discussions and analysis etc. You can propose future research suggestions that address the limitations of your study.

3. Constructing the same research in a new context, location and/or culture . It is most likely that you have addressed your research problem within the settings of specific context, location and/or culture. Accordingly, you can propose future studies that can address the same research problem in a different settings, context, location and/or culture.

4. Re-assessing and expanding theory, framework or model you have addressed in your research . Future studies can address the effects of specific event, emergence of a new theory or evidence and/or other recent phenomenon on your research problem.

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance  offers practical assistance to complete a dissertation with minimum or no stress. The e-book covers all stages of writing a dissertation starting from the selection to the research area to submitting the completed version of the work within the deadline. John Dudovskiy

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3 scenarios for the future of research – which is most likely?

March 20, 2019 | 11 min read

By Alison Bert, DMA

Experts at AAAS weigh in on the new Research Futures study by Elsevier and Ipsos MORI

Caption: Experts debate the future of research at an interactive panel at the AAAS Annual Meeting in Washington, DC (from left): Dr. Peter Tindemans, Secretary General of EuroScience; Mary Woolley, President and CEO of Research!America; Prof. Sir Peter Gluckman, President Elect of the International Science Council; Dr. Joanne Tornow, Assistant Director for Biological Sciences at the National Science Foundation and, at the podium, Adrian Mulligan, Research Director for Customer Insights at Elsevier. (Photos by Alison Bert)

Imagine yourself 10 years from now. It’s 2029, and the world of research has changed – dramatically for some of you. But how?

Where will your research funding come from? Will your collaborators be academics or colleagues at a tech company?

Will you use artificial intelligence to determine your research hypothesis – and will journals use AI to decide whether to accept your paper? Will that “paper” even look like the manuscript you’re used to submitting?

If you’re a professor, will your students come to the university or study from afar?

These are just a few of the questions the new  Research Futures  scenario-planning study delves into. To forecast how research might be created and exchanged 10 years from now, investigators from Elsevier and Isos MORI examined the literature and market drivers, interviewed over 50 funders, futurists, publishers and technology experts and surveyed more than 2,000 researchers.

From the analysis, key themes emerged. The investigators then held creative workshops, and participants used this knowledge to develop three plausible scenarios    of the future:

Brave open world considers the rise of open science.

Tech titans looks at the growing influence of technology.

Eastern ascendance considers the role the East – and China in particular – might play.

Elsevier colleagues initially conceived this project to gain insights into how they could collaborate with the research community to build a better information system supporting research.

“We needed some information to inform our own decisions as an information analytics provider,” said Hannfried von Hindenburg, SVP of Global Communications, in introducing the panel. “But we felt we should make it public so that all of you could make your decisions based on this research.

“It’s meant to stimulate a discussion, and it’s meant to stimulate decision-making.”

That conversation continued when the report was released at the  Annual Meeting of the American Association for the Advancement of Science (AAAS) opens in new tab/window  in Washington, DC. A panel of research leaders – along with researchers in the audience – weighed in on which scenarios seemed most likely.

“Since we’re envisioning the future, there are no wrong answers,” said moderator Dr. Brad Fenwick, SVP of Global Strategic Alliances at Elsevier.

Hannfried von Hindenburg, SVP of Global Communications at Elsevier, introduces the report and panel at AAAS.

Exploring the future through a 3D lens

Adrian Mulligan summarizes key themes and scenarios in the report before seeking input from the panel and audience.

In his introduction to the report, lead investigator  Adrian Mulligan opens in new tab/window , Director of Research for Customer Insights at Elsevier, summarized the key points – starting with the “three dimensions” the experts  used to contemplate the future.

Three dimensions were used to contemplate the future: the progress of technology (blue); the degree of openness and sharing of research (orange); and those who support research and whether they would be aligned or fragmented (grey).

Blue represents the world of technology. “On one extreme, technology is revolutionary and drastically alters the way science is done,” Mulligan explained. “On the other, evolutionary tech is just like it is now, steadily progressing.”

Orange, meanwhile, represents the exchange of research and data and the degree to which it will be open or controlled, and gray represents whether organizations or nation states are aligned or fragmented.

Each of these elements combines with the others in a distinct way in the three future scenarios.

Scenario 1: Brave open world

In the Brave open world scenario, various factors converge for open collaboration.

“Brave open world” is characterized by open sharing of research, revolutionary technology and more convergence among stakeholders, Mulligan explained. For example, big tech partners with funders and research institutes to develop interoperable machine learning tools and platforms.

“In this scenario, all the actors and funders … come together to create an open platform in which science is shared,” he said. “Research articles are all open access, and the research article moves on from the current format to a more dynamic ‘notebook’ style that is more atomized and broken up.”

In addition, AI accelerates the speed and volume of research, and researchers are rewarded by a range of measures, including interdisciplinary collaboration, data dissemination and social impact.

Trust in science has increased because the public has greater access to published science, and researchers are expected present their work in a way that’s understandable to the lay person.

Scenario 2: Tech titans

In the Tech titans scenario, big tech companies take charge of the research landscape.

The “Tech titans” scenario is characterized by revolutionary technology, with the large tech companies becoming the main supporters, curators and distributors of knowledge. “The big technology companies step in and play a key role in the communication of science and the funding of research,” Mulligan said. “There are massive advances in AI in this world. Here, we see AI play such an important role that it changes society in essential ways. There are lots of job losses … in research as well.”

Much of research has become automated, driven by AI and data mining, and AI enables data-driven hypothesis generation – a practice we’re already experimenting with. Researchers often work closely with industry as independent consultants for large corporations.

Data sharing and machine learning have supported successful commercial breakthroughs, and the platforms the tech companies create have lowered the cost of doing research. However, there are concerns about data being held by private companies and not being made public – or medical advances not being evenly distributed. That competitive drive would likely spill onto the global stage.

“A number of countries are competing to deploy artificial intelligence, keeping it close to their chests in terms of the knowledge they have acquired in developing of new products,” Mulligan said. “And we find some countries struggling to adapt to making use of these new technologies.”

Meanwhile, it’s a politically fragmented world; state funding for research has been reduced, and industry and philanthropic organizations have stepped in to fill the gap, investing in challenge-led science.

Scenario 3: Eastern ascendance

In the Eastern ascendance scenario, China’s desire to transform into a knowledge-based economy has led to heavy public investment in R&D.

The third scenario – Eastern ascendance – is also a fragmented world, with a sharp division between the United States and China. “China has invested massively into research and development, and it’s really paying dividends for them,” Mulligan said. “In the West, we’re unable to keep up with what China is doing, and as a consequence, the sheer volume of that investment is really shaping the way research is being communicated and the advances that are being made.

“Actually, the world changes so much that China becomes a magnet for western researchers. So rather than Western researchers going to Oxford or MIT or the top universities in Europe, they’re heading towards China.

“Open science is embraced in this world,” he continued, “but only partly embraced because it’s quite a fragmented world. People are trying to take commercial advantage of the data and science that’s been communicated, so there’s a lack of global alignment on research projects. Everyone’s trying to do things in their own way.”

As a result, products like self-driving cars, or developments in personalized medicine, are not universally available.

In publishing, the Impact Factor continues to prevail and the subscription model plays a role. Meanwhile, big tech companies form  partnerships with publishers  to provide AI-enabled workflow and publishing tools.

Researchers or technology: which will drive new knowledge?

For the rest of the workshop, Dr. Fenwick posted questions from the survey, and audience members used their smart phones to register their answers in  Menti opens in new tab/window . For example:

Question:  “In 10 years, the creative force   driving forward new knowledge will be …”

Answer:  Researchers – Technology – Either equally likely

Mulligan started by alluding to the “robust intelligence of the ‘tech titan’ world” and the expanding role of AI in driving research: Could AI become so advanced that it could create new science? “We had a number of experts say that much of the hypotheses being generated will be coming from machines rather than humans,” he said. “The role of technology has the the potential to transform research.”

Two panelists challenged the question itself.

"The real idea underlying this statement is that AI will replace researchers completely, and this will not be the case," said Dr. Peter Tindemans, founding member and Secretary General of  EuroScience opens in new tab/window .

“I think it depends how you look at this,” said  Prof. Sir Peter Gluckman opens in new tab/window , President Elect of the  International Science Council opens in new tab/window  and former Chief Science Advisor for the Prime Minister of New Zealand. He referred to Prof.  Dan Sarewitz’s 2016 essay “Saving Science” in  The New Atlantis opens in new tab/window :

As Dan Sarewitz suggests … science is driven by technological development. Until the microscope was invented, you couldn’t look at the cell – etcetera, etcetera, etcetera. … Always new technologies allow new questions to be answered. So by definition, much science is driven ultimately by technological possibilities.

Dr.  Joanne Tornow opens in new tab/window , Assistant Director for Biological Sciences at the  National Science Foundation opens in new tab/window , countered with a vote for the researcher:

Technology by itself doesn’t answer the questions. It’s the researcher. … You have to have the technology – I agree. And technology is as disruptive and as transformational as an aha moment in understanding. But it doesn’t in and of itself solve a problem.

Dr. Fenwick then asked: “Where will the new idea to do the research come from? Where will the idea for the hypothesis come from? (How will it be decided whether) it’s worth researching? Will this be  in silico opens in new tab/window  or will it still be the PI that comes up with the idea?”

Dr. Tornow responded with still another question: “Where does new technology come from? New technology comes from ideas that researchers have. It’s kind of a virtuous cycle.”

Dr. Fenwick agreed that technology is often developed to meet the needs of science: “You wouldn’t build a collider if you didn’t have the scientific community saying I need this tool to answer this question.”

Then he played devil’s advocate: “On the other hand, I could make an argument that if we can’t digest all the science, but a machine can through machine learning, what if a machine came up with a question or hypothesis or a question worth asking and answering? Would we accept it?”

Not only would we accept it; researchers who enable their questions to be generated by AI would have a competitive advantage, Prof. Gluckman said. “Those researchers who do big data and use big-data tools tend to write papers that get into high impact journals,” he said. “And funders love big-data-based, meta-analysis type research.”

As the “chicken-and-egg” aspect of this conundrum became increasingly apparent, a woman in the audience aptly pointed out, “Someone had to write the algorithm.”

Ultimately, the panelists as well as the audience voted more in favor of researchers.

In the  Research Futures  survey of researchers, the most popular response was ‘researchers.’

Will students actually  go  to universities?

The next question dealt with the rising trend of distance learning in higher education:

Question:  “In 10 years, university student will be educated …

Answer:  Mostly on campus – Mostly remotely – Either equally likely.

Dr. Tindemans said there are pressing reasons for students to be on campus:

Students go to a university not just to learn something. Secondly, in many areas of study, you need to work together with your professors by doing experiments (and) other things together, and that is very difficult to organize another way. And the third thing is simply the status: a diploma is a link to what university and not just to a collection of exams you have passed online.

Mary Woolley opens in new tab/window , President and CEO of  Research!America opens in new tab/window , said the answer depends on the university and subjects being studied:

I would say there’s a context … of elite vs non-elite university and college institutions and education. For the elite, students would be more likely on campus. But for all the rest, which is a much higher percentage, I would think it would be increasingly remotely.

Dr. Fenwick pointed out that more elite universities in the US are “making a bet that they can do more distance learning.” As an example, he mentioned a university that bought a large education company, using Elsevier to create their learning platform.

Prof. Gluckman agreed that university education is likely to change, with a rise in interdisciplinary and team-based research, but added that other as yet uncertain factors would also impact these future scenarios. Prof. Gluckman foresees the probability of a more focused investment of government funding in a smaller proportion of research-intensive universities, with the other universities becoming more education-focused and offering more distance-learning options for current and continuing education. However, it’s not clear what form “lifelong re-learning and retraining” will take for many people, he said, “and I think we’re still a decade away from understanding how that’s going to evolve.”

Woolley mentioned “competing pressures” that could turn the tide either way: “the move toward interdisciplinary work and team science that really does require (in-person) interaction” versus the fact that “we’re getting much, much better at connecting remotely.” Ultimately, she said, it would depend on what fields people are studying, some of which will still require a presence on campus.

Similar to the panel’s responses, the audience’s were equally divided, as were those of the researchers who took the survey:

In the  Research Futures  survey of researchers, responses were divided almost equally.

“The best way to influence the future …”

In reflecting on the topic and what was learned from the study, Mulligan said: “You can think about the future, but the best way to influence the future is to create the future.”

Download the report and supporting material

The report  Research Futures: drivers and scenarios for the next decade  is freely available.

Download the summary report (including scenarios) opens in new tab/window

Download the full report (including the scenarios and essays) opens in new tab/window

Download the monitoring framework opens in new tab/window

Elements of the underlying study data are also freely available:

Visit Mendeley to view the list of references used for the literature review opens in new tab/window

View the full results and charts for the researcher survey opens in new tab/window

Find the results of the researcher survey on Mendeley Data opens in new tab/window

Contributor

Alison Bert, DMA

Executive Editor, Global Communications

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The future of research: Emerging trends and new directions in scientific inquiry

The world of research is constantly evolving, and staying on top of emerging trends is crucial for advancing scientific inquiry. With the rapid development of technology and the increasing focus on interdisciplinary research, the future of research is filled with exciting opportunities and new directions.

In this article, we will explore the future of research, including emerging trends and new directions in scientific inquiry. We will examine the impact of technological advancements, interdisciplinary research, and other factors that are shaping the future of research.

One of the most significant trends shaping the future of research is the rapid development of technology. From big data analytics to machine learning and artificial intelligence, technology is changing the way we conduct research and opening up new avenues for scientific inquiry. With the ability to process vast amounts of data in real-time, researchers can gain insights into complex problems that were once impossible to solve.

Another important trend in the future of research is the increasing focus on interdisciplinary research. As the boundaries between different fields of study become more fluid, interdisciplinary research is becoming essential for addressing complex problems that require diverse perspectives and expertise. By combining the insights and methods of different fields, researchers can generate new insights and solutions that would not be possible with a single-discipline approach.

One emerging trend in research is the use of virtual and augmented reality (VR/AR) to enhance scientific inquiry. VR/AR technologies have the potential to transform the way we conduct experiments, visualize data, and collaborate with other researchers. For example, VR/AR simulations can allow researchers to explore complex data sets in three dimensions, enabling them to identify patterns and relationships that would be difficult to discern in two-dimensional representations.

Another emerging trend in research is the use of open science practices. Open science involves making research data, methods, and findings freely available to the public, facilitating collaboration and transparency in the scientific community. Open science practices can help to accelerate the pace of research by enabling researchers to build on each other’s work more easily and reducing the potential for duplication of effort.

The future of research is also marked by scientific innovation, with new technologies and approaches being developed to address some of the world’s most pressing problems. For example, gene editing technologies like CRISPR-Cas9 have the potential to revolutionize medicine by allowing scientists to edit DNA and cure genetic diseases. Similarly, nanotechnology has the potential to create new materials with unprecedented properties, leading to advances in fields like energy, electronics, and medicine.

One new direction in research is the focus on sustainability and the environment. With climate change and other environmental issues becoming increasingly urgent, researchers are turning their attention to developing sustainable solutions to the world’s problems. This includes everything from developing new materials and technologies to reduce greenhouse gas emissions to developing sustainable agricultural practices that can feed the world’s growing population without damaging the environment.

Another new direction in research is the focus on mental health and wellbeing. With mental health issues becoming increasingly prevalent, researchers are exploring new approaches to understanding and treating mental illness. This includes everything from developing new therapies and medications to exploring the role of lifestyle factors like diet, exercise, and sleep in mental health.

In conclusion, the future of research is filled with exciting opportunities and new directions. By staying on top of emerging trends, embracing interdisciplinary research, and harnessing the power of technological innovation, researchers can make significant contributions to scientific inquiry and address some of the world’s most pressing problems.

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September 1, 2016

11 min read

20 Big Questions about the Future of Humanity

We asked leading scientists to predict the future. Here’s what they had to say

Kyle Hilton

1. Does humanity have a future beyond Earth? “I think it’s a dangerous delusion to envisage mass emigration from Earth. There’s nowhere else in the solar system that’s as comfortable as even the top of Everest or the South Pole. We must address the world’s problems here. Nevertheless, I’d guess that by the next century, there will be groups of privately funded adventurers living on Mars and thereafter perhaps elsewhere in the solar system. We should surely wish these pioneer settlers good luck in using all the cyborg techniques and biotech to adapt to alien environments. Within a few centuries they will have become a new species: the posthuman era will have begun. Travel beyond the solar system is an enterprise for posthumans—organic or inorganic.” —Martin Rees, British cosmologist and astrophysicist

2. When and where do you think we will find extraterrestrial life? “If there is abundant microbial life on Mars, I suspect that we will find it within 20 years—if it is enough like our form of life. If an alien life-form differs much from what we have here on Earth, it is going to be difficult to detect. It’s also possible that any surviving Martian microbes are rare and located in places that are difficult for a robotic lander to reach. Jupiter’s moon Europa and Saturn’s moon Titan are more compelling places. Europa is a water world where more complex forms of life may have evolved. And Titan is probably the most interesting place in the solar system to look for life. It is rich in organic molecules but very cold and has no liquid water; if life exists on Titan, it will be very different from life on Earth.” —Carol E. Cleland, philosophy professor and co-investigator in the Center for Astrobiology at the University of Colorado Boulder

3. Will we ever understand the nature of consciousness? “Some philosophers, mystics and other confabulatores nocturne   pontificate about the impossibility of ever understanding the true nature of consciousness, of subjectivity. Yet there is little rationale for buying into such defeatist talk and every reason to look forward to the day, not that far off, when science will come to a naturalized, quantitative and predictive understanding of consciousness and its place in the universe.” — Christof Koch, president and CSO at the Allen Institute for Brain Science; member of the Scientific American Board of Advisers

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4. Will the entire world one day have adequate health care? “The global community has made tremendous progress toward health equity over the past 25 years, but these advances have not reached the world’s most remote communities. Deep in the rain forest, where people are cut off from transportation and cellular networks, mortality is the highest, access to health care is the most limited and quality of care is the worst. The World Health Organization estimates that one billion people go their entire lives without seeing a health worker because of distance. Health workers recruited directly from the communities they serve can bridge the gap. They can even fight epidemics such as Ebola and maintain access to primary care when health facilities are forced to shut their doors. My organization, Last Mile Health, now deploys more than 300 health workers in 300 communities across nine districts in partnership with the government of Liberia. But we can’t do this work alone. If the global community is serious about ensuring access to health care for all, it must invest in health workers who can reach the most remote communities.” —Raj Panjabi, co-founder and chief executive at Last Mile Health and instructor at Harvard Medical School

5. Will brain science change criminal law? “In all likelihood, the brain is a causal machine, in the sense that it goes from state to state as a function of antecedent conditions. The implications of this for criminal law are absolutely nil. For one thing, all mammals and birds have circuitry for self-control, which is modified through reinforcement learning (being rewarded for making good choices), especially in a social context. Criminal law is also about public safety and welfare. Even if we could identify circuitry unique to serial child rapists, for example, they could not just be allowed to go free, because they would be apt to repeat. Were we to conclude, regarding, say, Boston priest John Geoghan, who molested some 130 children, ‘It’s not his fault he has that brain, so let him go home,’ the result would undoubtedly be vigilante justice. And when rough justice takes the place of a criminal justice system rooted in years of making fair-minded law, things get very ugly very quickly.” —Patricia Churchland, professor of philosophy and neuroscience at the University of California, San Diego

6. What is the chance Homo sapiens will survive for the next 500 years? “I would say that the odds are good for our survival. Even the big threats—nuclear warfare or an ecological catastrophe, perhaps following from climate change—aren’t existential in the sense that they would wipe us out entirely. And the current bugaboo, in which our electronic progeny exceed us and decide they can live without us, can be avoided by unplugging them.” —Carlton Caves, Distinguished Professor in physics and astronomy at the University of New Mexico

7. Are we any closer to preventing nuclear holocaust? “Since 9/11 the U.S. has had a major policy focus on reducing the danger of nuclear terrorism by increasing the security of highly enriched uranium and plutonium and removing them from as many locations as possible. A nuclear terrorist event could kill 100,000 people. Three decades after the end of the cold war, however, the larger danger of a nuclear holocaust involving thousands of nuclear explosions and tens to hundreds of millions of immediate deaths still persists in the U.S.–Russia nuclear confrontation.

Remembering Pearl Harbor, the U.S. has postured its nuclear forces for the possibility of a bolt-out-of-the-blue first strike in which the Soviet Union would try to destroy all the U.S. forces that were targetable. We don’t expect such an attack today, but each side still keeps intercontinental and submarine-launched ballistic missiles carrying about 1,000 warheads in a launch-on-warning posture. Because the flight time of a ballistic missile is only 15 to 30 minutes, decisions that could result in hundreds of millions of deaths would have to be made within minutes. This creates a significant possibility of an accidental nuclear war or even hackers causing launches.

The U.S. does not need this posture to maintain deterrence, because it has about 800 warheads on untargetable submarines at sea at any time. If there is a nuclear war, however, U.S. Strategic Command and Russia’s Strategic Missile Forces want to be able to use their vulnerable land-based missiles before they can be destroyed. So the cold war may be over, but the Doomsday Machine that came out of the confrontation with the Soviets is still with us—and on a hair trigger.” —Frank von Hippel, emeritus professor at the Woodrow Wilson School of Public and International Affairs at Princeton University and co-founder of Princeton’s Program on Science and Global Security

8. Will sex become obsolescent? “No, but having sex to conceive babies is likely to become at least much less common. In 20 to 40 years we’ll be able to derive eggs and sperm from stem cells, probably the parents’ skin cells. This will allow easy preimplantation genetic diagnosis on a large number of embryos—or easy genome modification for those who want edited embryos instead of just selected ones.” —Henry Greely, director of the Center for Law and the Biosciences at Stanford University

9. Could we one day replace all of the tissues in the human body through engineering? “In 1995 Joseph Vacanti and I wrote for this magazine about advances in artificial pancreas technology, plastic-based tissues such as artificial skin and electronics that might permit blind people to see [see ‘ Artificial Organs ,’ by Robert Langer and Joseph P. Vacanti; Scientific American, September 1995]. All of these are coming to pass, either as real products or in clinical trials. Over the next few centuries it is quite possible that nearly every tissue in the body may be able to be replaced by such approaches. Creating or regenerating tissues such as those found in the brain, which is extremely complex and poorly understood, will take an enormous amount of research. The hope is, however, that research in this area will happen quickly enough to help with brain diseases such as Parkinson’s and Alzheimer’s.” —Robert Langer, David H. Koch Institute Professor at the Massachusetts Institute of Technology

10. Can we avoid a “sixth extinction”? “It can be slowed, then halted, if we take quick action. The greatest cause of species extinction is loss of habitat. That is why I’ve stressed an assembled global reserve occupying half the land and half the sea, as necessary, and in my book Half-Earth, I show how it can be done. With this initiative (and the development of a far better species-level ecosystem science than the one we have now), it will also be necessary to discover and characterize the 10 million or so species estimated to remain; we’ve only found and named two million to date. Overall, an extension of environmental science to include the living world should be, and I believe will be, a major initiative of science during the remainder of this century.” — Edward O. Wilson, University Research Professor emeritus at Harvard University

11. Can we feed the planet without destroying it? “Yes. Here’s what we need to do: reduce crop waste, consumer waste and meat consumption; integrate appropriate seed technologies and management practices; engage consumers about the challenges farmers face in both the developed and the developing world; increase public funding for agricultural research and development; and focus on advancing the socioeconomic and environmental aspects of farming that characterize sustainable agriculture.” —Pamela Ronald, professor in the Genome Center and the department of plant pathology at the University of California, Davis *

12. Will we ever colonize outer space? “That depends on the definition of ‘colonize.’ If landing robots qualifies, then we’ve already done it. If it means sending microbes from Earth and having them persist and maybe grow, then, unfortunately, it’s not unlikely that we’ve done that as well—possibly on Mars with the Phoenix spacecraft and almost certainly inside the Curiosity rover, which carries a heat source and was not fully baked the way Viking had been.

If it means having humans live elsewhere for a longer period of time, but not reproduce, then that’s something that might happen within the next 50 years or so. (Even some limited degree of reproduction might be feasible, recognizing that primates will be primates.) But if the idea is to construct a self-sustaining environment where humans can persist indefinitely with only modest help from Earth—the working definition of a ‘colony,’ according to the various European colonies outside of Europe—then I’d say this is very far in the future, if it’s possible at all. We currently have a very inadequate understanding of how to build closed ecosystems that are robust to perturbation by introduced organisms or nonbiological events ( Biosphere 2 , for example), and I suspect that the contained ecosystem problem will turn out to be much more challenging than the vast majority of space colonization advocates realize. There are a wide range of technical problems to solve, another being air handling. We haven’t bothered to colonize areas underwater on Earth yet. It’s far more challenging to colonize a place where there’s hardly any atmosphere at all.” —Catharine A. Conley, NASA planetary protection officer

13. Will we discover a twin Earth? “My money’s on yes. We’ve found that planets around other stars are far more abundant and diverse than scientists imagined just a couple of decades ago. And we’ve also found that the crucial ingredient for life on this planet—water—is common in space. I’d say nature seems to have stacked the deck in favor of a wide range of planets, including Earth-like planets. We just have to look for them.” —Aki Roberge, research astrophysicist focusing on exoplanets at NASA Goddard Space Flight Center

14. Will there ever be a cure for Alzheimer’s? “I am not sure if there will be a cure, per se, but I am very hopeful that there will be a successful disease-modifying therapy for Alzheimer’s disease within the next decade. We have now started prevention trials that are testing biological interventions even before people show clinical symptoms of the disease. And we don’t have to cure Alzheimer’s—we just need to delay dementia by five to 10 years. Estimates show that a five-year delay in the terrible and expensive dementia stage of the disease would reduce Medicare dementia costs by nearly 50 percent. Most important, that would mean that many older people could die while out ballroom dancing rather than in nursing homes.” —Reisa Sperling, professor of neurology at Harvard Medical School and director of the Center for Alzheimer Research and Treatment

15. Will we use wearable technologies to detect our emotions? “Emotions involve biochemical and electrical signals that reach every organ in our bodies—allowing, for example, stress to impact our physical and mental health. Wearable technologies let us quantify the patterns in these signals over long periods of time. In the coming decade wearables will enable the equivalent of personalized weather forecasts for our health: 80 percent increased probability in health and happiness for you next week, based on your recent stress/sleep/social-emotional activities. Unlike with weather, however, smart wearables can also identify patterns we might choose to change to reduce unwanted ‘storm’ events: Increase sleep to greater than or equal to nine hours per night and maintain current low-moderate stress, for a 60 percent reduced likelihood of seizure in the next four days. Over the next 20 years, wearables, and analytics derived from them, can dramatically reduce psychiatric and neurological disease.” —Rosalind Picard, founder and director of the Affective Computing research group at the M.I.T. Media Lab

16. Will we ever figure out what dark matter is? “Whether we can determine what dark matter is depends on what it turns out to be. Some forms of dark matter allow detection through small interactions with ordinary matter that have so far evaded detection. Others might be detectable through their influence on structures such as galaxies. I’m hopeful we will learn more through experiments or observations. But it’s not guaranteed.” —Lisa Randall, Frank B. Baird, Jr., professor of science in theoretical physics and cosmology at Harvard University

17. Will we get control of intractable brain diseases like schizophrenia or autism? “Diseases like autism and schizophrenia remain elusive because neuroscience hasn’t found a structural problem to fix. Some interpret this to mean future answers lie purely in biochemistry, not neural circuits. Others argue the key is for the neuroscientist to start to think in terms of overall brain architecture—not specific neural failures. Still, when thinking about the future, I am reminded of the Nobelist Charles Townes’s remark that the wonderful thing about a new idea is you don’t know about it.” —Michael Gazzaniga, director of the SAGE Center for the Study of the Mind at the University of California, Santa Barbara

18. Will technology eliminate the need for animal testing in drug development? “If human organs on chips can be shown to be robust and consistently recapitulate complex human organ physiology and disease phenotypes in unrelated laboratories around the world, as suggested by early proof-of-concept studies, then we will see them progressively replace one animal model at a time. That will eventually lead to significant reductions in use of animal testing. Importantly, these devices also will open up new approaches to drug development not possible with animal models today, such as personalized medicines and development of therapeutics for specific genetic subpopulations using chips created using cells from particular patients.” —Donald E. Ingber, founding director, Wyss Institute for Biologically Inspired Engineering at Harvard University

19. Will gender equality be achieved in the sciences? “Gender equality can be achieved, but we can’t just sit back and wait for it to happen. We need to ‘fix the numbers’ by recruiting more women into science and technology. We need to fix the institutions by implementing dual-career hiring, family-friendly policies, and new visions of what it means to be a leader. And, most importantly, we need to fix the knowledge by harnessing the creative power of gender analysis for discovery and innovation.” —Londa Schiebinger, John L. Hinds Professor of History of Science at Stanford University

20. Do you think we will one day be able to predict natural disasters such as earthquakes with warning times of days or hours? “Some natural disasters are easier to see coming than others. Hurricanes approach over days, volcanoes often build up to an eruption over days to hours, tornadoes strike within a few minutes. Earthquakes are perhaps the greatest challenge. What we know about the physics of earthquakes suggests that we will not be able to predict earthquakes days in advance. But what we can do is predict the damaging ground shaking just before it arrives and provide seconds to minutes of warning. Not enough time to get out of town, but enough time to get to a safe location.” —Richard M. Allen, director, Berkeley Seismological Laboratory, University of California, Berkeley

*Editor's Note (8/22/16): This biographical note was edited after posting to correct an error in Ronald's title. 

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• v.53(4); 2010 Aug

Research questions, hypotheses and objectives

Patricia farrugia.

* Michael G. DeGroote School of Medicine, the

Bradley A. Petrisor

† Division of Orthopaedic Surgery and the

Forough Farrokhyar

‡ Departments of Surgery and

§ Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ont

Mohit Bhandari

There is an increasing familiarity with the principles of evidence-based medicine in the surgical community. As surgeons become more aware of the hierarchy of evidence, grades of recommendations and the principles of critical appraisal, they develop an increasing familiarity with research design. Surgeons and clinicians are looking more and more to the literature and clinical trials to guide their practice; as such, it is becoming a responsibility of the clinical research community to attempt to answer questions that are not only well thought out but also clinically relevant. The development of the research question, including a supportive hypothesis and objectives, is a necessary key step in producing clinically relevant results to be used in evidence-based practice. A well-defined and specific research question is more likely to help guide us in making decisions about study design and population and subsequently what data will be collected and analyzed. 1

Objectives of this article

In this article, we discuss important considerations in the development of a research question and hypothesis and in defining objectives for research. By the end of this article, the reader will be able to appreciate the significance of constructing a good research question and developing hypotheses and research objectives for the successful design of a research study. The following article is divided into 3 sections: research question, research hypothesis and research objectives.

Research question

Interest in a particular topic usually begins the research process, but it is the familiarity with the subject that helps define an appropriate research question for a study. 1 Questions then arise out of a perceived knowledge deficit within a subject area or field of study. 2 Indeed, Haynes suggests that it is important to know “where the boundary between current knowledge and ignorance lies.” 1 The challenge in developing an appropriate research question is in determining which clinical uncertainties could or should be studied and also rationalizing the need for their investigation.

Increasing one’s knowledge about the subject of interest can be accomplished in many ways. Appropriate methods include systematically searching the literature, in-depth interviews and focus groups with patients (and proxies) and interviews with experts in the field. In addition, awareness of current trends and technological advances can assist with the development of research questions. 2 It is imperative to understand what has been studied about a topic to date in order to further the knowledge that has been previously gathered on a topic. Indeed, some granting institutions (e.g., Canadian Institute for Health Research) encourage applicants to conduct a systematic review of the available evidence if a recent review does not already exist and preferably a pilot or feasibility study before applying for a grant for a full trial.

In-depth knowledge about a subject may generate a number of questions. It then becomes necessary to ask whether these questions can be answered through one study or if more than one study needed. 1 Additional research questions can be developed, but several basic principles should be taken into consideration. 1 All questions, primary and secondary, should be developed at the beginning and planning stages of a study. Any additional questions should never compromise the primary question because it is the primary research question that forms the basis of the hypothesis and study objectives. It must be kept in mind that within the scope of one study, the presence of a number of research questions will affect and potentially increase the complexity of both the study design and subsequent statistical analyses, not to mention the actual feasibility of answering every question. 1 A sensible strategy is to establish a single primary research question around which to focus the study plan. 3 In a study, the primary research question should be clearly stated at the end of the introduction of the grant proposal, and it usually specifies the population to be studied, the intervention to be implemented and other circumstantial factors. 4

Hulley and colleagues 2 have suggested the use of the FINER criteria in the development of a good research question ( Box 1 ). The FINER criteria highlight useful points that may increase the chances of developing a successful research project. A good research question should specify the population of interest, be of interest to the scientific community and potentially to the public, have clinical relevance and further current knowledge in the field (and of course be compliant with the standards of ethical boards and national research standards).

FINER criteria for a good research question

Adapted with permission from Wolters Kluwer Health. 2

Whereas the FINER criteria outline the important aspects of the question in general, a useful format to use in the development of a specific research question is the PICO format — consider the population (P) of interest, the intervention (I) being studied, the comparison (C) group (or to what is the intervention being compared) and the outcome of interest (O). 3 , 5 , 6 Often timing (T) is added to PICO ( Box 2 ) — that is, “Over what time frame will the study take place?” 1 The PICOT approach helps generate a question that aids in constructing the framework of the study and subsequently in protocol development by alluding to the inclusion and exclusion criteria and identifying the groups of patients to be included. Knowing the specific population of interest, intervention (and comparator) and outcome of interest may also help the researcher identify an appropriate outcome measurement tool. 7 The more defined the population of interest, and thus the more stringent the inclusion and exclusion criteria, the greater the effect on the interpretation and subsequent applicability and generalizability of the research findings. 1 , 2 A restricted study population (and exclusion criteria) may limit bias and increase the internal validity of the study; however, this approach will limit external validity of the study and, thus, the generalizability of the findings to the practical clinical setting. Conversely, a broadly defined study population and inclusion criteria may be representative of practical clinical practice but may increase bias and reduce the internal validity of the study.

PICOT criteria 1

A poorly devised research question may affect the choice of study design, potentially lead to futile situations and, thus, hamper the chance of determining anything of clinical significance, which will then affect the potential for publication. Without devoting appropriate resources to developing the research question, the quality of the study and subsequent results may be compromised. During the initial stages of any research study, it is therefore imperative to formulate a research question that is both clinically relevant and answerable.

Research hypothesis

The primary research question should be driven by the hypothesis rather than the data. 1 , 2 That is, the research question and hypothesis should be developed before the start of the study. This sounds intuitive; however, if we take, for example, a database of information, it is potentially possible to perform multiple statistical comparisons of groups within the database to find a statistically significant association. This could then lead one to work backward from the data and develop the “question.” This is counterintuitive to the process because the question is asked specifically to then find the answer, thus collecting data along the way (i.e., in a prospective manner). Multiple statistical testing of associations from data previously collected could potentially lead to spuriously positive findings of association through chance alone. 2 Therefore, a good hypothesis must be based on a good research question at the start of a trial and, indeed, drive data collection for the study.

The research or clinical hypothesis is developed from the research question and then the main elements of the study — sampling strategy, intervention (if applicable), comparison and outcome variables — are summarized in a form that establishes the basis for testing, statistical and ultimately clinical significance. 3 For example, in a research study comparing computer-assisted acetabular component insertion versus freehand acetabular component placement in patients in need of total hip arthroplasty, the experimental group would be computer-assisted insertion and the control/conventional group would be free-hand placement. The investigative team would first state a research hypothesis. This could be expressed as a single outcome (e.g., computer-assisted acetabular component placement leads to improved functional outcome) or potentially as a complex/composite outcome; that is, more than one outcome (e.g., computer-assisted acetabular component placement leads to both improved radiographic cup placement and improved functional outcome).

However, when formally testing statistical significance, the hypothesis should be stated as a “null” hypothesis. 2 The purpose of hypothesis testing is to make an inference about the population of interest on the basis of a random sample taken from that population. The null hypothesis for the preceding research hypothesis then would be that there is no difference in mean functional outcome between the computer-assisted insertion and free-hand placement techniques. After forming the null hypothesis, the researchers would form an alternate hypothesis stating the nature of the difference, if it should appear. The alternate hypothesis would be that there is a difference in mean functional outcome between these techniques. At the end of the study, the null hypothesis is then tested statistically. If the findings of the study are not statistically significant (i.e., there is no difference in functional outcome between the groups in a statistical sense), we cannot reject the null hypothesis, whereas if the findings were significant, we can reject the null hypothesis and accept the alternate hypothesis (i.e., there is a difference in mean functional outcome between the study groups), errors in testing notwithstanding. In other words, hypothesis testing confirms or refutes the statement that the observed findings did not occur by chance alone but rather occurred because there was a true difference in outcomes between these surgical procedures. The concept of statistical hypothesis testing is complex, and the details are beyond the scope of this article.

Another important concept inherent in hypothesis testing is whether the hypotheses will be 1-sided or 2-sided. A 2-sided hypothesis states that there is a difference between the experimental group and the control group, but it does not specify in advance the expected direction of the difference. For example, we asked whether there is there an improvement in outcomes with computer-assisted surgery or whether the outcomes worse with computer-assisted surgery. We presented a 2-sided test in the above example because we did not specify the direction of the difference. A 1-sided hypothesis states a specific direction (e.g., there is an improvement in outcomes with computer-assisted surgery). A 2-sided hypothesis should be used unless there is a good justification for using a 1-sided hypothesis. As Bland and Atlman 8 stated, “One-sided hypothesis testing should never be used as a device to make a conventionally nonsignificant difference significant.”

The research hypothesis should be stated at the beginning of the study to guide the objectives for research. Whereas the investigators may state the hypothesis as being 1-sided (there is an improvement with treatment), the study and investigators must adhere to the concept of clinical equipoise. According to this principle, a clinical (or surgical) trial is ethical only if the expert community is uncertain about the relative therapeutic merits of the experimental and control groups being evaluated. 9 It means there must exist an honest and professional disagreement among expert clinicians about the preferred treatment. 9

Designing a research hypothesis is supported by a good research question and will influence the type of research design for the study. Acting on the principles of appropriate hypothesis development, the study can then confidently proceed to the development of the research objective.

Research objective

The primary objective should be coupled with the hypothesis of the study. Study objectives define the specific aims of the study and should be clearly stated in the introduction of the research protocol. 7 From our previous example and using the investigative hypothesis that there is a difference in functional outcomes between computer-assisted acetabular component placement and free-hand placement, the primary objective can be stated as follows: this study will compare the functional outcomes of computer-assisted acetabular component insertion versus free-hand placement in patients undergoing total hip arthroplasty. Note that the study objective is an active statement about how the study is going to answer the specific research question. Objectives can (and often do) state exactly which outcome measures are going to be used within their statements. They are important because they not only help guide the development of the protocol and design of study but also play a role in sample size calculations and determining the power of the study. 7 These concepts will be discussed in other articles in this series.

From the surgeon’s point of view, it is important for the study objectives to be focused on outcomes that are important to patients and clinically relevant. For example, the most methodologically sound randomized controlled trial comparing 2 techniques of distal radial fixation would have little or no clinical impact if the primary objective was to determine the effect of treatment A as compared to treatment B on intraoperative fluoroscopy time. However, if the objective was to determine the effect of treatment A as compared to treatment B on patient functional outcome at 1 year, this would have a much more significant impact on clinical decision-making. Second, more meaningful surgeon–patient discussions could ensue, incorporating patient values and preferences with the results from this study. 6 , 7 It is the precise objective and what the investigator is trying to measure that is of clinical relevance in the practical setting.

The following is an example from the literature about the relation between the research question, hypothesis and study objectives:

Study: Warden SJ, Metcalf BR, Kiss ZS, et al. Low-intensity pulsed ultrasound for chronic patellar tendinopathy: a randomized, double-blind, placebo-controlled trial. Rheumatology 2008;47:467–71.

Research question: How does low-intensity pulsed ultrasound (LIPUS) compare with a placebo device in managing the symptoms of skeletally mature patients with patellar tendinopathy?

Research hypothesis: Pain levels are reduced in patients who receive daily active-LIPUS (treatment) for 12 weeks compared with individuals who receive inactive-LIPUS (placebo).

Objective: To investigate the clinical efficacy of LIPUS in the management of patellar tendinopathy symptoms.

The development of the research question is the most important aspect of a research project. A research project can fail if the objectives and hypothesis are poorly focused and underdeveloped. Useful tips for surgical researchers are provided in Box 3 . Designing and developing an appropriate and relevant research question, hypothesis and objectives can be a difficult task. The critical appraisal of the research question used in a study is vital to the application of the findings to clinical practice. Focusing resources, time and dedication to these 3 very important tasks will help to guide a successful research project, influence interpretation of the results and affect future publication efforts.

Tips for developing research questions, hypotheses and objectives for research studies

• Perform a systematic literature review (if one has not been done) to increase knowledge and familiarity with the topic and to assist with research development.
• Learn about current trends and technological advances on the topic.
• Seek careful input from experts, mentors, colleagues and collaborators to refine your research question as this will aid in developing the research question and guide the research study.
• Use the FINER criteria in the development of the research question.
• Ensure that the research question follows PICOT format.
• Develop a research hypothesis from the research question.
• Develop clear and well-defined primary and secondary (if needed) objectives.
• Ensure that the research question and objectives are answerable, feasible and clinically relevant.

FINER = feasible, interesting, novel, ethical, relevant; PICOT = population (patients), intervention (for intervention studies only), comparison group, outcome of interest, time.

Competing interests: No funding was received in preparation of this paper. Dr. Bhandari was funded, in part, by a Canada Research Chair, McMaster University.