relevance of the study in research

How To Write Significance of the Study (With Examples) 

Whether you’re writing a research paper or thesis, a portion called Significance of the Study ensures your readers understand the impact of your work. Learn how to effectively write this vital part of your research paper or thesis through our detailed steps, guidelines, and examples.

Related: How to Write a Concept Paper for Academic Research

Table of Contents

What is the significance of the study.

The Significance of the Study presents the importance of your research. It allows you to prove the study’s impact on your field of research, the new knowledge it contributes, and the people who will benefit from it.

Related: How To Write Scope and Delimitation of a Research Paper (With Examples)

Where Should I Put the Significance of the Study?

The Significance of the Study is part of the first chapter or the Introduction. It comes after the research’s rationale, problem statement, and hypothesis.

Related: How to Make Conceptual Framework (with Examples and Templates)

Why Should I Include the Significance of the Study?

The purpose of the Significance of the Study is to give you space to explain to your readers how exactly your research will be contributing to the literature of the field you are studying 1 . It’s where you explain why your research is worth conducting and its significance to the community, the people, and various institutions.

How To Write Significance of the Study: 5 Steps

Below are the steps and guidelines for writing your research’s Significance of the Study.

1. Use Your Research Problem as a Starting Point

Your problem statement can provide clues to your research study’s outcome and who will benefit from it 2 .

Ask yourself, “How will the answers to my research problem be beneficial?”. In this manner, you will know how valuable it is to conduct your study. 

Let’s say your research problem is “What is the level of effectiveness of the lemongrass (Cymbopogon citratus) in lowering the blood glucose level of Swiss mice (Mus musculus)?”

Discovering a positive correlation between the use of lemongrass and lower blood glucose level may lead to the following results:

• Increased public understanding of the plant’s medical properties;
• Higher appreciation of the importance of lemongrass  by the community;
• Adoption of lemongrass tea as a cheap, readily available, and natural remedy to lower their blood glucose level.

Once you’ve zeroed in on the general benefits of your study, it’s time to break it down into specific beneficiaries.

2. State How Your Research Will Contribute to the Existing Literature in the Field

Think of the things that were not explored by previous studies. Then, write how your research tackles those unexplored areas. Through this, you can convince your readers that you are studying something new and adding value to the field.

3. Explain How Your Research Will Benefit Society

In this part, tell how your research will impact society. Think of how the results of your study will change something in your community. 

For example, in the study about using lemongrass tea to lower blood glucose levels, you may indicate that through your research, the community will realize the significance of lemongrass and other herbal plants. As a result, the community will be encouraged to promote the cultivation and use of medicinal plants.

4. Mention the Specific Persons or Institutions Who Will Benefit From Your Study

Using the same example above, you may indicate that this research’s results will benefit those seeking an alternative supplement to prevent high blood glucose levels.

5. Indicate How Your Study May Help Future Studies in the Field

You must also specifically indicate how your research will be part of the literature of your field and how it will benefit future researchers. In our example above, you may indicate that through the data and analysis your research will provide, future researchers may explore other capabilities of herbal plants in preventing different diseases.

Tips and Warnings

• Think ahead . By visualizing your study in its complete form, it will be easier for you to connect the dots and identify the beneficiaries of your research.
• Write concisely. Make it straightforward, clear, and easy to understand so that the readers will appreciate the benefits of your research. Avoid making it too long and wordy.
• Go from general to specific . Like an inverted pyramid, you start from above by discussing the general contribution of your study and become more specific as you go along. For instance, if your research is about the effect of remote learning setup on the mental health of college students of a specific university , you may start by discussing the benefits of the research to society, to the educational institution, to the learning facilitators, and finally, to the students.
• Seek help . For example, you may ask your research adviser for insights on how your research may contribute to the existing literature. If you ask the right questions, your research adviser can point you in the right direction.
• Revise, revise, revise. Be ready to apply necessary changes to your research on the fly. Unexpected things require adaptability, whether it’s the respondents or variables involved in your study. There’s always room for improvement, so never assume your work is done until you have reached the finish line.

Significance of the Study Examples

This section presents examples of the Significance of the Study using the steps and guidelines presented above.

Example 1: STEM-Related Research

Research Topic: Level of Effectiveness of the Lemongrass ( Cymbopogon citratus ) Tea in Lowering the Blood Glucose Level of Swiss Mice ( Mus musculus ).

Significance of the Study .

This research will provide new insights into the medicinal benefit of lemongrass ( Cymbopogon citratus ), specifically on its hypoglycemic ability.

Through this research, the community will further realize promoting medicinal plants, especially lemongrass, as a preventive measure against various diseases. People and medical institutions may also consider lemongrass tea as an alternative supplement against hyperglycemia. 

Moreover, the analysis presented in this study will convey valuable information for future research exploring the medicinal benefits of lemongrass and other medicinal plants.  

Example 2: Business and Management-Related Research

Research Topic: A Comparative Analysis of Traditional and Social Media Marketing of Small Clothing Enterprises.

Significance of the Study:

By comparing the two marketing strategies presented by this research, there will be an expansion on the current understanding of the firms on these marketing strategies in terms of cost, acceptability, and sustainability. This study presents these marketing strategies for small clothing enterprises, giving them insights into which method is more appropriate and valuable for them. 

Specifically, this research will benefit start-up clothing enterprises in deciding which marketing strategy they should employ. Long-time clothing enterprises may also consider the result of this research to review their current marketing strategy.

Furthermore, a detailed presentation on the comparison of the marketing strategies involved in this research may serve as a tool for further studies to innovate the current method employed in the clothing Industry.

Example 3: Social Science -Related Research.

Research Topic:  Divide Et Impera : An Overview of How the Divide-and-Conquer Strategy Prevailed on Philippine Political History.

Significance of the Study :

Through the comprehensive exploration of this study on Philippine political history, the influence of the Divide et Impera, or political decentralization, on the political discernment across the history of the Philippines will be unraveled, emphasized, and scrutinized. Moreover, this research will elucidate how this principle prevailed until the current political theatre of the Philippines.

In this regard, this study will give awareness to society on how this principle might affect the current political context. Moreover, through the analysis made by this study, political entities and institutions will have a new approach to how to deal with this principle by learning about its influence in the past.

In addition, the overview presented in this research will push for new paradigms, which will be helpful for future discussion of the Divide et Impera principle and may lead to a more in-depth analysis.

Example 4: Humanities-Related Research

Research Topic: Effectiveness of Meditation on Reducing the Anxiety Levels of College Students.

Significance of the Study: 

This research will provide new perspectives in approaching anxiety issues of college students through meditation. 

Specifically, this research will benefit the following:

 Community – this study spreads awareness on recognizing anxiety as a mental health concern and how meditation can be a valuable approach to alleviating it.

Academic Institutions and Administrators – through this research, educational institutions and administrators may promote programs and advocacies regarding meditation to help students deal with their anxiety issues.

Mental health advocates – the result of this research will provide valuable information for the advocates to further their campaign on spreading awareness on dealing with various mental health issues, including anxiety, and how to stop stigmatizing those with mental health disorders.

Parents – this research may convince parents to consider programs involving meditation that may help the students deal with their anxiety issues.

Students will benefit directly from this research as its findings may encourage them to consider meditation to lower anxiety levels.

Future researchers – this study covers information involving meditation as an approach to reducing anxiety levels. Thus, the result of this study can be used for future discussions on the capabilities of meditation in alleviating other mental health concerns.

Frequently Asked Questions

1. what is the difference between the significance of the study and the rationale of the study.

Both aim to justify the conduct of the research. However, the Significance of the Study focuses on the specific benefits of your research in the field, society, and various people and institutions. On the other hand, the Rationale of the Study gives context on why the researcher initiated the conduct of the study.

Let’s take the research about the Effectiveness of Meditation in Reducing Anxiety Levels of College Students as an example. Suppose you are writing about the Significance of the Study. In that case, you must explain how your research will help society, the academic institution, and students deal with anxiety issues through meditation. Meanwhile, for the Rationale of the Study, you may state that due to the prevalence of anxiety attacks among college students, you’ve decided to make it the focal point of your research work.

2. What is the difference between Justification and the Significance of the Study?

In Justification, you express the logical reasoning behind the conduct of the study. On the other hand, the Significance of the Study aims to present to your readers the specific benefits your research will contribute to the field you are studying, community, people, and institutions.

Suppose again that your research is about the Effectiveness of Meditation in Reducing the Anxiety Levels of College Students. Suppose you are writing the Significance of the Study. In that case, you may state that your research will provide new insights and evidence regarding meditation’s ability to reduce college students’ anxiety levels. Meanwhile, you may note in the Justification that studies are saying how people used meditation in dealing with their mental health concerns. You may also indicate how meditation is a feasible approach to managing anxiety using the analysis presented by previous literature.

3. How should I start my research’s Significance of the Study section?

– This research will contribute… – The findings of this research… – This study aims to… – This study will provide… – Through the analysis presented in this study… – This study will benefit…

Moreover, you may start the Significance of the Study by elaborating on the contribution of your research in the field you are studying.

4. What is the difference between the Purpose of the Study and the Significance of the Study?

The Purpose of the Study focuses on why your research was conducted, while the Significance of the Study tells how the results of your research will benefit anyone.

Suppose your research is about the Effectiveness of Lemongrass Tea in Lowering the Blood Glucose Level of Swiss Mice . You may include in your Significance of the Study that the research results will provide new information and analysis on the medical ability of lemongrass to solve hyperglycemia. Meanwhile, you may include in your Purpose of the Study that your research wants to provide a cheaper and natural way to lower blood glucose levels since commercial supplements are expensive.

5. What is the Significance of the Study in Tagalog?

In Filipino research, the Significance of the Study is referred to as Kahalagahan ng Pag-aaral.

• Draft your Significance of the Study. Retrieved 18 April 2021, from http://dissertationedd.usc.edu/draft-your-significance-of-the-study.html
• Regoniel, P. (2015). Two Tips on How to Write the Significance of the Study. Retrieved 18 April 2021, from https://simplyeducate.me/2015/02/09/significance-of-the-study/

Written by Jewel Kyle Fabula

in Career and Education , Juander How

Jewel Kyle Fabula

Jewel Kyle Fabula is a Bachelor of Science in Economics student at the University of the Philippines Diliman. His passion for learning mathematics developed as he competed in some mathematics competitions during his Junior High School years. He loves cats, playing video games, and listening to music.

Browse all articles written by Jewel Kyle Fabula

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The Savvy Scientist

Experiences of a London PhD student and beyond

What is the Significance of a Study? Examples and Guide

If you’re reading this post you’re probably wondering: what is the significance of a study?

No matter where you’re at with a piece of research, it is a good idea to think about the potential significance of your work. And sometimes you’ll have to explicitly write a statement of significance in your papers, it addition to it forming part of your thesis.

In this post I’ll cover what the significance of a study is, how to measure it, how to describe it with examples and add in some of my own experiences having now worked in research for over nine years.

If you’re reading this because you’re writing up your first paper, welcome! You may also like my how-to guide for all aspects of writing your first research paper .

Looking for guidance on writing the statement of significance for a paper or thesis? Click here to skip straight to that section.

What is the Significance of a Study?

For research papers, theses or dissertations it’s common to explicitly write a section describing the significance of the study. We’ll come onto what to include in that section in just a moment.

However the significance of a study can actually refer to several different things.

Working our way from the most technical to the broadest, depending on the context, the significance of a study may refer to:

• Within your study: Statistical significance. Can we trust the findings?
• Wider research field: Research significance. How does your study progress the field?
• Commercial / economic significance: Could there be business opportunities for your findings?
• Societal significance: What impact could your study have on the wider society.
• And probably other domain-specific significance!

We’ll shortly cover each of them in turn, including how they’re measured and some examples for each type of study significance.

But first, let’s touch on why you should consider the significance of your research at an early stage.

Why Care About the Significance of a Study?

No matter what is motivating you to carry out your research, it is sensible to think about the potential significance of your work. In the broadest sense this asks, how does the study contribute to the world?

After all, for many people research is only worth doing if it will result in some expected significance. For the vast majority of us our studies won’t be significant enough to reach the evening news, but most studies will help to enhance knowledge in a particular field and when research has at least some significance it makes for a far more fulfilling longterm pursuit.

Furthermore, a lot of us are carrying out research funded by the public. It therefore makes sense to keep an eye on what benefits the work could bring to the wider community.

Often in research you’ll come to a crossroads where you must decide which path of research to pursue. Thinking about the potential benefits of a strand of research can be useful for deciding how to spend your time, money and resources.

It’s worth noting though, that not all research activities have to work towards obvious significance. This is especially true while you’re a PhD student, where you’re figuring out what you enjoy and may simply be looking for an opportunity to learn a new skill.

However, if you’re trying to decide between two potential projects, it can be useful to weigh up the potential significance of each.

Let’s now dive into the different types of significance, starting with research significance.

Research Significance

What is the research significance of a study.

Unless someone specifies which type of significance they’re referring to, it is fair to assume that they want to know about the research significance of your study.

Research significance describes how your work has contributed to the field, how it could inform future studies and progress research.

Where should I write about my study’s significance in my thesis?

Typically you should write about your study’s significance in the Introduction and Conclusions sections of your thesis.

It’s important to mention it in the Introduction so that the relevance of your work and the potential impact and benefits it could have on the field are immediately apparent. Explaining why your work matters will help to engage readers (and examiners!) early on.

It’s also a good idea to detail the study’s significance in your Conclusions section. This adds weight to your findings and helps explain what your study contributes to the field.

On occasion you may also choose to include a brief description in your Abstract.

What is expected when submitting an article to a journal

It is common for journals to request a statement of significance, although this can sometimes be called other things such as:

• Impact statement
• Significance statement
• Advances in knowledge section

Here is one such example of what is expected:

Impact Statement:  An Impact Statement is required for all submissions.  Your impact statement will be evaluated by the Editor-in-Chief, Global Editors, and appropriate Associate Editor. For your manuscript to receive full review, the editors must be convinced that it is an important advance in for the field. The Impact Statement is not a restating of the abstract. It should address the following: Why is the work submitted important to the field? How does the work submitted advance the field? What new information does this work impart to the field? How does this new information impact the field? Experimental Biology and Medicine journal, author guidelines

Typically the impact statement will be shorter than the Abstract, around 150 words.

Defining the study’s significance is helpful not just for the impact statement (if the journal asks for one) but also for building a more compelling argument throughout your submission. For instance, usually you’ll start the Discussion section of a paper by highlighting the research significance of your work. You’ll also include a short description in your Abstract too.

How to describe the research significance of a study, with examples

Whether you’re writing a thesis or a journal article, the approach to writing about the significance of a study are broadly the same.

I’d therefore suggest using the questions above as a starting point to base your statements on.

• Why is the work submitted important to the field?
• How does the work submitted advance the field?
• What new information does this work impart to the field?
• How does this new information impact the field?

Answer those questions and you’ll have a much clearer idea of the research significance of your work.

When describing it, try to clearly state what is novel about your study’s contribution to the literature. Then go on to discuss what impact it could have on progressing the field along with recommendations for future work.

Potential sentence starters

If you’re not sure where to start, why not set a 10 minute timer and have a go at trying to finish a few of the following sentences. Not sure on what to put? Have a chat to your supervisor or lab mates and they may be able to suggest some ideas.

• This study is important to the field because…
• These findings advance the field by…
• Our results highlight the importance of…
• Our discoveries impact the field by…

Now you’ve had a go let’s have a look at some real life examples.

Statement of significance examples

A statement of significance / impact:

Impact Statement This review highlights the historical development of the concept of “ideal protein” that began in the 1950s and 1980s for poultry and swine diets, respectively, and the major conceptual deficiencies of the long-standing concept of “ideal protein” in animal nutrition based on recent advances in amino acid (AA) metabolism and functions. Nutritionists should move beyond the “ideal protein” concept to consider optimum ratios and amounts of all proteinogenic AAs in animal foods and, in the case of carnivores, also taurine. This will help formulate effective low-protein diets for livestock, poultry, and fish, while sustaining global animal production. Because they are not only species of agricultural importance, but also useful models to study the biology and diseases of humans as well as companion (e.g. dogs and cats), zoo, and extinct animals in the world, our work applies to a more general readership than the nutritionists and producers of farm animals. Wu G, Li P. The “ideal protein” concept is not ideal in animal nutrition.  Experimental Biology and Medicine . 2022;247(13):1191-1201. doi: 10.1177/15353702221082658

And the same type of section but this time called “Advances in knowledge”:

Advances in knowledge: According to the MY-RADs criteria, size measurements of focal lesions in MRI are now of relevance for response assessment in patients with monoclonal plasma cell disorders. Size changes of 1 or 2 mm are frequently observed due to uncertainty of the measurement only, while the actual focal lesion has not undergone any biological change. Size changes of at least 6 mm or more in  T 1  weighted or  T 2  weighted short tau inversion recovery sequences occur in only 5% or less of cases when the focal lesion has not undergone any biological change. Wennmann M, Grözinger M, Weru V, et al. Test-retest, inter- and intra-rater reproducibility of size measurements of focal bone marrow lesions in MRI in patients with multiple myeloma [published online ahead of print, 2023 Apr 12].  Br J Radiol . 2023;20220745. doi: 10.1259/bjr.20220745

Other examples of research significance

Moving beyond the formal statement of significance, here is how you can describe research significance more broadly within your paper.

Describing research impact in an Abstract of a paper:

Three-dimensional visualisation and quantification of the chondrocyte population within articular cartilage can be achieved across a field of view of several millimetres using laboratory-based micro-CT. The ability to map chondrocytes in 3D opens possibilities for research in fields from skeletal development through to medical device design and treatment of cartilage degeneration. Conclusions section of the abstract in my first paper .

In the Discussion section of a paper:

We report for the utility of a standard laboratory micro-CT scanner to visualise and quantify features of the chondrocyte population within intact articular cartilage in 3D. This study represents a complimentary addition to the growing body of evidence supporting the non-destructive imaging of the constituents of articular cartilage. This offers researchers the opportunity to image chondrocyte distributions in 3D without specialised synchrotron equipment, enabling investigations such as chondrocyte morphology across grades of cartilage damage, 3D strain mapping techniques such as digital volume correlation to evaluate mechanical properties  in situ , and models for 3D finite element analysis  in silico  simulations. This enables an objective quantification of chondrocyte distribution and morphology in three dimensions allowing greater insight for investigations into studies of cartilage development, degeneration and repair. One such application of our method, is as a means to provide a 3D pattern in the cartilage which, when combined with digital volume correlation, could determine 3D strain gradient measurements enabling potential treatment and repair of cartilage degeneration. Moreover, the method proposed here will allow evaluation of cartilage implanted with tissue engineered scaffolds designed to promote chondral repair, providing valuable insight into the induced regenerative process. The Discussion section of the paper is laced with references to research significance.

How is longer term research significance measured?

Looking beyond writing impact statements within papers, sometimes you’ll want to quantify the long term research significance of your work. For instance when applying for jobs.

The most obvious measure of a study’s long term research significance is the number of citations it receives from future publications. The thinking is that a study which receives more citations will have had more research impact, and therefore significance , than a study which received less citations. Citations can give a broad indication of how useful the work is to other researchers but citations aren’t really a good measure of significance.

Bear in mind that us researchers can be lazy folks and sometimes are simply looking to cite the first paper which backs up one of our claims. You can find studies which receive a lot of citations simply for packaging up the obvious in a form which can be easily found and referenced, for instance by having a catchy or optimised title.

Likewise, research activity varies wildly between fields. Therefore a certain study may have had a big impact on a particular field but receive a modest number of citations, simply because not many other researchers are working in the field.

Nevertheless, citations are a standard measure of significance and for better or worse it remains impressive for someone to be the first author of a publication receiving lots of citations.

Other measures for the research significance of a study include:

• Accolades: best paper awards at conferences, thesis awards, “most downloaded” titles for articles, press coverage.
• How much follow-on research the study creates. For instance, part of my PhD involved a novel material initially developed by another PhD student in the lab. That PhD student’s research had unlocked lots of potential new studies and now lots of people in the group were using the same material and developing it for different applications. The initial study may not receive a high number of citations yet long term it generated a lot of research activity.

That covers research significance, but you’ll often want to consider other types of significance for your study and we’ll cover those next.

Statistical Significance

What is the statistical significance of a study.

Often as part of a study you’ll carry out statistical tests and then state the statistical significance of your findings: think p-values eg <0.05. It is useful to describe the outcome of these tests within your report or paper, to give a measure of statistical significance.

Effectively you are trying to show whether the performance of your innovation is actually better than a control or baseline and not just chance. Statistical significance deserves a whole other post so I won’t go into a huge amount of depth here.

Things that make publication in  The BMJ  impossible or unlikely Internal validity/robustness of the study • It had insufficient statistical power, making interpretation difficult; • Lack of statistical power; The British Medical Journal’s guide for authors

Calculating statistical significance isn’t always necessary (or valid) for a study, such as if you have a very small number of samples, but it is a very common requirement for scientific articles.

Writing a journal article? Check the journal’s guide for authors to see what they expect. Generally if you have approximately five or more samples or replicates it makes sense to start thinking about statistical tests. Speak to your supervisor and lab mates for advice, and look at other published articles in your field.

How is statistical significance measured?

Statistical significance is quantified using p-values . Depending on your study design you’ll choose different statistical tests to compute the p-value.

A p-value of 0.05 is a common threshold value. The 0.05 means that there is a 1/20 chance that the difference in performance you’re reporting is just down to random chance.

• p-values above 0.05 mean that the result isn’t statistically significant enough to be trusted: it is too likely that the effect you’re showing is just luck.
• p-values less than or equal to 0.05 mean that the result is statistically significant. In other words: unlikely to just be chance, which is usually considered a good outcome.

Low p-values (eg p = 0.001) mean that it is highly unlikely to be random chance (1/1000 in the case of p = 0.001), therefore more statistically significant.

It is important to clarify that, although low p-values mean that your findings are statistically significant, it doesn’t automatically mean that the result is scientifically important. More on that in the next section on research significance.

How to describe the statistical significance of your study, with examples

In the first paper from my PhD I ran some statistical tests to see if different staining techniques (basically dyes) increased how well you could see cells in cow tissue using micro-CT scanning (a 3D imaging technique).

In your methods section you should mention the statistical tests you conducted and then in the results you will have statements such as:

Between mediums for the two scan protocols C/N [contrast to noise ratio] was greater for EtOH than the PBS in both scanning methods (both  p  < 0.0001) with mean differences of 1.243 (95% CI [confidence interval] 0.709 to 1.778) for absorption contrast and 6.231 (95% CI 5.772 to 6.690) for propagation contrast. … Two repeat propagation scans were taken of samples from the PTA-stained groups. No difference in mean C/N was found with either medium: PBS had a mean difference of 0.058 ( p  = 0.852, 95% CI -0.560 to 0.676), EtOH had a mean difference of 1.183 ( p  = 0.112, 95% CI 0.281 to 2.648). From the Results section of my first paper, available here . Square brackets added for this post to aid clarity.

From this text the reader can infer from the first paragraph that there was a statistically significant difference in using EtOH compared to PBS (really small p-value of <0.0001). However, from the second paragraph, the difference between two repeat scans was statistically insignificant for both PBS (p = 0.852) and EtOH (p = 0.112).

By conducting these statistical tests you have then earned your right to make bold statements, such as these from the discussion section:

Propagation phase-contrast increases the contrast of individual chondrocytes [cartilage cells] compared to using absorption contrast. From the Discussion section from the same paper.

Without statistical tests you have no evidence that your results are not just down to random chance.

Beyond describing the statistical significance of a study in the main body text of your work, you can also show it in your figures.

In figures such as bar charts you’ll often see asterisks to represent statistical significance, and “n.s.” to show differences between groups which are not statistically significant. Here is one such figure, with some subplots, from the same paper:

In this example an asterisk (*) between two bars represents p < 0.05. Two asterisks (**) represents p < 0.001 and three asterisks (***) represents p < 0.0001. This should always be stated in the caption of your figure since the values that each asterisk refers to can vary.

Now that we know if a study is showing statistically and research significance, let’s zoom out a little and consider the potential for commercial significance.

Commercial and Industrial Significance

What are commercial and industrial significance.

Moving beyond significance in relation to academia, your research may also have commercial or economic significance.

Simply put:

• Commercial significance: could the research be commercialised as a product or service? Perhaps the underlying technology described in your study could be licensed to a company or you could even start your own business using it.
• Industrial significance: more widely than just providing a product which could be sold, does your research provide insights which may affect a whole industry? Such as: revealing insights or issues with current practices, performance gains you don’t want to commercialise (e.g. solar power efficiency), providing suggested frameworks or improvements which could be employed industry-wide.

I’ve grouped these two together because there can certainly be overlap. For instance, perhaps your new technology could be commercialised whilst providing wider improvements for the whole industry.

Commercial and industrial significance are not relevant to most studies, so only write about it if you and your supervisor can think of reasonable routes to your work having an impact in these ways.

How are commercial and industrial significance measured?

Unlike statistical and research significances, the measures of commercial and industrial significance can be much more broad.

Here are some potential measures of significance:

Commercial significance:

• How much value does your technology bring to potential customers or users?
• How big is the potential market and how much revenue could the product potentially generate?
• Is the intellectual property protectable? i.e. patentable, or if not could the novelty be protected with trade secrets: if so publish your method with caution!
• If commercialised, could the product bring employment to a geographical area?

Industrial significance:

What impact could it have on the industry? For instance if you’re revealing an issue with something, such as unintended negative consequences of a drug , what does that mean for the industry and the public? This could be:

• Reduced overhead costs
• Better safety
• Faster production methods
• Improved scaleability

How to describe the commercial and industrial significance of a study, with examples

Commercial significance.

If your technology could be commercially viable, and you’ve got an interest in commercialising it yourself, it is likely that you and your university may not want to immediately publish the study in a journal.

You’ll probably want to consider routes to exploiting the technology and your university may have a “technology transfer” team to help researchers navigate the various options.

However, if instead of publishing a paper you’re submitting a thesis or dissertation then it can be useful to highlight the commercial significance of your work. In this instance you could include statements of commercial significance such as:

The measurement technology described in this study provides state of the art performance and could enable the development of low cost devices for aerospace applications. An example of commercial significance I invented for this post

Industrial significance

First, think about the industrial sectors who could benefit from the developments described in your study.

For example if you’re working to improve battery efficiency it is easy to think of how it could lead to performance gains for certain industries, like personal electronics or electric vehicles. In these instances you can describe the industrial significance relatively easily, based off your findings.

For example:

By utilising abundant materials in the described battery fabrication process we provide a framework for battery manufacturers to reduce dependence on rare earth components. Again, an invented example

For other technologies there may well be industrial applications but they are less immediately obvious and applicable. In these scenarios the best you can do is to simply reframe your research significance statement in terms of potential commercial applications in a broad way.

As a reminder: not all studies should address industrial significance, so don’t try to invent applications just for the sake of it!

Societal Significance

What is the societal significance of a study.

The most broad category of significance is the societal impact which could stem from it.

If you’re working in an applied field it may be quite easy to see a route for your research to impact society. For others, the route to societal significance may be less immediate or clear.

Studies can help with big issues facing society such as:

• Medical applications : vaccines, surgical implants, drugs, improving patient safety. For instance this medical device and drug combination I worked on which has a very direct route to societal significance.
• Political significance : Your research may provide insights which could contribute towards potential changes in policy or better understanding of issues facing society.
• Public health : for instance COVID-19 transmission and related decisions.
• Climate change : mitigation such as more efficient solar panels and lower cost battery solutions, and studying required adaptation efforts and technologies. Also, better understanding around related societal issues, for instance this study on the effects of temperature on hate speech.

How is societal significance measured?

Societal significance at a high level can be quantified by the size of its potential societal effect. Just like a lab risk assessment, you can think of it in terms of probability (or how many people it could help) and impact magnitude.

Societal impact = How many people it could help x the magnitude of the impact

Think about how widely applicable the findings are: for instance does it affect only certain people? Then think about the potential size of the impact: what kind of difference could it make to those people?

Between these two metrics you can get a pretty good overview of the potential societal significance of your research study.

How to describe the societal significance of a study, with examples

Quite often the broad societal significance of your study is what you’re setting the scene for in your Introduction. In addition to describing the existing literature, it is common to for the study’s motivation to touch on its wider impact for society.

For those of us working in healthcare research it is usually pretty easy to see a path towards societal significance.

Our CLOUT model has state-of-the-art performance in mortality prediction, surpassing other competitive NN models and a logistic regression model … Our results show that the risk factors identified by the CLOUT model agree with physicians’ assessment, suggesting that CLOUT could be used in real-world clinicalsettings. Our results strongly support that CLOUT may be a useful tool to generate clinical prediction models, especially among hospitalized and critically ill patient populations. Learning Latent Space Representations to Predict Patient Outcomes: Model Development and Validation

In other domains the societal significance may either take longer or be more indirect, meaning that it can be more difficult to describe the societal impact.

Even so, here are some examples I’ve found from studies in non-healthcare domains:

We examined food waste as an initial investigation and test of this methodology, and there is clear potential for the examination of not only other policy texts related to food waste (e.g., liability protection, tax incentives, etc.; Broad Leib et al., 2020) but related to sustainable fishing (Worm et al., 2006) and energy use (Hawken, 2017). These other areas are of obvious relevance to climate change… AI-Based Text Analysis for Evaluating Food Waste Policies

The continued development of state-of-the art NLP tools tailored to climate policy will allow climate researchers and policy makers to extract meaningful information from this growing body of text, to monitor trends over time and administrative units, and to identify potential policy improvements. BERT Classification of Paris Agreement Climate Action Plans

Top Tips For Identifying & Writing About the Significance of Your Study

• Writing a thesis? Describe the significance of your study in the Introduction and the Conclusion .
• Submitting a paper? Read the journal’s guidelines. If you’re writing a statement of significance for a journal, make sure you read any guidance they give for what they’re expecting.
• Take a step back from your research and consider your study’s main contributions.
• Read previously published studies in your field . Use this for inspiration and ideas on how to describe the significance of your own study
• Discuss the study with your supervisor and potential co-authors or collaborators and brainstorm potential types of significance for it.

Now you’ve finished reading up on the significance of a study you may also like my how-to guide for all aspects of writing your first research paper .

Writing an academic journal paper

I hope that you’ve learned something useful from this article about the significance of a study. If you have any more research-related questions let me know, I’m here to help.

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How To Write a Significance Statement for Your Research

A significance statement is an essential part of a research paper. It explains the importance and relevance of the study to the academic community and the world at large. To write a compelling significance statement, identify the research problem, explain why it is significant, provide evidence of its importance, and highlight its potential impact on future research, policy, or practice. A well-crafted significance statement should effectively communicate the value of the research to readers and help them understand why it matters.

Updated on May 4, 2023

A significance statement is a clearly stated, non-technical paragraph that explains why your research matters. It’s central in making the public aware of and gaining support for your research.

Write it in jargon-free language that a reader from any field can understand. Well-crafted, easily readable significance statements can improve your chances for citation and impact and make it easier for readers outside your field to find and understand your work.

Read on for more details on what a significance statement is, how it can enhance the impact of your research, and, of course, how to write one.

What is a significance statement in research?

A significance statement answers the question: How will your research advance scientific knowledge and impact society at large (as well as specific populations)? 

You might also see it called a “Significance of the study” statement. Some professional organizations in the STEM sciences and social sciences now recommended that journals in their disciplines make such statements a standard feature of each published article. Funding agencies also consider “significance” a key criterion for their awards.

Read some examples of significance statements from the Proceedings of the National Academy of Sciences (PNAS) here .

Depending upon the specific journal or funding agency’s requirements, your statement may be around 100 words and answer these questions:

1. What’s the purpose of this research?

2. What are its key findings?

3. Why do they matter?

4. Who benefits from the research results?

Readers will want to know: “What is interesting or important about this research?” Keep asking yourself that question.

Where to place the significance statement in your manuscript

Most journals ask you to place the significance statement before or after the abstract, so check with each journal’s guide. 

This article is focused on the formal significance statement, even though you’ll naturally highlight your project’s significance elsewhere in your manuscript. (In the introduction, you’ll set out your research aims, and in the conclusion, you’ll explain the potential applications of your research and recommend areas for future research. You’re building an overall case for the value of your work.)

Developing the significance statement

The main steps in planning and developing your statement are to assess the gaps to which your study contributes, and then define your work’s implications and impact.

Identify what gaps your study fills and what it contributes

Your literature review was a big part of how you planned your study. To develop your research aims and objectives, you identified gaps or unanswered questions in the preceding research and designed your study to address them.

Go back to that lit review and look at those gaps again. Review your research proposal to refresh your memory. Ask:

• How have my research findings advanced knowledge or provided notable new insights?
• How has my research helped to prove (or disprove) a hypothesis or answer a research question?
• Why are those results important?

Consider your study’s potential impact at two levels: 

• What contribution does my research make to my field?
• How does it specifically contribute to knowledge; that is, who will benefit the most from it?

Define the implications and potential impact

As you make notes, keep the reasons in mind for why you are writing this statement. Whom will it impact, and why?

The first audience for your significance statement will be journal reviewers when you submit your article for publishing. Many journals require one for manuscript submissions. Study the author’s guide of your desired journal to see its criteria ( here’s an example ). Peer reviewers who can clearly understand the value of your research will be more likely to recommend publication. 

Second, when you apply for funding, your significance statement will help justify why your research deserves a grant from a funding agency . The U.S. National Institutes of Health (NIH), for example, wants to see that a project will “exert a sustained, powerful influence on the research field(s) involved.” Clear, simple language is always valuable because not all reviewers will be specialists in your field.

Third, this concise statement about your study’s importance can affect how potential readers engage with your work. Science journalists and interested readers can promote and spread your work, enhancing your reputation and influence. Help them understand your work.

You’re now ready to express the importance of your research clearly and concisely. Time to start writing.

How to write a significance statement: Key elements 

When drafting your statement, focus on both the content and writing style.

• In terms of content, emphasize the importance, timeliness, and relevance of your research results. 
• Write the statement in plain, clear language rather than scientific or technical jargon. Your audience will include not just your fellow scientists but also non-specialists like journalists, funding reviewers, and members of the public. 

Follow the process we outline below to build a solid, well-crafted, and informative statement. 

Get started

Some suggested opening lines to help you get started might be:

• The implications of this study are… 
• Building upon previous contributions, our study moves the field forward because…
• Our study furthers previous understanding about…

Alternatively, you may start with a statement about the phenomenon you’re studying, leading to the problem statement.

Include these components

Next, draft some sentences that include the following elements. A good example, which we’ll use here, is a significance statement by Rogers et al. (2022) published in the Journal of Climate .

1. Briefly situate your research study in its larger context . Start by introducing the topic, leading to a problem statement. Here’s an example:

‘Heatwaves pose a major threat to human health, ecosystems, and human systems.”

2. State the research problem.

“Simultaneous heatwaves affecting multiple regions can exacerbate such threats. For example, multiple food-producing regions simultaneously undergoing heat-related crop damage could drive global food shortages.”

3. Tell what your study does to address it.

“We assess recent changes in the occurrence of simultaneous large heatwaves.”

4. Provide brief but powerful evidence to support the claims your statement is making , Use quantifiable terms rather than vague ones (e.g., instead of “This phenomenon is happening now more than ever,” see below how Rogers et al. (2022) explained it). This evidence intensifies and illustrates the problem more vividly:

“Such simultaneous heatwaves are 7 times more likely now than 40 years ago. They are also hotter and affect a larger area. Their increasing occurrence is mainly driven by warming baseline temperatures due to global heating, but changes in weather patterns contribute to disproportionate increases over parts of Europe, the eastern United States, and Asia.

5. Relate your study’s impact to the broader context , starting with its general significance to society—then, when possible, move to the particular as you name specific applications of your research findings. (Our example lacks this second level of application.) 

“Better understanding the drivers of weather pattern changes is therefore important for understanding future concurrent heatwave characteristics and their impacts.”

Refine your English

Don’t understate or overstate your findings – just make clear what your study contributes. When you have all the elements in place, review your draft to simplify and polish your language. Even better, get an expert AJE edit . Be sure to use “plain” language rather than academic jargon.

• Avoid acronyms, scientific jargon, and technical terms 
• Use active verbs in your sentence structure rather than passive voice (e.g., instead of “It was found that...”, use “We found...”)
• Make sentence structures short, easy to understand – readable
• Try to address only one idea in each sentence and keep sentences within 25 words (15 words is even better)
• Eliminate nonessential words and phrases (“fluff” and wordiness)

Enhance your significance statement’s impact

Always take time to review your draft multiple times. Make sure that you:

• Keep your language focused
• Provide evidence to support your claims
• Relate the significance to the broader research context in your field

After revising your significance statement, request feedback from a reading mentor about how to make it even clearer. If you’re not a native English speaker, seek help from a native-English-speaking colleague or use an editing service like AJE to make sure your work is at a native level.

Understanding the significance of your study

Your readers may have much less interest than you do in the specific details of your research methods and measures. Many readers will scan your article to learn how your findings might apply to them and their own research. 

Different types of significance

Your findings may have different types of significance, relevant to different populations or fields of study for different reasons. You can emphasize your work’s statistical, clinical, or practical significance. Editors or reviewers in the social sciences might also evaluate your work’s social or political significance.

Statistical significance means that the results are unlikely to have occurred randomly. Instead, it implies a true cause-and-effect relationship.

Clinical significance means that your findings are applicable for treating patients and improving quality of life.

Practical significance is when your research outcomes are meaningful to society at large, in the “real world.” Practical significance is usually measured by the study’s  effect size . Similarly, evaluators may attribute social or political significance to research that addresses “real and immediate” social problems.

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• Relevance of Your Dissertation Topic | Criteria & Tips

Relevance of Your Dissertation Topic | Criteria & Tips

Published on November 14, 2022 by Sarah Vinz . Revised on May 31, 2023.

A relevant dissertation topic means that your research will contribute something worthwhile to your field in a scientific, social, or practical way.

As you plan out your dissertation process , make sure that you’re writing something that is important and interesting to you personally, as well as appropriate within your field.

If you’re a bit stuck on where to begin, consider framing your questions in terms of their relevance: scientifically to your discipline, socially to the world at large, or practically to an industry or organization.

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Table of contents

Scientific relevance, social and practical relevance, other interesting articles, frequently asked questions about relevant topics.

If you are studying hard or social sciences, the scientific relevance of your dissertation is crucial. Your research should fill a gap in existing scientific knowledge, something that hasn’t been extensively studied before.

One way to find a relevant topic is to look at the recommendations for follow-up studies that are made in existing scientific articles and the works they cite. From there, you can pursue quantitative research , statistical analyses , or the relevant methodology for the type of research you choose to undertake.

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Most theses are required to have social relevance, which basically means that they help us to better understand society. These can use ethnographies , interviews , or other types of field work to collect data

However, in some disciplines it may be more important that a dissertation have practical relevance. Research that has practical relevance adds value. For instance, it could make a recommendation for a particular industry or suggest ways to improve certain processes within an organization.

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

Methodology

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

 Statistics

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

Research bias

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

Formulating a main research question can be a difficult task. Overall, your question should contribute to solving the problem that you have defined in your problem statement .

However, it should also fulfill criteria in three main areas:

• Researchability
• Feasibility and specificity
• Relevance and originality

A dissertation prospectus or proposal describes what or who you plan to research for your dissertation. It delves into why, when, where, and how you will do your research, as well as helps you choose a type of research to pursue. You should also determine whether you plan to pursue qualitative or quantitative methods and what your research design will look like.

It should outline all of the decisions you have taken about your project, from your dissertation topic to your hypotheses and research objectives , ready to be approved by your supervisor or committee.

Note that some departments require a defense component, where you present your prospectus to your committee orally.

A thesis or dissertation outline is one of the most critical first steps in your writing process. It helps you to lay out and organize your ideas and can provide you with a roadmap for deciding what kind of research you’d like to undertake.

Generally, an outline contains information on the different sections included in your thesis or dissertation , such as:

• Your anticipated title
• Your abstract
• Your chapters (sometimes subdivided into further topics like literature review , research methods , avenues for future research, etc.)

All research questions should be:

• Focused on a single problem or issue
• Researchable using primary and/or secondary sources
• Feasible to answer within the timeframe and practical constraints
• Specific enough to answer thoroughly
• Complex enough to develop the answer over the space of a paper or thesis
• Relevant to your field of study and/or society more broadly

You can assess information and arguments critically by asking certain questions about the source. You can use the CRAAP test , focusing on the currency , relevance , authority , accuracy , and purpose of a source of information.

Ask questions such as:

• Who is the author? Are they an expert?
• Why did the author publish it? What is their motivation?
• How do they make their argument? Is it backed up by evidence?

The best way to remember the difference between a research plan and a research proposal is that they have fundamentally different audiences. A research plan helps you, the researcher, organize your thoughts. On the other hand, a dissertation proposal or research proposal aims to convince others (e.g., a supervisor, a funding body, or a dissertation committee) that your research topic is relevant and worthy of being conducted.

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Vinz, S. (2023, May 31). Relevance of Your Dissertation Topic | Criteria & Tips. Scribbr. Retrieved August 21, 2024, from https://www.scribbr.com/research-process/relevance-dissertation-topic/

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Sarah's academic background includes a Master of Arts in English, a Master of International Affairs degree, and a Bachelor of Arts in Political Science. She loves the challenge of finding the perfect formulation or wording and derives much satisfaction from helping students take their academic writing up a notch.

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What is the Significance of the Study?

• By DiscoverPhDs
• August 25, 2020

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

What does Significance of the Study mean?

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

Why is the Significance of the Study important?

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

How do you write the Significance of the Study?

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

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

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

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

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

Significance of the Study: An example

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

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

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

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

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The term rationale of research means the reason for performing the research study in question.

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Understanding relevance of health research: considerations in the context of research impact assessment

Mark j. dobrow.

1 Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, 155 College Street, 4th Floor, Toronto, ON M5T 3M6 Canada

Fiona A. Miller

2 Alberta Innovates - Health Solutions, Edmonton, Alberta Canada

Adalsteinn D. Brown

Associated data.

Not applicable. No datasets were generated or analysed during the development of the article.

With massive investment in health-related research, above and beyond investments in the management and delivery of healthcare and public health services, there has been increasing focus on the impact of health research to explore and explain the consequences of these investments and inform strategic planning. Relevance is reflected by increased attention to the usability and impact of health research, with research funders increasingly engaging in relevance assessment as an input to decision processes. Yet, it is unclear whether relevance is a synonym for or predictor of impact, a necessary condition or stage in achieving it, or a distinct aim of the research enterprise. The main aim of this paper is to improve our understanding of research relevance, with specific objectives to (1) unpack research relevance from both theoretical and practical perspectives, and (2) outline key considerations for its assessment.

Our approach involved the scholarly strategy of review and reflection. We prepared a draft paper based on an exploratory review of literature from various fields, and gained from detailed and insightful analysis and critique at a roundtable discussion with a group of key health research stakeholders. We also solicited review and feedback from a small sample of expert reviewers.

Conclusions

Research relevance seems increasingly important in justifying research investments and guiding strategic research planning. However, consideration of relevance has been largely tacit in the health research community, often depending on unexplained interpretations of value, fit and potential for impact. While research relevance seems a necessary condition for impact – a process or component of efforts to make rigorous research usable – ultimately, relevance stands apart from research impact. Careful and explicit consideration of research relevance is vital to gauge the overall value and impact of a wide range of individual and collective research efforts and investments. To improve understanding, this paper outlines four key considerations, including how research relevance assessments (1) orientate to, capture and compare research versus non-research sources, (2) consider both instrumental versus non-instrumental uses of research, (3) accommodate dynamic temporal-shifting perspectives on research, and (4) align with an intersubjective understanding of relevance.

Various levels of government in Canada collectively invest multiple billions of dollars in health-related research per annum, above and beyond investments in the management and delivery of healthcare and public health services. In recognition of this sizeable collective commitment, much work has focused on the impact of health research to explore and explain the consequences of these investments and inform strategic planning. Relevance is tacit in the increased attention to the usability and impact of health research. Additionally, research funders increasingly engage in relevance assessment as an input to decision processes; yet, it is unclear whether relevance is a synonym for or predictor of impact, a necessary condition or stage in achieving it, or a distinct aim of the research enterprise. Therefore, the main aim of this paper is to improve our understanding of research relevance as it relates to research quality and research impact, with specific objectives to (1) unpack research relevance from both theoretical and practical perspectives, and (2) outline key considerations for the assessment of research relevance.

Globally, there has been increasing critical assessment of the value of health research investments [ 1 – 3 ], with growing interest in research impact assessment (RIA) in the health sector [ 4 – 6 ]. RIA focuses on understanding how research activity can directly and indirectly advance knowledge, influence decision-making, and effect health and socio-economic outcomes, with a small but growing body of work seeking to develop better measures to evaluate (and ideally attribute) the returns on health research investments [ 6 ]. The Canadian Academy of Health Sciences (CAHS) released a comprehensive report on the subject in 2009 that presented a call for action, with a number of recommendations including establishing collaborative efforts among Canadian research funders to advance frameworks and sets of indicators and metrics for health research impact [ 4 ]. The CAHS impact framework [ 4 ], which drew on the Buxton and Hanney [ 7 ] ‘payback model’, among others, has provided a thoughtful starting point for considering the impact of health research in Canada. Subsequent work by Alberta Innovates – Health Solutions (AIHS) on a Research to Impact Framework (described in Graham et al. [ 8 ]) provides further insights on operationalising RIA frameworks for health research in Canada.

These initiatives are part of a broadly discussed shift in approaches to knowledge production, from an emphasis on investigator-initiated, curiosity driven work judged and guided by scientists, to expanded approaches to knowledge production, drawing on a wider set of actors and approaches, and emphasising relevance and usability. This shift from science produced by and for scientists to knowledge production that is “ socially distributed, application-oriented, trans-disciplinary, and subject to multiple accountabilities ” [ 9 ] has been characterised as a shift from ‘mode 1’ to ‘mode 2’ knowledge regimes. In the language of mode 2, interest in research ‘impact’ expresses a concern for application or consequence, and – in the economic language of return on investment – a concern that the yield is at least equal to the investment in the research itself. Extending this reasoning, interest in research ‘relevance’ may reflect a concern for accountability – linking research to the actor(s) for whom the research is performed and who will, ideally, put it to use.

In Canada, interest in research impact and relevance appears to have been felt most forcefully in the context of health services and policy research, which has long been encouraged to orient to the needs of policymakers, health system planners and related decision makers. More recently, there has been increased attention to ensuring that all forms of health research are ‘patient oriented’ – that is, that the research is prioritised, conducted and applied in ways that are accountable to this important end user. This call has been picked up on several fronts, including by the Canadian Institutes of Health Research (CIHR), which released its Strategy for Patient-Oriented Research (SPOR) in 2011. The SPOR vision “…is to demonstrably improve health outcomes and enhance patients’ health care experience through integration of evidence at all levels in the health care system ” [ 10 ]. In some respects, it represents a fundamental re-orientation for the primary funder of health research in Canada.

Though relevance is tacit in attention to research impact and the wider concern with mode 2 knowledge production, explicit attention to the meaning or measurement of research relevance is limited. The CAHS and AIHS frameworks, for example, acknowledge ‘relevance’ of health research but do not clearly define the term nor describe approaches for assessing it [ 4 , 8 ]. Rather, these frameworks emphasise the role of broad stakeholder engagement approaches and feedback mechanisms as methods for addressing relevance. For example, the AIHS framework notes the challenge of, and need to, move “ …beyond the collection of traditional scientific indicators […] to include measures of greater interest to the broader stakeholder community… ” [ 8 ] without stating explicitly how “ greater interest ” or related concepts such as relevance should be judged. As currently constructed, these RIA frameworks provide important advances in how we think about the impact of health research, but they were not intended to provide guidance specifically to the assessment of the relevance of health research.

Despite this lack of specific guidance on research relevance from a scholarly or measurement perspective, attention to it as a practical component of health research funding and organisation is evolving. There is, for example, growing use of ‘relevance assessment’ by research funders. The Canadian Health Services Research Foundation, in particular, was an innovator in incorporating relevance review into its applied research funding programmes, including promoting partnerships and knowledge translation (KT) with health system stakeholders [ 11 ]. Current applications for funding from the Institute of Gender and Health at CIHR go through ‘relevance review’ ( http://www.cihr-irsc.gc.ca/e/45212.html ). Similarly, applications for Ontario’s Health System Research Fund are judged based on ‘internal review of relevance and impact’ ( http://www.health.gov.on.ca/en/pro/ministry/research/cihr.aspx ). However, given the lack of conceptual clarity on research relevance, and in particular, how relevance assessment aligns with and differs from impact assessment, there is a critical gap in our understanding that has implications for both its contemporary and ongoing application and our ability to make sound research investment decisions.

This work was commissioned by the Ontario SPOR SUPPORT (Support for People and Patient-Oriented Research and Trials) Unit (OSSU) – one of several units established at provincial and regional levels across Canada to work with CIHR in pursuing the SPOR. Like other research organisations, OSSU saw the need to consider the relevance of the research it supported, and it established both scientific and relevance advisory committees as part of its original governance structure [ 12 ], tasking the latter to “ …develop a measure, or small set of strategic measures, that serves to inspire the Ontario research, implementation, provider and patient communities to come together to make a difference for patients ” [ 12 ]. In the spirit of research and scholarship, OSSU then asked what exactly this commitment to research ‘relevance’ entailed.

Our approach to answering this question involved the scholarly strategy of review and reflection. As with the early investigations into research impact assessment, we were surprised to find so little reflexive attention to the topic within the health research community [ 13 ]. We prepared a draft paper based on an exploratory review of literature from various fields, and gained from detailed and insightful analysis and critique at a roundtable discussion with a small group of key health research stakeholders. We also solicited review and feedback from a small sample of expert reviewers.

The structure of our paper is as follows. First, to ‘unpack’ the concept of relevance, we review theoretical literature and then consider practical work both from within and outside the health sector, to ask what has been argued and concluded about the nature of relevance and its appropriate assessment. Next, we outline a series of forward-looking considerations for assessing research relevance and conclude with reflections on how research relevance assessment fits with evolving interest in RIA.

Unpacking relevance

Theoretical perspectives.

Before considering the relevance of health research, we need to step back and consider what we mean by the term ‘relevance’. A range of descriptors is often used to define relevance, including ‘pertinent to…’, ‘bearing upon…’, ‘connected with…’, or ‘appropriate to…’, ‘…the matter at hand’, as well as ‘germane’, ‘apropos’, ‘material’, ‘applicable’ and ‘satisfactory’. A large body of dedicated theoretical work on relevance, drawn from many fields and perspectives, such as computer science, information science, statistics/probability theory, artificial intelligence, cognitive science, epistemology, linguistics and jurisprudence [ 14 ], reflects its importance but also the challenge for establishing a common understanding of the term [ 14 , 15 ]. For example, Gärdenfors [ 16 ], in his discussion on the logic of relevance, noted that “ …relevance ought to be a central concept in the philosophy of science… ” given the position that “ …it is only relevant information that is of any importance… ” (p. 351). However, from a ‘research’ relevance perspective, the theoretical work on relevance has been linked to ‘information’, ‘evidence’, ‘reasoning’, ‘argument’ and ‘decision’ [ 15 – 18 ], each presenting variable framing that impedes practical definition or consistent comprehension of the term. Floridi [ 14 ] recently suggested that existing theories are “ …utterly useless when it comes to establish the actual relevance of some specific piece of information ” (p. 69), and goes on to advance a ‘subjectivist’ interpretation, with relevance judged by the questioner. While a subjectivist approach to relevance is intuitively appealing, its contribution to the assessment of research relevance presents particular challenges that we will discuss later in the paper.

Another approach to unpacking relevance is to consider the theoretical model behind the broad-based research strategies that have governed research investments and policies in high-income countries since the end of the Second World War. For the better part of the 20th century, a linear model was the dominant conceptual framework, whereby basic research was viewed as a necessary input for applied research, which then led to development and production [ 19 , 20 ]. In the late 1990s, an alternate thesis was introduced when Stokes proposed a new model for broad-based research strategy – known as Pasteur’s Quadrant – that highlighted the conceptual relationship between the ‘quest to understand’ and ‘practical needs’ [ 21 ]. While some research is clearly focused on advances in basic research (e.g. Niels Bohr’s foundational research on atomic structure and quantum theory), and some research is clearly focused on applied problems (e.g. Thomas Edison’s practical inventions), Stokes emphasised the potential for use-inspired basic research (e.g. Louis Pasteur’s foundational research on microbiology that addressed contemporaneous population health challenges). Pasteur’s Quadrant invokes consideration of ‘relevance’ with some commentators framing the two-by-two relationship as the relevance for advancement of basic knowledge and the relevance for immediate application [ 22 ]. Stokes’ model adds conceptual insight on the role of relevance when considering the value of research to society, however, it was not intended to specifically conceptualise the term and does not distinguish it from other related concepts such as research impact or value. Therefore, to provide further insights, we next consider relevance in practical settings.

Health sector perspectives

In the health sector, the idea that research should be ‘relevant’ is commonplace. Commitments to ‘knowledge translation’ and the ‘knowledge to action cycle’ [ 23 ] emphasise issues of relevance and provide considerable insight into approaches to ensuring research usability and use. At the same time, the health research community has given disproportionate attention to issues of research quality, with an emphasis on internal validity that may downplay external validity and suggest some tension between rigour and relevance. Thus, though the concept of relevance is of central importance to the health research enterprise, the failure to unpack it or explore it both theoretically and practically leaves room for misunderstanding and misapplication.

In the health sector, research relevance often arises as a practical question of the ‘fit’ between a body of knowledge or research approach and a specific field or issue (e.g. public health, primary healthcare, healthcare access, genomics, alternative healthcare, healthcare reform in rural areas). The results of two recent International Society for Pharmacoeconomics and Outcomes Research task forces take this approach. The task forces developed questionnaires to assess the relevance and credibility of research other than randomised controlled trials (e.g. observational research, meta-network analysis) to inform healthcare decision-making [ 24 , 25 ]. Both make similar observations about relevance, reinforcing the subjectivist approach noted earlier, and can be summarised by the following statement by Berger et al. [ 24 ]:

“ Relevance addresses whether the results of the study/apply [sic] to the setting of interest to the decision maker. It addresses issues of external validity similar to the population, interventions, comparators, outcomes, and setting framework from evidence based medicine. There is no correct answer for relevance. Relevance is determined by each decision maker, and the relevance assessment determined by one decision maker will not necessarily apply to other decision makers. Individual studies may be designed with the perspective of particular decision makers in mind (e.g. payer or provider) ” (p.148, emphasis added).

Research relevance in health is also noted in discussion and debate regarding the value of qualitative research relative to the more established forms of quantitative health research. For example, Mays and Pope [ 26 ] suggest that qualitative research can be assessed “… by two broad criteria: validity and relevance ”. Their further discussion provides some insight into the several ways that research might be relevant, suggesting that:

“[r] esearch can be relevant when it either adds to knowledge or increases the confidence with which existing knowledge is regarded. Another important dimension of relevance is the extent to which findings can be generalised beyond the setting in which they were generated ” [ 27 ].

The work of Mays and Pope positions research relevance amidst the longstanding tension between internal and external validity. This tension reflects opposing foci on internal validity as the quality/rigour of research methodology and external validity as the applicability/transferability of research to other settings or contexts. While external validity is not the only measure of relevance – as research may remain relevant to some contexts even when not generalisable to others – it is an important component, and one that has not always attracted sufficient attention. For example, the Canadian health research community has focused considerable practical attention on internal validity as a critical component of evidence for clinical and health policy decisions. Evidence-based medicine, the Cochrane Collaboration, the Canadian and United States task forces on preventive healthcare/services and a long list of aligned groups have developed and established many tools to assess the quality of research evidence (e.g. GRADE [ 28 ]), with a predominant focus on issues of internal validity, and an emphasis on evidence hierarchies that is sometimes seen to be incompatible with ‘real world’ relevance. The relative lack of similar approaches or tools that focus on external validity in health research is notable, though movements to marshal evidence in support of sound public policy, such as the Campbell Collaboration, have attended to issues of external validity in other areas of health and social policy [ 29 ]. Further, there are emerging approaches and tools for documenting the external validity of health research and facilitating its use [ 30 ]. For example, WHO has supported the development of workbooks to contextualise health systems guidance for different contexts [ 31 ] and the field of local applicability and transferability of research has emerged to facilitate the adaptation of interventions from one setting to another, including the development of some well-documented tools like RE-AIM [ 32 ].

Alongside these emerging approaches and tools sits the established field of KT. KT has a strong history in Canada with a distinctive feature being a reliance on stakeholder engagement to support a commitment to improve research relevance. For example, the AIHS framework relies heavily on KT and stakeholder engagement approaches as part of its RIA, describing the mobilisation of knowledge through “ …a process of interactions, feedback, and engagement using a variety of mechanisms (e.g. collaborations, partnerships, networks, knowledge brokering) with relevant target audiences (i.e. actors and performers) across the health sector ” ([ 8 ] p. 362). Experience in stakeholder engagement, particularly with clinical, management and policy decision-makers, has become fairly extensive and there is now increased attention on engaging patients as core stakeholders in health research. If relevance is truly subjective, then KT efforts (including engagement, dissemination, promotion, communication) would appear to represent reasonable approaches for articulating, conveying and improving research relevance. However, if there are underlying elements of relevance that are more universal, then there is a risk that KT efforts – and subjectivist approaches to ensuring relevance – are akin to commercial marketing or communication strategies where the aim is to ‘sell’ more product and/or generate more influence that may not align with a more objective lens.

In sum, the health research community in Canada has a longstanding history of critically appraising research quality based on study design and research methodology, with greater emphasis on internal rather than external validity. As the same time, there is established expertise in KT, emphasising engagement with research users and adaptation to settings or contexts of use – approaches that may imply a subjectivist interpretation of relevance. Thus, while relevance is an important concept for the health research enterprise, its use is largely tacit and taken for granted.

Non-health sector perspectives

To unpack relevance further we consider some non-health sector perspectives that give attention to the term, often with formal definitions or taxonomies established. Examples include the legal, financial accounting, education and web search (information retrieval) sectors, each of which are briefly described below.

From a legal perspective, relevance has a specific meaning that relates to the admissibility of evidence in terms of its probative value (i.e. the extent to which evidence contributes to proving an important matter of fact) [ 33 ]. For example, a common objection to legal testimony or evidence is that it is ‘irrelevant’ [ 34 ]. Legal processes for considering the admissibility or legal-relevance of evidence are firmly established, requiring explicit declaration of evidentiary sources and direct consideration of that evidence as it relates both to a specific case and related historical precedents, something that is undeveloped in the health sector [ 35 ]. It is the formality, explicitness and retrospective nature of this process, which is directly associated with a specific case (or decision), that is characteristic of the consideration of relevance in the legal context.

Financial accounting provides another perspective on relevance. In this field, relevance is viewed as a fundamental component of generally accepted accounting principles. Relevance and materiality are emphasised such that accountants and auditors focus on financial information that meets the decision-making needs of users and is expected to affect their decisions. In financial accounting, ‘value relevance’ provides a more focused perspective on relevance, defined as “ …the ability of information disclosed by financial statements to capture and summarise firm value. Value relevance can be measured through the statistical relations between information presented by financial statements and stock market values or returns ” [ 36 ]. Similar to the legal perspective, the financial accounting perspective on relevance is set with a formal context, where the focal point (i.e. financial performance) is clear and principles (i.e. generally accepted accounting principles) and processes (i.e. financial reporting and auditing) are clearly established and monitored.

Education provides a slightly more expansive approach to operationalising relevance, given the more general aim of the enterprise. In the United States, the Glossary of Education Reform [ 37 ] notes that “ …the term relevance typically refers to learning experiences that are either directly applicable to the personal aspirations, interests, or cultural experiences of students (personal relevance) or that are connected in some way to real-world issues, problems, and contexts (life relevance) ”. They further state that “ personal relevance occurs when learning is connected to an individual student’s interests, aspirations, and life experiences ”, while “ life relevance occurs when learning is connected in some way to real-world issues, problems, and contexts outside of school ”. A similar framing of relevance in this context suggests that it “…extends the learning beyond the classroom by teaching students to apply what they are learning to real world situations ” [ 38 ]. While the education sector also makes numerous references to a ‘rigour and relevance’ dyad [ 39 ] in contrast to the dominance of the internal validity focus in healthcare, it is the prominent dual focus on ‘personal’ relevance (with its subjectivist orientation) and ‘life’ or ‘real world’ relevance (with its more universal orientation) that seems to most clearly define the education sector’s perspective on relevance.

One of the most intensive and competitive sectors focusing on relevance is the web search (or information retrieval) field. This includes dominant search engines such as Google and Bing, as well as a wide range of commercial and social media sites such as Amazon, eBay, Facebook and LinkedIn, that compete either directly or indirectly on their ability to identify relevant information in response to user queries. Therefore, the ability of these organisations to advance the theory and practice related to relevance is fundamental to their success. For example, Google was built upon the effectiveness of its search algorithm, which is in a constant state of evolution. Both explicit and implicit approaches to assess relevance are used to contribute to search algorithm refinements [ 40 ]. The explicit approach focuses on ‘relevance ratings’, whereby evaluators (e.g. human raters) are contracted to assess the degree of ‘helpfulness’ of search results paired to specific search queries [ 41 ]. The implicit approach to assess relevance monitors and aggregates search behaviour of millions of users who are likely unaware that their behaviour is being assessed. Google has more recently advanced ‘personalised relevance’, which uses past individual search behaviour to personalise/tailor future search results for the same individual. Pariser has critiqued this concept as “ the filter bubble ” [ 42 ], warning that Google’s intent to optimise search algorithms for personal relevance creates a “ …personal ecosystem of information… ” that limits the diversity of search results and promotes insularity. This personal relevance is situated within the pervasiveness of social media, which facilitates the advancement of ‘social relevance’. Personal and social relevance highlight two important orientations towards relevance – one built on increasingly detailed understanding of individual preferences and the other reflecting the growing power and increasing accessibility of crowd-sourced perspectives. Overall, web search has made important contributions to how we understand and operationalise relevance, including the use of increasingly sophisticated explicit and implicit feedback mechanisms and the ability to draw upon and analyse big data sets. Web search has also exposed the contrasting orientations of personal and social relevance that underscore the challenges of combining or integrating different relevance assessments.

These non-health sector perspectives on relevance highlight several considerations. First, they reinforce general findings that point to perspective, decision context, timeliness and precision of focus or ‘fit’ as key elements of relevance. Additionally, they highlight a few distinctive considerations. The formalistic contexts of financial accounting and law emphasise issues such as precedent and legitimacy, implying that relevance in a research sense might require the demonstration of some legitimate or credible association between research and its use or user, among other considerations. Further, the complex consumerist world of social media highlights some of the challenges of a purely subjectivist definition of relevance. Whereas the International Society for Pharmacoeconomics and Outcomes Research guidance takes a subjectivist stance in suggesting that, “[t] here is no correct answer for relevance ” [ 24 ], the “ filter bubble ” criticised by Pariser [ 42 ] suggests otherwise. Relevance solely to the personally-perceived interests of a research user is unlikely to adequately serve the collective commitments to health and health equity that are especially germane to the health research enterprise.

Forward-looking considerations for assessing the relevance of health research

To this point, we have endeavoured to unpack relevance from theoretical and practical perspectives. In light of these insights and in the context of persistent interest in research impact assessment and evolving interest in research relevance, we now turn to some specific forward-looking considerations for research relevance assessment (RRA).

Relevance of research versus everything else

The first consideration for RRA is the acknowledgement that research is only one of many sources of insight to inform the needs or actions of research users. A research user is influenced by a wide range of political, legal, media, economic and other contextual information, interactions and experiences, as well as prevailing organisational governance, leadership, culture and values that all serve to complement (and often dominate) any insights that might be derived from research [ 43 ]. This reality implies that ‘relevance’ has a different meaning for researchers and research users. Researchers are typically interested in the relevance of a specific research product or activity for identifiable actions of (potentially) multiple research users; relevance is here judged relative to both the perceived needs of research users, and the extent and content of other related research. In contrast, research users are typically focused on identifying multiple relevant inputs to guide a specific action, only some of which may be research; relevance is here judged relative to both the research user’s needs and the form and content of the other inputs.

Given these distinct orientations to research relevance, RRA needs to be explicit about its comparative lens. Clear distinctions should be made between relevance based on the merits of the research product or activity (researcher lens) and relevance based on the relative value of research compared to other research and non-research sources (research user lens). RRA provides an opportunity to build more robust ways to characterise and assess the contribution of research to research users, including a more systematic and transparent articulation of anticipated research uses (akin to the Research Councils UK’s ‘Pathways to Impact’ [ 44 ] or descriptions of planned study design and methodological approach published in study protocols/registrations for randomised controlled trials or systematic reviews).

Beyond instrumental uses of research

The considerations noted above rely heavily on instrumental uses of research. Theoretically derived definitions of relevance, such as Floridi’s [ 14 ], tend to focus on the response to a specified question. This suggests a direct and tangible connection between research and its ‘use’. However, as Weiss [ 43 ] and others have observed, most types of research use are not instrumental, where use is documented and explicitly addresses a specific query or challenge for a research user. Rather, research use tends to be more conceptual, where use is indirect and evolves over time, or symbolic, where use may be politically or tactically motivated [ 43 ]. Research may also create externalities or unintended effects. For example, general research activity might support an engaged learning environment, interactive research relationships, and additional research-related discourse that provides benefits that are not attributable to any specific research product or activity. This has important ramifications for how research is funded and the role that relevance can play in that assessment. Ultimately, RRA needs to go beyond a singular understanding of research use as instrumental use, to develop better methods for capturing and assessing the relevance of the many non-instrumental uses of research.

The temporal factor

Another closely related consideration for RRA is the temporal context. Almost all research is conducted in a temporally defined period. Yet, while the quality of research is typically characterised by its methodology, which is a static feature typically not subject to temporal variation (e.g. the assessed quality of a randomised controlled trial should be consistent over time), relevance of research can be considered at any time (e.g. prior to the initiation of a research study or at different points in time post-completion) and is therefore subject to dynamic perceptions as they pertain to evolving action or decision contexts. Cohen [ 15 ] suggests that “ …relevance, like reasoning, has a prospective dimension as well as a retrospective one. It helps prediction as well as explanation ” (p. 182). The important insight is that, in contrast to research quality, the relevance of a specific research product can change over time, making assessment of research relevance more challenging.

This requires RRA to acknowledge the temporal factor and its associated implications for research relevance. At minimum, RRA should specify the temporal context as either pre-research (e.g. proposal/funding stage) or post-research (e.g. after research results have been produced). RRA at the pre-research stage focuses on proposed inputs and hypothetical outputs and outcomes, and may be more likely to overestimate instrumental research use and underestimate non-instrumental use. RRA at the post-research stage focuses mainly on the importance and value of actual outputs and tangible results, and may capture more non-instrumental research use. The pre-research stage is clearly aligned with research funding/investment processes, while the post-research stage can contribute to retrospective return-on-investment calculations and more general research impact assessment. However, employing this simple temporal categorisation should not lead us to lose sight of the dynamic, iterative nature of research relevance and the opportunity to assess it at interim and ongoing stages that captures re-interpretations or re-applications of research findings over time.

Moving from a subjective to an intersubjective understanding of relevance

An underlying theme in our review of relevance is subjectivity. Consider the broad scientific paradigms of positivism and interpretivism that are typically respectively aligned with research quality and research relevance. Research quality can be viewed as relating to characteristics or features that are assessed objectively, while research relevance may be seen as subjectively adjudicated. The subjective focus emphasises the variability of different perspectives and contexts and the suggestion that anyone can have a different take on the relevance of a specific research product or activity. For RRA, this reinforces a user-centred orientation to relevance assessment that privileges the judgment of the interrogator and raises the key question regarding who is positioned as the main arbiter of research relevance.

However, while relevance may never be characterised as universal, it could be argued that it is not purely subjective either. Rather, relevance may be more consistent with an intersubjective understanding that emphasises the extent of agreement or shared understanding among individual subjective perspectives representing a way to bridge the personal and the universal. The intersubjective view, while not presenting an objective approach to measuring relevance, does provide a road towards a meaningful and structured assessment of research relevance. It also emphasises the importance of representation in forging the intersubjective judgments that guide the research enterprise.

This paper has unpacked research relevance from different perspectives and outlined key considerations for its assessment. Alongside research impact assessment, research relevance seems increasingly important in justifying research investments and guiding strategic research planning. Indeed, judgments of ‘relevance’ are becoming a key component of the health research enterprise. However, consideration of relevance has been largely tacit in the health research community, often depending on unexplained interpretations of value, fit and potential for impact. Reviewing the various uses of relevance in health research, the concept is sometimes used as a synonym for research impact or positioned as a reliable predictor of later consequence. In many ways, research relevance seems a necessary condition for impact – a process or component of efforts to make rigorous research usable. However, relevance is not a necessary or sufficient condition to achieve impact. We expect that research that is relevant, and thus accountable to specific and legitimate users, will be impactful, but this may not necessarily be the case where other factors intervene. Additionally, we may expect that research that is impactful will be appropriately accountable – but again, this is not necessarily the case. Ultimately, relevance stands apart from research impact. Like rigour, relevance is a complementary but distinctive dimension of what it is that ensures ‘the good’ in health research.

While ‘relevance’ is ever-present, understanding of the concept in terms of health research is emergent and not well codified. To improve our understanding, this paper outlines four key considerations, including how research relevance assessments (1) orientate to, capture and compare research versus non-research sources, (2) consider both instrumental versus non-instrumental uses of research, (3) accommodate dynamic temporal-shifting perspectives on research, and (4) align with an intersubjective understanding of relevance. We believe careful and explicit consideration of research relevance, guided by transparent principles and processes is vital to gauge the overall value and impact of a wide range of individual and collective research efforts and investments. We hope this paper generates more discussion and debate to facilitate progress.

Acknowledgements

We acknowledge and appreciate the contributions of participants of a roundtable discussion to gather feedback on an earlier version of this paper. Participants included Simon Denegri, National Director for Public Participation and Engagement in Research, National Institute for Health Research (NIHR) UK, and Chair of INVOLVE, UK; Lee Fairclough, Vice-President, Quality Improvement, Health Quality Ontario; Michael Hillmer, Director, Planning, Research and Analysis Branch, Ontario Ministry of Health and Long-Term Care; John McLaughlin, Chief Science Officer and Senior Scientist, Public Health Ontario; Allison Paprica, Director, Strategic Partnerships, ICES; Michael Schull, President and CEO, ICES; and Vasanthi Srinivasan, Executive Director, Ontario Strategy for Patient-Oriented Research (SPOR) SUPPORT Unit (OSSU). We also want to thank John Lavis of the McMaster Health Forum for his very helpful comments on an earlier draft. Though we owe these individuals and organisations many thanks for their insights and support, we alone are responsible for the final product.

This work was commissioned by the Ontario SPOR Support Unit (OSSU). The executive director of the OSSU was one of the participants in a roundtable discussion to gather feedback on an earlier version of this paper, but beyond that, the OSSU did not have any role in the design of the study, collection, analysis or interpretation of the data, or writing of the manuscript.

Availability of data and materials

Authors’ contributions.

ADB acquired funding for the study. MJD, FAM and ADB conceptualised the study. MJD, FAM, CF and ADB participated in the review and writing of the manuscript. MJD, FAM and ADB participated in the roundtable discussion. MJD, FAM and ADB reviewed and approved the final version of the manuscript (CF passed away prior to submission of the manuscript).

Competing interests

The authors declare that they have no competing interests.

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Not applicable.

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Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Abbreviations

This article is dedicated to the memory of Dr Cy Frank, our co-author and esteemed colleague, whose untimely death occurred midway through development of this work. Among his many interests, Dr Frank was a champion for improving understanding of research impact assessment and provided many insights on the concept of research relevance, some of which we expand upon in this article. His many contributions to the health sector will live on, but he will be greatly missed.

Contributor Information

Mark J. Dobrow, Email: [email protected] .

Fiona A. Miller, Email: [email protected] .

Adalsteinn D. Brown, Email: [email protected] .

Significance of a Study: Revisiting the “So What” Question

• Open Access
• First Online: 03 December 2022

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• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  

Part of the book series: Research in Mathematics Education ((RME))

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Every researcher wants their study to matter—to make a positive difference for their professional communities. To ensure your study matters, you can formulate clear hypotheses and choose methods that will test them well, as described in Chaps. 1, 2, 3 and 4. You can go further, however, by considering some of the terms commonly used to describe the importance of studies, terms like significance, contributions, and implications. As you clarify for yourself the meanings of these terms, you learn that whether your study matters depends on how convincingly you can argue for its importance. Perhaps most surprising is that convincing others of its importance rests with the case you make before the data are ever gathered. The importance of your hypotheses should be apparent before you test them. Are your predictions about things the profession cares about? Can you make them with a striking degree of precision? Are the rationales that support them compelling? You are answering the “So what?” question as you formulate hypotheses and design tests of them. This means you can control the answer. You do not need to cross your fingers and hope as you collect data.

You have full access to this open access chapter,  Download chapter PDF

Part I. Setting the Groundwork

One of the most common questions asked of researchers is “So what?” What difference does your study make? Why are the findings important? The “so what” question is one of the most basic questions, often perceived by novice researchers as the most difficult question to answer. Indeed, addressing the “so what” question continues to challenge even experienced researchers. It is not always easy to articulate a convincing argument for the importance of your work. It can be especially difficult to describe its importance without falling into the trap of making claims that reach beyond the data.

That this issue is a challenge for researchers is illustrated by our analysis of reviewer comments for JRME . About one-third of the reviews for manuscripts that were ultimately rejected included concerns about the importance of the study. Said another way, reviewers felt the “So what?” question had not been answered. To paraphrase one journal reviewer, “The manuscript left me unsure of what the contribution of this work to the field’s knowledge is, and therefore I doubt its significance.” We expect this is a frequent concern of reviewers for all research journals.

Our goal in this chapter is to help you navigate the pressing demands of journal reviewers, editors, and readers for demonstrating the importance of your work while staying within the bounds of acceptable claims based on your results. We will begin by reviewing what we have said about these issues in previous chapters. We will then clarify one of the confusing aspects of developing appropriate arguments—the absence of consensus definitions of key terms such as significance, contributions, and implications. Based on the definitions we propose, we will examine the critical role of alignment for realizing the potential significance of your study. Because the importance of your study is communicated through your evolving research paper, we will fold suggestions for writing your paper into the discussion of creating and executing your study.

We laid the groundwork in Chap. 1 for what we consider to be important research in education:

In our view, the ultimate goal of education is to offer all students the best possible learning opportunities. So, we believe the ultimate purpose of scientific inquiry in education is to support the improvement of learning opportunities for all students…. If there is no way to imagine a connection to improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Of course, you might prefer another “ultimate purpose” for research in education. That’s fine. The critical point is that the argument for the importance of the hypotheses you are testing should be connected to the value of a long-term goal you can describe. As long as most of the educational community agrees with this goal, and you can show how testing your hypotheses will move the field forward to achieving this goal, you will have developed a convincing argument for the importance of your work.

In Chap. 2 , we argued the importance of your hypotheses can and should be established before you collect data. Your theoretical framework should carry the weight of your argument because it should describe how your hypotheses will extend what is already known. Your methods should then show that you will test your hypotheses in an appropriate way—in a way that will allow you to detect how the results did, and did not, confirm the hypotheses. This will, in turn, allow you to formulate revised hypotheses. We described establishing the importance of your study by saying, “The importance can come from the fact that, based on the results, you will be able to offer revised hypotheses that help the field better understand an issue relevant for improving all students’ learning opportunities.”

The ideas from Chaps. 1 , 2 , and 3 go a long way toward setting the parameters for what counts as an important study and how its importance can be determined. Chapter 4 focused on ensuring that the importance of a study can be realized. The next section fills in the details by proposing definitions for the most common terms used to claim importance: significance, contributions, and implications.

You might notice that we do not have a chapter dedicated to discussing the presentation of the findings—that is, a “results” chapter. We do not mean to imply that presenting results is trivial. However, we believe that if you follow our recommendations for writing your evolving research paper, presenting the results will be quite straightforward. The key is to present your results so they can be most easily compared with your predictions. This means, among other things, organizing your presentation of results according to your earlier presentation of hypotheses.

Part II. Clarifying Importance by Revisiting the Definitions of Key Terms

What does it mean to say your findings are significant? Statistical significance is clear. There are widely accepted standards for determining the statistical significance of findings. But what about educational significance? Is this the same as claiming that your study makes an important contribution? Or, that your study has important implications? Different researchers might answer these questions in different ways. When key terms like these are overused, their definitions gradually broaden or shift, and they can lose their meaning. That is unfortunate, because it creates confusion about how to develop claims for the importance of a study.

By clarifying the definitions, we hope to clarify what is required to claim that a study is significant , that it makes a contribution , and that it has important implications . Not everyone defines the terms as we do. Our definitions are probably a bit narrower or more targeted than those you may encounter elsewhere. Depending on where you want to publish your study, you may want to adapt your use of these terms to match more closely the expectations of a particular journal. But the way we define and address these terms is not antithetical to common uses. And we believe ridding the terms of unnecessary overlap allows us to discriminate among different key concepts with respect to claims for the importance of research studies. It is not necessary to define the terms exactly as we have, but it is critical that the ideas embedded in our definitions be distinguished and that all of them be taken into account when examining the importance of a study.

We will use the following definitions:

Significance: The importance of the problem, questions, and/or hypotheses for improving the learning opportunities for all students (you can substitute a different long-term goal if its value is widely shared). Significance can be determined before data are gathered. Significance is an attribute of the research problem , not the research findings .

Contributions : The value of the findings for revising the hypotheses, making clear what has been learned, what is now better understood.

Implications : Deductions about what can be concluded from the findings that are not already included in “contributions.” The most common deductions in educational research are for improving educational practice. Deductions for research practice that are not already defined as contributions are often suggestions about research methods that are especially useful or methods to avoid.

Significance

The significance of a study is built by formulating research questions and hypotheses you connect through a careful argument to a long-term goal of widely shared value (e.g., improving learning opportunities for all students). Significance applies both to the domain in which your study is located and to your individual study. The significance of the domain is established by choosing a goal of widely shared value and then identifying a domain you can show is connected to achieving the goal. For example, if the goal to which your study contributes is improving the learning opportunities for all students, your study might aim to understand more fully how things work in a domain such as teaching for conceptual understanding, or preparing teachers to attend to all students, or designing curricula to support all learners, or connecting learning opportunities to particular learning outcomes.

The significance of your individual study is something you build ; it is not predetermined or self-evident. Significance of a study is established by making a case for it, not by simply choosing hypotheses everyone already thinks are important. Although you might believe the significance of your study is obvious, readers will need to be convinced.

Significance is something you develop in your evolving research paper. The theoretical framework you present connects your study to what has been investigated previously. Your argument for significance of the domain comes from the significance of the line of research of which your study is a part. The significance of your study is developed by showing, through the presentation of your framework, how your study advances this line of research. This means the lion’s share of your answer to the “So what?” question will be developed as part of your theoretical framework.

Although defining significance as located in your paper prior to presenting results is not a definition universally shared among educational researchers, it is becoming an increasingly common view. In fact, there is movement toward evaluating the significance of a study based only on the first sections of a research paper—the sections prior to the results (Makel et al., 2021 ).

In addition to addressing the “So what?” question, your theoretical framework can address another common concern often voiced by readers: “What is so interesting? I could have predicted those results.” Predictions do not need to be surprising to be interesting and significant. The significance comes from the rationales that show how the predictions extend what is currently known. It is irrelevant how many researchers could have made the predictions. What makes a study significant is that the theoretical framework and the predictions make clear how the study will increase the field’s understanding toward achieving a goal of shared value.

An important consequence of interpreting significance as a carefully developed argument for the importance of your research study within a larger domain is that it reveals the advantage of conducting a series of connected studies rather than single, disconnected studies. Building the significance of a research study requires time and effort. Once you have established significance for a particular study, you can build on this same argument for related studies. This saves time, allows you to continue to refine your argument across studies, and increases the likelihood your studies will contribute to the field.

Contributions

As we have noted, in fields as complicated as education, it is unlikely that your predictions will be entirely accurate. If the problem you are investigating is significant, the hypotheses will be formulated in such a way that they extend a line of research to understand more deeply phenomena related to students’ learning opportunities or another goal of shared value. Often, this means investigating the conditions under which phenomena occur. This gets complicated very quickly, so the data you gather will likely differ from your predictions in a variety of ways. The contributions your study makes will depend on how you interpret these results in light of the original hypotheses.

Contributions Emerge from Revisions to your Hypotheses

We view interpreting results as a process of comparing the data with the predictions and then examining the way in which hypotheses should be revised to more fully account for the results. Revising will almost always be warranted because, as we noted, predictions are unlikely to be entirely accurate. For example, if researchers expect Outcome A to occur under specified conditions but find that it does not occur to the extent predicted or actually does occur but without all the conditions, they must ask what changes to the hypotheses are needed to predict more accurately the conditions under which Outcome A occurred. Are there, for example, essential conditions that were not anticipated and that should be included in the revised hypotheses?

Consider an example from a recently published study (Wang et al., 2021 ). A team of researchers investigated the following research question: “How are students’ perceptions of their parents’ expectations related to students’ mathematics-related beliefs and their perceived mathematics achievement?” The researchers predicted that students’ perceptions of their parents’ expectations would be highly related to students’ mathematics-related beliefs and their perceived mathematics achievement. The rationale was based largely on prior research that had consistently found parents’ general educational expectations to be highly correlated with students’ achievement.

The findings showed that Chinese high school students’ perceptions of their parents’ educational expectations were positively related to these students’ mathematics-related beliefs. In other words, students who believed their parents expected them to attain higher levels of education had more desirable mathematics-related beliefs.

However, students’ perceptions of their parents’ expectations about mathematics achievement were not related to students’ mathematics-related beliefs in the same way as the more general parental educational expectations. Students who reported that their parents had no specific expectations possessed more desirable mathematics-related beliefs than all other subgroups. In addition, these students tended to perceive their mathematics achievement rank in their class to be higher on average than students who reported that their parents expressed some level of expectation for mathematics achievement.

Because this finding was not predicted, the researchers revised the original hypothesis. Their new prediction was that students who believe their parents have no specific mathematics achievement expectations possess more positive mathematics-related beliefs and higher perceived mathematics achievement than students who believe their parents do have specific expectations. They developed a revised rationale that drew on research on parental pressure and mathematics anxiety, positing that parents’ specific mathematics achievement expectations might increase their children’s sense of pressure and anxiety, thus fostering less positive mathematics-related beliefs. The team then conducted a follow-up study. Their findings aligned more closely with the new predictions and affirmed the better explanatory power of the revised rationale. The contributions of the study are found in this increased explanatory power—in the new understandings of this phenomenon contained in the revisions to the rationale.

Interpreting findings in order to revise hypotheses is not a straightforward task. Usually, the rationales blend multiple constructs or variables and predict multiple outcomes, with different outcomes connected to different research questions and addressed by different sets of data. Nevertheless, the contributions of your study depend on specifying the differences between your original hypotheses and your revised hypotheses. What can you explain now that you could not explain before?

We believe that revising hypotheses is an optimal response to any question of contributions because a researcher’s initial hypotheses plus the revisions suggested by the data are the most productive way to tie a study into the larger chain of research of which it is a part. Revised hypotheses represent growth in knowledge. Building on other researchers’ revised hypotheses and revising them further by more explicitly and precisely describing the conditions that are expected to influence the outcomes in the next study accumulates knowledge in a form that can be recorded, shared, built upon, and improved.

The significance of your study is presented in the opening sections of your evolving research paper whereas the contributions are presented in the final section, after the results. In fact, the central focus in this “Discussion” section should be a specification of the contributions (note, though, that this guidance may not fully align with the requirements of some journals).

Contributions Answer the Question of Generalizability

A common and often contentious, confusing issue that can befuddle novice and experienced researchers alike is the generalizability of results. All researchers prefer to believe the results they report apply to more than the sample of participants in their study. How important would a study be if the results applied only to, say, two fourth-grade classrooms in one school, or to the exact same tasks used as measures? How do you decide to which larger population (of students or tasks) your results could generalize? How can you state your claims so they are precisely those justified by the data?

To illustrate the challenge faced by researchers in answering these questions, we return to the JRME reviewers. We found that 30% of the reviews expressed concerns about the match between the results and the claims. For manuscripts that ultimately received a decision of Reject, the majority of reviewers said the authors had overreached—the claims were not supported by the data. In other words, authors generalized their claims beyond those that could be justified.

The Connection Between Contributions and Generalizability

In our view, claims about contributions can be examined productively alongside considerations of generalizability. To make the case for this view, we need to back up a bit. Recall that the purpose of research is to understand a phenomenon. To understand a phenomenon, you need to determine the conditions under which it occurs. Consequently, productive hypotheses specify the conditions under which the predictions hold and explain why and how these conditions make a difference. And the conditions set the parameters on generalizability. They identify when, where, and for whom the effect or situation will occur. So, hypotheses describe the extent of expected generalizability, and revised hypotheses that contain the contributions recalibrate generalizability and offer new predictions within these parameters.

An Example That Illustrates the Connection

In Chap. 4 , we introduced an example with a research question asking whether second graders improve their understanding of place value after a specially designed instructional intervention. We suggested asking a few second and third graders to complete your tasks to see if they generated the expected variation in performance. Suppose you completed this pilot study and now have satisfactory tasks. What conditions might influence the effect of the intervention? After careful study, you developed rationales that supported three conditions: the entry level of students’ understanding, the way in which the intervention is implemented, and the classroom norms that set expectations for students’ participation.

Suppose your original hypotheses predicted the desired effect of the intervention only if the students possessed an understanding of several concepts on which place value is built, only if the intervention was implemented with fidelity to the detailed instructional guidelines, and only if classroom norms encouraged students to participate in small-group work and whole-class discussions. Your claims of generalizability will apply to second-grade settings with these characteristics.

Now suppose you designed the study so the intervention occurred in five second-grade classrooms that agreed to participate. The pre-intervention assessment showed all students with the minimal level of entry understanding. The same well-trained teacher was employed to teach the intervention in all five classrooms, none of which included her own students. And you learned from prior observations and reports of the classroom teachers that three of the classrooms operated with the desired classroom norms, but two did not. Because of these conditions, your study is now designed to test one of your hypotheses—the desired effect will occur only if classroom norms encouraged students to participate in small-group work and whole-class discussions. This is the only condition that will vary; the other two (prior level of understanding and fidelity of implementation) are the same across classrooms so you will not learn how these affect the results.

Suppose the classrooms performed equally well on the post-intervention assessments. You expected lower performance in the two classrooms with less student participation, so you need to revise your hypotheses. The challenge is to explain the higher-than-expected performance of these students. Because you were interested in understanding the effects of this condition, you observed several lessons in all the classrooms during the intervention. You can now use this information to explain why the intervention worked equally well in classrooms with different norms.

Your revised hypothesis captures this part of your study’s contribution. You can now say more about the ways in which the intervention can help students improve their understanding of place value because you have different information about the role of classroom norms. This, in turn, allows you to specify more precisely the nature and extent of the generalizability of your findings. You now can generalize your findings to classrooms with different norms. However, because you did not learn more about the impact of students’ entry level understandings or of different kinds of implementation, the generalizability along these dimensions remains as limited as before.

This example is simplified. In many studies, the findings will be more complicated, and more conditions will likely be identified, some of which were anticipated and some of which emerged while conducting the study and analyzing the data. Nevertheless, the point is that generalizability should be tied to the conditions that are expected to affect the results. Further, unanticipated conditions almost always appear, so generalizations should be conservative and made with caution and humility. They are likely to change after testing the new predictions.

Contributions Are Assured When Hypotheses Are Significant and Methods Are Appropriate and Aligned

We have argued that the contributions of your study are produced by the revised hypotheses you can formulate based on your results. Will these revisions always represent contributions to the field? What if the revisions are minor? What if your results do not inform revisions to your hypotheses?

We will answer these questions briefly now and then develop them further in Part IV of this chapter. The answer to the primary question is “yes,” your revisions will always be a contribution to the field if (1) your hypotheses are significant and (2) you crafted appropriate methods to test the hypotheses. This is true even if your revisions are minor or if your data are not as informative as you expected. However, this is true only if you meet the two conditions in the earlier sentence. The first condition (significant hypotheses) can be satisfied by following the suggestions in the earlier section on significance. The second condition (appropriate methods) is addressed further in Part III in this chapter.

Implications

Before examining the role of methods in connecting significance with important contributions, we elaborate briefly our definition of “implications.” We reserve implications for the conclusions you can logically deduce from your findings that are not already presented as contributions. This means that, like contributions, implications are presented in the Discussion section of your research paper.

Many educational researchers present two types of implications: implications for future research and implications for practice. Although we are aware of this common usage, we believe our definition of “contributions” cover these implications. Clarifying why we call these “contributions” will explain why we largely reserve the word “implications” for recommendations regarding methods.

Implications for Future Research

Implications for future research often include (1) recommendations for empirical studies that would extend the findings of this study, (2) inferences about the usefulness of theoretical constructs, and (3) conclusions about the advisability of using particular kinds of methods. Given our earlier definitions, we prefer to label the first two types of implications as contributions.

Consider recommendations for empirical studies. After analyzing the data and presenting the results, we have suggested you compare the results with those predicted, revise the rationales for the original predictions to account for the results, and make new predictions based on the revised rationales. It is precisely these new predictions that can form the basis for recommending future research. Testing these new predictions is what would most productively extend this line of research. It can sometimes sound as if researchers are recommending future studies based on hunches about what research might yield useful findings. But researchers can do better than this. It would be more productive to base recommendations on a careful analysis of how the predictions of the original study could be sharpened and improved.

Now consider inferences about the usefulness of theoretical constructs. Our argument for labeling these inferences as contributions is similar. Rationales for predictions are where the relevant theoretical constructs are located. Revisions to these rationales based on the differences between the results and the predictions reveal the theoretical constructs that were affirmed to support accurate predictions and those that must be revised. In our view, usefulness is determined through this revision process.

Implications that do not come under our meaning of contributions are in the third type of implications, namely the appropriateness of methods for generating rich contributions. These kinds of implications are produced by your evaluation of your methods: research design, sampling procedures, tasks, data collection procedures, and data analyses. Although not always included in the discussion of findings, we believe it would be helpful for researchers to identify particular methods that were useful for conducting their study and those that should be modified or avoided. We believe these are appropriately called implications.

Implications for Practice

If the purpose of research is to better understand how to improve learning opportunities for all students, then it is appropriate to consider whether implications for improving educational practice can be drawn from the results of a study. How are these implications formulated? This is an important question because, in our view, these claims often come across as an afterthought, “Oh, I need to add some implications for practice.” But here is the sobering reality facing researchers: By any measure, the history of educational research shows that identifying these implications has had little positive effect on practice.

Perhaps the most challenging task for researchers who attempt to draw implications for practice is to interpret their findings for appropriate settings. A researcher who studied the instructional intervention for second graders on place value and found that average performance in the intervention classrooms improved more than in the textbook classrooms might be tempted to draw implications for practice. What should the researcher say? That second-grade teachers should adopt the intervention? Such an implication would be an overreach because, as we noted earlier, the findings cannot be generalized to all second-grade classrooms. Moreover, an improvement in average performance does not mean the intervention was better for all students.

The challenge is to identify the conditions under which the intervention would improve the learning opportunities for all students. Some of these conditions will be identified as the theoretical framework is built because the predictions need to account for these conditions. But some will be unforeseen, and some that are identified will not be informed by the findings. Recall that, in the study described earlier, a condition of entry level of understanding was hypothesized but the design of the study did not allow the researcher to draw any conclusions about its effect.

What can researchers say about implications for practice given the complexities involved in generalizing findings to other settings? We offer two recommendations. First, because it is difficult to specify all the conditions under which a phenomenon occurs, it is rarely appropriate to prescribe an educational practice. Researchers cannot anticipate the conditions under which individual teachers operate, conditions that often require adaptation of a suggested practice rather than implementation of a practice as prescribed.

Our second recommendation comes from returning to the purpose for educational research—to understand more fully how to improve learning opportunities for all students (or to achieve another goal of widely shared value). As we have described, understanding comes primarily from building and reevaluating rationales for your predictions. If you reach a new understanding related to improving learning opportunities, an understanding that could have practical implications, we recommend you share this understanding as an implication for practice.

For example, suppose the researcher who found better average performance of second graders after the intervention on place value had also studied several conditions under which performance improved. And suppose the researcher found that most students who did not improve their performance misunderstood a concept that appeared early in the intervention (e.g., the multiplicative relationship between positional values of a numeral). An implication for practice the researcher might share would be to describe the potential importance of understanding this concept early in the sequence of activities if teachers try out this intervention.

If you use our definitions, these implications for practice would be presented as contributions because they emerge directly from reevaluating and revising your rationales. We believe it is appropriate to use “Contributions” as the heading for this section in the Discussion section of your research paper. However, if editors prefer “Implications” we recommend following their suggestion.

We want to be clear that the terms you use for the different ways your study is important is not critical. We chose to define the terms significance, contributions, and implications in very specific and not universally shared ways to distinguish all the meanings of importance you should consider. Some of these can be established through your theoretical framework, some by the revisions of your hypotheses, and some by reflecting on the value of particular methods. The important thing, from our point of view, is that the ideas we defined for each of these terms are distinguished and recognized as specific ways of determining the importance of your study.

Part III. The Role of Methods in Determining Contributions

We have argued that every part of the study (and of the evolving research paper) should be aligned. All parts should be connected through a coherent chain of reasoning. In this chapter, we argue that the chain of reasoning is not complete until the methods are presented and the results are interpreted and discussed. The methods of the study create a bridge that connects the introductory material (research questions, theoretical framework, literature review, hypotheses) with the results and interpretations.

The role that methods play in scientific inquiry is to ensure that your hypotheses will be tested appropriately so the significance of your study will yield its potential contributions. To do this, the methods must do more than follow the standard guidelines and be technically correct (see Chap. 4 ). They must also fit with the surrounding parts of the study. We call this coherence.

Coherence Across the Phases of Scientific Inquiry

Coherence means the parts of a whole are fully aligned. When doing scientific inquiry, the early parts or phases should motivate the later phases. The methods you use should be motivated or explained by the earlier phases (e.g., research questions, theoretical framework, hypotheses). Your methods, in turn, should produce results that can be interpreted by comparing them with your predictions. Methods are aligned with earlier phases when you can use the rationales contained in your hypotheses to decide what kinds of data are needed to test your predictions, how best to gather these kinds of data, and what analyses should be performed (see Chap. 4 and Cai et al., 2019a ).

For a visual representation of this coherence, see Fig. 5.1 . Each box identifies an aspect of scientific inquiry. Hypotheses (shown in Box 1) include the rationales and predictions. Because the rationales encompass the theoretical framework and the literature review, Box 1 establishes the significance of the study. Box 2 represents the methods, which we defined in Chap. 4 as the entire set of procedures you will use, including the basic design, measures for collecting data, and analytic approaches. In Fig. 5.1 , the hypothesis in Box 1 points you to the methods you will use. That is, you will choose methods that provide data for analyses that will generate results or findings (Box 3) that allow you to make comparisons against your predictions. Based on those comparisons, you will revise your hypotheses and derive the contributions and implications of your study (Box 4).

The Chain of Coherence That Runs Through All Parts of a Research Study

We intend Fig. 5.1 to carry several messages. One is that coherence of a study and the associated research paper require all aspects of the study to flow from one into the other. Each set of prior entries must motivate and justify the next one. For example, the data and analyses you intend to gather and use in Box 2 (Methods) must be those that are motivated and explained by the research question and hypothesis (prediction and rationale) in Box 1.

A second message in the figure is that coherence includes Box 4, “Discussion.” Aligned with the first three boxes, the fourth box flows from these boxes but is also constrained by them. The contributions and implications authors describe in the Discussion section of the paper cannot go beyond what is allowed by the original hypotheses and the revisions to these hypotheses indicated by the findings.

Methods Enable Significance to Yield Contributions

We begin this section by identifying a third message conveyed in Fig. 5.1 . The methods of the study, represented by Box 2, provide a bridge that connects the significance of the study (Box 1) with the contributions of the study (Box 4). The results (Box 3) indicate the nature of the contributions by determining the revisions to the original hypotheses.

In our view, the connecting role played by the methods is often underappreciated. Crafting appropriate methods aligned with the significance of the study, on one hand, and the interpretations, on the other, can determine whether a study is judged to make a contribution.

If the hypotheses are established as significant, and if appropriate methods are used to test the predictions, the study will make important contributions even if the data are not statistically significant. We can say this another way. When researchers establish the significance of the hypotheses (i.e., convince readers they are of interest to the field) and use methods that provide a sound test of these hypotheses, the data they present will be of interest regardless of how they turn out. This is why Makel et al. ( 2021 ) endorse a review process for publication that emphasizes the significance of the study as presented in the first sections of a research paper.

Treating the methods as connecting the introductory arguments to the interpretations of data prevent researchers from making a common mistake: When writing the research paper, some researchers lose track of the research questions and/or the predictions. In other words, results are presented but are not interpreted as answers to the research questions or compared with the predictions. It is as if the introductory material of the paper begins one story, and the interpretations of results ends a different story. Lack of alignment makes it impossible to tell one coherent story.

A final point is that the alignment of a study cannot be evaluated and appreciated if the methods are not fully described. Methods must be described clearly and completely in the research paper so readers can see how they flow from the earlier phases of the study and how they yield the data presented. We suggested in Chap. 4 a rule of thumb for deciding whether the methods have been fully described: “Readers should be able to replicate the study if they wish.”

Part IV. Special Considerations that Affect a Study’s Contributions

We conclude Chap. 5 by addressing two additional issues that can affect how researchers interpret the results and make claims about the contributions of a study. Usually, researchers deal with these issues in the Discussion section of their research paper, but we believe it is useful to consider them as you plan and conduct your study. The issues can be posed as questions: How should I treat the limitations of my study? How should I deal with findings that are completely unexpected?

Limitations of a Study

We can identify two kinds of limitations: (1) limitations that constrain your ability to interpret your results because of unfortunate choices you made, and (2) limitations that constrain your ability to generalize your results because of missing variables you could not fit into the scope of your study or did not anticipate. We recommend different ways of dealing with these.

Limitations Due to Unfortunate Choices

All researchers make unfortunate choices. These are mistakes that could have been prevented. Often, they are choices in how a study was designed and/or executed. Maybe the sample did not have the characteristics assumed, or a task did not assess what was expected, or the intervention was not implemented as planned. Although many unfortunate choices can be prevented by thinking through the consequences of every decision or by conducting a well-designed pilot study or two, some will occur anyway. How should you deal with them?

The consequence of unfortunate choices is that the data do not test the hypotheses as precisely or completely as hoped. When this happens, the data must be interpreted with these constraints in mind. Almost always, this limits the researcher to making fewer or narrower claims than desired about differences and similarities between the results and the predictions. Usually this means conclusions about the ways in which the rationales must be revised require extra qualifications. In other words, claims about contributions of the study must be made with extra caution.

Research papers frequently include a subsection in the Discussion called “Limitations of the Study.” Researchers often use this subsection to identify the study’s limitations by describing the unfortunate choices, but they do not always spell out how these limitations should affect the contributions of the paper. Sometimes, it appears that researchers are simply checking off a requirement to identify the limitations by saying something like “The results should be interpreted with caution.” But this does not help readers understand exactly what cautions should be applied and it does not hold researchers accountable for the limitations.

We recommend something different. We suggest you do the hard work of figuring out how the data should be interpreted in light of the limitations and share these details with the readers. You might do this when the results are presented or when you interpret them. Rather than presenting your claims about the contributions of the study and then saying readers should interpret these with “caution” because of the study’s limitations, we suggest presenting only those interpretations and claims of contributions that can be made with the limitations in mind.

One way to think about the constraints you will likely need to impose on your interpretations is in terms of generalizability. Recall that earlier in this chapter, we described the close relationship between contributions and generalizability. When generalizability is restricted, so are contributions.

Limitations Due to Missing Variables

Because of the complexity of problems, questions, and hypotheses explored in educational research, researchers are unlikely to anticipate in their studies all the variables that affect the data and results. In addition, tradeoffs often must be made. Researchers cannot study everything at once, so decisions must be made about which variables to study carefully and which to either control or ignore.

In the earlier example of studying whether second graders improve their understanding of place value after a specially designed instructional intervention, the researcher identified three variables that were expected to influence the effect of the intervention: students’ entry level of understanding, implementation of the intervention, and norms of the classrooms in which the intervention was implemented. The researcher decided to control the implementation variable by hiring one experienced teacher to implement the intervention in all the classrooms. This meant the variable of individual teacher differences was not included in the study and the researcher could not generalize to classrooms with these differences.

Some researchers might see controlling the implementation of the intervention as a limitation. We do not. As a factor that is not allowed to vary, it constrains the generalizations a researcher can make, but we believe these kinds of controlled variables are better treated as opportunities for future research. Perhaps the researcher’s observations in the classroom provided information that could be used to make some predictions about which elements of the intervention are essential and which are optional—about which aspects of the intervention must be implemented as written and which can vary with different teachers. When revising the rationales to show what was learned in this study, the researcher could include rationales for new, tentative predictions about the effects of the intervention in classrooms where implementation differed in specified ways. These predictions create a genuine contribution of the study. If you use our definitions, these new predictions, often presented under “implications for future research,” would be presented as “contributions.”

Notice that if you follow our advice, you would not need to include a separate section in the Discussion of your paper labeled “Limitations.” We acknowledge, however, that some journal editors recommend such a subsection. In this case, we suggest you include this subsection along with treating the two different kinds of limitations as we recommend. You can do both.

Dealing with Unexpected Findings

Researchers are often faced with unexpected and perhaps surprising results, even when they have developed a convincing theoretical framework, posed research questions tightly connected to this framework, presented predictions about expected outcomes, and selected methods that appropriately test these predictions. Indeed, the unexpected findings can be the most interesting and valuable products of the study. They can range from mildly surprising to “Wow. I didn’t expect that.” How should researchers treat such findings? Our answer is based on two principles.

The first principle is that the value of research does not lie in whether the predictions are completely accurate but in helping the field learn more about the explanatory power of theoretical frameworks. That is, the value lies in the increased understanding of phenomena generated by examining the ability of theoretical frameworks (or rationales) to predict outcomes and explain results. The second principle, a corollary to the first, is to treat unexpected findings in a way that is most educative for the reader.

Based on our arguments to this point, you could guess we will say there will always be unexpected findings. Predicted answers to significant research questions in education will rarely, if ever, be entirely accurate. So, you can count on dealing with unexpected findings.

Consistent with the two principles above, your goal should be to use unexpected findings to understand more fully the phenomenon under investigation. We recommend one of three different paths. The choice of which path to take depends on what you decide after reflecting again on the decisions you made at each phase of the study.

The first path is appropriate when researchers reexamine their theoretical framework in light of the unexpected findings and decide that it is still a compelling framework based on previous work. They reason that readers are likely to have been convinced by this framework and would likely have made similar predictions. In this case, we believe that it is educative for researchers to (a) summarize their initial framework, (b) present the findings and distinguish those that were aligned with the predictions from those that were not, and (c) explain why the theoretical framework was inadequate and propose changes to the framework that would have created more alignment with the unexpected findings.

Revisions to initial hypotheses are especially useful if they include explanations for why a researcher might have been wrong (and researchers who ask significant questions in domains as complex as education are almost always wrong in some way). Depending on the ways in which the revised framework differs from the original, the authors have two options. If the revised framework is an expansion of the original, it would be appropriate for the authors to propose directions for future research that would extend this study. Alternatively, if the revised framework is still largely within the scope of the original study and consists of revisions to the original hypotheses, the revisions could guide a second study to check the adequacy of the revisions. This second study could be conducted by the same researchers (perhaps before the final manuscript is written and presented as two parts of the same report) or it could be proposed in the Discussion as a specific study that could be conducted by other researchers.

The second path is appropriate when researchers reexamine their theoretical framework in light of the unexpected findings and recognize serious flaws in the framework. The flaws could result from a number of factors, including defining elements of the framework in too general a way to formulate well-grounded hypotheses, failing to include a variable, or not accounting carefully enough for the previous work in this domain, both theoretical and empirical. In many of these cases, readers would not be well served by reading a poorly developed framework and then learning that the framework, which had not been convincing, did not accurately predict the results. Before scrapping the study and starting over, we suggest stepping back and reexamining the framework. Is it possible to develop a more coherent, complete, and convincing framework? Would this framework predict the results more accurately? If the findings remain unexpected based on the predictions generated by this revised, more compelling framework, then the first path applies.

It is likely that the new framework will better predict the findings. After all, the researchers now know the findings they will report. However, it is unlikely that the framework will accurately predict all the findings. This is because the framework is not built around the findings of this study of which authors are now aware (but have not yet been presented). Frameworks are built on research and theory already published. This means the redesigned framework is built from exactly the same empirical findings and theoretical arguments available before the study was conducted. The redesigned framework also is constrained by needing to justify exactly those methods used in the study. The redesigned framework cannot justify different methods or even slightly altered methods. The task for researchers is to show how the new theoretical framework necessarily generates, using the same methods, the predictions they present in the research paper. Just as before, it is unlikely this framework can account for all the findings. Just as before, after presenting the results the researchers should explain why they believe particular hypotheses were confirmed and why others should be revised, even in small ways, based on the findings reported. Researchers can now use these findings to revise the hypotheses presented in the paper. The point we are making is that we believe it is acceptable to reconstruct frameworks before writing research reports if doing so would be more educative for the reader.

Finally, the third path becomes appropriate when researchers, in reexamining their theoretical framework, trace the problem to a misalignment between the methods they used and the theoretical framework or the research questions. Perhaps the researchers recognize that the tasks they used did not yield data that could test the predictions and address the research questions. Or perhaps the researchers realize that the sample they selected would likely have been heavily influenced by a factor they failed to take into account. In other words, the researchers decide that the unexpected findings were due to a problem with the methods they used, not with the framework or the accompanying predictions. In this case, we recommend that the researchers correct the methodological problems and conduct the study again.

Part V. A Few Suggestions for Structuring Your Discussion Section

Writing the Discussion section of your research paper can be overwhelming given all our suggestions about what to include in this section. Here are a few tips that might help you create a simple template for this section.

We recommend the Discussion begin with a brief summary of the main results, especially those you will interpret in this section. This summary should not contain new data or results not previously presented in the paper.

The Discussion could then move to presenting the contributions in the ways we have described. To do this you could point out the ways in which the results differed from the predictions and suggest revisions to your rationales that would have better predicted the results. Doing this will show how the contributions of your study extend what is known beyond the research you drew on to build your original rationale. You can then propose how to extend your contributions to research by proposing future research studies that would test your new predictions. If you believe the revisions you make to your rationales produce new insights or understandings that could be helpful for educational practitioners, you can identify these contributions to practice as well. This comprises the bulk of the Discussion section.

If you have embedded the limitations in earlier sections of the paper, you will have presented your results and interpreted your findings constrained by these limitations. If you choose (or are asked) to describe limitations in the Discussion, you could identify the limitations and then point to the ways they affected your interpretations of the findings. Finally, the Discussion could conclude with the implications of the study for methodological choices that could improve research in the domain in which your study is located or how future studies could overcome the limitations you identified.

Because we are providing guidance on writing your research paper for publication, we will reiterate here that you should investigate the expectations and conventions of the journal to which you will submit your paper. Usually, it will be acceptable to use the terms “significance,” “contributions,” and “implications” as we have defined them. However, if the editors expect you to use the terms differently, follow the editors’ expectations. Our definitions in this chapter are meant to help you think clearly about the different ways you can make a case for the importance of your research. What matters is that you have carefully built and described a coherent chain of scientific inquiry that allows your study to translate the significance of your research problem into contributions to the field.

We began the chapter with the “So what?” question. The question looks simple and straightforward but is challenging and complicated. Its simple appearance can lead researchers to believe it should have a simple answer. But it almost never does. In this chapter, we tried to address the many complications that arise when answering the question. We hope you now have some new insights and new tools for answering the question in your next study.

Cai, J., Morris, A., Hohensee, C., Hwang, S., Robison, V., Cirillo, M., Kramer, S. L., & Hiebert, J. (2019a). Choosing and justifying robust methods for educational research. Journal for Research in Mathematics Education, 50 (4), 342–348. https://doi.org/10.5951/jresematheduc.50.2.0114

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Wang, G., Zhang, S., & Cai, J. (2021). How are parental expectations related to students’ beliefs and their perceived achievement? Educational Studies in Mathematics., 108 , 429–450. https://doi.org/10.1007/s10649-021-10073-w

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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). Significance of a Study: Revisiting the “So What” Question. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_5

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Home » Background of The Study – Examples and Writing Guide

Background of The Study – Examples and Writing Guide

Table of Contents

Background of The Study

Definition:

Background of the study refers to the context, circumstances, and history that led to the research problem or topic being studied. It provides the reader with a comprehensive understanding of the subject matter and the significance of the study.

The background of the study usually includes a discussion of the relevant literature, the gap in knowledge or understanding, and the research questions or hypotheses to be addressed. It also highlights the importance of the research topic and its potential contributions to the field. A well-written background of the study sets the stage for the research and helps the reader to appreciate the need for the study and its potential significance.

How to Write Background of The Study

Here are some steps to help you write the background of the study:

Identify the Research Problem

Start by identifying the research problem you are trying to address. This problem should be significant and relevant to your field of study.

Provide Context

Once you have identified the research problem, provide some context. This could include the historical, social, or political context of the problem.

Review Literature

Conduct a thorough review of the existing literature on the topic. This will help you understand what has been studied and what gaps exist in the current research.

Identify Research Gap

Based on your literature review, identify the gap in knowledge or understanding that your research aims to address. This gap will be the focus of your research question or hypothesis.

State Objectives

Clearly state the objectives of your research . These should be specific, measurable, achievable, relevant, and time-bound (SMART).

Discuss Significance

Explain the significance of your research. This could include its potential impact on theory , practice, policy, or society.

Finally, summarize the key points of the background of the study. This will help the reader understand the research problem, its context, and its significance.

How to Write Background of The Study in Proposal

The background of the study is an essential part of any proposal as it sets the stage for the research project and provides the context and justification for why the research is needed. Here are the steps to write a compelling background of the study in your proposal:

• Identify the problem: Clearly state the research problem or gap in the current knowledge that you intend to address through your research.
• Provide context: Provide a brief overview of the research area and highlight its significance in the field.
• Review literature: Summarize the relevant literature related to the research problem and provide a critical evaluation of the current state of knowledge.
• Identify gaps : Identify the gaps or limitations in the existing literature and explain how your research will contribute to filling these gaps.
• Justify the study : Explain why your research is important and what practical or theoretical contributions it can make to the field.
• Highlight objectives: Clearly state the objectives of the study and how they relate to the research problem.
• Discuss methodology: Provide an overview of the methodology you will use to collect and analyze data, and explain why it is appropriate for the research problem.
• Conclude : Summarize the key points of the background of the study and explain how they support your research proposal.

How to Write Background of The Study In Thesis

The background of the study is a critical component of a thesis as it provides context for the research problem, rationale for conducting the study, and the significance of the research. Here are some steps to help you write a strong background of the study:

• Identify the research problem : Start by identifying the research problem that your thesis is addressing. What is the issue that you are trying to solve or explore? Be specific and concise in your problem statement.
• Review the literature: Conduct a thorough review of the relevant literature on the topic. This should include scholarly articles, books, and other sources that are directly related to your research question.
• I dentify gaps in the literature: After reviewing the literature, identify any gaps in the existing research. What questions remain unanswered? What areas have not been explored? This will help you to establish the need for your research.
• Establish the significance of the research: Clearly state the significance of your research. Why is it important to address this research problem? What are the potential implications of your research? How will it contribute to the field?
• Provide an overview of the research design: Provide an overview of the research design and methodology that you will be using in your study. This should include a brief explanation of the research approach, data collection methods, and data analysis techniques.
• State the research objectives and research questions: Clearly state the research objectives and research questions that your study aims to answer. These should be specific, measurable, achievable, relevant, and time-bound.
• Summarize the chapter: Summarize the chapter by highlighting the key points and linking them back to the research problem, significance of the study, and research questions.

How to Write Background of The Study in Research Paper

Here are the steps to write the background of the study in a research paper:

• Identify the research problem: Start by identifying the research problem that your study aims to address. This can be a particular issue, a gap in the literature, or a need for further investigation.
• Conduct a literature review: Conduct a thorough literature review to gather information on the topic, identify existing studies, and understand the current state of research. This will help you identify the gap in the literature that your study aims to fill.
• Explain the significance of the study: Explain why your study is important and why it is necessary. This can include the potential impact on the field, the importance to society, or the need to address a particular issue.
• Provide context: Provide context for the research problem by discussing the broader social, economic, or political context that the study is situated in. This can help the reader understand the relevance of the study and its potential implications.
• State the research questions and objectives: State the research questions and objectives that your study aims to address. This will help the reader understand the scope of the study and its purpose.
• Summarize the methodology : Briefly summarize the methodology you used to conduct the study, including the data collection and analysis methods. This can help the reader understand how the study was conducted and its reliability.

Examples of Background of The Study

Here are some examples of the background of the study:

Problem : The prevalence of obesity among children in the United States has reached alarming levels, with nearly one in five children classified as obese.

Significance : Obesity in childhood is associated with numerous negative health outcomes, including increased risk of type 2 diabetes, cardiovascular disease, and certain cancers.

Gap in knowledge : Despite efforts to address the obesity epidemic, rates continue to rise. There is a need for effective interventions that target the unique needs of children and their families.

Problem : The use of antibiotics in agriculture has contributed to the development of antibiotic-resistant bacteria, which poses a significant threat to human health.

Significance : Antibiotic-resistant infections are responsible for thousands of deaths each year and are a major public health concern.

Gap in knowledge: While there is a growing body of research on the use of antibiotics in agriculture, there is still much to be learned about the mechanisms of resistance and the most effective strategies for reducing antibiotic use.

Edxample 3:

Problem : Many low-income communities lack access to healthy food options, leading to high rates of food insecurity and diet-related diseases.

Significance : Poor nutrition is a major contributor to chronic diseases such as obesity, type 2 diabetes, and cardiovascular disease.

Gap in knowledge : While there have been efforts to address food insecurity, there is a need for more research on the barriers to accessing healthy food in low-income communities and effective strategies for increasing access.

Examples of Background of The Study In Research

Here are some real-life examples of how the background of the study can be written in different fields of study:

Example 1 : “There has been a significant increase in the incidence of diabetes in recent years. This has led to an increased demand for effective diabetes management strategies. The purpose of this study is to evaluate the effectiveness of a new diabetes management program in improving patient outcomes.”

Example 2 : “The use of social media has become increasingly prevalent in modern society. Despite its popularity, little is known about the effects of social media use on mental health. This study aims to investigate the relationship between social media use and mental health in young adults.”

Example 3: “Despite significant advancements in cancer treatment, the survival rate for patients with pancreatic cancer remains low. The purpose of this study is to identify potential biomarkers that can be used to improve early detection and treatment of pancreatic cancer.”

Examples of Background of The Study in Proposal

Here are some real-time examples of the background of the study in a proposal:

Example 1 : The prevalence of mental health issues among university students has been increasing over the past decade. This study aims to investigate the causes and impacts of mental health issues on academic performance and wellbeing.

Example 2 : Climate change is a global issue that has significant implications for agriculture in developing countries. This study aims to examine the adaptive capacity of smallholder farmers to climate change and identify effective strategies to enhance their resilience.

Example 3 : The use of social media in political campaigns has become increasingly common in recent years. This study aims to analyze the effectiveness of social media campaigns in mobilizing young voters and influencing their voting behavior.

Example 4 : Employee turnover is a major challenge for organizations, especially in the service sector. This study aims to identify the key factors that influence employee turnover in the hospitality industry and explore effective strategies for reducing turnover rates.

Examples of Background of The Study in Thesis

Here are some real-time examples of the background of the study in the thesis:

Example 1 : “Women’s participation in the workforce has increased significantly over the past few decades. However, women continue to be underrepresented in leadership positions, particularly in male-dominated industries such as technology. This study aims to examine the factors that contribute to the underrepresentation of women in leadership roles in the technology industry, with a focus on organizational culture and gender bias.”

Example 2 : “Mental health is a critical component of overall health and well-being. Despite increased awareness of the importance of mental health, there are still significant gaps in access to mental health services, particularly in low-income and rural communities. This study aims to evaluate the effectiveness of a community-based mental health intervention in improving mental health outcomes in underserved populations.”

Example 3: “The use of technology in education has become increasingly widespread, with many schools adopting online learning platforms and digital resources. However, there is limited research on the impact of technology on student learning outcomes and engagement. This study aims to explore the relationship between technology use and academic achievement among middle school students, as well as the factors that mediate this relationship.”

Examples of Background of The Study in Research Paper

Here are some examples of how the background of the study can be written in various fields:

Example 1: The prevalence of obesity has been on the rise globally, with the World Health Organization reporting that approximately 650 million adults were obese in 2016. Obesity is a major risk factor for several chronic diseases such as diabetes, cardiovascular diseases, and cancer. In recent years, several interventions have been proposed to address this issue, including lifestyle changes, pharmacotherapy, and bariatric surgery. However, there is a lack of consensus on the most effective intervention for obesity management. This study aims to investigate the efficacy of different interventions for obesity management and identify the most effective one.

Example 2: Antibiotic resistance has become a major public health threat worldwide. Infections caused by antibiotic-resistant bacteria are associated with longer hospital stays, higher healthcare costs, and increased mortality. The inappropriate use of antibiotics is one of the main factors contributing to the development of antibiotic resistance. Despite numerous efforts to promote the rational use of antibiotics, studies have shown that many healthcare providers continue to prescribe antibiotics inappropriately. This study aims to explore the factors influencing healthcare providers’ prescribing behavior and identify strategies to improve antibiotic prescribing practices.

Example 3: Social media has become an integral part of modern communication, with millions of people worldwide using platforms such as Facebook, Twitter, and Instagram. Social media has several advantages, including facilitating communication, connecting people, and disseminating information. However, social media use has also been associated with several negative outcomes, including cyberbullying, addiction, and mental health problems. This study aims to investigate the impact of social media use on mental health and identify the factors that mediate this relationship.

Purpose of Background of The Study

The primary purpose of the background of the study is to help the reader understand the rationale for the research by presenting the historical, theoretical, and empirical background of the problem.

More specifically, the background of the study aims to:

• Provide a clear understanding of the research problem and its context.
• Identify the gap in knowledge that the study intends to fill.
• Establish the significance of the research problem and its potential contribution to the field.
• Highlight the key concepts, theories, and research findings related to the problem.
• Provide a rationale for the research questions or hypotheses and the research design.
• Identify the limitations and scope of the study.

When to Write Background of The Study

The background of the study should be written early on in the research process, ideally before the research design is finalized and data collection begins. This allows the researcher to clearly articulate the rationale for the study and establish a strong foundation for the research.

The background of the study typically comes after the introduction but before the literature review section. It should provide an overview of the research problem and its context, and also introduce the key concepts, theories, and research findings related to the problem.

Writing the background of the study early on in the research process also helps to identify potential gaps in knowledge and areas for further investigation, which can guide the development of the research questions or hypotheses and the research design. By establishing the significance of the research problem and its potential contribution to the field, the background of the study can also help to justify the research and secure funding or support from stakeholders.

Advantage of Background of The Study

The background of the study has several advantages, including:

• Provides context: The background of the study provides context for the research problem by highlighting the historical, theoretical, and empirical background of the problem. This allows the reader to understand the research problem in its broader context and appreciate its significance.
• Identifies gaps in knowledge: By reviewing the existing literature related to the research problem, the background of the study can identify gaps in knowledge that the study intends to fill. This helps to establish the novelty and originality of the research and its potential contribution to the field.
• Justifies the research : The background of the study helps to justify the research by demonstrating its significance and potential impact. This can be useful in securing funding or support for the research.
• Guides the research design: The background of the study can guide the development of the research questions or hypotheses and the research design by identifying key concepts, theories, and research findings related to the problem. This ensures that the research is grounded in existing knowledge and is designed to address the research problem effectively.
• Establishes credibility: By demonstrating the researcher’s knowledge of the field and the research problem, the background of the study can establish the researcher’s credibility and expertise, which can enhance the trustworthiness and validity of the research.

Disadvantages of Background of The Study

Some Disadvantages of Background of The Study are as follows:

• Time-consuming : Writing a comprehensive background of the study can be time-consuming, especially if the research problem is complex and multifaceted. This can delay the research process and impact the timeline for completing the study.
• Repetitive: The background of the study can sometimes be repetitive, as it often involves summarizing existing research and theories related to the research problem. This can be tedious for the reader and may make the section less engaging.
• Limitations of existing research: The background of the study can reveal the limitations of existing research related to the problem. This can create challenges for the researcher in developing research questions or hypotheses that address the gaps in knowledge identified in the background of the study.
• Bias : The researcher’s biases and perspectives can influence the content and tone of the background of the study. This can impact the reader’s perception of the research problem and may influence the validity of the research.
• Accessibility: Accessing and reviewing the literature related to the research problem can be challenging, especially if the researcher does not have access to a comprehensive database or if the literature is not available in the researcher’s language. This can limit the depth and scope of the background of the study.

About the author

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Researcher, Academic Writer, Web developer

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Social and scientific relevance of your thesis

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What does the relevance of your thesis mean?

Social relevance thesis, scientific relevance thesis, practical relevance thesis, sample relevance thesis, we are happy to review your thesis.

It is important that your thesis topic is relevant. That means it is useful for society, for science and/or for practice. Therefore, when choosing a thesis topic, also look at the relevance of your subject. Also, dedicate a paragraph in your introduction to the relevance of your thesis. Read below what to look out for.

The outcomes of your thesis should be interesting and useful to others in one or more ways. People should be able to do something with it: in practice, in science and/or in society.

You explain the relevance of your thesis in the introduction and address this in your plan of action.

A thesis topic can be relevant in several ways. For instance, your chosen topic should be relevant to your study field and your possible client. In addition, there are three types of relevance:

• social relevance of your thesis;
• scientific relevance of your thesis;
• practical relevance of your thesis.

For practical theses, practical and social relevance are usually the most important. For university theses, scientific relevance can also be very important and practical relevance is not always as important. Your thesis supervisor can tell you what to pay more attention to in your thesis.

Besides choosing a relevant topic, your thesis topic must meet certain requirements . Furthermore, make sure you demarcate the topic properly.

A socially relevant thesis topic is useful to society. You help find a solution to a social problem or provide insight into a current issue with your thesis research.

For example, we speak of social relevance when...

• ... your research leads to recommendations for a problem solution.
• ... when your research explores a current social issue.
• ... if your research shows whether or not a particular method contributes to an important social solution.
• ... when you figure out what underlies a particular problem.
• ... when you gauge people's opinions on a topic to learn more about it.

In addition, your thesis may be academically relevant. This applies especially to theses written for a university course. The scientific relevance of your thesis means that your research complements existing scientific literature. You supplement the literature with new knowledge on a particular topic.

To choose a scientifically relevant topic, first, delve into available literature. What has already been researched? What are possible gaps in the literature?

We may speak of the scientific relevance of your thesis if e.g.

• ... you highlight a specific aspect of a topic that has not yet been researched.
• ... if you build on the suggestions for follow-up research in previous studies.
• ... if you use a new research method to investigate a particular topic.

Are you writing your thesis for a client? In that case, the practical relevance of your thesis is important. Even if you are writing your thesis for your study programme, practical relevance is sometimes important.

There is practical relevance if your thesis leads to recommendations or insights that are useful to practitioners (a profession, industry, organisation, etc.).

Suppose you are writing a thesis for a GP practice on more effective education on diabetes for overweight patients. In this case, the results of your research will be relevant for the staff of this GP practice. Other GP practices may also benefit.

In the introduction of your thesis, you briefly note what makes your thesis topic relevant. This example shows how to describe the relevance of your thesis.

This study is practically relevant because the results will help GP practice Jansen to improve their education on diabetes. This will make it more appealing for the target group to attend this information evening and allow the practice to motivate more patients to start losing weight and thus prevent diabetes.

The recommendations arising from the study are also relevant for other GPs in the Netherlands and diabetes prevention in general. Obesity is a major contributor to type 2 diabetes, a disease currently affecting over X Dutch people. The more people are aware of the link between obesity and type 2 diabetes, the more we can prevent it from reaching that point in obese people.

Furthermore, this study is scientifically relevant because little research has been done on diabetes education in the form of presentations by GPs. Previously, leaflets and brochures on this disease have been studied, but little is known about presentations. This study contributes to the knowledge on this topic, providing a more complete picture of effective education about type 2 diabetes.

The relevance of your thesis is one of the many things you need to formulate correctly in your thesis. Do you doubt whether your thesis is well put together in terms of structure, argumentation, language and spelling? Have our experienced editors review your thesis and give you personal feedback.

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

6-Evaluating Sources

2. Evaluating for Relevancy

Relevant sources are those that pertain to your research question. You’ll be able to identify them fairly quickly by reading or skimming particular parts of sources and maybe jotting down little tables that help you keep track. We’ll show you how below, including where to look in specific kinds of sources and what questions to ask yourself as you do.

One thing to consider early on as you make inferences about relevancy is the effect that timeliness– called a source’s currency–should have on deciding whether a source is relevant. Sometimes timeliness has a lot to do with relevancy; sometimes it is less important. Your research question and your discipline will determine that.

For instance, if your research question is about the life sciences, you probably should consider only the most recent sources relevant for citing because the life sciences are changing so quickly. There is a good chance that anything but the most recent sources may be out of date. So it’s a good idea to aim for life sciences sources no more than 5 years old. (An example of a discipline that calls for even newer sources is computer security.)

Sometimes emergencies change the schedule of what is recent enough. For instance, when the Covid-19 pandemic started, it was incredibility important for scientists to share their research information as quickly as possible. At that time, scientific information about Covid-19 could become outdated in weeks or months–before the peer review process was barely started.

Lives were at stake and for that reason, scientists started publishing their new research results on Covid-19 as preprints —publications of results that had not yet been peer-reviewed–in an attempt to have them be useful faster. Nonetheless, after preprint publication, the peer review process continued for much of that research.

But pre-prints didn’t start with the Covid pandemic. Around for more than 30 years and now at Cornell University, arXiv is a free distribution service and an open-access archive for more than two million scholarly articles first published as preprints in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. Materials on the site are not peer-reviewed by arXiv itself. (arXiv is pronounced archive.)

Before using preprints as sources, talk with your professor about whether she or he recommends their use in your situation.

Many sciences other than life sciences primarily use newer content under 10 years old. But not always. That’s because the history department is not alone in valuing older content. For instance, mathematics is a discipline that makes heavy use of older content. So how important the currency of your sources is will depend on your research question and your discipline. Your professor can guide you about your own situation.

In most cases, it’s best not to use a hard and fast rule about how current your sources have to be. Instead, consider your discipline and research question and do some critical thinking. For example, suppose your research question is about the Edo Period in Japan (1603-1868) or about Robert Falcon Scott, who explored the Antarctic from 1901-1913. In these cases, an item from 1918 might be just as useful as an item from 2018 (although new information may have been found in the 100-year gap). But something from 1899 about Antarctica or from 1597 about Japan would not be current enough for these research questions.

These examples also give you two more clues about how to treat the timeliness or currency of sources as you consider relevance:

• Because of how long ago they lived or occurred, it would be unusual for many sources on Robert Scott or the Edo Period to have been published very recently. So, unlike sources for the life sciences, whether a source is very recent should probably not determine its relevancy to research questions about Scott or the Edo Period.
• Primary sources might be considered especially relevant to many humanities and other non-science research questions. For disciplines in the humanities, the phrase primary sources refers to sources created at the same time as something under study—in this case, things such as Scott’s diaries and expedition photographs, as well as paintings, literature, clothing, and household items from the Edo Period. They go a long way to explain faraway people and times. (See Primary, Secondary, & Tertiary Sources .) On the other hand, when science disciplines use the phrase primary source, they usually mean where they primarily find the information they consider valid—in research journals.

EXAMPLE: TED Currency

Check out how currency is handled on TED . This site provides videos of speakers talking about new ideas in technology, entertainment, and design. (That’s what TED stands for.) Some videos are labeled “Newest Talks,” and TED tells when every video was recorded. That’s because currency matters with TED Talks.

For your own sources for which timeliness matters, see the section below called Where to Look, which includes where to look in websites, articles, and books for information about a source’s currency.

Time-Saving Tips

Instead of thinking you have to read all of every source in order to figure out whether it’s relevant, read or skim only parts of each source. If you’re looking at the right parts, that should give you enough information to make an educated guess about relevancy and currency.

But what should you be looking for as you do that reading and skimming? One way to figure that out is to first parse your research question so that you can figure out its main concepts . (This is like identifying main concepts in your research question in order to search precisely, as we advise in Chapter 4.)

For instance, suppose your research question is: How does having diverse members in a group increase the critical thinking of the group?

What are this question’s main concepts? Our answer is: group diversity and critical thinking.

So when trying to judge which sources are relevant to these main concepts, you would assess whether each source you’ve found pertains to at least one of these main concepts. We recommend you jot down a little table like the one in the example below to keep track of which sources address each main concept.

To be considered relevant to your research question, a source wouldn’t necessarily have to cover all of your main concepts. But finding sources that do is ideal. Otherwise, you just have to make do with what you’ve got. Don’t forget that each source would have to pass the currency test, too, if the currency is important to your research question. So it saves time to record your decisions about the sources’ currency on your tables, too.

EXAMPLE: Sources’ Main Concepts and Currency

Research question: How does having diverse members in a group increase the critical thinking of the group?

The table in this hypothetical example indicates that both Sources A and C are relevant because each pertains to at least one main concept from the research question. Currency doesn’t seem to matter much to our research question, so all three sources were marked current. But since currency is all that Source B has to offer, it is not relevant for this project.

If you do make little tables for relevance, it’s probably a good idea to hang on to them. You might find them helpful later in your research process.

Where to Look in Websites, Articles, and Books

The information below tells where to look and what questions to ask yourself to assess the relevancy of articles, books, and websites. The name of a source seldom tells you enough about its relevance, so whatever you do, don’t stop evaluating after looking only at a website’s name or the title of another source.

Save time by looking in particular places in sources for information that will help you figure out whether the source is relevant to your research project. Much of our advice below comes from “Speedy Reading” in The Craft of Research , second edition, by Wayne Booth, Gregory Colomb, and Joseph Williams, University of Chicago Press, 2003, pp. 108-109.

On a website , check the name of the website and its articles for clues that they contain material relevant to your research question. Consider whether time should have an impact on what information can be considered relevant to your research question. If so:

• Skim any dates, datelines, What’s New pages, and press releases to see whether any website content works with the time considerations you need.
• Check for page creation or revision dates that you find. What you’ve already learned from other sources can also help. For instance, you may know that the information covered by a particular website, which seems relevant, is no longer considered the latest thinking. In that case, you could mark it irrelevant on your little table.
• Skim any site map and index on the website for key words related to your research question.
• Try the key words of your research question in the search box. Do you see enough content about your keywords to make you think parts of the website could be helpful?

For a research journal article, magazine article, or newspaper article , think about the title. Does it have something to do with your research question? Consider whether time should have an impact on what sources can be considered relevant. If so:

• Is the publication date of any of these three kinds of articles within your parameters?
• Skim the abstract of a journal article to see whether the article works with the time considerations you need. For instance, if there is a time period in your research question, does the article address the same time period or was it created during that time period?
• Look at the abstract and section headings in a journal article or the early parts of a newspaper or magazine article to locate the problem or question that the article addresses, its solution, and the outline of the article’s argument for its main claim. Can those help answer your research question? Do they make it seem as if the article will give you information about what others have written about your research question? Do they offer a description of the situation surrounding your research question?
• Do the journal article’s introduction and conclusion sections help you answer your research question and/or offer a description of the situation surrounding your question so you can explain in your final product why the question is important?
• Check whether the journal article’s bibliography contains keywords related to your research question. Do the sources cited by the bibliography pertain to your research question? (Bibliographies are especially good places to look for sources.)
• If you decide the newspaper or magazine article is relevant, look at sources quoted or otherwise identified within it. Those may be additional sources for you.

For a book (perhaps in its library catalog listing) , check whether the title and/or subtitle indicates the book could be about your research question. You can find a lot of such information about the book from its listing in a library catalog. Consider whether time should have an impact on what sources can be considered relevant.

• Is the publication date or copyright date (usually listed in the library catalog or on the back of the book’s title page) too early or late for any time constraints in your research question? Maybe it’s just right.
• Skim some of the preface and introduction to see whether the book works with the time considerations you need.
• Check the bibliography to see whether the sources cited are about your research question.
• Skim the book’s table of contents and any summary chapters to locate the problem or question that the book addresses, its solution, and the broad outline of the book’s argument for its main claim. Will any of that be helpful in answering your research question?
• Do those sections give you information about what others have written about your research question?
• Do they offer a description of the situation surrounding your research question?
• Look for your key words in the bibliography. Do the sources cited pertain to your research question?
• Skim the index for topics with the most page references. Do the topics with the most page references pertain to your research question?

ACTIVITY: Follow a Title’s Clues for Relevance

Instructions: This quiz asks you to use logic, the titles of sources, and their publication dates, to identify the source most likely to be relevant to each research question. (Outside of this quiz, sources are not actually in competition with one another to be relevant. But this seemed like a good way to have you practice your skills at assessing relevance.) Many titles and dates below are fictitious, but that doesn’t affect their relevance within the quiz. Book, journal, website, and newspaper titles are italicized; chapter and article titles are in quotes.

• For each, read the information about the research question and each source.
• For each, record your judgments on a little table that you jot down like those illustrated earlier.
• For each, mark your answer, which should be the most relevant source according to the little table you completed for the question.
• Check your answers with our feedback.

ACTIVITY: Connecting the Dots Beyond the Title

Instructions: You always need to go beyond the title of a source when judging relevance. In the previous activity, you evaluated the titles of sources for currency and relevance. For this activity, you will investigate beyond the title to see whether one of the (hypothetical) articles named in the last activity is indeed relevant to meeting your information needs.

• Read the abstract of the article below, using your critical thinking skills to try to identify the information needs of your project it could help you meet.
• Then answer the questions about which information needs the source can help you meet. (Mark all that apply.)
• If there is at least one need it can help meet, you should judge the article relevant. Don’t forget to compare your answers with our feedback.

Your research question is: How does “prospect theory” in behavioral economics help explain medical doctors’ decisions to favor surgery or radiation to cure cancer in patients?

As usual, your information needs are:

• To learn more background information.
• To answer your research question.
• To convince your audience that your answer is correct or, at least, the most reasonable answer.
• To describe the situation surrounding your research question for your audience and explain why it’s important,
• To report what others have said about your question, including any different answers to your research question.

Abstract: “Cancer Treatment Prescription–Advancing Prospect Theory beyond Economics,” in Journal of The American Medical Association Oncology , June, 2022. (This article and abstract are fictitious but the journal and its form for abstracts are real.) Importance Cancer treatment is complex. We expect oncologists to make treatment decisions according to definitive standards of care. Finding out that prospect theory demonstrates that they react very much like most other people when deciding to recommend surgery or chemotherapy for their patients indicates that more self-reflection on oncologists’ part could help patients make better decisions. (Prospect theory describes how people choose between alternatives that have risk when the probability of different outcomes is unknown.) Objective To show whether prospect theory applies to how oncologists framed their recommendations for surgery or chemotherapy for patients in good condition and bad condition. Design, Settings, and Participants Records of 100 U.S. oncologists were examined for the years 2019 and 2020, which documented patient conditions and the way oncologists framed their recommendations regarding surgery or chemotherapy. Records of nine thousand patients were involved. Thus, a quasiexperimental ex post facto design was used for the study. Main Outcomes and Measures This study explored the relationship between the way in which the oncologists “framed” the choice of surgery or chemotherapy as they made recommendations to patients, the patients’ conditions, and the choice actually made. Those results were compared to what prospect theory would predict for this situation. Results Physicians seemed to present their recommendation of surgery or chemotherapy in a loss frame (e.g., “This is likely to happen to you if you don’t have this procedure”) when patients’ conditions were poor and in a gain frame (e.g., “By having this procedure, you can probably dramatically cut your chances of reoccurrence”) when their conditions were less poor. These results are what prospect theory would have predicted. Conclusions and Relevance This study opens up the possibility that, as described by prospect theory, a person’s choice of framing behavior is not limited to how we naturally act for ourselves but includes how we act for other people, as the oncologists were acting on behalf of their patients. More research is necessary to confirm this line of evidence and determine whether oncologists’ decision making and framing is the most effective and entirely according to the best standards of care.

Which information needs could this source help you meet if your research question was: How does “prospect theory” in behavioral economics help explain medical doctors’ decisions to favor surgery or radiation to cure cancer in patients?

A brief summary of what a journal article is about and a quick read in order to decide whether the article is likely to contain information relevant to your research project. The abstract may appear in research databases and, sometimes, in the article itself.

Choosing & Using Sources: A Guide to Academic Research Copyright © 2015 by Teaching & Learning, Ohio State University Libraries is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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Overview of Relevance in Research

Published 16 October, 2023

Relevance in research is an interconnection of one research topic with others. It is basically the level up to which you can apply research findings in real life. In simple words, the investigation which you are conducting is useful for others.

Meaning of Relevance in Research

The relevance in research is the understanding of how finding or studying one thing affects another. “Relevance” can also be seen as the extent to which a certain study or theory is significant.

Research is the pursuit of new knowledge. The relevancy in research means that study which you are performing should be useful for others as well- and high relevancies mean research which you are performing has great potential to fill a gap in knowledge, especially if it’s something people currently don’t know about or understand very well!

For instance:

• If you are conducting a market survey for an organization then the data which you are collecting through the survey research should be useful for your firm. High relevancy means the investigation which you are performing has a high potential of filling the knowledge gap.
• If you are selecting the unemployment issue as your research topic. You are performing a research process for identifying the root cause of unemployment and then information which you have gathered through research can be helpful for formulating effective policies for the nation.

Significance of relevance in research

Relevance has great significance in research as it helps you in maintaining the momentum. In addition to this, it is the relevant information that will help you in making your dissertation interesting to the reader. Relevancy is the factor in research that helps you and the reader in developing confidence about the findings and outcome of the investigation.

Maintaining a high level of relevance is also very crucial for getting the dissertation approved by the tutor. It is very much essential for you to make sure that the topic or field which you are selecting for performing the investigation has academic and social relevance. A high level of relevancy in research is very much crucial for eliminating risk and ethical issues.

Types of relevance in research        

The different types of relevance in research are:

1. Academic relevance

This basically means level up to which investigation performed on a particular topic has helped you in accomplishing your academic goals. Academic relevance is a measure of how much something helped you progress towards your academic goals. In order to be academically relevant, the information one has learned must have been able to assist in some way with achieving their own personal goal or objective.

Academic relevance is an important consideration for any student when deciding to study a subject. It can help you determine if the investigation performed on that topic will be helpful in achieving your academic goals.

2. Societal relevance  

It is referred to as the information gathered through investigation helps in developing the understanding of the society. Good research will help us understand society better by giving insight into how it functions- or more specifically what processes are occurring behind the scenes that we might not see otherwise due to our own biases as someone embedded in this culture.

3. Practical relevance  

It is basically an extent up to which the findings could be applied in real-life situations . Research that has practical relevance not only adds value but also can make a recommendation for particular industries or improve processes in an organization.

4. Scientific relevance

It is basically an extent up to which you can fill the knowledge gap thorough research on a specific topic. You have to make sure that the research you are doing will fill in a gap of knowledge for the scientific community. The best way to do this is by extensively researching your topic and finding what hasn’t been researched yet. It’s important not just because it makes an impact on science but also so that you find something stimulating enough for you as well!

Read Also: Paragraph Structure in Research Paper

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

What is the Rationale of the Study?

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

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

Table of Contents:

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

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

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

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

When is the Rationale for Research Written?

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

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

What to Include in the Study Rationale

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

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

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

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

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

Methodological limitations

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

Contextual limitations

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

Conceptual limitations

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

Study Rationale Examples

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

Background presentation

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

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

Rationale of the study

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

Statement of the problem

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

How long is a study rationale?

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

Consider Using Professional Academic Editing Services

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

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

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Relevance Of Research – Why Is It So Important?

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Research is a significant element in academia. It is a tool that helps us solve problems, make new discoveries, and understand the world better in general. During the research process , you can make a difference in people’s lives or in society. For this reason, students must complete research papers as part of any course in higher education. This article discusses the relevance of research in different fields of academic writing .

Inhaltsverzeichnis

• 1 In a nutshell: Relevance of research
• 2 Definition: Relevance of research
• 3 How to conduct research
• 4 Relevance of research in different courses
• 5 Types of relevance in research
• 6 Knowledge and learning
• 7 Issues and public awareness
• 8 A successful business
• 9 Lies and truths
• 10 Opportunities
• 11 Information
• 12 Relevance of research: Exercise for the mind

In a nutshell: Relevance of research

• Many academic fields require students to conduct academic research as part of their studies. Overall, research is also applied heavily by students in learning and the academic writing process.
• The key relevance of research in academia is that it allows students and researchers to find sources to make their arguments on a specific topic. Furthermore, most opinions are conceived through the research process.
• Besides students, trained professionals also recognize the relevance of research.

Definition: Relevance of research

Relevance of research refers to the importance of research in various fields. Here are a few reasons why research is relevant:

• It builds knowledge and promotes learning.
• It helps to increase public awareness.
• Research promotes success in business and other fields.
• It encourages the disapproval of lies and supports facts and truths.
• Research is a means for discovering opportunities and helps build credibility.
• It promotes confidence and passion in reading, sharing information, analyzing, and writing.
• Research nourishes and helps exercise the mind.

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How to conduct research

The relevance of research is not a topic of debate. Therefore, students must learn how to research, so they can enjoy the benefits. The following steps explain how to conduct research.

• Choosing a topic and identifying a problem: Firstly, you must come up with ideas and find a general area of interest. Once you are settled on a topic, you must determine an issue that needs to be addressed in the area and why it matters.
• Formulating research questions and creating a research design: Next, you must create one or more research questions that target what you want to find out through your research. Additionally, create a practical framework for answering your research questions (research design).
• Writing a research proposal: Finally, create a research proposal that outlines the relevance of the research, context, purpose, and your plan. From there, you can start searching for sources and gathering information for your research.

Relevance of research in different courses

The relevance of research stands out in different courses. For this reason, most courses encourage their students to apply research in their studies and academic writing. Universities encourage and engage in research as part of their mission to promote learning and discovery.

Let us look at the relevance of research in different courses:

Types of relevance in research

There are different forms of the relevance of research. Let us look at some of the key ones.

Academic relevance

Societal relevance, practical relevance, scientific relevance.

The academic relevance of research is perhaps the most critical. Research is critical in the promotion of academic knowledge of a subject. Moreover, research helps individuals meet their academic goals. Academic relevance comes from learned information, which is obtained through research.

The purpose of research extends beyond academia and has a significant impact on society. Research generates knowledge that aids in addressing real-world problems and making informed decisions. Research provides a more profound understanding of society and its functions.

The relevance of research is also important in everyday life. Research findings apply in real-life situations to various extents. For instance, research allows entrepreneurs to discover problems and wants in society, and the findings help resolve these problems. Researchers make recommendations for particular industries and promote improved processes in critical organizations.

Research allows practitioners in various fields of science to bridge the knowledge gap in various subjects. Research also helps scientists make new and significant discoveries that help advance different fields. Scientists need research to come up with life-changing inventions.

Knowledge and learning

Research helps facilitate knowledge acquisition and learning. Students, academics, professionals, and non-professionals depend on research as a tool for learning and understanding a subject better. Research also equips individuals with information about the world and skills for survival and life improvement.

Issues and public awareness

Research is a tool for understanding issues and raising public awareness. It helps people understand each other and their world. People use research to understand current issues.

A successful business

Research is critical for business success. Successful companies and individuals rely on market and client research. It helps them understand their clients, their needs, and how to provide them with what they need. Therefore, research helps with targeted marketing. It also helps businesses understand their competition and establish ways to stand out.

Lies and truths

Background research and private investigations are critical in debunking lies and promoting truths. Researchers apply field-testing and peer reviews to validate facts. Therefore, research builds integrity and competence in facts. Fact-checking helps discover research bias, fake news, and propaganda.

Opportunities

Research helps people find, gauge, and seize opportunities. Therefore, it helps individuals nurture their potential and achieve goals by taking advantage of opportunities. People can use research to maximize career options and investments.

Information

Research promotes a passion and love for reading, writing, analyzing, and sharing information. It is a tool for critical thinking and comprehension. Sharing research promotes a wider understanding of a subject.

Relevance of research: Exercise for the mind

Research nourishes and exercises the mind. Critical thinking is a tool for promoting mental health. Students earn critical reasoning skills from research, which helps with their learning. Various studies have proven that mentally stimulating activities like research can promote brain health.

What is the meaning of relevance in research?

The relevance of research is the understanding of how studying one thing can affect another. It is the extent to which a specific study or theory is significant.

What are the different types of relevance of research?

The various forms of the relevance of research are:

How does research promote mental health?

Research nourishes and exercises the mind. Critical thinking is a tool for promoting mental health. Students earn critical reasoning skills from research, which helps with their learning.

What is the scientific relevance of research?

Research allows practitioners in various fields of science to bridge the knowledge gap in various subjects. It helps scientists make new and significant discoveries that help advance different fields.

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August 23, 2024

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Good sleep habits important for overweight adults, study suggests

by Erik Robinson, Oregon Health & Science University

New research from Oregon Health & Science University reveals negative health consequences for people who are overweight and ignore their body's signals to sleep at night, with specific differences between men and women.

The study published this week in The Journal of Clinical Endocrinology & Metabolism .

"This study builds support for the importance of good sleep habits," said lead author Brooke Shafer, Ph.D., a postdoctoral researcher in the Sleep, Chronobiology and Health Laboratory in the OHSU School of Nursing. "Sleep practices, like going to bed when you're tired or setting aside your screen at night, can help to promote good overall health."

The study recruited 30 people, split evenly between men and women. All had a body mass index above 25, which put them into an overweight or obese category.

"Obesity and cardiometabolic disease are growing public health concerns," Shafer said. "Our research shows that disruptions in the body's internal biological clock could contribute to negative health consequences for people who may already be vulnerable due to weight."

Generally healthy participants contributed a saliva sample every 30 minutes until late in the night at a sleep lab on OHSU's Marquam Hill campus to determine the time at which their body started naturally producing the hormone melatonin . Melatonin is generally understood to begin the process of falling asleep, and its onset varies with an individual's internal biological clock.

Participants then went home and logged their sleep habits over the following seven days.

Researchers assessed the time difference between melatonin onset and average sleep timing for each participant, categorizing them into two groups: those who had a narrow window, with a short time duration between melatonin onset and sleep, and those with a wide window, with a longer duration between melatonin onset and sleep. A narrow window suggests someone who is staying awake too late for their internal body clock and is generally associated with poorer health outcomes.

The new study confirmed a variety of potentially harmful health measures in the group that went to sleep closer to melatonin onset.

It also found key differences between men and women. Men in this group had higher levels of belly fat and fatty triglycerides in the blood, and higher overall metabolic syndrome risk scores than the men who slept better. Women in this group had higher overall body fat percentage, glucose and resting heart rates.

"It was really somewhat surprising to see these differences present themselves in a sex-dependent manner," said senior author Andrew McHill, Ph.D., assistant professor in the OHSU School of Nursing, the School of Medicine and the Oregon Institute of Occupational Health Sciences at OHSU. "It's not one size fits all, as we sometimes think in academic medicine."

The next phase of research will determine sex-specific differences in groups that experience more severe changes in sleep patterns, such as workers pulling overnight shifts.

"We want to figure out possible interventions that keep this vital core group of the workforce healthy," Shafer said.

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The Vital Importance of Human Touch

The science of human touch and what to do if you're feeling deprived..

Posted August 3, 2021 | Reviewed by Abigail Fagan

• What Is Depression?
• Take our Depression Test
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• The need for human touch is one of our most basic, primal needs.
• Touch deprivation is correlated with negative health outcomes such as anxiety, depression, and immune system disorders.
• Ways to address touch deprivation include massage therapy, pets, and weighted blankets.

Let’s be honest. The past 18 months have not invited a lot of touch. Quarantined at home and isolated from friends, many people have felt a lack of connection both emotionally as well as physically. Hugs and handshaking happen much less frequently now. And although the world is slowly returning to normal, the rise of the Delta variant suggests that social distancing will likely continue to define our social interactions for some time.

Much has been written in the media about the limits that social distancing has placed on single people’s sexual activity. As a human sexuality professor, I hear all about this from my students as well as from my followers. What’s largely been missed, though, is a more subtle yet even more fundamental need: the need for human touch.

The Science of Touch

The research demonstrating the need for human touch is vast. From a developmental standpoint, infants literally cannot survive without human touch. Skin-to-skin contact in even in the first hour after birth has been shown to help regulate newborns’ temperature, heart rate, and breathing, and decreases crying (Ferber, Feldman, & Makhoul, 2008). Touch also increases mothers' relaxation hormones and aids in the release of oxytocin . A now-famous study examined the sensory deprivation of children in understaffed orphanages in Romania (Carlson & Earls, 1997). The touch-deprived children, the authors found, had strikingly lower cortisol and growth development levels for their age group.

Harlow’s Monkey experiments (Harlow & Harlow, 1965) are perhaps the most famous example of research pointing at the primacy of the need for touch. In a series of experiments, Harlow created inanimate surrogate mothers for baby monkeys made from wire and wool. Each infant became attached to its particular “mother,” recognizing its unique face and preferring it above others.

Next, Harlow presented the infants with a soft, cuddly clothed "mother" as well as a wire "mother" located in two separate but attached chambers. Only the wire “mother” held a bottle with food. Harlow found that the monkeys spent far more time next snuggled against the cloth “mother” than they spent with the wire “mother” even though the wire “mother” was the only one with food. Food may be necessary for survival, but touch is what sustains us.

Later in his career , Harlow carried out perhaps his most controversial study, by cultivating infant monkeys in isolation chambers for up to 24 months. The infant monkeys emerged from isolation deeply disturbed, a finding of which many credit as having started the animal rights movement.

Since Harlow’s experiments, research has uncovered an astonishing number of poor health outcomes that result when we are deprived of touch. The correlation between anxiety , depression and stress and touch is large and inversely related. It has been found that touch calms our nervous center and slows down our heartbeat. Human touch also lowers blood pressure as well as cortisol, our stress hormone. It also triggers the release of oxytocin, a hormone known for promoting emotional bonding to others.

Studies using PET scans have found that the brain quiets in response to stress when a person’s hand is held. The effect is greatest when the hand being held is that of a loved one, but it still works even if it’s just a stranger (Field, 2010).

Research also suggests a negative correlation between touch and the severity of borderline personality disorder symptoms (Field, 2010). This suggests that the effects of touch extend to our basic neural circuitry. Even our immune response seems to be somewhat governed by touch, with the finding that those who are deprived of human touch are more likely to suffer from immune system diseases. It’s ironic that during a highly contagious pandemic where our immune systems are being the most stressed , we are being deprived of something (human touch) that is so essential to its function.

How to Increase Touch in Your Life

Given the obvious importance of human touch, one question may be how to introduce more of it into your life. Even for those lucky enough to live with families or other people one has podded with, the amount of touch we are receiving has undoubtedly decreased since before the pandemic.

Research shows that one of the most effective ways to benefit from the therapeutic benefits of touch is through massage. Massage therapy has been shown to ease depression, increase attentiveness and enhance immune function (Lindgren, Jacobsson & Lamas, 2014). If massage therapy is not your thing, maybe a manicure or pedicure or other type of spa treatment that involves touch is. Pets have also been found to mimic some of the benefits of human touch, so long as you spend ample time petting them (Young et al. 2020). Although weighted blankets aren’t human, they’ve been found to calm the nervous system in the same manner as touch. Just pretend you are one of Harlow’s monkeys.

Consent is Key

One final note: Although the need for human touch is immense, it’s important to highlight consent. Just because you are in desperate need of touch does not mean that any other person is obligated to give it to you, nor should they be pressured into doing so. This rule extends to children especially, who are learning the importance of recognizing their own privacy spheres. This may not go over well with grandma and grandpa, but the criticality of consent is an important enough lesson that drawing the line is worth it.

Facebook image: AlessandroBiascioli/Shutterstock

CARLSON, M. and EARLS, F. (1997), Psychological and Neuroendocrinological Sequelae of Early Social Deprivation in Institutionalized Children in Romania. Annals of the New York Academy of Sciences, 807: 419-428

Harlow HF, Dodsworth RO & Harlow MK (1965). "Total social isolation in monkeys". Proceedings of the National Academy of Sciences of the United States of America. Proceedings of the National Academy of Sciences. 54 (1): 90–97.

Lindgren L, Jacobsson M, Lämås K. “Touch Massage, a Rewarding Experience.” Journal of Holistic Nursing. 2014;32(4):261-268.

Ferber, Feldman & Makhoul (2010) “The development of maternal touch across the first year of life,” Early Human Development, Volume 84, Issue 6,

Field, T. (2010),”Touch for socioemotional and physical well-being: A review”

Developmental Review, Volume 30, Issue 4, Pages 367-383

Young J., Pritchard R., Nottle C., & Banwell H. (2020) “Pets, touch, and COVID-19: health benefits from non-human touch through times of stress.” Journal of Behavioral Economics for Policy, Vol. 4

Nicole K. McNichols, Ph.D., is an Associate Teaching Professor in the Department of Psychology at the University of Washington in Seattle. She teaches "The Diversity of Human Sexuality," the university's largest and most popular undergraduate course.

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eTable 1.  ICD-10 Codes and Alcohol-Attributable Fraction Information by Causes of Death in the Alcohol-Related Disease Impact Application

eTable 2. Adjusted Prevalence of US Mean Daily Alcohol Consumption by Level of Consumption and Age Group

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Esser MB , Leung G , Sherk A, et al. Estimated Deaths Attributable to Excessive Alcohol Use Among US Adults Aged 20 to 64 Years, 2015 to 2019. JAMA Netw Open. 2022;5(11):e2239485. doi:10.1001/jamanetworkopen.2022.39485

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Estimated Deaths Attributable to Excessive Alcohol Use Among US Adults Aged 20 to 64 Years, 2015 to 2019

• 1 Division of Population Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
• 2 Canadian Institute for Substance Use Research, University of Victoria, Victoria, Canada

Question   What is the estimated proportion of deaths among US adults aged 20 to 64 years attributable to excessive alcohol consumption, and are there differences by sex, age, and US state?

Findings   The estimates in this cross-sectional study of 694 660 mean deaths per year between 2015 and 2019 suggest that excessive alcohol consumption accounted for 12.9% of total deaths among adults aged 20 to 64 years and 20.3% of deaths among adults aged 20 to 49 years. Among adults aged 20 to 64 years, the proportion of alcohol-attributable deaths to total deaths varied by state.

Meaning   These findings suggest that an estimated 1 in 8 deaths among adults aged 20 to 64 years were attributable to excessive alcohol use and that greater implementation of evidence-based alcohol policies could reduce this proportion.

Importance   Alcohol consumption is a leading preventable cause of death in the US, and death rates from fully alcohol-attributable causes (eg, alcoholic liver disease) have increased in the past decade, including among adults aged 20 to 64 years. However, a comprehensive assessment of alcohol-attributable deaths among this population, including from partially alcohol-attributable causes, is lacking.

Objective   To estimate the mean annual number of deaths from excessive alcohol use relative to total deaths among adults aged 20 to 64 years overall; by sex, age group, and state; and as a proportion of total deaths.

Design, Setting, and Participants   This population-based cross-sectional study of mean annual alcohol-attributable deaths among US residents between January 1, 2015, and December 31, 2019, used population-attributable fractions. Data were analyzed from January 6, 2021, to May 2, 2022.

Exposures   Mean daily alcohol consumption among the 2 089 287 respondents to the 2015-2019 Behavioral Risk Factor Surveillance System was adjusted using national per capita alcohol sales to correct for underreporting. Adjusted mean daily alcohol consumption prevalence estimates were applied to relative risks to generate alcohol-attributable fractions for chronic partially alcohol-attributable conditions. Alcohol-attributable fractions based on blood alcohol concentrations were used to assess acute partially alcohol-attributable deaths.

Main Outcomes and Measures   Alcohol-attributable deaths for 58 causes of death, as defined in the Centers for Disease Control and Prevention’s Alcohol-Related Disease Impact application. Mortality data were from the National Vital Statistics System.

Results   During the 2015-2019 study period, of 694 660 mean deaths per year among adults aged 20 to 64 years (men: 432 575 [66.3%]; women: 262 085 [37.7%]), an estimated 12.9% (89 697 per year) were attributable to excessive alcohol consumption. This percentage was higher among men (15.0%) than women (9.4%). By state, alcohol-attributable deaths ranged from 9.3% of total deaths in Mississippi to 21.7% in New Mexico. Among adults aged 20 to 49 years, alcohol-attributable deaths (44 981 mean annual deaths) accounted for an estimated 20.3% of total deaths.

Conclusions And Relevance   The findings of this cross-sectional study suggest that an estimated 1 in 8 total deaths among US adults aged 20 to 64 years were attributable to excessive alcohol use, including 1 in 5 deaths among adults aged 20 to 49 years. The number of premature deaths could be reduced with increased implementation of evidenced-based, population-level alcohol policies, such as increasing alcohol taxes or regulating alcohol outlet density.

Excessive alcohol use is associated with several leading causes of death among adults aged 20 to 64 years in the US, including heart disease, cancer, unintentional injury, and liver disease. 1 Excessive alcohol use is a leading preventable cause of premature death, 2 and rates of deaths due to fully alcohol-attributable causes (eg, alcoholic liver disease) have increased in the past decade, including among adults aged 20 to 64 years. 3 However, a US-based assessment of alcohol-attributable deaths among this population that also accounts for partially alcohol-attributable causes (eg, cancers) is lacking. Using the conditions in the Centers for Disease Control and Prevention’s Alcohol-Related Disease Impact (ARDI) application, 4 this study estimated the mean annual number of deaths due to excessive alcohol use among adults aged 20 to 64 years overall; by sex, age group, and US state; and as a proportion of total deaths.

Mean annual national and state mortality data from January 1, 2015, to December 31, 2019, were obtained from the National Vital Statistics System, WONDER, 5 and the ARDI application for the 58 alcohol-related causes. In addition to deaths due to fully alcohol-attributable causes, deaths due to partially alcohol-attributable conditions were calculated in the ARDI application using cause-specific, alcohol-attributable fractions (AAFs) for select acute (eg, injuries) and chronic (eg, cancers) conditions (eTable 1 in the Supplement ). Deaths due to acute conditions were calculated using direct AAFs based on high blood alcohol concentrations (eg, ≥0.10 g/dL). Deaths due to 23 chronic conditions were calculated using indirect AAFs, which include the prevalence of mean daily alcohol consumption levels and cause-specific relative risks that corresponded to those consumption levels. 6 To account for substantial underreporting of alcohol consumption in nationwide surveys, the same methodology as in the ARDI application was used to adjust alcohol consumption from 2 089 287 respondents to the 2015-2019 Behavioral Risk Factor Surveillance System. 6 Consumption was adjusted to 73% of national per capita alcohol sales (from tax and shipment data in the Alcohol Epidemiologic Data System) to align with alcohol use reported in US epidemiologic cohort studies. 7 This study estimated deaths due to excessive alcohol consumption; therefore, for chronic conditions, the adjusted prevalence of medium (>1 to ≤2 alcoholic drinks for women or >2 to ≤4 drinks for men) and high (>2 alcoholic drinks for women or >4 drinks for men) mean daily alcohol consumption (eTable 2 in the Supplement ) were applied to relative risks to generate cause-specific AAFs. 4 Alcohol-attributable fractions and relative risks are generally not available by race and ethnicity, and alcohol attribution to deaths might differ across these groups; therefore, deaths in this study were not estimated by race and ethnicity. Because data were deidentified and secondary analyses were performed, institutional review board oversight and informed consent were not required as determined by the Centers for Disease Control and Prevention under 45 CFR 46. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline.

Analyses of alcohol consumption prevalence were conducted using SAS, version 9.4 (SAS Institute Inc). We used the ARDI application to assess the mean annual number of deaths due to excessive drinking and the leading causes of death. 4 Alcohol-attributable deaths were calculated as a percentage of total deaths overall and by sex, age, and US state. Alcohol-attributable death rates per 100 000 population were assessed using US Census population counts from WONDER. 5

Our findings suggest that an estimated annual mean of 140 557 deaths (men: 97 182 [69.1%]; women: 43 375 [30.9%]) could be attributed to excessive alcohol consumption in the US during the 2015-2019 study period, accounting for 5.0% of total deaths ( Table 1 ). Among all adults aged 20 to 64 years, 694 660 annual mean total deaths were noted (men: 432 575 [66.3%]; women: 262 085 [37.7%]), and an estimated 89 697 of these (12.9%) were alcohol-attributable (64 998 [15.0%] among men and 24 699 [9.4%] among women). Our analysis showed that although the number and rate of alcohol-attributable deaths per 100 000 increased by age group, alcohol-attributable deaths accounted for a larger proportion of total deaths among younger groups: 19 782 of 77 973 total deaths (25.4%) among adults aged 20 to 34 years and 25 199 of 143 663 (17.5%) among those aged 35 to 49 years. The 3 leading causes of alcohol-attributable deaths by age group were the same for men and women (eg, adults aged 20-34 years: other poisonings, motor vehicle traffic crashes, and homicide; adults aged 35-49 years: other poisonings, alcoholic liver disease, and motor vehicle traffic crashes).

By state, alcohol-attributable deaths among adults aged 20 to 64 years ranged from 9.3% of total deaths in Mississippi to 21.7% in New Mexico ( Table 2 ). State-level variations were found by age group (eg, the proportion of alcohol-attributable deaths to total deaths among adults aged 20-34 years ranged from 22.4% in Utah to 33.3% in New Mexico). Among adults aged 20 to 49 years, our estimates suggest that excessive drinking was responsible for 44 981 mean annual deaths, or 20.3% of total deaths. This percentage was generally lower in states in the Southeast and higher in the West, upper Midwest, and New England ( Figure ).

We found that 89 697 of an estimated 140 557 deaths due to excessive alcohol use annually during the 2015-2019 study period, or nearly two-thirds of the deaths, were among adults aged 20 to 64 years. Our estimates suggest that alcohol-attributable deaths were responsible for 1 in 8 deaths among adults aged 20 to 64 years, including 1 in 5 deaths among adults aged 20 to 49 years.

Compared with 2019, death rates involving alcohol as an underlying or contributing cause of death increased during the first year of the COVID-19 pandemic in 2020, including among adults aged 20 to 64 years. 8 Therefore, the proportion of deaths due to excessive drinking among total deaths might be higher than reported in this study. Nevertheless, these study findings are consistent with the epidemiology of excessive drinking. For example, the prevalence of binge drinking is generally higher among younger adults, and this population tends to consume more alcohol while binge drinking, 9 which contributes to their leading causes of alcohol-attributable deaths.

The methods for estimating deaths due to excessive alcohol consumption in this study differ somewhat from those of other studies. From 2006 to 2010, an estimated 1 in 10 deaths among adults aged 20 to 64 years was attributable to excessive alcohol consumption. 10 That finding was partially based on self-reported mean daily consumption prevalence estimates that were adjusted to account for binge drinking occasions but not per capita alcohol sales. Because survey-based adjustments alone can lead to underestimates of alcohol-attributable deaths that are calculated using indirect AAF methods, this study adjusted self-reported alcohol use data to account for 73% of per capita alcohol sales. 7 Global studies estimating alcohol-attributable deaths also adjust using per capita alcohol sales, but they generally adjust to 80%. 11 The ARDI methods used in this study provide estimates of deaths pertaining to excessive drinking rather than all levels of consumption. Also, the ARDI application uses direct AAFs for estimating the number of alcohol-attributable deaths due to acute causes. This method differs from those of global studies that estimate alcohol-attributable deaths across all levels of consumption and consistently base estimates on continuous risk functions. 11 , 12

This study has some limitations. The alcohol-attributable death estimates in this study may be conservative because they are based on deaths due to alcohol-related conditions that were identified as the underlying cause of death only; contributing causes of death were not included. In addition, alcohol-attributable deaths due to partially alcohol-attributable conditions were not estimated for adults who formerly used alcohol, despite some dying of alcohol-related causes, 11 because the prevalence of former alcohol consumption is not collected in the Behavioral Risk Factor Surveillance System. Direct AAFs were used to estimate alcohol-attributable deaths due to acute causes (eg, injuries) 6 ; however, the sources of some AAFs were based on older data that may less accurately represent current alcohol-attribution. Last, some conditions related to alcohol use (eg, HIV/AIDS) were not included because suitable AAFs for the US were not available.

The findings of this cross-sectional study suggest that an estimated 1 in 8 deaths among adults aged 20 to 64 years was attributable to excessive alcohol consumption, including 1 in 5 deaths among adults aged 20 to 49 years. These premature deaths could be reduced through increased implementation of evidence-based alcohol policies (eg, increasing alcohol taxes, regulating alcohol outlet density), 13 and alcohol screening and brief intervention. 14

Accepted for Publication: September 16, 2022.

Published: November 1, 2022. doi:10.1001/jamanetworkopen.2022.39485

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2022 Esser MB et al. JAMA Network Open .

Corresponding Author: Marissa B. Esser, PhD, Division of Population Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, 4770 Buford Hwy NE, Mail Stop S107-6, Atlanta, GA 30341 ( [email protected] ).

Author Contributions: Dr Esser had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Esser, Sherk, Naimi.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Esser, Leung, Sherk, Lu, Naimi.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Leung, Sherk, Liu.

Administrative, technical, or material support: Esser, Sherk, Bohm.

Supervision: Esser.

Conflict of Interest Disclosures: Dr Sherk reported receiving grant funding from the Centers for Disease Control and Prevention (CDC) of the Department of Health and Human Services (HHS), during the conduct of the study. Dr Naimi reported grant funding from the CDC/HHS, during the conduct of the study. No other disclosures were reported.

Funding/Support: This study was partially supported by a financial assistance award by the CDC/HHS as part of a financial assistance award totaling $81 125 (Drs Sherk and Naimi), with 100% funded by the CDC/HHS.

Role of the Funder/Sponsor: The sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the CDC.

Additional Contributions: The state coordinators of the Behavioral Risk Factor Surveillance System facilitated data collection in their respective states. These individuals were not compensated financially for their contributions beyond their salaries.

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Late Nights and Early Mornings: Emphasizing the Importance of Research on Social Jet Lag

Gabe Dennett (left) and Nate Goodwin (right). Photo credit: Jeremy Gasowski

I am a rising senior at UNH with a double major in Exercise Science and Nutrition. This summer, my colleague, Nate Goodwin, and I are conducting a research study funded by a Summer Undergraduate Research Fellowship (SURF) from the Hamel Center for Undergraduate Research. Our project has two distinct aims. Nate is focusing on the effects of an acute model of circadian misalignment on central blood pressure, heart rate variability, and inflammation. The main purpose of my study is to assess the impact of such a disrupted sleep schedule on substrate utilization and exercise capacity. Specifically, I was interested in assessing if a misaligned circadian pattern would hinder fat oxidation, decrease aerobic capacity, and elevate heart rate during exercise.

As you probably could have guessed by my fields of study, health and fitness are a pillar of my life and a passion I love sharing with others. I enjoy learning about practical changes we can all make to optimize our wellbeing and physical fitness. One such area is sleep! A common stereotypical experience in the college population is a chronic lack of sleep fueled by social commitments, long nights of studying, or spontaneous fun. Recognizing this phenomenon in many of my peers and friends led me to ponder the field of research dedicated to sleep and its importance in health and fitness. Such a phenomena marked by chronic fluctuations in sleep and wake times, despite maintaining adequate amounts of sleep, is circadian misalignment, or social jet lag. Social jet lag refers to the all-too-common discrepancy between sleep and wake times, often between weekdays and weekends. In diving into the sleep and social jet lag literature that Nate and I reviewed to develop our SURF proposal it became apart to me that this can have serious implications for daily function, and long-term health.

Specifically, research done in shift-workers have demonstrated increased rates and risk for a plethora of chronic diseases and cardiometabolic events, including heart attacks, cardiovascular disease, stroke, type II diabetes, and excess adiposity and obesity. Mechanistically, the increased risk of disease is related to our body’s internal “clock,” mediated by external stimuli like light, exercise, and feeding times, that control the physiology on a deep internal level, affecting every layer of biology from the cell to the organism as a whole. This concept, however, remained largely unexplored in a college aged population, who are among the most common to experience such drastic, chronic fluctuations in sleep timing . By conducting this social jet lag study in a college-aged population, I aimed to generate novel insights into circadian misalignment that extend beyond the traditionally studied shift-worker demographic, addressing an important gap in our understanding of this phenomenon.

Nate Goodwin (left), Dr. Michael Brian (middle) and Gabe Dennett (right). Photo credit: Jeremy Gasowski

To research social jet lag, we employ two sleep protocols, a standardized and a misaligned, and collect data on variables such as central blood pressure, heart rate variability, C-Reactive Protein as a marker of systemic inflammation, and exercising substrate utilization and oxygen consumption. By assessing these variables, we look at the effects of misalignment on both daily exercise performance and day-to-day function, as well as a predictive measure of potential long-term degradation of health and increased risk of a cardiometabolic disease later in the lifespan. The standardized protocol is based on preferential sleep and wake times, with an eight-hour sleep window, four days in a row, which Nate outlines in greater detail in his own post .

I’ll walk you through a typical post-sleep intervention visit: Our participants enter the lab in the morning. First, we collect the blood pressure and heart rate variability data. Since these are Nate’s variables of interest, he heads this portion of the study visit. (Please read Nate’s blog post to learn more about this step in the research process.) Then, we invite them to the exercise testing area where I operate the metabolic cart and proctor a graded exercise test. This is a stationary cycling test lasts 30 minutes and increases in difficulty every 5 minutes with added resistance. The cycling protocol is designed to test the participants’ ability to switch between different fuel sources—fats and carbohydrates—at a submaximal exercise intensity. The participants wear a mask to measure gas exchange, specifically the amount of oxygen they are inhaling and carbon dioxide they are exhaling. By measuring this exchange, the metabolic cart can quantify my variables of interest for data collection: substate utilization, fat oxidation, carbohydrate oxidation, aerobic capacity and oxygen consumption.

This SURF granted me an opportunity to submerge myself in a research lab setting and gain an understanding of how exercise science research is conducted from start to finish. Specifically, working with human subjects, proctoring exercise tests, collecting and analyzing blood samples, and running data analyses are important skills that acquiring this early on in my academic career will equip me to enter any lab with ease.

However, the truly invaluable aspect of my experience this summer is the relationships I was able to build with my mentor, colleague, and fellow lab mates. The environment we created this summer reflected the “work hard, play hard” mentality. In between hard work and diligent effort, we always found time to laugh and enjoy each other’s company. Many jokes and fits of laughter emerged from our time working together and the people I began this project with as colleagues became some of my closest friends. One of the most pleasurable parts, was our Journal Club “JC,” where we would read peer-reviewed articles and discuss them in an in-depth manner. This almost always regressed into humorous conversation. Working with such a genuine, hardworking, jovial group of people in Dr. Brian’s cardiometabolic research group taught me just how much a team effort can elevate your success. For me, the relationships built this summer with our team were equally, if not more, important than the knowledge gained on the effects of social jet lag.

My experience this summer has prepared me thoroughly to continue my education and research endeavors at the graduate level. Long-term, my goal is to further my education in a master’s program, then work towards earning a PhD.

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