what is variable gap in research

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• Intro to Academic Literature
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What is a gap?

Your assignment asks you to find a "gap" in research literature, meaning you are looking for an area or angle that has been explored very little or not at all. It is a gap in the existing knowledge about a subject. Examples of where gaps exist are: population sample (size, type, location), demographic, research method, data collection, or other research variables or conditions. You are being asked to address a gap that, when explored, could contribute new information.

How do you identify a gap?

Your assignment guidelines recommend finding and reading 10 peer-reviewed academic articles as part of a literature review. When you read across the breadth of a topic and think critically in the process about what information appears over and over and what questions remain unanswered as you read, this helps you identify gaps in existing research. By reading 10 sources you should find a balance between:

• Studies that provide context or an overview on key aspects of your topic
• Studies that illustrate key themes, theories, or methods
• Studies directly related to your are of interest and potential gap

Where can you look for gaps?

When you are reading an academic peer-reviewed article it will be divided into sections with subheadings. Look for the sections of the article under Discussion or Future Research or Implications to understand what the researchers know and what they still have questions about, or how they see their own research being built upon by others.

Ask questions in order to think critically as you read: who, what, when, where and how about the population, conditions or variables, methods or analysis, measurements, or outcomes of the research explored in each article you read.

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FAQ: What is a research gap and how do I find one?

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Last Updated: Jun 27, 2023 Views: 481317

What is a research gap.

A research gap is a question or a problem that has not been answered by any of the existing studies or research within your field. Sometimes, a research gap exists when there is a concept or new idea that hasn't been studied at all. Sometimes you'll find a research gap if all the existing research is outdated and in need of new/updated research (studies on Internet use in 2001, for example). Or, perhaps a specific population has not been well studied (perhaps there are plenty of studies on teenagers and video games, but not enough studies on toddlers and video games, for example). These are just a few examples, but any research gap you find is an area where more studies and more research need to be conducted. Please view this video clip from our Sage Research Methods database for more helpful information: How Do You Identify Gaps in Literature?

How do I find one?

It will take a lot of research and reading.  You'll need to be very familiar with all the studies that have already been done, and what those studies contributed to the overall body of knowledge about that topic. Make a list of any questions you have about your topic and then do some research to see if those questions have already been answered satisfactorily. If they haven't, perhaps you've discovered a gap!  Here are some strategies you can use to make the most of your time:

• One useful trick is to look at the “suggestions for future research” or conclusion section of existing studies on your topic. Many times, the authors will identify areas where they think a research gap exists, and what studies they think need to be done in the future.
• As you are researching, you will most likely come across citations for seminal works in your research field. These are the research studies that you see mentioned again and again in the literature.  In addition to finding those and reading them, you can use a database like Web of Science to follow the research trail and discover all the other articles that have cited these. See the FAQ: I found the perfect article for my paper. How do I find other articles and books that have cited it? on how to do this. One way to quickly track down these seminal works is to use a database like SAGE Navigator, a social sciences literature review tool. It is one of the products available via our SAGE Knowledge database.
• In the PsycINFO and PsycARTICLES databases, you can select literature review, systematic review, and meta analysis under the Methodology section in the advanced search to quickly locate these. See the FAQ: Where can I find a qualitative or quantitative study? for more information on how to find the Methodology section in these two databases.
• In CINAHL , you can select Systematic review under the Publication Type field in the advanced search. 
• In Web of Science , check the box beside Review under the Document Type heading in the “Refine Results” sidebar to the right of the list of search hits.
• If the database you are searching does not offer a way to filter your results by document type, publication type, or methodology in the advanced search, you can include these phrases (“literature reviews,” meta-analyses, or “systematic reviews”) in your search string.  For example, “video games” AND “literature reviews” could be a possible search that you could try.

Please give these suggestions a try and contact a librarian for additional assistance.

Content authored by: GS

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Identifying the gap

Research involves highlighting the questions that remain unanswered in your area of research. This is often referred to as ‘identifying the gap’ in the literature and tells the reader what areas need further investigation in your research area. Identifying ‘the gap’ in your research is fundamental to finding your position in an ongoing conversation by deciding how much you accept, question, or reject the claims that your sources make.

When you start to write about that research, you need to figure out how to signal that position, as you quote, summarize, or paraphrase from your sources.

Read the following text and note the way the researcher identifies the gap in the research as a way of positioning themselves in the research field.

This research project sets out to discover if an experience of Antarctica, specifically mine, could be interpreted through the creation of souvenirs and jewellery. Although Antarctica is considered to be a very remote place it has a long and significant history of science and exploration and most recently has become the destination for tourism [a] . However, unlike most tourist destinations Antarctica has not been memorialised through jewellery and souvenirs in the way of historic tourist locations in the world [b]. Throughout Antarctica’s history explorers have painted images and more recently documented it through photography [c] . Whalers and fishermen have made their own representations of this isolated and uninhabited continent, however, none of these matches the proliferation of souvenirs that have been produced to provide memories and reminders of Europe for example during the times of the Grand Tour or the commonly available souvenirs of popular resorts, sites and locations today [d] .

Excerpt from Kirsten Haydon’s dissertation  Antarctic landscapes in the souvenir and jewellery  (used with permission)

Check your understanding

Research and Writing Skills for Academic and Graduate Researchers Copyright © 2022 by RMIT University is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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Research: Establishing the Problem Space

• Establishing the Problem Space
• Finding Qualitative Research
• Finding Quantitative Research
• What is Emperical Research?
• What is Seminal Research?

What is the Problem Space?

A gap is a space between two objects or a break in continuity.  A research gap is a break or missing part of the existing research when you define the research gap or the problem space you are defining what is known and what is missing in the existing research.  The "problem space" of a study is a definition of the topic, the problem statements or research gaps mentioned by other researchers, and the steps other researchers took to answer the research question. The problem space is a way to identify and establish boundaries for your research, it helps to guide what should be included or excluded from your research.  The problem statement expresses how your study will answer or fill the research gap.

The problem space is thus comprised of identifying what is known about a topic, understanding how it has come to be known (the theories, designs, methods, instruments), and then figuring out what is not yet known (or perspective not explored) .   Problem spaces are built by taking note of the limitations and recommendations discussed in the empirical research articles you gather as you build your literature review.

• Don't know where to start? 6 Tips on identifying research gaps
• What are Gap Statements? From the Middlebury University 'Write Like a Scientist" guide.
• Farooq, R. (2017). A framework for identifying research gap in social sciences: Evidence from the past. IUP Journal of Management Research, 16(4), 66-75. Retrieved from https://uscupstate.idm.oclc.org/login?url=https://www.proquest.com/scholarly-journals/
• Robinson KA, Akinyede O, Dutta T, et al. Framework for Determining Research Gaps During Systematic Review: Evaluation [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2013 Feb. Introduction. Available from: https://www.ncbi.nlm

Examples From Empirical Articles

When looking to find discussions of research that has yet to be done (AKA research gap) in existing articles there are a few keywords to look out for such as limitations identified, further research needed, needs clarification, not been reported (studied, reported, or elucidated), suggestions for further research, questions remains, poorly understood, and/or lack of studies

Below are two examples of types of passages to look for.

Example of a Limitations Section

From the article:

Spanhove, V., De Wandele, I., Kjær, B. H., Malfait, F., Vanderstukken, F., & Cools, A. (2020). The effect of five isometric exercises on glenohumeral translations in healthy subjects and patients with the hypermobility type of the ehlers-danlos syndrome (heds) or hypermobility spectrum disorder (hsd) with multidirectional shoulder instability: an observational study.  Physiotherapy ,  107 , 11–18. https://doi.org/10.1016/j.physio.2019.06.010

From this passage, an argument could be made for performing a similar study, but with 3D analysis.

Example of a Recommendation for Further Research

Some articles will go beyond discussing their limitations and describe further research that should be done. 

For example, this article:

Carey, J., Pathak, A., & Johnson, S. C. (2020). Use, Perceptions, and Awareness of LibGuides among Undergraduate and Graduate Health Professions Students.  Evidence Based Library and Information Practice ,  15 (3), 157-172. https://doi.org/10.18438/eblip29653

Suggests several different avenues of further research:

How to Use Review Articles

Review articles can help formulate a gap, or at least point out a direction to look for one. Since they provide an overview of the published literature, they can give you a head start on what kinds of research are lacking.

How to Locate Review Articles: Systematic Reviews, Literature Reviews, and Meta-Analyses

• handwashing or hand washing or hand hygiene or hand sanitation
• systematic review or meta-analysis or literature review or scoping review
• Adjust dates to be within 2 years. 
• For instance the above search was used to locate this article:

Seo, H.-J., Sohng, K.-Y., Chang, S. O., Chaung, S. K., Won, J. S., & Choi, M.-J. (2019). Interventions to improve hand hygiene compliance in emergency departments: a systematic review. The Journal of Hospital Infection , 102(4), 394–406. https://doi.org/10.1016/j.jhin.2019.03.013

• (hand antisepsis or handwash* or hand wash* or hand disinfection or hand hygiene or surgical scrub*)
• With terms that should be included when searching on this topic.
• "Further well-designed controlled studies are necessary to examine the true effects and identify which intervention modalities are more effective than others for HHC improvement in EDs."
• Reviewing the articles this article studied would then provide support for this gap.

Pursuing a health care topic? Search Cochrane Reviews or Joanna Biggs EBP as well as the more general databases.

Example of a Review Article With a Discussion of Areas Needing Research

Example of a Review Article

Review articles can clarify where a lack of research exists. To then establish the problem space fully, you will need to track down the articles cited in the review.

For instance, consider the following passage from this review article:

Martin, A. (2019). An acquired or heritable connective tissue disorder? A review of hypermobile Ehlers Danlos Syndrome. European Journal of Medical Genetics, 62(7), 103672. https://doi.org/10.1016/j.ejmg.2019.103672

This is indicating a need for longitudinal studies for this condition to better understand the relationship between muscle strength and muscle waste. Further examining the cited articles would establish this avenue for a study.

Problem Formulation

• Trochim, William M.K. “Problem Formulation.” Research Methods Knowledge Base, Conjoint.ly, https://conjointly.com/kb/problem-formulation/.
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What Is A Research Gap? (With Tips + Examples)

A research gap is a specific area within a field of study that remains unexplored or under-explored. Identifying a research gap involves recognizing where existing research is lacking or where there are unanswered questions that could provide opportunities for further investigation. Understanding research gaps is crucial for advancing knowledge, as it helps scholars and researchers focus their efforts on areas that can contribute significantly to their field.

What Is A Research Gap?

It is actually a question or any issue that needs to be solved by any pre-existing work or research in your area of study. A research gap can also exist where some new idea still needs to be studied.

Tips on Identifying Research Gap

Research always plays an essential role in acquiring more knowledge and addressing the gaps in different fields. When you are identifying a research gap, you are taking a very important step in the whole research process. This aids the researchers in contributing meaningful insights and triggers the knowledge boundaries.

Understanding the Literature You Are Studying: In order to identify any research gap, it is essential to have an excellent advertising of the preexisting literature in your study field.

Here, you need to conduct a review of many books, scholarly articles, conferences, and other relevant sources. In this way, you can get a good foundation as well as insights into any present state of in-depth knowledge in your own study area.

Defining Your Own Research Question: After getting a good knowledge of the pre-existing literature, you need to define a concise and clear idea of the research question. This research question needs to be very specific, attainable, measurable, time-bound and relevant. An acronym for this entire thing is known as SMART. This also needs to address any significant issue that still needs to be fully solved or adequately answered.

Identifying Your Study Objectives: Here, you need to identify the major objectives of your research paper. All these objectives need to be aligned with the identified research gap. These objectives always guide the researcher and aid you in determining the direction and scope of your research study.

Analyze the Existing Studies: Here, you need to analyze very carefully all the existing studies that are related to your research question. Here, it would help if you looked at the most common recurring findings, themes, and patterns of the discussed literature. Here, you also need to pay a lot of attention to the conflicted areas with the results, unanswered questions, and contradictory theories. These areas show the research gaps that can be explored later.

Consider The Practical Relevance: You always need to evaluate the very practical relevance of the research question as well as its potential impact on society. Here, it would help if you always considered the importance of addressing your own research gap as you identified it.

Here, you also need to assess whether your findings can contribute to the original theoretical framework and offer all the practical solutions for leading to the policy recommendations. These practical ads are relevant to the research paper and trigger its impact.

Consulting With the Experts and Peers: You always need to engage you’re discussing with your mentors, peers, and experts in your own field of study. Here, you always need to seek their opinions and perspectives on the research question to identify potential research gaps.

These can provide valuable insights into assumption challenges, and this helps you refine your research work. Your peers and experts can give you a new idea and help you identify the errors in your thinking.

Conducting Your Pilot Study: You need to conduct it to test the viability and feasibility of the research question. This pilot study provides you with feedback and data on the research design, approach and methodology.

This also helps you identify the potential limitations or challenges that need to be solved before conducting the full research studies.

Reflecting and Refining: You need to vividly reflect on the research progress to refine your research preferences. You need to add the objectives. As you go deeper into your research process, additional research gaps may be uncovered to refine your own research needs.

If you follow this process, you can adapt your own approach to ensure the research gaps.

As per the example of the research gap, identifying your research gap allows your research to contribute to gaining more knowledge to address the pre-existing limitations.

This way, you will understand the existing literature to define a crystal clear research statement. You can identify the research gaps by analyzing the existing studies to consider their relevance. According to the research gap finder, if you consult with your peers, doing all the pilot studies reflects on your research process progress.

If you follow the guide mentioned above, you can always embark on meaningful research studies to trigger your knowledge in your subject area and make a prominent contribution to your field.

Also Read: Struggling with Research Paper Writing?

Different Types of Research Gaps

Identifying research gaps is essential for advancing knowledge in any field. Research gaps are areas where more information is available or existing research needs to be more consistent or conclusive. Here are different types of research gaps:

• Evidence Gap

This gap occurs when no empirical evidence supports certain theories, practices, or interventions. It can also refer to areas where existing studies need to sufficiently cover the topic or lack rigorous methodological approaches.

Example: A need for randomized controlled trials on the effectiveness of a new drug.

• Knowledge Gap

This gap refers to areas where there is a deficiency in understanding or awareness about a particular topic. It can be due to outdated information, incomplete research, or the absence of research on emerging issues.

Example: Limited knowledge about the long-term effects of exposure to new environmental pollutants.

• Theoretical Gap

Theoretical gaps arise when existing theories do not fully explain certain phenomena or when there is a lack of theoretical frameworks to guide research in a particular area.

Example: More theoretical models need to be developed to explain the psychological impacts of social media usage on teenagers.

• Methodological Gap

Methodological gaps exist when current research methods are inadequate for addressing certain research questions or when there is a need for new or improved methodologies.

Example: More robust qualitative methods are needed to study the experiences of marginalized communities.

• Population Gap

This type of gap occurs when certain populations are underrepresented in research. It can involve demographics like age, gender, ethnicity, socioeconomic status, or geographic location.

Example: Lack of research on the mental health of older adults living in rural areas.

Geographical Gap

Geographical gaps refer to areas or regions that are under-researched. These gaps highlight the need for studies in different geographic contexts to understand local issues better.

Example: Limited studies on the effects of climate change in the Arctic regions.

Strategies to Identify Research Gaps:

• Literature Reviews: Comprehensive reviews can help identify where current research is lacking or inconsistent.
• Systematic Reviews and Meta-Analyses: These methods provide a structured approach to synthesize existing research and identify gaps.
• Expert Consultations: Discussions with experts in the field can uncover areas that require further investigation.
• Research Databases: Utilizing databases and citation analysis tools to track research trends and identify under-researched areas.
• Interdisciplinary Approaches: Engaging with multiple disciplines can reveal gaps that are not apparent within a single field.

Understanding and addressing these gaps is crucial for advancing research and knowledge across various domains.

Read More: How To Get A+ Grade In Research Paper?

What is a Research Gap Example?

A Research Paper Example gives you a very clear idea of how to find your research gaps and examples in textual forms. A few examples are given below:

• Context Healthcare: Although there have been enough researchers on the management of diabetes, there has been a research gap in understanding the impact of digital health interventions in the rural areas of Europe.
• Content environmental science: In a wealth of research regarding the huge environmental pollution caused by the use of plastics, there are fewer findings of how the plastic material really accumulates in certain areas like lakes, rivers, etc. and why these materials are never biodegradable.
• Context Education: The empirical research surrounding the online mode has become tremendously popular over the past few years. However, there needs to be more solid studies regarding the impact of the online learning process on the students who need special education. In each of these examples, you can see that the writer begins by acknowledging the preexisting reach results and then explains thoroughly the present area where the research gap really exists.

Also Read: Why Research Is Essential For Students? 20 Common Reasons!

How to Find a Research Gap?

After getting a very clear idea of various types of research gaps, the vet’s next question comes to mind is how to find a research gap. There is a basic 2 step strategy to find the research gap.

In the beginning, you need to find a lot of literature reviews, meta-analyses, and systematic reviews covering your research area of interest. Moreover, it would help if you dug into the very recent journals for wrapping your head in your own knowledge area.

Here, you can also study the current theses and dissertations, especially those in the doctoral degree courses. A number of dissertation databases, such as Open Access, EBSCO, Pro-Quest, etc., are very useful in this regard. Here. You also need to ensure that you are always looking for the most recent sources.

After gathering a good collection of these resources, you need to focus on further research opportunities. In this section, you need to state explicitly where more studies are needed. It would help if you also looked at the present research study’s limitation areas and where the research gaps might exist.

Following this procedure will help you become oriented to the present research area. This can serve as a foundation for finding the potential research gaps. Then, you need to shortlist the main ideas and evaluate them as per the given topic. It would help if you also looked only for the recent articles here.

Also Read:  Expert Literature Review Writing Services

How to Deal with Literature Gap?

In any project, a literature review is always very important. It helps you in identifying your excusing knowledge, methods and theories in your own field. However, conducting a literature review has its own challenges.

• Defiling your research question: The very first step is to define your own research question very clearly and briefly. It will help you narrow your scope and focus on the crucial sources. It would help if you used less information here. Your research must always be very specific, answerable, and original. The research project always needs to have real objectives and a purpose.
• Searching and selecting the sources: Your next step is to search and select the sources. That is very much reliable and relevant to your research field. There are a number of databases, like keywords, search engines, etc., related to your study field. However, there are also a lot of limitations to these tools, like currency, coverage, and quality of the sources. Here, certain criteria have to be applied to filter the sources, such as relevance, authority, timeline, and accuracy of the information.
• Analyzing and synthesizing the literature: This is the third step, where you need to analyze and synthesize the literature you selected. Here, you need to summarize the sources and compare, contrast and critique them. In this section, you also need to look for the similarities and differences, the strengths and weaknesses, and the gaps and inconsistencies of the literature review paper. The writers can also identify the major trends, themes, and debates in the discussed field. These should also be related to your research question.
• Fill in the gaps after identifying them: This is the 4th step to filling the literature review research paper. This gap needs to be addressed or is under the researched area and is to be addressed by you with the help of your knowledge. These gaps can be filled by looking for the limitations, contradictions or controversies in the review. You can also do this by asking new questions or proposing new ideas. The gaps can also be filled by providing the newest evidence, arguments or even insights related to your field of study.
• Organizing and structuring the literature review: This is the 5th step of your review, where you need to organize and structure the whole paper in a compact and logical manner. Here, you always need to follow certain guidelines as given by your institute and use the best style and font. Proper headings, subheading citations, and traditions should also be used here. This will help your readers follow your arguments and understand what you want to say. A very clear introduction should also be written, along with a good conclusion and summary to highlight your writing.
• Refining and Revising: The literature review is the final step of writing your literature review. Here, you need to ensure that your review is quite accurate, concise and clear. You must check your literature review thoroughly to make it free from errors, gaps, or inconsistencies in language, content, or presentation. Here, you can also seek feedback from your peers, experts or supervisors in your own field. Their suggestions will help you in performing well. The whore literature review should be thoroughly proofread and edited before the final submission.

Last but not least, never copy from any source; it will be considered plagiarism, and your paper will be cancelled then and there. Thus, write only from your own creativity and not from the writing and articles of other writers.

Read More: Dissertation Literature Review For Masters & PhD

Final Words

Writing a research paper is a challenging task. It would help if you had a lot of Research Skills to accomplish it. You will be given a Research topic on which you have to write. Your ultimate aim in writing the research paper is to get the top grade. This can be done by availing of the best online Case Study Help Service from a reliable provider. The Casestudyhelp is the best choice for you in this respect.

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How to Identify Gaps in Research: Tips to Speed Up the Process

If you have ever wondered how to identify research gaps, well, you’re not alone. All researchers looking to make a solid contribution to their field need to start by identifying a topic or issue that hasn’t been tackled before and coming up with possible solutions for it. This is where learning what is a research gap, knowing about some research gap examples, and knowing how to identify research gaps becomes important. Through this article, we will try answering these questions for you.

Table of Contents

What is a research gap ?  

Research gaps are areas requiring more studies or research. 1  They can be:   

• an unsolved question or problem within your field.   
• a case where inconclusive or contradictive results exist.   
• a new concept or idea that hasn’t been studied.   
• a new/updated research to replace the outdated existing research.   
• a specific demographic or location that has not been well studied.   

Why is it important to identify research gaps ?  

Identifying and prioritizing research gaps  is an essential part of any research for the following reasons. 2  This can help you:  

• ensure the rapid generation of subsequent research that is informed by input from previous research studies.    
• understand areas of uncertainty within the research problem.   
• establish the research problem and scope of the study.   
• determine the scope of funding opportunities.   

Identifying research gaps : A challenge for early researchers  

Coming up with original, innovative ideas in your chosen area of research can be tricky, especially if you are an early career researcher, for the following reasons: 3,4

• Enormous information available : The introduction, discussion, and future research sections in published research articles provide information about gaps in the research field. It is easy to get overwhelmed and feel confused about which one to address. Using digital tools can help you seek out popular topics or the most cited research papers.   
• Difficulty in organizing the data : One can quickly lose ideas if not appropriately noted. Mapping the question to the resource and maintaining a record can help narrow research gap s.  
• Fear of challenging the existing knowledge : Beginner researchers may not feel confident to question established norms in their field. A good plan of action would be discussing such ideas with your advisor and proceeding according to their feedback or suggestions.   
• Lack of direction and motivation : Early researchers have reported negative emotions regarding academic research, including feeling directionless or frustrated with the effort required in identifying research topics. Again a good advisor can help you stay focused. Mentors can help novice researchers avoid cases with a high risk of failure, from misunderstanding the literature, weak design, or too many unknowns. Talking with other fellow researchers can also help overcome some of the anxiety.

How to identify research gaps  in the literature  

More than 7 million papers get published annually. 5  Considering the volume of existing research, identifying research gaps  from existing literature may seem a daunting task. While there are no hard rules for identifying research gaps, the literature has provided some guidelines for identifying problems worth investigating.   

1. Observe : Personal interests and experiences can provide insight into possible research problems. For example, a researcher interested in teaching may start with a simple observation of students’ classroom behavior and observe the link with learning theories. Developing the habit of reading literature using smart apps like  R Discovery   can keep you updated with the latest trends and developments in the field.   

2. Search : Exploring existing literature will help to identify if the observed problem is documented. One approach is identifying the independent variables used to solve the researcher’s topic of interest (i.e., the dependent variable). Databases such as Emerald, ProQuest, EbscoHost, PubMed, and ScienceDirect can help potential researchers explore existing research gaps. The following steps can help with optimizing the search process once you decide on the key research question based on your interests.

-Identify key terms.

-Identify relevant articles based on the keywords.

-Review selected articles to identify gaps in the literature.  

3. Map : This involves mapping key issues or aspects across the literature. The map should be updated whenever a researcher comes across an article of interest.   

4. Synthesize : Synthesis involves integrating the insights of multiple but related studies. A research gap is identified by combining results and findings across several interrelated studies. 6

5. Consult:  Seeking expert feedback will help you understand if the  research gaps identified are adequate and feasible or if improvements are required.  

6. Prioritize : It is possible that you have identified multiple questions requiring answers. Prioritize the question that can be addressed first, considering their relevance, resource availability, and your research strengths.  

7. Enroll : Research Skills Development Programs, including workshops and discussion groups within or outside the research institution, can help develop research skills, such as framing the research problem. Networking and corroborating in such events with colleagues and experts might help you know more about current issues and problems in your research domain.   

While there is no well-defined process to identify gaps in knowledge, curiosity, judgment, and creativity can help you in identifying these research gaps . Regardless of whether the  research gaps identified are large or small, the study design must be sufficient to contribute toward advancing your field of research.    

References  

• Dissanayake, D. M. N. S. W. (2013). Research, research gap and the research problem.  
• Nyanchoka, L., Tudur-Smith, C., Porcher, R., & Hren, D. Key stakeholders’ perspectives and experiences with defining, identifying and displaying gaps in health research: a qualitative study.  BMJ open ,  10 (11), e039932 (2020).  
• Müller-Bloch, C., & Kranz, J. (2015). A framework for rigorously identifying research gaps in qualitative literature reviews.  
• Creswell, J. W., & Clark, V. L. P. (2017).  Designing and conducting mixed methods research . Sage publications.  
• Fire, M., & Guestrin, C. Over-optimization of academic publishing metrics: observing Goodhart’s Law in action.  GigaScience ,  8 (6), giz053 (2019).  
• Ellis, T. J., & Levy, Y. Framework of problem-based research: A guide for novice researchers on the development of a research-worthy problem.  Informing Science: the International Journal of an Emerging Transdiscipline Volume 11, 2008 ). 

Frequently Asked Questions (FAQs)

Question: How can research gaps be addressed?

Research gaps can be addressed by conducting further studies, experiments, or investigations that specifically target the areas where knowledge is lacking or incomplete. This involves conducting a thorough literature review to identify existing gaps, designing research methodologies to address these gaps, and collecting new data or analyzing existing data to fill the void. Collaboration among researchers, interdisciplinary approaches, and innovative research designs can also help bridge research gaps and contribute to the advancement of knowledge in a particular field.

Question: Can research gaps change over time?

Yes, research gaps can change over time. As new studies are conducted, technologies advance, and societal needs evolve, gaps in knowledge may be identified or existing gaps may become more pronounced. Research gaps are dynamic and subject to shifts as new discoveries are made, new questions arise, and priorities change. It is crucial for researchers to continuously assess and update their understanding of the field to identify emerging research gaps and adapt their research efforts accordingly.

Question: Are research gaps specific to a particular discipline or field?

Research gaps can exist within any discipline or field. Each discipline has its own unique body of knowledge and areas where understanding may be limited. Research gaps can arise from unanswered questions, unexplored phenomena, conflicting findings, practical challenges, or new frontiers of knowledge. They are not limited to a specific discipline or field, as gaps can exist in natural sciences, social sciences, humanities, engineering, or any other area of study.

Question: How can research gaps contribute to the research proposal?

Research gaps play a significant role in the development of research proposals. They help researchers identify a clear rationale and justification for their study. By addressing identified gaps in knowledge, researchers can demonstrate the significance and relevance of their proposed research. Research proposals often include a literature review section that highlights existing gaps and positions the proposed study as a contribution to the field. By explicitly addressing research gaps, researchers can strengthen the credibility and importance of their research proposal, as well as its potential impact on advancing knowledge and addressing critical questions or challenges.

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Variables in Research – Definition, Types and Examples

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Variables in Research

Definition:

In Research, Variables refer to characteristics or attributes that can be measured, manipulated, or controlled. They are the factors that researchers observe or manipulate to understand the relationship between them and the outcomes of interest.

Types of Variables in Research

Types of Variables in Research are as follows:

Independent Variable

This is the variable that is manipulated by the researcher. It is also known as the predictor variable, as it is used to predict changes in the dependent variable. Examples of independent variables include age, gender, dosage, and treatment type.

Dependent Variable

This is the variable that is measured or observed to determine the effects of the independent variable. It is also known as the outcome variable, as it is the variable that is affected by the independent variable. Examples of dependent variables include blood pressure, test scores, and reaction time.

Confounding Variable

This is a variable that can affect the relationship between the independent variable and the dependent variable. It is a variable that is not being studied but could impact the results of the study. For example, in a study on the effects of a new drug on a disease, a confounding variable could be the patient’s age, as older patients may have more severe symptoms.

Mediating Variable

This is a variable that explains the relationship between the independent variable and the dependent variable. It is a variable that comes in between the independent and dependent variables and is affected by the independent variable, which then affects the dependent variable. For example, in a study on the relationship between exercise and weight loss, the mediating variable could be metabolism, as exercise can increase metabolism, which can then lead to weight loss.

Moderator Variable

This is a variable that affects the strength or direction of the relationship between the independent variable and the dependent variable. It is a variable that influences the effect of the independent variable on the dependent variable. For example, in a study on the effects of caffeine on cognitive performance, the moderator variable could be age, as older adults may be more sensitive to the effects of caffeine than younger adults.

Control Variable

This is a variable that is held constant or controlled by the researcher to ensure that it does not affect the relationship between the independent variable and the dependent variable. Control variables are important to ensure that any observed effects are due to the independent variable and not to other factors. For example, in a study on the effects of a new teaching method on student performance, the control variables could include class size, teacher experience, and student demographics.

Continuous Variable

This is a variable that can take on any value within a certain range. Continuous variables can be measured on a scale and are often used in statistical analyses. Examples of continuous variables include height, weight, and temperature.

Categorical Variable

This is a variable that can take on a limited number of values or categories. Categorical variables can be nominal or ordinal. Nominal variables have no inherent order, while ordinal variables have a natural order. Examples of categorical variables include gender, race, and educational level.

Discrete Variable

This is a variable that can only take on specific values. Discrete variables are often used in counting or frequency analyses. Examples of discrete variables include the number of siblings a person has, the number of times a person exercises in a week, and the number of students in a classroom.

Dummy Variable

This is a variable that takes on only two values, typically 0 and 1, and is used to represent categorical variables in statistical analyses. Dummy variables are often used when a categorical variable cannot be used directly in an analysis. For example, in a study on the effects of gender on income, a dummy variable could be created, with 0 representing female and 1 representing male.

Extraneous Variable

This is a variable that has no relationship with the independent or dependent variable but can affect the outcome of the study. Extraneous variables can lead to erroneous conclusions and can be controlled through random assignment or statistical techniques.

Latent Variable

This is a variable that cannot be directly observed or measured, but is inferred from other variables. Latent variables are often used in psychological or social research to represent constructs such as personality traits, attitudes, or beliefs.

Moderator-mediator Variable

This is a variable that acts both as a moderator and a mediator. It can moderate the relationship between the independent and dependent variables and also mediate the relationship between the independent and dependent variables. Moderator-mediator variables are often used in complex statistical analyses.

Variables Analysis Methods

There are different methods to analyze variables in research, including:

• Descriptive statistics: This involves analyzing and summarizing data using measures such as mean, median, mode, range, standard deviation, and frequency distribution. Descriptive statistics are useful for understanding the basic characteristics of a data set.
• Inferential statistics : This involves making inferences about a population based on sample data. Inferential statistics use techniques such as hypothesis testing, confidence intervals, and regression analysis to draw conclusions from data.
• Correlation analysis: This involves examining the relationship between two or more variables. Correlation analysis can determine the strength and direction of the relationship between variables, and can be used to make predictions about future outcomes.
• Regression analysis: This involves examining the relationship between an independent variable and a dependent variable. Regression analysis can be used to predict the value of the dependent variable based on the value of the independent variable, and can also determine the significance of the relationship between the two variables.
• Factor analysis: This involves identifying patterns and relationships among a large number of variables. Factor analysis can be used to reduce the complexity of a data set and identify underlying factors or dimensions.
• Cluster analysis: This involves grouping data into clusters based on similarities between variables. Cluster analysis can be used to identify patterns or segments within a data set, and can be useful for market segmentation or customer profiling.
• Multivariate analysis : This involves analyzing multiple variables simultaneously. Multivariate analysis can be used to understand complex relationships between variables, and can be useful in fields such as social science, finance, and marketing.

Examples of Variables

• Age : This is a continuous variable that represents the age of an individual in years.
• Gender : This is a categorical variable that represents the biological sex of an individual and can take on values such as male and female.
• Education level: This is a categorical variable that represents the level of education completed by an individual and can take on values such as high school, college, and graduate school.
• Income : This is a continuous variable that represents the amount of money earned by an individual in a year.
• Weight : This is a continuous variable that represents the weight of an individual in kilograms or pounds.
• Ethnicity : This is a categorical variable that represents the ethnic background of an individual and can take on values such as Hispanic, African American, and Asian.
• Time spent on social media : This is a continuous variable that represents the amount of time an individual spends on social media in minutes or hours per day.
• Marital status: This is a categorical variable that represents the marital status of an individual and can take on values such as married, divorced, and single.
• Blood pressure : This is a continuous variable that represents the force of blood against the walls of arteries in millimeters of mercury.
• Job satisfaction : This is a continuous variable that represents an individual’s level of satisfaction with their job and can be measured using a Likert scale.

Applications of Variables

Variables are used in many different applications across various fields. Here are some examples:

• Scientific research: Variables are used in scientific research to understand the relationships between different factors and to make predictions about future outcomes. For example, scientists may study the effects of different variables on plant growth or the impact of environmental factors on animal behavior.
• Business and marketing: Variables are used in business and marketing to understand customer behavior and to make decisions about product development and marketing strategies. For example, businesses may study variables such as consumer preferences, spending habits, and market trends to identify opportunities for growth.
• Healthcare : Variables are used in healthcare to monitor patient health and to make treatment decisions. For example, doctors may use variables such as blood pressure, heart rate, and cholesterol levels to diagnose and treat cardiovascular disease.
• Education : Variables are used in education to measure student performance and to evaluate the effectiveness of teaching strategies. For example, teachers may use variables such as test scores, attendance, and class participation to assess student learning.
• Social sciences : Variables are used in social sciences to study human behavior and to understand the factors that influence social interactions. For example, sociologists may study variables such as income, education level, and family structure to examine patterns of social inequality.

Purpose of Variables

Variables serve several purposes in research, including:

• To provide a way of measuring and quantifying concepts: Variables help researchers measure and quantify abstract concepts such as attitudes, behaviors, and perceptions. By assigning numerical values to these concepts, researchers can analyze and compare data to draw meaningful conclusions.
• To help explain relationships between different factors: Variables help researchers identify and explain relationships between different factors. By analyzing how changes in one variable affect another variable, researchers can gain insight into the complex interplay between different factors.
• To make predictions about future outcomes : Variables help researchers make predictions about future outcomes based on past observations. By analyzing patterns and relationships between different variables, researchers can make informed predictions about how different factors may affect future outcomes.
• To test hypotheses: Variables help researchers test hypotheses and theories. By collecting and analyzing data on different variables, researchers can test whether their predictions are accurate and whether their hypotheses are supported by the evidence.

Characteristics of Variables

Characteristics of Variables are as follows:

• Measurement : Variables can be measured using different scales, such as nominal, ordinal, interval, or ratio scales. The scale used to measure a variable can affect the type of statistical analysis that can be applied.
• Range : Variables have a range of values that they can take on. The range can be finite, such as the number of students in a class, or infinite, such as the range of possible values for a continuous variable like temperature.
• Variability : Variables can have different levels of variability, which refers to the degree to which the values of the variable differ from each other. Highly variable variables have a wide range of values, while low variability variables have values that are more similar to each other.
• Validity and reliability : Variables should be both valid and reliable to ensure accurate and consistent measurement. Validity refers to the extent to which a variable measures what it is intended to measure, while reliability refers to the consistency of the measurement over time.
• Directionality: Some variables have directionality, meaning that the relationship between the variables is not symmetrical. For example, in a study of the relationship between smoking and lung cancer, smoking is the independent variable and lung cancer is the dependent variable.

Advantages of Variables

Here are some of the advantages of using variables in research:

• Control : Variables allow researchers to control the effects of external factors that could influence the outcome of the study. By manipulating and controlling variables, researchers can isolate the effects of specific factors and measure their impact on the outcome.
• Replicability : Variables make it possible for other researchers to replicate the study and test its findings. By defining and measuring variables consistently, other researchers can conduct similar studies to validate the original findings.
• Accuracy : Variables make it possible to measure phenomena accurately and objectively. By defining and measuring variables precisely, researchers can reduce bias and increase the accuracy of their findings.
• Generalizability : Variables allow researchers to generalize their findings to larger populations. By selecting variables that are representative of the population, researchers can draw conclusions that are applicable to a broader range of individuals.
• Clarity : Variables help researchers to communicate their findings more clearly and effectively. By defining and categorizing variables, researchers can organize and present their findings in a way that is easily understandable to others.

Disadvantages of Variables

Here are some of the main disadvantages of using variables in research:

• Simplification : Variables may oversimplify the complexity of real-world phenomena. By breaking down a phenomenon into variables, researchers may lose important information and context, which can affect the accuracy and generalizability of their findings.
• Measurement error : Variables rely on accurate and precise measurement, and measurement error can affect the reliability and validity of research findings. The use of subjective or poorly defined variables can also introduce measurement error into the study.
• Confounding variables : Confounding variables are factors that are not measured but that affect the relationship between the variables of interest. If confounding variables are not accounted for, they can distort or obscure the relationship between the variables of interest.
• Limited scope: Variables are defined by the researcher, and the scope of the study is therefore limited by the researcher’s choice of variables. This can lead to a narrow focus that overlooks important aspects of the phenomenon being studied.
• Ethical concerns: The selection and measurement of variables may raise ethical concerns, especially in studies involving human subjects. For example, using variables that are related to sensitive topics, such as race or sexuality, may raise concerns about privacy and discrimination.

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What is a Research Gap

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If you are a young researcher, or even still finishing your studies, you’ll probably notice that your academic environment revolves around certain research topics, probably linked to your department or to the interest of your mentor and direct colleagues. For example, if your department is currently doing research in nanotechnology applied to medicine, it is only natural that you feel compelled to follow this line of research. Hopefully, it’s something you feel familiar with and interested in – although you might take your own twists and turns along your career.

Many scientists end up continuing their academic legacy during their professional careers, writing about their own practical experiences in the field and adapting classic methodologies to a present context. However, each and every researcher dreams about being a pioneer in a subject one day, by discovering a topic that hasn’t been approached before by any other scientist. This is a research gap.

Research gaps are particularly useful for the advance of science, in general. Finding a research gap and having the means to develop a complete and sustained study on it can be very rewarding for the scientist (or team of scientists), not to mention how its new findings can positively impact our whole society.

How to Find a Gap in Research

How many times have you felt that you have finally formulated THAT new and exciting question, only to find out later that it had been addressed before? Probably more times than you can count.

There are some steps you can take to help identify research gaps, since it is impossible to go through all the information and research available nowadays:

• Select a topic or question that motivates you: Research can take a long time and surely a large amount of physical, intellectual and emotional effort, therefore choose a topic that can keep you motivated throughout the process.
• Find keywords and related terms to your selected topic: Besides synthesizing the topic to its essential core, this will help you in the next step.
• Use the identified keywords to search literature: From your findings in the above step, identify relevant publications and cited literature in those publications.
• Look for topics or issues that are missing or not addressed within (or related to) your main topic.
• Read systematic reviews: These documents plunge deeply into scholarly literature and identify trends and paradigm shifts in fields of study. Sometimes they reveal areas or topics that need more attention from researchers and scientists.

Keeping track of all the new literature being published every day is an impossible mission. Remember that there is technology to make your daily tasks easier, and reviewing literature can be one of them. Some online databases offer up-to-date publication lists with quite effective search features:

• Elsevier’s Scope
• Google Scholar

Of course, these tools may be more or less effective depending on knowledge fields. There might be even better ones for your specific topic of research; you can learn about them from more experienced colleagues or mentors.

Find out how FINER research framework can help you formulate your research question.

Literature Gap

The expression “literature gap” is used with the same intention as “research gap.” When there is a gap in the research itself, there will also naturally be a gap in the literature. Nevertheless, it is important to stress out the importance of language or text formulations that can help identify a research/literature gap or, on the other hand, making clear that a research gap is being addressed.

When looking for research gaps across publications you may have noticed sentences like:

…has/have not been… (studied/reported/elucidated) …is required/needed… …the key question is/remains… …it is important to address…

These expressions often indicate gaps; issues or topics related to the main question that still hasn’t been subject to a scientific study. Therefore, it is important to take notice of them: who knows if one of these sentences is hiding your way to fame.

Language Editing Services by Elsevier Author Services:

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Answered By: Jeremy McGinniss Last Updated: Nov 21, 2022     Views: 348

A research gap, or gap in research, is an area in the scholarship of a particular field or discipline that has not been comprehensively studied or analyzed. Locating these gaps in scholarship is time-intensive and challenging as the ability to identify a gap in research emerges from a comprehensive knowledge of the field. To determine if a research gap exists, it is necessary to examine the current literature related to the particular research area.  This process, usually referenced as a literature review, includes gathering a significant number of resources that are representative of the research area. The literature review process is undertaken with the goal of seeing what gaps might exist in the current scholarly literature.  For assistance in beginning the literature review process, please contact one of your school’s subject librarians to set up a research consultation.

If you have any additional questions, feel free to reach out to us at (434) 582-2220 or at [email protected] .

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Research Variables 101

Independent variables, dependent variables, control variables and more

By: Derek Jansen (MBA) | Expert Reviewed By: Kerryn Warren (PhD) | January 2023

If you’re new to the world of research, especially scientific research, you’re bound to run into the concept of variables , sooner or later. If you’re feeling a little confused, don’t worry – you’re not the only one! Independent variables, dependent variables, confounding variables – it’s a lot of jargon. In this post, we’ll unpack the terminology surrounding research variables using straightforward language and loads of examples .

Overview: Variables In Research

What (exactly) is a variable?

The simplest way to understand a variable is as any characteristic or attribute that can experience change or vary over time or context – hence the name “variable”. For example, the dosage of a particular medicine could be classified as a variable, as the amount can vary (i.e., a higher dose or a lower dose). Similarly, gender, age or ethnicity could be considered demographic variables, because each person varies in these respects.

Within research, especially scientific research, variables form the foundation of studies, as researchers are often interested in how one variable impacts another, and the relationships between different variables. For example:

• How someone’s age impacts their sleep quality
• How different teaching methods impact learning outcomes
• How diet impacts weight (gain or loss)

As you can see, variables are often used to explain relationships between different elements and phenomena. In scientific studies, especially experimental studies, the objective is often to understand the causal relationships between variables. In other words, the role of cause and effect between variables. This is achieved by manipulating certain variables while controlling others – and then observing the outcome. But, we’ll get into that a little later…

The “Big 3” Variables

Variables can be a little intimidating for new researchers because there are a wide variety of variables, and oftentimes, there are multiple labels for the same thing. To lay a firm foundation, we’ll first look at the three main types of variables, namely:

• Independent variables (IV)
• Dependant variables (DV)
• Control variables

What is an independent variable?

Simply put, the independent variable is the “ cause ” in the relationship between two (or more) variables. In other words, when the independent variable changes, it has an impact on another variable.

For example:

• Increasing the dosage of a medication (Variable A) could result in better (or worse) health outcomes for a patient (Variable B)
• Changing a teaching method (Variable A) could impact the test scores that students earn in a standardised test (Variable B)
• Varying one’s diet (Variable A) could result in weight loss or gain (Variable B).

It’s useful to know that independent variables can go by a few different names, including, explanatory variables (because they explain an event or outcome) and predictor variables (because they predict the value of another variable). Terminology aside though, the most important takeaway is that independent variables are assumed to be the “cause” in any cause-effect relationship. As you can imagine, these types of variables are of major interest to researchers, as many studies seek to understand the causal factors behind a phenomenon.

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What is a dependent variable?

While the independent variable is the “ cause ”, the dependent variable is the “ effect ” – or rather, the affected variable . In other words, the dependent variable is the variable that is assumed to change as a result of a change in the independent variable.

Keeping with the previous example, let’s look at some dependent variables in action:

• Health outcomes (DV) could be impacted by dosage changes of a medication (IV)
• Students’ scores (DV) could be impacted by teaching methods (IV)
• Weight gain or loss (DV) could be impacted by diet (IV)

In scientific studies, researchers will typically pay very close attention to the dependent variable (or variables), carefully measuring any changes in response to hypothesised independent variables. This can be tricky in practice, as it’s not always easy to reliably measure specific phenomena or outcomes – or to be certain that the actual cause of the change is in fact the independent variable.

As the adage goes, correlation is not causation . In other words, just because two variables have a relationship doesn’t mean that it’s a causal relationship – they may just happen to vary together. For example, you could find a correlation between the number of people who own a certain brand of car and the number of people who have a certain type of job. Just because the number of people who own that brand of car and the number of people who have that type of job is correlated, it doesn’t mean that owning that brand of car causes someone to have that type of job or vice versa. The correlation could, for example, be caused by another factor such as income level or age group, which would affect both car ownership and job type.

To confidently establish a causal relationship between an independent variable and a dependent variable (i.e., X causes Y), you’ll typically need an experimental design , where you have complete control over the environmen t and the variables of interest. But even so, this doesn’t always translate into the “real world”. Simply put, what happens in the lab sometimes stays in the lab!

As an alternative to pure experimental research, correlational or “ quasi-experimental ” research (where the researcher cannot manipulate or change variables) can be done on a much larger scale more easily, allowing one to understand specific relationships in the real world. These types of studies also assume some causality between independent and dependent variables, but it’s not always clear. So, if you go this route, you need to be cautious in terms of how you describe the impact and causality between variables and be sure to acknowledge any limitations in your own research.

What is a control variable?

In an experimental design, a control variable (or controlled variable) is a variable that is intentionally held constant to ensure it doesn’t have an influence on any other variables. As a result, this variable remains unchanged throughout the course of the study. In other words, it’s a variable that’s not allowed to vary – tough life 🙂

As we mentioned earlier, one of the major challenges in identifying and measuring causal relationships is that it’s difficult to isolate the impact of variables other than the independent variable. Simply put, there’s always a risk that there are factors beyond the ones you’re specifically looking at that might be impacting the results of your study. So, to minimise the risk of this, researchers will attempt (as best possible) to hold other variables constant . These factors are then considered control variables.

Some examples of variables that you may need to control include:

• Temperature
• Time of day
• Noise or distractions

Which specific variables need to be controlled for will vary tremendously depending on the research project at hand, so there’s no generic list of control variables to consult. As a researcher, you’ll need to think carefully about all the factors that could vary within your research context and then consider how you’ll go about controlling them. A good starting point is to look at previous studies similar to yours and pay close attention to which variables they controlled for.

Of course, you won’t always be able to control every possible variable, and so, in many cases, you’ll just have to acknowledge their potential impact and account for them in the conclusions you draw. Every study has its limitations , so don’t get fixated or discouraged by troublesome variables. Nevertheless, always think carefully about the factors beyond what you’re focusing on – don’t make assumptions!

Other types of variables

As we mentioned, independent, dependent and control variables are the most common variables you’ll come across in your research, but they’re certainly not the only ones you need to be aware of. Next, we’ll look at a few “secondary” variables that you need to keep in mind as you design your research.

• Moderating variables
• Mediating variables
• Confounding variables
• Latent variables

Let’s jump into it…

What is a moderating variable?

A moderating variable is a variable that influences the strength or direction of the relationship between an independent variable and a dependent variable. In other words, moderating variables affect how much (or how little) the IV affects the DV, or whether the IV has a positive or negative relationship with the DV (i.e., moves in the same or opposite direction).

For example, in a study about the effects of sleep deprivation on academic performance, gender could be used as a moderating variable to see if there are any differences in how men and women respond to a lack of sleep. In such a case, one may find that gender has an influence on how much students’ scores suffer when they’re deprived of sleep.

It’s important to note that while moderators can have an influence on outcomes , they don’t necessarily cause them ; rather they modify or “moderate” existing relationships between other variables. This means that it’s possible for two different groups with similar characteristics, but different levels of moderation, to experience very different results from the same experiment or study design.

What is a mediating variable?

Mediating variables are often used to explain the relationship between the independent and dependent variable (s). For example, if you were researching the effects of age on job satisfaction, then education level could be considered a mediating variable, as it may explain why older people have higher job satisfaction than younger people – they may have more experience or better qualifications, which lead to greater job satisfaction.

Mediating variables also help researchers understand how different factors interact with each other to influence outcomes. For instance, if you wanted to study the effect of stress on academic performance, then coping strategies might act as a mediating factor by influencing both stress levels and academic performance simultaneously. For example, students who use effective coping strategies might be less stressed but also perform better academically due to their improved mental state.

In addition, mediating variables can provide insight into causal relationships between two variables by helping researchers determine whether changes in one factor directly cause changes in another – or whether there is an indirect relationship between them mediated by some third factor(s). For instance, if you wanted to investigate the impact of parental involvement on student achievement, you would need to consider family dynamics as a potential mediator, since it could influence both parental involvement and student achievement simultaneously.

What is a confounding variable?

A confounding variable (also known as a third variable or lurking variable ) is an extraneous factor that can influence the relationship between two variables being studied. Specifically, for a variable to be considered a confounding variable, it needs to meet two criteria:

• It must be correlated with the independent variable (this can be causal or not)
• It must have a causal impact on the dependent variable (i.e., influence the DV)

Some common examples of confounding variables include demographic factors such as gender, ethnicity, socioeconomic status, age, education level, and health status. In addition to these, there are also environmental factors to consider. For example, air pollution could confound the impact of the variables of interest in a study investigating health outcomes.

Naturally, it’s important to identify as many confounding variables as possible when conducting your research, as they can heavily distort the results and lead you to draw incorrect conclusions . So, always think carefully about what factors may have a confounding effect on your variables of interest and try to manage these as best you can.

What is a latent variable?

Latent variables are unobservable factors that can influence the behaviour of individuals and explain certain outcomes within a study. They’re also known as hidden or underlying variables , and what makes them rather tricky is that they can’t be directly observed or measured . Instead, latent variables must be inferred from other observable data points such as responses to surveys or experiments.

For example, in a study of mental health, the variable “resilience” could be considered a latent variable. It can’t be directly measured , but it can be inferred from measures of mental health symptoms, stress, and coping mechanisms. The same applies to a lot of concepts we encounter every day – for example:

• Emotional intelligence
• Quality of life
• Business confidence
• Ease of use

One way in which we overcome the challenge of measuring the immeasurable is latent variable models (LVMs). An LVM is a type of statistical model that describes a relationship between observed variables and one or more unobserved (latent) variables. These models allow researchers to uncover patterns in their data which may not have been visible before, thanks to their complexity and interrelatedness with other variables. Those patterns can then inform hypotheses about cause-and-effect relationships among those same variables which were previously unknown prior to running the LVM. Powerful stuff, we say!

Let’s recap

In the world of scientific research, there’s no shortage of variable types, some of which have multiple names and some of which overlap with each other. In this post, we’ve covered some of the popular ones, but remember that this is not an exhaustive list .

To recap, we’ve explored:

• Independent variables (the “cause”)
• Dependent variables (the “effect”)
• Control variables (the variable that’s not allowed to vary)

If you’re still feeling a bit lost and need a helping hand with your research project, check out our 1-on-1 coaching service , where we guide you through each step of the research journey. Also, be sure to check out our free dissertation writing course and our collection of free, fully-editable chapter templates .

Psst... there’s more!

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

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7 Types of Research Gaps in Literature Review | Examples

This article discusses the 7 types of research gaps with examples and the situation in which its application is required. In the end this article explains how you can write research gaps in your research thesis/ dissertation.

Research gaps should be organized and classified based on their usefulness.  As a result, researchers now have a fundamental framework for identifying them in the literature. Miles (2017) suggested a model which consists of seven research gaps.

Table of Contents

7 Types of Research Gaps

Evidence gap.

It arises when study data allow for conclusions in and of themselves, but are contradictory when considered from a more abstract perspective.

Knowledge Gap

The knowledge gap is a common gap in previous research. There are two conditions in which a knowledge void might exist.

✔ Knowledge Gap is known as Knowledge Void Gap

Practical-Knowledge Conflict Gap

Empirical gap.

The kind of gap that addresses gaps in previous research is an empirical gap.  This gap relates to study conclusions or claims that need to be assessed or experimentally confirmed.

Theoretical Gap

The type of gap known as a theoretical gap is one that deals with the gaps between theory and earlier research.

✔ Theoretical Gap is known as Theory Application Void Gap

Methodological Gap

✔ Methodological Gap is known as Methodology Void Gap.

Population Gap

Research gap types.

Learn how to Identify Research Gap : Find Research Gap from Research Articles

Steps to Write Research Gaps in your Research

1-discuss some of the previous research.

There have been various aspects of _______ that have been studied in the past, including (1) ( cite two to three articles ), (2) (cite two to three articles), and (3) (cite two to three articles).

2-Identify Important Gaps

In the perspective of ___________ , several of these unexplored________ seem significant and worthy of investigation. An investigation of these issues is important because ___________ . Additionally, the main subject of earlier empirical research has been ___________. On ___ ________ , very little research has been conducted.

3- Write Concluding Statement

Second, a population gap is evident after reviewing earlier research. A gap exists with _______ . In the earlier studies, this population group has received insufficient attention. Additionally, ____ ___ includes a number of unexplored dimensions that recently have drawn research interest from different fields. (cite two to three relevant articles).

Other articles

Please read through some of our other articles with examples and explanations if you’d like to learn more about research methodology.

Related Posts

Research paper outline template: examples of structured research paper outlines, alternative hypothesis: types and examples, causal research: examples, benefits, and practical tips, 7 types of observational studies | examples, writing an introduction for a research paper: a guide (with examples), clinical research design: elements and importance, dependent variable in research: examples, what is an independent variable, how to write a conclusion for research paper | examples, six useful tips for finding research gap.

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

Home » Education » What is the Difference Between Research Gap and Research Problem

What is the Difference Between Research Gap and Research Problem

The main difference between research gap and research problem is that a research gap identifies a gap in knowledge about a subject, whereas a research problem identifies and articulates the need for research .

Research gap and research problem are two very similar elements of a research study. They are closely related and play a crucial role in research. In fact, a researcher cannot identify a research problem without a research gap, and it’s impossible to conduct a research study without both. A researcher first identifies a research gap (an area that has not been explored in previous literature on the subject) after conducting a thorough literature review . Then he/she formulates a clear research problem from this research gap.

Key Areas Covered

1.  What is a Research Gap       – Definition, Features, Function 2. What is a Research Problem      – Definition, Features, Function 3.  Difference Between Research Gap and Research Problem      – Comparison of Key Differences

Research Gap, Research Problem

What is a Research Gap

A research gap is a key element in any research study. It’s the center of a research project and determines the area that lacks crucial information. We can define a research gap as a question that has not been addressed or an area of interest that has not been explored in previous literature on the subject. For example, a researcher in the field of health or medicine can research the long-term effects of Covid-19 vaccines, which is a research gap in the existing literature on the subject. To identify the research gap, the researcher has to gather and study all relevant books, reports, and journal articles on the subject. Researchers can usually decide on their research gap once they have conducted their literature review.

A research gap can exist when there are no studies on a new concept or idea. Sometimes, researchers can also find a research gap if the existing research is not up to date and needs modification or updates. For example, research on internet use in 2002 is no longer valid today, and the data needs modification. A researcher can also choose a specific population that has not been studied well.

What is a Research Problem

A research problem is a question(s) the researcher wants to answer through his study. Research problems introduce the readers to the topic that is being discussed. It also places the problem in a particular context, defining the parameters of the investigation. Finally, it provides the framework for reporting the results of the research, reveals what is necessary to conduct the research, and explains how the information will be presented.

A research problem must cover the essential issues at hand and be specific. Moreover, the researcher must present it logically and clearly. The research problem must also ensure that the research is based on actual facts and evidence and not on beliefs and opinions.

There are four general types of research problems:

• Casuist Research Problem – involves the determination of right and wrong in questions of conduct or conscience
• Difference Research Problem – compares and contrasts two or more phenomena
• Descriptive Research Problem – describes the significance of a state, situation, phenomenon
• Relational Research Problem – indicates a relationship between two or more variables

Without a well-defined research problem, a researcher will be more likely to end up with an unfocused and unmanageable research study.

Difference Between Research Gap and Research Problem

A research gap is an area of interest that has not been explored in previous literature on the subject, while a research problem is a definite or clear statement about an area of concern that points to a need for meaningful understanding and deliberate investigation.

First, the researcher has to identify a research gap in the area of interest and then form his/her research problem.

A research gap identifies a gap in knowledge about a subject, whereas a research problem identifies and articulates the need for research.

A researcher identifies a research gap after conducting a thorough literature review. Then he/she formulates a clear research problem from this research gap. Therefore, the difference between research gap and research problem is the order of sequence. A research gap further justifies the research problem.

1. “ FAQ: What is a research gap and how do I find one? ” Shapiro Library. Southern New Hampshire University. 2. McCombes, Shona. “ How to Define a Research Problem | Ideas & Examples ” Scribber.

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What is the key difference between the term "Research Gaps" and the terms "Literature Survey" or "Literature Review"?

The difference between the terms "Literature Survey" and "Literature Review" is covered in this question and answers . But how do they differ from "Research Gaps" in the context of a research proposal?

• literature-review

The difference between "Literature review" and "Literature survey" is small, if it exists at all - people may use the two terms to mean the same thing. It has been discussed in this question .

A "research gap" is an area of research that has not yet been done. You may identify a research gap by doing a literature review or survey.

• Thank you very much for the clarification. –  HNavanjani Commented Jan 31, 2020 at 13:19

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The Racial Wealth Gap is Persistent – and Growing

The racial wealth gap continues to deepen in large part due to the cumulative impact of the country’s racial history.

Research & Commentary

June 27, 2024.

by Amber Holland

The data is clear – the racial wealth gap in the United States is persistent and growing. Why, sixty years after the formal end of Jim Crow, is the gap between Black and white families still widening? And what can we do to narrow it? 

Researchers from the Samuel DuBois Cook Center on Social Equity at Duke University  set out to address these questions and debunk common myths in their new study “Setting the Record Straight on Racial Wealth Inequality,” available here .  

The wealth gap between Black and white households has not improved in over 50 years; in fact, it has slightly widened. Between 2019 and 2022, according to Federal  Reserve data, the real disparity in the racial wealth gap in the U.S. grew by about 23 percent at the median and 16 percent at the mean. 

Why is the gap between the wealth of Black households and their white counterparts not only persisting but deepening? 

DIVE DEEPER

The facts on the racial wealth gap

One mainstream view, held by many prominent economists, chalks it down to a gap in human capital. More education leads to higher earnings, which allows for more saving and, eventually, more wealth. Black households, the logic holds, have less wealth because their lower levels of human capital generate lower earnings and less savings.

To eliminate the racial wealth gap, this view argues, one must first eliminate the earnings gap. 

The authors of this new study – Fenaba R. Addo, William A. Darity, Jr., and Samuel L. Myers, Jr. – poke several flaws in that logic, including that:

• Black households with a college degree hold less wealth than white households headed by someone with a high school diploma or GED.
• Black households headed by someone in a managerial or professional position consistently have significantly less than White households in the same occupations; in fact, Black households in a managerial or professional position make even less than white households headed by someone with working-class employment.
• Ultimately, Black households in the middle-income range have less than one-third the wealth of white households in the same range. 

“When it comes to wealth inequality, a rising tide lifted all boats … inequitably,” said Addo, the report’s lead author and an associate professor of public policy at the University of North Carolina-Chapel Hill. “Black-white wealth inequality persists, and it has expanded with the onset of the pandemic.”

The mainstream view focused on earnings overlooks the crucial impact of inherited wealth, which the authors refer to as the “intergenerational transmission chain.” Black households are far less likely to receive familial inheritances or in vivo transfers, gifts made while the donor is still living like vehicles, access to education or homes. Just the anticipation of a gift or inheritance allows white families to make riskier investments, providing assurance for their decisions and thus deepening the divide. 

BREAK THE CHAIN

End estate tax manipulations

Policy solutions should focus on directly addressing racial wealth disparities rather than simply trying to close the earnings gap. 

Federal tax laws have allowed affluent families to transfer wealth to future generations inexpensively. Given that these policies mainly favored white families, reforming inheritance rules could help reduce the racial wealth gap.

How can the U.S. implement reforms that eliminate the racial wealth gap without driving white wealth down? 

Another solution the authors recommend is reparations for Black Americans whose ancestors were enslaved in the United States. The most comprehensive plan for this does not involve confiscation of white assets.

The key to closing the wealth gap begins with acknowledging its origins – America’s unfair racial history and the unequal passing down of resources between white and Black American families across generations.

Amber Holland, PhD, is a Senior Research Associate and Communications Strategist with the Samuel DuBois Cook Center on Social Equity at Duke University.

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A practical guide to variable-density thinning for supporting forest biodiversity

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New guide supports managers implementing the “skips and gaps” approach

Past forest management strategies often relied on clear-cut timber harvests that were replanted with single tree species. Millions of acres of these single-species plantations have aged over time into forests that have simpler structure and plant species compositions than the original, pre-harvest forests or areas that regenerated naturally after harvest. There is increasing interest from forest and land managers to encourage more variability in forest structure in even-aged stands to support more plant and animal species. Variable-density thinning (VDT) is a management strategy that can accomplish this goal, but there is little practical information to guide managers on implementing VDT approaches.

The "skips and gaps" approach increases structural variability in forests

Forester Leslie Brodie and emeritus scientist Connie Harrington with the Pacific Northwest Research Station developed a guide that aids land managers using the “skips and gaps” approach to VDT. This approach increases structural complexity in tree stands over time by creating skips (untreated areas) and gaps (small patch cuts). It is relatively easy to implement using standard marking and thinning practices and has the advantage of maintaining any existing structural complexity in a tree stand. The guide also contains practical examples for managers of VDT treatments used in Washington State Parks and on study sites in the Olympic National Forest. 

• Leslie C. Brodie, Constance A. Harrington. 2020. Guide to variable-density thinning using skips and gaps

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Microsoft unveils new research and technology to bridge the disconnect between leaders and employees so companies can thrive amid economic uncertainty

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Microsoft expands Microsoft Viva platform to connect employees to company culture, business goals and one another

REDMOND, Wash. — Sept. 22, 2022 — On Thursday, Microsoft Corp. released a Work Trend Index Pulse report, “Hybrid Work Is Just Work. Are We Doing It Wrong?” The company also announced new capabilities in Microsoft Viva, its employee experience platform, designed to help empower and energize employees in a time of economic uncertainty.

The data makes clear that hybrid work has created a growing disconnect between employees and leaders. They’re at odds about what constitutes productivity, how to maintain autonomy while ensuring accountability, the benefits of flexibility and the role of the office. To bridge this gap, a new approach is needed that recognizes work is no longer just a place but an experience that needs to transcend time and space so employees can stay engaged and connected no matter where they are working.

“Thriving employees are what will give organizations a competitive advantage in today’s dynamic economic environment,” said Satya Nadella, chairman and CEO, Microsoft. “Today, we’re announcing new innovations across our employee experience platform Microsoft Viva to help leaders end productivity paranoia, rebuild social capital, and re-recruit and re-energize their employees.”

To help leaders navigate the new realities of work, the Work Trend Index Pulse report [1] points to three urgent pivots every leader should make:

• End productivity paranoia: 87% of employees report they are productive at work, but 85% of leaders say the shift to hybrid work has made it challenging to have confidence their employees are being productive. Leaders need to create clarity and alignment around company goals, eliminate busywork that doesn’t support those goals and listen to their people — 57% of companies are rarely, if ever, collecting employee feedback.
• Embrace that people come in for each other: 73% of employees say they need a better reason to go into the office besides company expectations — but they would be motivated to go in if they could socialize with co-workers (84%) or rebuild team bonds (85%). Digital communication will be crucial to keep people connected inside and out the office — both employees and leaders rank communication as the No. 1 most critical skill needed to be successful in their roles this year.
• Re-skill to re-recruit your employees: 55% of employees say the best way to develop their skills is to change companies. However, they also say they would stay longer at their company if it was easier to change jobs internally (68%) or if they could benefit more from learning and development support (76%).

To address these challenges, Microsoft is expanding its employee experience platform Microsoft Viva to help companies deliver an employee experience optimized for the way people now work. Today, Microsoft is announcing several new and enhanced capabilities coming to Viva:

• Viva Pulse is a new app that will enable managers and team leads to seek regular and confidential feedback on their team’s experience. Viva Pulse uses smart templates and research-backed questions to help managers pinpoint what’s working well and where to focus, and also provides suggested learning and actions to address team needs.
• Viva Amplify is a new app that will empower leaders and communicators to elevate their message and reach employees where they are with consistency and impact. The app centralizes communications campaigns, offers writing guidance to improve message resonance, enables publishing across multiple channels and distribution groups in Microsoft 365, and provides metrics for improvement.
• Answers in Viva is a new capability that will use AI to match employee questions to answers and experts across the organization to help put collective knowledge to work for all employees.
• People in Viva is a new capability that will use AI to create rich profile cards with details on an employee’s interests, knowledge and team goals to help colleagues easily discover connections, experts and insights across the organization. These insights will be available through Microsoft 365 profile cards and as a new app.
• Microsoft recently launched Viva Engage, which fosters digital community building through conversations and self-expression tools with stories and storylines. Leadership Corner is coming to Viva Engage as a space to invite employees to interact directly with leadership, share ideas and perspectives, participate in organization initiatives, and more.
• Viva Goals helps organizations align employee work to business outcomes. New integrations in Viva Goals will bring goals into the flow of work including a richer integration with Microsoft Teams to check in on OKRs, an extension in Azure DevOps to complete work items, a connection to Power BI datasets to track KPIs and Key Results, and integrations with Microsoft Planner and Microsoft Project for automatic project management updates.
• Enhanced integrations between Viva Learning and LinkedIn Learning will make it even easier for people to access content from LinkedIn Learning Hub right in the flow of work in Teams. Learners will see all their LinkedIn Learning Hub content synced, including custom content, curated learning paths and the courses they have already completed, all reflected directly within Viva. And administrators will be able to set the integration up directly within their settings on LinkedIn Learning Hub — no APIs needed.
• Viva Sales, the first role-based experience app in the platform, will be generally available Oct. 3. Viva Sales brings together a seller’s CRM with Microsoft 365 and Teams to provide a more streamlined and AI-powered selling experience — right in the tools they’re using every day to connect with customers and close deals. Microsoft is announcing a partnership with Seismic to personalize and scale customer engagements through AI-generated content recommendations.
• To streamline access to Viva and help employees start their day on track, a new home experience in Viva Connections will bring all the Viva apps together in one place, and updates to the Viva briefing email will provide more personalized productivity recommendations to help employees catch up on work, meetings and learning.

The new Viva capabilities will begin rolling out to customers in early 2023.

To learn more, visit the Official Microsoft Blog , Microsoft 365 Blog and the new Work Trend Index Pulse report .

Microsoft (Nasdaq “MSFT” @microsoft) enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more.

[1] The Work Trend Index Pulse report is based on an external study of 20,000 people in 11 countries, along with analysis of trillions of Microsoft 365 productivity signals, LinkedIn labor trends and Glint People Science insights.

For more information, press only:

Microsoft Media Relations, WE Communications, (425) 638-7777,  [email protected]

Note to editors: For more information, news and perspectives from Microsoft, please visit the Microsoft News Center at  http://news.microsoft.com . Web links, telephone numbers and titles were correct at time of publication but may have changed. For additional assistance, journalists and analysts may contact Microsoft’s Rapid Response Team or other appropriate contacts listed at  https://news.microsoft.com/microsoft-public-relations-contacts .

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One Cohort at a Time: A New Perspective on the Declining Gender Pay Gap

This paper studies the interaction between the decrease in the gender pay gap and the stagnation in the careers of younger workers, analyzing data from the United States, Italy, Canada, and the United Kingdom. We propose a model of the labor market in which a larger supply of older workers can crowd out younger workers from top-paying positions. These negative career spillovers disproportionately affect the career trajectories of younger men because they are more likely than younger women to hold higher-paying jobs at baseline. The data strongly support this cohort-driven interpretation of the shrinking gender pay gap. The whole decline in the gap originates from (i) newer worker cohorts who enter the labor market with smaller-than-average gender pay gaps and (ii) older worker cohorts who exit with higher-than-average gender pay gaps. As predicted by the model, the gender pay convergence at labor-market entry stems from younger men's larger positional losses in the wage distribution. Younger men experience the largest positional losses within higher-paying firms, in which they become less represented over time at a faster rate than younger women. Finally, we document that labor-market exit is the sole contributor to the decline in the gender pay gap after the mid-1990s, which implies no full gender pay convergence for the foreseeable future. Consistent with our framework, we find evidence that most of the remaining gender pay gap at entry depends on predetermined educational choices.

We thank Patricia Cortés, Gordon Dahl, Fabian Lange, Claudia Olivetti, Michael Powell, Uta Schönberg, as well as participants at various seminars and conferences for helpful comments. We thank Sergey Abramenko, Thomas Barden, Carolina Bussotti, Sean Chen, and Chengmou Lei for outstanding research assistance. The realization of this article was possible thanks to the sponsorship of the “VisitINPS Scholars” program. The views expressed in this paper are those of the authors only and should not be attributed to the Bank of Italy, the Eurosystem, or the National Bureau of Economic Research.

MARC RIS BibTeΧ

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