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Significance of the Study – Examples and Writing Guide

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Significance of the Study

Definition:

Significance of the study in research refers to the potential importance, relevance, or impact of the research findings. It outlines how the research contributes to the existing body of knowledge, what gaps it fills, or what new understanding it brings to a particular field of study.

In general, the significance of a study can be assessed based on several factors, including:

• Originality : The extent to which the study advances existing knowledge or introduces new ideas and perspectives.
• Practical relevance: The potential implications of the study for real-world situations, such as improving policy or practice.
• Theoretical contribution: The extent to which the study provides new insights or perspectives on theoretical concepts or frameworks.
• Methodological rigor : The extent to which the study employs appropriate and robust methods and techniques to generate reliable and valid data.
• Social or cultural impact : The potential impact of the study on society, culture, or public perception of a particular issue.

Types of Significance of the Study

The significance of the Study can be divided into the following types:

Theoretical Significance

Theoretical significance refers to the contribution that a study makes to the existing body of theories in a specific field. This could be by confirming, refuting, or adding nuance to a currently accepted theory, or by proposing an entirely new theory.

Practical Significance

Practical significance refers to the direct applicability and usefulness of the research findings in real-world contexts. Studies with practical significance often address real-life problems and offer potential solutions or strategies. For example, a study in the field of public health might identify a new intervention that significantly reduces the spread of a certain disease.

Significance for Future Research

This pertains to the potential of a study to inspire further research. A study might open up new areas of investigation, provide new research methodologies, or propose new hypotheses that need to be tested.

How to Write Significance of the Study

Here’s a guide to writing an effective “Significance of the Study” section in research paper, thesis, or dissertation:

• Background : Begin by giving some context about your study. This could include a brief introduction to your subject area, the current state of research in the field, and the specific problem or question your study addresses.
• Identify the Gap : Demonstrate that there’s a gap in the existing literature or knowledge that needs to be filled, which is where your study comes in. The gap could be a lack of research on a particular topic, differing results in existing studies, or a new problem that has arisen and hasn’t yet been studied.
• State the Purpose of Your Study : Clearly state the main objective of your research. You may want to state the purpose as a solution to the problem or gap you’ve previously identified.
• Contributes to the existing body of knowledge.
• Addresses a significant research gap.
• Offers a new or better solution to a problem.
• Impacts policy or practice.
• Leads to improvements in a particular field or sector.
• Identify Beneficiaries : Identify who will benefit from your study. This could include other researchers, practitioners in your field, policy-makers, communities, businesses, or others. Explain how your findings could be used and by whom.
• Future Implications : Discuss the implications of your study for future research. This could involve questions that are left open, new questions that have been raised, or potential future methodologies suggested by your study.

Significance of the Study in Research Paper

The Significance of the Study in a research paper refers to the importance or relevance of the research topic being investigated. It answers the question “Why is this research important?” and highlights the potential contributions and impacts of the study.

The significance of the study can be presented in the introduction or background section of a research paper. It typically includes the following components:

• Importance of the research problem: This describes why the research problem is worth investigating and how it relates to existing knowledge and theories.
• Potential benefits and implications: This explains the potential contributions and impacts of the research on theory, practice, policy, or society.
• Originality and novelty: This highlights how the research adds new insights, approaches, or methods to the existing body of knowledge.
• Scope and limitations: This outlines the boundaries and constraints of the research and clarifies what the study will and will not address.

Suppose a researcher is conducting a study on the “Effects of social media use on the mental health of adolescents”.

The significance of the study may be:

“The present study is significant because it addresses a pressing public health issue of the negative impact of social media use on adolescent mental health. Given the widespread use of social media among this age group, understanding the effects of social media on mental health is critical for developing effective prevention and intervention strategies. This study will contribute to the existing literature by examining the moderating factors that may affect the relationship between social media use and mental health outcomes. It will also shed light on the potential benefits and risks of social media use for adolescents and inform the development of evidence-based guidelines for promoting healthy social media use among this population. The limitations of this study include the use of self-reported measures and the cross-sectional design, which precludes causal inference.”

Significance of the Study In Thesis

The significance of the study in a thesis refers to the importance or relevance of the research topic and the potential impact of the study on the field of study or society as a whole. It explains why the research is worth doing and what contribution it will make to existing knowledge.

For example, the significance of a thesis on “Artificial Intelligence in Healthcare” could be:

• With the increasing availability of healthcare data and the development of advanced machine learning algorithms, AI has the potential to revolutionize the healthcare industry by improving diagnosis, treatment, and patient outcomes. Therefore, this thesis can contribute to the understanding of how AI can be applied in healthcare and how it can benefit patients and healthcare providers.
• AI in healthcare also raises ethical and social issues, such as privacy concerns, bias in algorithms, and the impact on healthcare jobs. By exploring these issues in the thesis, it can provide insights into the potential risks and benefits of AI in healthcare and inform policy decisions.
• Finally, the thesis can also advance the field of computer science by developing new AI algorithms or techniques that can be applied to healthcare data, which can have broader applications in other industries or fields of research.

Significance of the Study in Research Proposal

The significance of a study in a research proposal refers to the importance or relevance of the research question, problem, or objective that the study aims to address. It explains why the research is valuable, relevant, and important to the academic or scientific community, policymakers, or society at large. A strong statement of significance can help to persuade the reviewers or funders of the research proposal that the study is worth funding and conducting.

Here is an example of a significance statement in a research proposal:

Title : The Effects of Gamification on Learning Programming: A Comparative Study

Significance Statement:

This proposed study aims to investigate the effects of gamification on learning programming. With the increasing demand for computer science professionals, programming has become a fundamental skill in the computer field. However, learning programming can be challenging, and students may struggle with motivation and engagement. Gamification has emerged as a promising approach to improve students’ engagement and motivation in learning, but its effects on programming education are not yet fully understood. This study is significant because it can provide valuable insights into the potential benefits of gamification in programming education and inform the development of effective teaching strategies to enhance students’ learning outcomes and interest in programming.

Examples of Significance of the Study

Here are some examples of the significance of a study that indicates how you can write this into your research paper according to your research topic:

Research on an Improved Water Filtration System : This study has the potential to impact millions of people living in water-scarce regions or those with limited access to clean water. A more efficient and affordable water filtration system can reduce water-borne diseases and improve the overall health of communities, enabling them to lead healthier, more productive lives.

Study on the Impact of Remote Work on Employee Productivity : Given the shift towards remote work due to recent events such as the COVID-19 pandemic, this study is of considerable significance. Findings could help organizations better structure their remote work policies and offer insights on how to maximize employee productivity, wellbeing, and job satisfaction.

Investigation into the Use of Solar Power in Developing Countries : With the world increasingly moving towards renewable energy, this study could provide important data on the feasibility and benefits of implementing solar power solutions in developing countries. This could potentially stimulate economic growth, reduce reliance on non-renewable resources, and contribute to global efforts to combat climate change.

Research on New Learning Strategies in Special Education : This study has the potential to greatly impact the field of special education. By understanding the effectiveness of new learning strategies, educators can improve their curriculum to provide better support for students with learning disabilities, fostering their academic growth and social development.

Examination of Mental Health Support in the Workplace : This study could highlight the impact of mental health initiatives on employee wellbeing and productivity. It could influence organizational policies across industries, promoting the implementation of mental health programs in the workplace, ultimately leading to healthier work environments.

Evaluation of a New Cancer Treatment Method : The significance of this study could be lifesaving. The research could lead to the development of more effective cancer treatments, increasing the survival rate and quality of life for patients worldwide.

When to Write Significance of the Study

The Significance of the Study section is an integral part of a research proposal or a thesis. This section is typically written after the introduction and the literature review. In the research process, the structure typically follows this order:

• Title – The name of your research.
• Abstract – A brief summary of the entire research.
• Introduction – A presentation of the problem your research aims to solve.
• Literature Review – A review of existing research on the topic to establish what is already known and where gaps exist.
• Significance of the Study – An explanation of why the research matters and its potential impact.

In the Significance of the Study section, you will discuss why your study is important, who it benefits, and how it adds to existing knowledge or practice in your field. This section is your opportunity to convince readers, and potentially funders or supervisors, that your research is valuable and worth undertaking.

Advantages of Significance of the Study

The Significance of the Study section in a research paper has multiple advantages:

• Establishes Relevance: This section helps to articulate the importance of your research to your field of study, as well as the wider society, by explicitly stating its relevance. This makes it easier for other researchers, funders, and policymakers to understand why your work is necessary and worth supporting.
• Guides the Research: Writing the significance can help you refine your research questions and objectives. This happens as you critically think about why your research is important and how it contributes to your field.
• Attracts Funding: If you are seeking funding or support for your research, having a well-written significance of the study section can be key. It helps to convince potential funders of the value of your work.
• Opens up Further Research: By stating the significance of the study, you’re also indicating what further research could be carried out in the future, based on your work. This helps to pave the way for future studies and demonstrates that your research is a valuable addition to the field.
• Provides Practical Applications: The significance of the study section often outlines how the research can be applied in real-world situations. This can be particularly important in applied sciences, where the practical implications of research are crucial.
• Enhances Understanding: This section can help readers understand how your study fits into the broader context of your field, adding value to the existing literature and contributing new knowledge or insights.

Limitations of Significance of the Study

The Significance of the Study section plays an essential role in any research. However, it is not without potential limitations. Here are some that you should be aware of:

• Subjectivity: The importance and implications of a study can be subjective and may vary from person to person. What one researcher considers significant might be seen as less critical by others. The assessment of significance often depends on personal judgement, biases, and perspectives.
• Predictability of Impact: While you can outline the potential implications of your research in the Significance of the Study section, the actual impact can be unpredictable. Research doesn’t always yield the expected results or have the predicted impact on the field or society.
• Difficulty in Measuring: The significance of a study is often qualitative and can be challenging to measure or quantify. You can explain how you think your research will contribute to your field or society, but measuring these outcomes can be complex.
• Possibility of Overstatement: Researchers may feel pressured to amplify the potential significance of their study to attract funding or interest. This can lead to overstating the potential benefits or implications, which can harm the credibility of the study if these results are not achieved.
• Overshadowing of Limitations: Sometimes, the significance of the study may overshadow the limitations of the research. It is important to balance the potential significance with a thorough discussion of the study’s limitations.
• Dependence on Successful Implementation: The significance of the study relies on the successful implementation of the research. If the research process has flaws or unexpected issues arise, the anticipated significance might not be realized.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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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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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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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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What Is The Significance Of The Study?

In the vast landscape of academia, every research study serves a purpose beyond just adding to the pile of existing knowledge. It’s about unraveling mysteries, solving problems, and making the world a little better. But before diving into any research, one crucial question needs answering: What is the significance of the study? Let’s embark on a journey to understand the importance of this question and how it shapes the landscape of research.

What Is The Importance Of Studying?

Table of Contents

Studying is a fundamental aspect of human learning and development, playing a crucial role in various aspects of life. Its importance spans across personal, academic, professional, and societal domains. Here’s a breakdown of why studying is essential:

• Academic Achievement: Studying is essential for academic success. It helps students grasp concepts, retain information, and demonstrate their understanding through assessments. Whether it’s preparing for exams, completing assignments, or engaging in class discussions, studying forms the backbone of academic achievement.
• Skill Development: Studying isn’t just about memorizing facts; it’s also about developing critical skills such as problem-solving, analytical thinking, and communication. Through studying, individuals hone these skills, which are invaluable in both academic and real-world settings.
• Personal Growth: Studying expands one’s horizons and fosters personal growth. It exposes individuals to new ideas, perspectives, and experiences, challenging them to think critically and question assumptions. Additionally, studying encourages self-discipline, time management, and perseverance, all of which are essential qualities for personal success.
• Career Advancement: In today’s competitive job market, continuous learning is essential for career advancement. Studying allows individuals to acquire new knowledge, skills, and qualifications, making them more competitive and marketable to employers. Whether it’s pursuing higher education, attending professional development courses, or staying updated on industry trends, studying is crucial for career growth.
• Intellectual Stimulation: Studying stimulates the mind and fosters intellectual curiosity. It allows individuals to delve into topics of interest, explore complex ideas, and engage in meaningful intellectual discourse. This intellectual stimulation not only enriches one’s understanding of the world but also enhances cognitive abilities and overall mental well-being.
• Societal Contribution: Studying plays a vital role in advancing society as a whole. Through research, innovation, and knowledge dissemination, studying drives progress in various fields, from science and technology to arts and humanities. Additionally, educated individuals are better equipped to contribute positively to their communities, advocate for social change, and address pressing global challenges.

The significance of a study lies in its ability to address a specific problem or question, contribute to existing knowledge, and have practical applications or implications for various stakeholders. Let’s delve into each aspect with relevant examples:

Addressing a Specific Problem or Question

• Example: A study on the impact of social media usage on mental health among teenagers addresses the pressing concern of rising mental health issues in young people attributed to excessive screen time and online interactions.

Contributing to Existing Knowledge

• Example: A research project investigating the effects of climate change on biodiversity builds upon previous studies by providing new insights into how changing environmental conditions affect different species and ecosystems. By adding to the body of knowledge on this topic, the study contributes to our understanding of the complex interactions between climate and biodiversity.

Practical Applications or Implications

• Example: A study on the effectiveness of mindfulness-based interventions in reducing workplace stress offers practical implications for employers and employees alike. By demonstrating the positive impact of mindfulness practices on employee well-being and productivity, the study informs organizational policies and practices aimed at promoting a healthier work environment.

Informing Policy Decisions

• Example: Research on the economic impact of renewable energy adoption provides policymakers with valuable insights into the potential benefits of transitioning to sustainable energy sources. By quantifying the economic advantages and environmental benefits of renewable energy investments, the study informs policy decisions related to energy planning and resource allocation.

Addressing Social or Health Issues

• Example: Research into how well vaccination campaigns work to lower the spread of diseases is important for public health. This kind of study looks at how good vaccination plans are at stopping diseases from spreading. It also figures out what stops people from getting vaccinated. With this information, health programs can do better at preventing outbreaks and keeping communities safe from diseases.

Fostering Innovation and Progress

• Example: Research on the development of artificial intelligence algorithms for medical diagnosis advances technological innovation in healthcare. By harnessing the power of machine learning and data analytics, the study enables more accurate and efficient diagnosis of medical conditions, leading to improved patient outcomes and advancements in medical practice.

What Is The Significance Of The Study And Statement Of The Problem?

The significance of the study and the statement of the problem are two critical components of any research endeavor, as they lay the foundation for the entire study. Let’s explore their significance individually:

Significance of the Study

• The significance of the study articulates why the research is important and why it matters. It provides justification for conducting the study and highlights its relevance in the broader context of academia, society, or a specific field.
• Significance is about identifying the value and impact of the research in terms of its potential contributions to knowledge, practical applications, policy implications, or societal relevance.
• Without a clear understanding of the significance of the study, researchers may struggle to convey the importance of their work to stakeholders, peers, and the broader community.
• A well-defined significance statement serves as a guiding principle throughout the research process, helping researchers stay focused on the overarching goals and objectives of their study.

Statement of the Problem

• The statement of the problem defines the specific issue or question that the research seeks to address. It clarifies the scope and boundaries of the study by identifying the key variables, concepts, or phenomena under investigation.
• The problem statement highlights the gap or deficiency in existing knowledge that the research aims to fill. It identifies the research gap by demonstrating what is currently unknown, unresolved, or underexplored in the literature.
• A well-crafted problem statement provides a clear and concise description of the research problem, making it easier for readers to understand the purpose and rationale behind the study.
• By defining the problem upfront, researchers can effectively plan their research design, methodology, and data collection strategies to address the identified research gap.
• The statement of the problem serves as a roadmap for the research, guiding the selection of research questions, hypotheses, and analytical approaches to be used in the study.

How Do You Write The Significance Of Research?

Writing the significance of research involves clearly articulating why the study is important, relevant, and worthy of attention. Here’s a step-by-step guide on how to write the significance of research:

• Identify the Problem or Issue

Begin by clearly defining the problem, question, or issue that the research seeks to address. This sets the stage for explaining why the research is necessary.

• Review Existing Literature

Conduct a thorough review of existing literature in the field to understand what has already been studied and what gaps or limitations exist in current knowledge.

• Highlight the Gap in Knowledge

Identify the specific gap or deficiency in existing research that the study aims to fill. This could be a lack of research on a particular topic, conflicting findings in the literature, or unanswered questions that need further exploration.

• Explain the Relevance and Importance

Clearly articulate why the research is important and relevant in the broader context. Consider the potential implications of the research for theory development, practical applications, policy decisions, or societal impact.

• Demonstrate Potential Contributions

Explain how the research will contribute to advancing knowledge in the field. This could involve providing new insights, validating existing theories, developing innovative methodologies, or addressing practical problems.

• Consider Stakeholder Perspectives

Identify the stakeholders or audiences who will benefit from the research findings. Consider their perspectives and interests when explaining the significance of the research.

• Emphasize Practical Applications

Highlight any practical applications or real-world implications of the research. This could include informing policy decisions, improving practices, addressing societal challenges, or benefiting specific industries or communities.

• Provide Justification for Conducting the Study

Offer a compelling rationale for why the research is worth undertaking. This could involve emphasizing the urgency of the problem, the potential benefits of finding a solution, or the intellectual merit of exploring a novel research question.

• Be Concise and Clear

Write the significance of research in a clear, concise, and compelling manner. Avoid jargon or technical language that may obscure the message and focus on communicating the importance of the research in accessible terms.

• Revise and Refine

Review and revise the significance of research to ensure clarity, coherence, and persuasiveness. Solicit feedback from peers, mentors, or colleagues to refine your argument and strengthen your rationale.

In the ever-evolving world of research, the significance of each study lies in its ability to push the boundaries of knowledge, address pressing issues, and make a meaningful impact on the world.

By understanding why a study matters, researchers can ensure that their work contributes meaningfully to the collective pursuit of knowledge and progress. 

So the next time you embark on a research journey, remember to ask yourself: What is the significance of the study? The answer could shape the course of history.

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How to Discuss the Significance of Your Research

• 6-minute read
• 10th April 2023

Introduction

Research papers can be a real headache for college students . As a student, your research needs to be credible enough to support your thesis statement. You must also ensure you’ve discussed the literature review, findings, and results.

However, it’s also important to discuss the significance of your research . Your potential audience will care deeply about this. It will also help you conduct your research. By knowing the impact of your research, you’ll understand what important questions to answer.

If you’d like to know more about the impact of your research, read on! We’ll talk about why it’s important and how to discuss it in your paper.

What Is the Significance of Research?

This is the potential impact of your research on the field of study. It includes contributions from new knowledge from the research and those who would benefit from it. You should present this before conducting research, so you need to be aware of current issues associated with the thesis before discussing the significance of the research.

Why Does the Significance of Research Matter?

Potential readers need to know why your research is worth pursuing. Discussing the significance of research answers the following questions:

●  Why should people read your research paper ?

●  How will your research contribute to the current knowledge related to your topic?

●  What potential impact will it have on the community and professionals in the field?

Not including the significance of research in your paper would be like a knight trying to fight a dragon without weapons.

Where Do I Discuss the Significance of Research in My Paper?

As previously mentioned, the significance of research comes before you conduct it. Therefore, you should discuss the significance of your research in the Introduction section. Your reader should know the problem statement and hypothesis beforehand.

Steps to Discussing the Significance of Your Research

Discussing the significance of research might seem like a loaded question, so we’ve outlined some steps to help you tackle it.

Step 1: The Research Problem

The problem statement can reveal clues about the outcome of your research. Your research should provide answers to the problem, which is beneficial to all those concerned. For example, imagine the problem statement is, “To what extent do elementary and high school teachers believe cyberbullying affects student performance?”

Learning teachers’ opinions on the effects of cyberbullying on student performance could result in the following:

●  Increased public awareness of cyberbullying in elementary and high schools

●  Teachers’ perceptions of cyberbullying negatively affecting student performance

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●  Whether cyberbullying is more prevalent in elementary or high schools

The research problem will steer your research in the right direction, so it’s best to start with the problem statement.

Step 2: Existing Literature in the Field

Think about current information on your topic, and then find out what information is missing. Are there any areas that haven’t been explored? Your research should add new information to the literature, so be sure to state this in your discussion. You’ll need to know the current literature on your topic anyway, as this is part of your literature review section .

Step 3: Your Research’s Impact on Society

Inform your readers about the impact on society your research could have on it. For example, in the study about teachers’ opinions on cyberbullying, you could mention that your research will educate the community about teachers’ perceptions of cyberbullying as it affects student performance. As a result, the community will know how many teachers believe cyberbullying affects student performance.

You can also mention specific individuals and institutions that would benefit from your study. In the example of cyberbullying, you might indicate that school principals and superintendents would benefit from your research.

Step 4: Future Studies in the Field

Next, discuss how the significance of your research will benefit future studies, which is especially helpful for future researchers in your field. In the example of cyberbullying affecting student performance, your research could provide further opportunities to assess teacher perceptions of cyberbullying and its effects on students from larger populations. This prepares future researchers for data collection and analysis.

Discussing the significance of your research may sound daunting when you haven’t conducted it yet. However, an audience might not read your paper if they don’t know the significance of the research. By focusing on the problem statement and the research benefits to society and future studies, you can convince your audience of the value of your research.

Remember that everything you write doesn’t have to be set in stone. You can go back and tweak the significance of your research after conducting it. At first, you might only include general contributions of your study, but as you research, your contributions will become more specific.

You should have a solid understanding of your topic in general, its associated problems, and the literature review before tackling the significance of your research. However, you’re not trying to prove your thesis statement at this point. The significance of research just convinces the audience that your study is worth reading.

Finally, we always recommend seeking help from your research advisor whenever you’re struggling with ideas. For a more visual idea of how to discuss the significance of your research, we suggest checking out this video .

1. Do I need to do my research before discussing its significance?

No, you’re discussing the significance of your research before you conduct it. However, you should be knowledgeable about your topic and the related literature.

2. Is the significance of research the same as its implications?

No, the research implications are potential questions from your study that justify further exploration, which comes after conducting the research.

 3. Discussing the significance of research seems overwhelming. Where should I start?

We recommend the problem statement as a starting point, which reveals clues to the potential outcome of your research.

4. How can I get feedback on my discussion of the significance of my research?

Our proofreading experts can help. They’ll check your writing for grammar, punctuation errors, spelling, and concision. Submit a 500-word document for free today!

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The significance of a study is its importance . It refers to the contribution(s) to and impact of the study on a research field. The significance also signals who benefits from the research findings and how.

Purpose of writing the significance of a study

A study’s significance should spark the interest of the reader. Researchers will be able to appreciate your work better when they understand the relevance and its (potential) impact. Peer reviewers also assess the significance of the work, which will influence the decision made (acceptance/rejection) on the manuscript. 

Sections in which the significance of the study is written

Introduction.

In the Introduction of your paper, the significance appears where you talk about the potential importance and impact of the study. It should flow naturally from the problem , aims and objectives, and rationale .

The significance is described in more detail in the concluding paragraph(s) of the Discussion or the dedicated Conclusions section. Here, you put the findings into perspective and outline the contributions of the findings in terms of implications and applications.

The significance may or may not appear in the abstract . When it does, it is written in the concluding lines of the abstract.

Significance vs. other introductory elements of your paper

In the Introduction…

• The problem statement outlines the concern that needs to be addressed.
• The research aim describes the purpose of the study.
• The objectives indicate how that aim will be achieved.
• The rationale explains why you are performing the study.
• The significance tells the reader how the findings affect the topic/broad field. In other words, the significance is about how much the findings matter.

How to write the significance of the study

A good significance statement may be written in different ways. The approach to writing it also depends on the study area. In the arts and humanities , the significance statement might be longer and more descriptive. In applied sciences , it might be more direct.

a. Suggested sequence for writing the significance statement

• Think of the gaps your study is setting out to address.
• Look at your research from general and specific angles in terms of its (potential) contribution .
• Once you have these points ready, start writing them, connecting them to your study as a whole.

b. Some ways to begin your statement(s) of significance

Here are some opening lines to build on:

• The particular significance of this study lies in the… 
• We argue that this study moves the field forward because…
• This study makes some important contributions to…
• Our findings deepen the current understanding about…

c. Don’ts of writing a significance statement

• Don’t make it too long .
• Don’t repeat any information that has been presented in other sections.
• Don’t overstate or exaggerat e the importance; it should match your actual findings.

Example of significance of a study

Note the significance statements highlighted in the following fictional study.

Significance in the Introduction

The effects of Miyawaki forests on local biodiversity in urban housing complexes remain poorly understood. No formal studies on negative impacts on insect activity, populations or diversity have been undertaken thus far. In this study, we compared the effects that Miyawaki forests in urban dwellings have on local pollinator activity. The findings of this study will help improve the design of this afforestation technique in a way that balances local fauna, particularly pollinators, which are highly sensitive to microclimatic changes.

Significance in the Conclusion

[…] The findings provide valuable insights for guiding and informing Miyawaki afforestation in urban dwellings. We demonstrate that urban planning and landscaping policies need to consider potential declines.

A study’s significance usually appears at the end of the Introduction and in the Conclusion to describe the importance of the research findings. A strong and clear significance statement will pique the interest of readers, as well as that of relevant stakeholders.

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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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StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

StatPearls [Internet].

Statistical significance.

Steven Tenny ; Ibrahim Abdelgawad .

Affiliations

Last Update: November 23, 2023 .

• Introduction

In research, statistical significance measures the probability of the null hypothesis being true compared to the acceptable level of uncertainty regarding the true answer. We can better understand statistical significance if we break apart a study design. [1] [2] [3] [4] [5] [6] [7]

When creating a study, the researcher has to start with a hypothesis; that is, they must have some idea of what they think the outcome may be. For example, a study is researching a new medication to lower blood pressure. The researcher hypothesizes that the new medication lowers systolic blood pressure by at least 10 mm Hg compared to not taking the new medication. The hypothesis can be stated: "Taking the new medication will lower systolic blood pressure by at least 10 mm Hg compared to not taking the medication." In science, researchers can never prove any statement as there are infinite alternatives as to why the outcome may have occurred. They can only try to disprove a specific hypothesis. The researcher must then formulate a question they can disprove while concluding that the new medication lowers systolic blood pressure. The hypothesis to be disproven is the null hypothesis and typically the inverse statement of the hypothesis. Thus, the null hypothesis for our researcher would be, "Taking the new medication will not lower systolic blood pressure by at least 10 mm Hg compared to not taking the new medication." The researcher now has the null hypothesis for the research and must specify the significance level or level of acceptable uncertainty.

Even when disproving a hypothesis, the researcher can not be 100% certain of the outcome. The researcher must then settle for some level of confidence, or the degree of significance, for which they want to be confident their finding is correct. The significance level is given the Greek letter alpha and specified as the probability the researcher is willing to be incorrect. Generally, a researcher wants to be correct about their outcome 95% of the time, so the researcher is willing to be incorrect 5% of the time. Probabilities are decimals, with 1.0 being entirely positive (100%) and 0 being completely negative (0%). Thus, the researcher who wants to be 95% sure about the outcome of their study is willing to be wrong about the result 5% of the time. The alpha is the decimal expression of how much they are ready to be incorrect. For the current example, the alpha is 0.05. The level of uncertainty the researcher is willing to accept (alpha or significance level) is 0.05, or a 5% chance they are incorrect about the study's outcome.

Now, the researcher can perform the research. In this example, a prospective randomized controlled study is conducted in which the researcher gives some individuals the new medication and others a placebo. The researcher then evaluates the blood pressure of both groups after a specified time and performs a statistical analysis of the results to obtain a  P  value (probability value). Several different tests can be performed depending on the type of variable being studied and the number of subjects. The exact test is outside the scope of this review, but the output would be a  P  value. Using the correct statistical analysis tool when calculating the  P  value is imperative. If the researchers use the wrong test, the  P  value will not be accurate, and this result can mislead the researcher. A  P  value is a probability under a specified statistical model that a statistical summary of the data (eg, the sample mean difference between 2 compared groups) would be equal to or more extreme than its observed value.

In this example, the researcher hypothetically found blood pressure tended to decrease after taking the new medication, with an average decrease of 15 mm Hg in the group taking the new medication. The researcher then used the help of their statistician to perform the correct analysis and arrived at a  P  value of 0.02 for a decrease in blood pressure in those taking the new medication versus those not taking the new medication. This researcher now has the 3 required pieces of information to look at statistical significance: the null hypothesis, the significance level, and the  P  value.

The researcher can finally assess the statistical significance of the new medication. A study result is statistically significant if the  P  value of the data analysis is less than the prespecified alpha (significance level). In this example, the P value is 0.02, which is less than the prespecified alpha of 0.05, so the researcher rejects the null hypothesis, which has been determined within the predetermined confidence level to be disproven, and accepts the hypothesis, thus concluding there is statistical significance for the finding that the new medication lowers blood pressure. 

What does this mean? The P value is not the probability of the null hypothesis itself. It is the probability that, if the study were repeated an infinite number of times, one would expect the findings to be as, or more extreme, than the one calculated in this test. Therefore, the  P  value of 0.02 would signify that 2% of the infinite tests would find a result at least as extreme as the one in this study. Given that the null hypothesis states that there is no significant change in blood pressure if the patient is or is not taking the new medication, we can assume that this statement is false, as 98% of the infinite studies would find that there was indeed a reduction in blood pressure. However, as the  P  value implies, there is a chance that this is false, and there truly is no effect of the medication on the blood pressure. However, as the researcher prespecified an acceptable confidence level with an alpha of 0.05, and the  P  value is 0.02, less than the acceptable alpha of 0.05, the researcher rejects the null hypothesis. By rejecting the null hypothesis, the researcher accepts the alternative hypothesis. The researcher rejects the idea that there is no difference in systolic blood pressure with the new medication and accepts a difference of at least 10 mm Hg in systolic blood pressure when taking the new medication.

If the researcher had prespecified an alpha of 0.01, implying they wanted to be 99% sure the new medication lowered the blood pressure by at least 10 mm Hg, the  P  value of 0.02 would be more significant than the prespecified alpha of 0.01. The researcher would conclude the study did not reach statistical significance as the  P  value is equal to or greater than the prespecified alpha. The research would then not be able to reject the null hypothesis.

A study is statistically significant if the  P  value is less than the pre-specified alpha. Stated succinctly:

• A  P  value less than a predetermined alpha is considered a statistically significant result 
• A  P  value greater than or equal to alpha is not a statistically significant result.
• Issues of Concern

A few issues of concern when looking at statistical significance are evident. These issues include choosing the alpha, statistical analysis method, and clinical significance.

Many current research articles specify an alpha of 0.05 for their significance level. It cannot be stated strongly enough that there is nothing special, mathematical, or certain about picking an alpha of 0.05. Historically, the originators concluded that for many applications, an alpha of 0.05, or a one in 20 chance of being incorrect, was good enough. The researcher must consider what the confidence level should genuinely be for the research question being asked. A smaller alpha, say 0.01, may be more appropriate.

When creating a study, the alpha, or confidence level, should be specified before any intervention or collection of data. It is easy for a researcher to "see what the data shows" and then pick an alpha to give a statistically significant result. Such approaches compromise the data and results as the researcher is more likely to be lax on confidence level selection to obtain a result that looks statistically significant.

A second important issue is selecting the correct statistical analysis method. There are numerous methods for obtaining a  P  value. The method chosen depends on the type of data, the number of data points, and the question being asked. It is essential to consider these questions during the study design so the statistical analysis can be correctly identified before the research. The statistical analysis method can help determine how to collect the data correctly and the number of data points needed. If the wrong statistical method is used, the results may be meaningless, as an incorrect  P  value would be calculated.

• Clinical Significance

A key distinction between statistical significance and clinical significance is evident. Statistical significance determines if there is mathematical significance to the analysis of the results. Clinical significance means the difference is vital to the patient and the clinician. This study's statistical significance would be present as the  P  value was less than the prespecified alpha. The clinical significance would be the 10 mmHg drop in systolic blood pressure. [6]

Two studies can have a similar statistical significance but vastly differ in clinical significance. In a hypothetical example of 2 new chemotherapy agents for treating cancer, Drug A increased survival by at least 10 years with a  P  value of 0.01 and an alpha for the study of 0.05. Thus, this study has statistical significance ( P  value less than alpha) and clinical significance (increased survival by 10 years). A second chemotherapy agent, Drug B, increases survival by at least 10 minutes with a  P  value of 0.01 and alpha for the study of 0.05. The study for Drug B also found statistical significance ( P  value less than alpha) but no clinical significance (a 10-minute increase in life expectancy is not clinically significant). In a separate study, those taking Drug A lived an average of 8 years after starting the medication versus living for only 2 more years for those not taking Drug A, with a  P  value of 0.08 and alpha for this second study of Drug A of 0.05. In this second study of Drug A, there is no statistical significance ( P  value greater than or equal to alpha).

• Enhancing Healthcare Team Outcomes

Each healthcare team member needs a basic understanding of statistical significance. All members of the care continuum, including nurses, physicians, advanced practitioners, social workers, and pharmacists, peruse copious literature and consider conclusions based on statistical significance. Suppose team members do not have a cohesive and harmonious understanding of the statistical significance and its implications for research studies and findings. In that case, various members may draw opposing conclusions from the same research.

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Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

Disclosure: Ibrahim Abdelgawad declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Tenny S, Abdelgawad I. Statistical Significance. [Updated 2023 Nov 23]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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What Is Research, and Why Do People Do It?

• Open Access
• First Online: 03 December 2022

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• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
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Part of the book series: Research in Mathematics Education ((RME))

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Abstractspiepr Abs1

Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain, and by its commitment to learn from everyone else seriously engaged in research. We call this kind of research scientific inquiry and define it as “formulating, testing, and revising hypotheses.” By “hypotheses” we do not mean the hypotheses you encounter in statistics courses. We mean predictions about what you expect to find and rationales for why you made these predictions. Throughout this and the remaining chapters we make clear that the process of scientific inquiry applies to all kinds of research studies and data, both qualitative and quantitative.

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

Part I. What Is Research?

Have you ever studied something carefully because you wanted to know more about it? Maybe you wanted to know more about your grandmother’s life when she was younger so you asked her to tell you stories from her childhood, or maybe you wanted to know more about a fertilizer you were about to use in your garden so you read the ingredients on the package and looked them up online. According to the dictionary definition, you were doing research.

Recall your high school assignments asking you to “research” a topic. The assignment likely included consulting a variety of sources that discussed the topic, perhaps including some “original” sources. Often, the teacher referred to your product as a “research paper.”

Were you conducting research when you interviewed your grandmother or wrote high school papers reviewing a particular topic? Our view is that you were engaged in part of the research process, but only a small part. In this book, we reserve the word “research” for what it means in the scientific world, that is, for scientific research or, more pointedly, for scientific inquiry .

Exercise 1.1

Before you read any further, write a definition of what you think scientific inquiry is. Keep it short—Two to three sentences. You will periodically update this definition as you read this chapter and the remainder of the book.

This book is about scientific inquiry—what it is and how to do it. For starters, scientific inquiry is a process, a particular way of finding out about something that involves a number of phases. Each phase of the process constitutes one aspect of scientific inquiry. You are doing scientific inquiry as you engage in each phase, but you have not done scientific inquiry until you complete the full process. Each phase is necessary but not sufficient.

In this chapter, we set the stage by defining scientific inquiry—describing what it is and what it is not—and by discussing what it is good for and why people do it. The remaining chapters build directly on the ideas presented in this chapter.

A first thing to know is that scientific inquiry is not all or nothing. “Scientificness” is a continuum. Inquiries can be more scientific or less scientific. What makes an inquiry more scientific? You might be surprised there is no universally agreed upon answer to this question. None of the descriptors we know of are sufficient by themselves to define scientific inquiry. But all of them give you a way of thinking about some aspects of the process of scientific inquiry. Each one gives you different insights.

Exercise 1.2

As you read about each descriptor below, think about what would make an inquiry more or less scientific. If you think a descriptor is important, use it to revise your definition of scientific inquiry.

Creating an Image of Scientific Inquiry

We will present three descriptors of scientific inquiry. Each provides a different perspective and emphasizes a different aspect of scientific inquiry. We will draw on all three descriptors to compose our definition of scientific inquiry.

Descriptor 1. Experience Carefully Planned in Advance

Sir Ronald Fisher, often called the father of modern statistical design, once referred to research as “experience carefully planned in advance” (1935, p. 8). He said that humans are always learning from experience, from interacting with the world around them. Usually, this learning is haphazard rather than the result of a deliberate process carried out over an extended period of time. Research, Fisher said, was learning from experience, but experience carefully planned in advance.

This phrase can be fully appreciated by looking at each word. The fact that scientific inquiry is based on experience means that it is based on interacting with the world. These interactions could be thought of as the stuff of scientific inquiry. In addition, it is not just any experience that counts. The experience must be carefully planned . The interactions with the world must be conducted with an explicit, describable purpose, and steps must be taken to make the intended learning as likely as possible. This planning is an integral part of scientific inquiry; it is not just a preparation phase. It is one of the things that distinguishes scientific inquiry from many everyday learning experiences. Finally, these steps must be taken beforehand and the purpose of the inquiry must be articulated in advance of the experience. Clearly, scientific inquiry does not happen by accident, by just stumbling into something. Stumbling into something unexpected and interesting can happen while engaged in scientific inquiry, but learning does not depend on it and serendipity does not make the inquiry scientific.

Descriptor 2. Observing Something and Trying to Explain Why It Is the Way It Is

When we were writing this chapter and googled “scientific inquiry,” the first entry was: “Scientific inquiry refers to the diverse ways in which scientists study the natural world and propose explanations based on the evidence derived from their work.” The emphasis is on studying, or observing, and then explaining . This descriptor takes the image of scientific inquiry beyond carefully planned experience and includes explaining what was experienced.

According to the Merriam-Webster dictionary, “explain” means “(a) to make known, (b) to make plain or understandable, (c) to give the reason or cause of, and (d) to show the logical development or relations of” (Merriam-Webster, n.d. ). We will use all these definitions. Taken together, they suggest that to explain an observation means to understand it by finding reasons (or causes) for why it is as it is. In this sense of scientific inquiry, the following are synonyms: explaining why, understanding why, and reasoning about causes and effects. Our image of scientific inquiry now includes planning, observing, and explaining why.

We need to add a final note about this descriptor. We have phrased it in a way that suggests “observing something” means you are observing something in real time—observing the way things are or the way things are changing. This is often true. But, observing could mean observing data that already have been collected, maybe by someone else making the original observations (e.g., secondary analysis of NAEP data or analysis of existing video recordings of classroom instruction). We will address secondary analyses more fully in Chap. 4 . For now, what is important is that the process requires explaining why the data look like they do.

We must note that for us, the term “data” is not limited to numerical or quantitative data such as test scores. Data can also take many nonquantitative forms, including written survey responses, interview transcripts, journal entries, video recordings of students, teachers, and classrooms, text messages, and so forth.

Exercise 1.3

What are the implications of the statement that just “observing” is not enough to count as scientific inquiry? Does this mean that a detailed description of a phenomenon is not scientific inquiry?

Find sources that define research in education that differ with our position, that say description alone, without explanation, counts as scientific research. Identify the precise points where the opinions differ. What are the best arguments for each of the positions? Which do you prefer? Why?

Descriptor 3. Updating Everyone’s Thinking in Response to More and Better Information

This descriptor focuses on a third aspect of scientific inquiry: updating and advancing the field’s understanding of phenomena that are investigated. This descriptor foregrounds a powerful characteristic of scientific inquiry: the reliability (or trustworthiness) of what is learned and the ultimate inevitability of this learning to advance human understanding of phenomena. Humans might choose not to learn from scientific inquiry, but history suggests that scientific inquiry always has the potential to advance understanding and that, eventually, humans take advantage of these new understandings.

Before exploring these bold claims a bit further, note that this descriptor uses “information” in the same way the previous two descriptors used “experience” and “observations.” These are the stuff of scientific inquiry and we will use them often, sometimes interchangeably. Frequently, we will use the term “data” to stand for all these terms.

An overriding goal of scientific inquiry is for everyone to learn from what one scientist does. Much of this book is about the methods you need to use so others have faith in what you report and can learn the same things you learned. This aspect of scientific inquiry has many implications.

One implication is that scientific inquiry is not a private practice. It is a public practice available for others to see and learn from. Notice how different this is from everyday learning. When you happen to learn something from your everyday experience, often only you gain from the experience. The fact that research is a public practice means it is also a social one. It is best conducted by interacting with others along the way: soliciting feedback at each phase, taking opportunities to present work-in-progress, and benefitting from the advice of others.

A second implication is that you, as the researcher, must be committed to sharing what you are doing and what you are learning in an open and transparent way. This allows all phases of your work to be scrutinized and critiqued. This is what gives your work credibility. The reliability or trustworthiness of your findings depends on your colleagues recognizing that you have used all appropriate methods to maximize the chances that your claims are justified by the data.

A third implication of viewing scientific inquiry as a collective enterprise is the reverse of the second—you must be committed to receiving comments from others. You must treat your colleagues as fair and honest critics even though it might sometimes feel otherwise. You must appreciate their job, which is to remain skeptical while scrutinizing what you have done in considerable detail. To provide the best help to you, they must remain skeptical about your conclusions (when, for example, the data are difficult for them to interpret) until you offer a convincing logical argument based on the information you share. A rather harsh but good-to-remember statement of the role of your friendly critics was voiced by Karl Popper, a well-known twentieth century philosopher of science: “. . . if you are interested in the problem which I tried to solve by my tentative assertion, you may help me by criticizing it as severely as you can” (Popper, 1968, p. 27).

A final implication of this third descriptor is that, as someone engaged in scientific inquiry, you have no choice but to update your thinking when the data support a different conclusion. This applies to your own data as well as to those of others. When data clearly point to a specific claim, even one that is quite different than you expected, you must reconsider your position. If the outcome is replicated multiple times, you need to adjust your thinking accordingly. Scientific inquiry does not let you pick and choose which data to believe; it mandates that everyone update their thinking when the data warrant an update.

Doing Scientific Inquiry

We define scientific inquiry in an operational sense—what does it mean to do scientific inquiry? What kind of process would satisfy all three descriptors: carefully planning an experience in advance; observing and trying to explain what you see; and, contributing to updating everyone’s thinking about an important phenomenon?

We define scientific inquiry as formulating , testing , and revising hypotheses about phenomena of interest.

Of course, we are not the only ones who define it in this way. The definition for the scientific method posted by the editors of Britannica is: “a researcher develops a hypothesis, tests it through various means, and then modifies the hypothesis on the basis of the outcome of the tests and experiments” (Britannica, n.d. ).

Notice how defining scientific inquiry this way satisfies each of the descriptors. “Carefully planning an experience in advance” is exactly what happens when formulating a hypothesis about a phenomenon of interest and thinking about how to test it. “ Observing a phenomenon” occurs when testing a hypothesis, and “ explaining ” what is found is required when revising a hypothesis based on the data. Finally, “updating everyone’s thinking” comes from comparing publicly the original with the revised hypothesis.

Doing scientific inquiry, as we have defined it, underscores the value of accumulating knowledge rather than generating random bits of knowledge. Formulating, testing, and revising hypotheses is an ongoing process, with each revised hypothesis begging for another test, whether by the same researcher or by new researchers. The editors of Britannica signaled this cyclic process by adding the following phrase to their definition of the scientific method: “The modified hypothesis is then retested, further modified, and tested again.” Scientific inquiry creates a process that encourages each study to build on the studies that have gone before. Through collective engagement in this process of building study on top of study, the scientific community works together to update its thinking.

Before exploring more fully the meaning of “formulating, testing, and revising hypotheses,” we need to acknowledge that this is not the only way researchers define research. Some researchers prefer a less formal definition, one that includes more serendipity, less planning, less explanation. You might have come across more open definitions such as “research is finding out about something.” We prefer the tighter hypothesis formulation, testing, and revision definition because we believe it provides a single, coherent map for conducting research that addresses many of the thorny problems educational researchers encounter. We believe it is the most useful orientation toward research and the most helpful to learn as a beginning researcher.

A final clarification of our definition is that it applies equally to qualitative and quantitative research. This is a familiar distinction in education that has generated much discussion. You might think our definition favors quantitative methods over qualitative methods because the language of hypothesis formulation and testing is often associated with quantitative methods. In fact, we do not favor one method over another. In Chap. 4 , we will illustrate how our definition fits research using a range of quantitative and qualitative methods.

Exercise 1.4

Look for ways to extend what the field knows in an area that has already received attention by other researchers. Specifically, you can search for a program of research carried out by more experienced researchers that has some revised hypotheses that remain untested. Identify a revised hypothesis that you might like to test.

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

To get a full sense of the definition of scientific inquiry we will use throughout this book, it is helpful to spend a little time with each of the key terms.

We first want to make clear that we use the term “hypothesis” as it is defined in most dictionaries and as it used in many scientific fields rather than as it is usually defined in educational statistics courses. By “hypothesis,” we do not mean a null hypothesis that is accepted or rejected by statistical analysis. Rather, we use “hypothesis” in the sense conveyed by the following definitions: “An idea or explanation for something that is based on known facts but has not yet been proved” (Cambridge University Press, n.d. ), and “An unproved theory, proposition, or supposition, tentatively accepted to explain certain facts and to provide a basis for further investigation or argument” (Agnes & Guralnik, 2008 ).

We distinguish two parts to “hypotheses.” Hypotheses consist of predictions and rationales . Predictions are statements about what you expect to find when you inquire about something. Rationales are explanations for why you made the predictions you did, why you believe your predictions are correct. So, for us “formulating hypotheses” means making explicit predictions and developing rationales for the predictions.

“Testing hypotheses” means making observations that allow you to assess in what ways your predictions were correct and in what ways they were incorrect. In education research, it is rarely useful to think of your predictions as either right or wrong. Because of the complexity of most issues you will investigate, most predictions will be right in some ways and wrong in others.

By studying the observations you make (data you collect) to test your hypotheses, you can revise your hypotheses to better align with the observations. This means revising your predictions plus revising your rationales to justify your adjusted predictions. Even though you might not run another test, formulating revised hypotheses is an essential part of conducting a research study. Comparing your original and revised hypotheses informs everyone of what you learned by conducting your study. In addition, a revised hypothesis sets the stage for you or someone else to extend your study and accumulate more knowledge of the phenomenon.

We should note that not everyone makes a clear distinction between predictions and rationales as two aspects of hypotheses. In fact, common, non-scientific uses of the word “hypothesis” may limit it to only a prediction or only an explanation (or rationale). We choose to explicitly include both prediction and rationale in our definition of hypothesis, not because we assert this should be the universal definition, but because we want to foreground the importance of both parts acting in concert. Using “hypothesis” to represent both prediction and rationale could hide the two aspects, but we make them explicit because they provide different kinds of information. It is usually easier to make predictions than develop rationales because predictions can be guesses, hunches, or gut feelings about which you have little confidence. Developing a compelling rationale requires careful thought plus reading what other researchers have found plus talking with your colleagues. Often, while you are developing your rationale you will find good reasons to change your predictions. Developing good rationales is the engine that drives scientific inquiry. Rationales are essentially descriptions of how much you know about the phenomenon you are studying. Throughout this guide, we will elaborate on how developing good rationales drives scientific inquiry. For now, we simply note that it can sharpen your predictions and help you to interpret your data as you test your hypotheses.

Hypotheses in education research take a variety of forms or types. This is because there are a variety of phenomena that can be investigated. Investigating educational phenomena is sometimes best done using qualitative methods, sometimes using quantitative methods, and most often using mixed methods (e.g., Hay, 2016 ; Weis et al. 2019a ; Weisner, 2005 ). This means that, given our definition, hypotheses are equally applicable to qualitative and quantitative investigations.

Hypotheses take different forms when they are used to investigate different kinds of phenomena. Two very different activities in education could be labeled conducting experiments and descriptions. In an experiment, a hypothesis makes a prediction about anticipated changes, say the changes that occur when a treatment or intervention is applied. You might investigate how students’ thinking changes during a particular kind of instruction.

A second type of hypothesis, relevant for descriptive research, makes a prediction about what you will find when you investigate and describe the nature of a situation. The goal is to understand a situation as it exists rather than to understand a change from one situation to another. In this case, your prediction is what you expect to observe. Your rationale is the set of reasons for making this prediction; it is your current explanation for why the situation will look like it does.

You will probably read, if you have not already, that some researchers say you do not need a prediction to conduct a descriptive study. We will discuss this point of view in Chap. 2 . For now, we simply claim that scientific inquiry, as we have defined it, applies to all kinds of research studies. Descriptive studies, like others, not only benefit from formulating, testing, and revising hypotheses, but also need hypothesis formulating, testing, and revising.

One reason we define research as formulating, testing, and revising hypotheses is that if you think of research in this way you are less likely to go wrong. It is a useful guide for the entire process, as we will describe in detail in the chapters ahead. For example, as you build the rationale for your predictions, you are constructing the theoretical framework for your study (Chap. 3 ). As you work out the methods you will use to test your hypothesis, every decision you make will be based on asking, “Will this help me formulate or test or revise my hypothesis?” (Chap. 4 ). As you interpret the results of testing your predictions, you will compare them to what you predicted and examine the differences, focusing on how you must revise your hypotheses (Chap. 5 ). By anchoring the process to formulating, testing, and revising hypotheses, you will make smart decisions that yield a coherent and well-designed study.

Exercise 1.5

Compare the concept of formulating, testing, and revising hypotheses with the descriptions of scientific inquiry contained in Scientific Research in Education (NRC, 2002 ). How are they similar or different?

Exercise 1.6

Provide an example to illustrate and emphasize the differences between everyday learning/thinking and scientific inquiry.

Learning from Doing Scientific Inquiry

We noted earlier that a measure of what you have learned by conducting a research study is found in the differences between your original hypothesis and your revised hypothesis based on the data you collected to test your hypothesis. We will elaborate this statement in later chapters, but we preview our argument here.

Even before collecting data, scientific inquiry requires cycles of making a prediction, developing a rationale, refining your predictions, reading and studying more to strengthen your rationale, refining your predictions again, and so forth. And, even if you have run through several such cycles, you still will likely find that when you test your prediction you will be partly right and partly wrong. The results will support some parts of your predictions but not others, or the results will “kind of” support your predictions. A critical part of scientific inquiry is making sense of your results by interpreting them against your predictions. Carefully describing what aspects of your data supported your predictions, what aspects did not, and what data fell outside of any predictions is not an easy task, but you cannot learn from your study without doing this analysis.

Analyzing the matches and mismatches between your predictions and your data allows you to formulate different rationales that would have accounted for more of the data. The best revised rationale is the one that accounts for the most data. Once you have revised your rationales, you can think about the predictions they best justify or explain. It is by comparing your original rationales to your new rationales that you can sort out what you learned from your study.

Suppose your study was an experiment. Maybe you were investigating the effects of a new instructional intervention on students’ learning. Your original rationale was your explanation for why the intervention would change the learning outcomes in a particular way. Your revised rationale explained why the changes that you observed occurred like they did and why your revised predictions are better. Maybe your original rationale focused on the potential of the activities if they were implemented in ideal ways and your revised rationale included the factors that are likely to affect how teachers implement them. By comparing the before and after rationales, you are describing what you learned—what you can explain now that you could not before. Another way of saying this is that you are describing how much more you understand now than before you conducted your study.

Revised predictions based on carefully planned and collected data usually exhibit some of the following features compared with the originals: more precision, more completeness, and broader scope. Revised rationales have more explanatory power and become more complete, more aligned with the new predictions, sharper, and overall more convincing.

Part II. Why Do Educators Do Research?

Doing scientific inquiry is a lot of work. Each phase of the process takes time, and you will often cycle back to improve earlier phases as you engage in later phases. Because of the significant effort required, you should make sure your study is worth it. So, from the beginning, you should think about the purpose of your study. Why do you want to do it? And, because research is a social practice, you should also think about whether the results of your study are likely to be important and significant to the education community.

If you are doing research in the way we have described—as scientific inquiry—then one purpose of your study is to understand , not just to describe or evaluate or report. As we noted earlier, when you formulate hypotheses, you are developing rationales that explain why things might be like they are. In our view, trying to understand and explain is what separates research from other kinds of activities, like evaluating or describing.

One reason understanding is so important is that it allows researchers to see how or why something works like it does. When you see how something works, you are better able to predict how it might work in other contexts, under other conditions. And, because conditions, or contextual factors, matter a lot in education, gaining insights into applying your findings to other contexts increases the contributions of your work and its importance to the broader education community.

Consequently, the purposes of research studies in education often include the more specific aim of identifying and understanding the conditions under which the phenomena being studied work like the observations suggest. A classic example of this kind of study in mathematics education was reported by William Brownell and Harold Moser in 1949 . They were trying to establish which method of subtracting whole numbers could be taught most effectively—the regrouping method or the equal additions method. However, they realized that effectiveness might depend on the conditions under which the methods were taught—“meaningfully” versus “mechanically.” So, they designed a study that crossed the two instructional approaches with the two different methods (regrouping and equal additions). Among other results, they found that these conditions did matter. The regrouping method was more effective under the meaningful condition than the mechanical condition, but the same was not true for the equal additions algorithm.

What do education researchers want to understand? 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 develop understanding that supports the improvement of learning opportunities for all students. We say “ultimate” because there are lots of issues that must be understood to improve learning opportunities for all students. Hypotheses about many aspects of education are connected, ultimately, to students’ learning. For example, formulating and testing a hypothesis that preservice teachers need to engage in particular kinds of activities in their coursework in order to teach particular topics well is, ultimately, connected to improving students’ learning opportunities. So is hypothesizing that school districts often devote relatively few resources to instructional leadership training or hypothesizing that positioning mathematics as a tool students can use to combat social injustice can help students see the relevance of mathematics to their lives.

We do not exclude the importance of research on educational issues more removed from improving students’ learning opportunities, but we do think the argument for their importance will be more difficult to make. If there is no way to imagine a connection between your hypothesis and improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Notice that we said the ultimate goal of education is to offer all students the best possible learning opportunities. For too long, educators have been satisfied with a goal of offering rich learning opportunities for lots of students, sometimes even for just the majority of students, but not necessarily for all students. Evaluations of success often are based on outcomes that show high averages. In other words, if many students have learned something, or even a smaller number have learned a lot, educators may have been satisfied. The problem is that there is usually a pattern in the groups of students who receive lower quality opportunities—students of color and students who live in poor areas, urban and rural. This is not acceptable. Consequently, we emphasize the premise that the purpose of education research is to offer rich learning opportunities to all students.

One way to make sure you will be able to convince others of the importance of your study is to consider investigating some aspect of teachers’ shared instructional problems. Historically, researchers in education have set their own research agendas, regardless of the problems teachers are facing in schools. It is increasingly recognized that teachers have had trouble applying to their own classrooms what researchers find. To address this problem, a researcher could partner with a teacher—better yet, a small group of teachers—and talk with them about instructional problems they all share. These discussions can create a rich pool of problems researchers can consider. If researchers pursued one of these problems (preferably alongside teachers), the connection to improving learning opportunities for all students could be direct and immediate. “Grounding a research question in instructional problems that are experienced across multiple teachers’ classrooms helps to ensure that the answer to the question will be of sufficient scope to be relevant and significant beyond the local context” (Cai et al., 2019b , p. 115).

As a beginning researcher, determining the relevance and importance of a research problem is especially challenging. We recommend talking with advisors, other experienced researchers, and peers to test the educational importance of possible research problems and topics of study. You will also learn much more about the issue of research importance when you read Chap. 5 .

Exercise 1.7

Identify a problem in education that is closely connected to improving learning opportunities and a problem that has a less close connection. For each problem, write a brief argument (like a logical sequence of if-then statements) that connects the problem to all students’ learning opportunities.

Part III. Conducting Research as a Practice of Failing Productively

Scientific inquiry involves formulating hypotheses about phenomena that are not fully understood—by you or anyone else. Even if you are able to inform your hypotheses with lots of knowledge that has already been accumulated, you are likely to find that your prediction is not entirely accurate. This is normal. Remember, scientific inquiry is a process of constantly updating your thinking. More and better information means revising your thinking, again, and again, and again. Because you never fully understand a complicated phenomenon and your hypotheses never produce completely accurate predictions, it is easy to believe you are somehow failing.

The trick is to fail upward, to fail to predict accurately in ways that inform your next hypothesis so you can make a better prediction. Some of the best-known researchers in education have been open and honest about the many times their predictions were wrong and, based on the results of their studies and those of others, they continuously updated their thinking and changed their hypotheses.

A striking example of publicly revising (actually reversing) hypotheses due to incorrect predictions is found in the work of Lee J. Cronbach, one of the most distinguished educational psychologists of the twentieth century. In 1955, Cronbach delivered his presidential address to the American Psychological Association. Titling it “Two Disciplines of Scientific Psychology,” Cronbach proposed a rapprochement between two research approaches—correlational studies that focused on individual differences and experimental studies that focused on instructional treatments controlling for individual differences. (We will examine different research approaches in Chap. 4 ). If these approaches could be brought together, reasoned Cronbach ( 1957 ), researchers could find interactions between individual characteristics and treatments (aptitude-treatment interactions or ATIs), fitting the best treatments to different individuals.

In 1975, after years of research by many researchers looking for ATIs, Cronbach acknowledged the evidence for simple, useful ATIs had not been found. Even when trying to find interactions between a few variables that could provide instructional guidance, the analysis, said Cronbach, creates “a hall of mirrors that extends to infinity, tormenting even the boldest investigators and defeating even ambitious designs” (Cronbach, 1975 , p. 119).

As he was reflecting back on his work, Cronbach ( 1986 ) recommended moving away from documenting instructional effects through statistical inference (an approach he had championed for much of his career) and toward approaches that probe the reasons for these effects, approaches that provide a “full account of events in a time, place, and context” (Cronbach, 1986 , p. 104). This is a remarkable change in hypotheses, a change based on data and made fully transparent. Cronbach understood the value of failing productively.

Closer to home, in a less dramatic example, one of us began a line of scientific inquiry into how to prepare elementary preservice teachers to teach early algebra. Teaching early algebra meant engaging elementary students in early forms of algebraic reasoning. Such reasoning should help them transition from arithmetic to algebra. To begin this line of inquiry, a set of activities for preservice teachers were developed. Even though the activities were based on well-supported hypotheses, they largely failed to engage preservice teachers as predicted because of unanticipated challenges the preservice teachers faced. To capitalize on this failure, follow-up studies were conducted, first to better understand elementary preservice teachers’ challenges with preparing to teach early algebra, and then to better support preservice teachers in navigating these challenges. In this example, the initial failure was a necessary step in the researchers’ scientific inquiry and furthered the researchers’ understanding of this issue.

We present another example of failing productively in Chap. 2 . That example emerges from recounting the history of a well-known research program in mathematics education.

Making mistakes is an inherent part of doing scientific research. Conducting a study is rarely a smooth path from beginning to end. We recommend that you keep the following things in mind as you begin a career of conducting research in education.

First, do not get discouraged when you make mistakes; do not fall into the trap of feeling like you are not capable of doing research because you make too many errors.

Second, learn from your mistakes. Do not ignore your mistakes or treat them as errors that you simply need to forget and move past. Mistakes are rich sites for learning—in research just as in other fields of study.

Third, by reflecting on your mistakes, you can learn to make better mistakes, mistakes that inform you about a productive next step. You will not be able to eliminate your mistakes, but you can set a goal of making better and better mistakes.

Exercise 1.8

How does scientific inquiry differ from everyday learning in giving you the tools to fail upward? You may find helpful perspectives on this question in other resources on science and scientific inquiry (e.g., Failure: Why Science is So Successful by Firestein, 2015).

Exercise 1.9

Use what you have learned in this chapter to write a new definition of scientific inquiry. Compare this definition with the one you wrote before reading this chapter. If you are reading this book as part of a course, compare your definition with your colleagues’ definitions. Develop a consensus definition with everyone in the course.

Part IV. Preview of Chap. 2

Now that you have a good idea of what research is, at least of what we believe research is, the next step is to think about how to actually begin doing research. This means how to begin formulating, testing, and revising hypotheses. As for all phases of scientific inquiry, there are lots of things to think about. Because it is critical to start well, we devote Chap. 2 to getting started with formulating hypotheses.

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• Published: 17 May 2024

Assessing the status quo of international employees’ adjustment research, 1990–2022: a review and future research agenda

• Irma Baneviciene 1 ,
• Maike Andresen 2 &
• Vilmante Kumpikaite-Valiuniene 3  

Humanities and Social Sciences Communications volume  11 , Article number:  633 ( 2024 ) Cite this article

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• Business and management
• Politics and international relations

This study aims to comprehensively review scientific journal articles related to the adjustment of international employees within the management and business domain from 1990 to 2022. The study seeks to identify trends and patterns in research topics and to propose a future research agenda. To achieve this, we analysed 222 articles from the Web of Science Core Collection database through two main steps: (1) a bibliometric analysis to track the field’s evolution over time and (2) a content analysis of abstracts to examine covered topics and pinpoint research gaps. Our findings indicate that the theory surrounding the adjustment of international employees is still in the process of maturation, with several potential areas for future research emerging. The analysis reveals that factors influencing adjustment are the most extensively researched for assigned expatriates, leaving other international employees relatively under-researched. Moreover, quantitative research emerged as the most prevalent methodological approach among the included studies. Most study samples predominantly consisted of individuals moving between Asia, Europe, and North America, underscoring the significance of Africa—characterised by substantial migration flows within the region—as a focal point for future adjustment research. Moreover, individual-, organisation-, and country-related antecedents of international employees’ anticipatory and in-country adjustments were analysed to present conclusions for future research. This study supplements the domains of international human resource management and international business by identifying research priorities concerning the adjustment of international employees and outlining an agenda for further research.

Introduction

Economic globalisation facilitates the movement of people, capital, goods, and ideas across borders, leading to a significant rise in international mobility among the workforce, a trend that is of global relevance (Duan et al. 2021 ). According to the International Organisation for Migration (IOM UN Migration 2022 ), the global population of international migrants reached approximately 281 million in 2020, representing 3.6% of the world’s population. This figure marks a significant increase from previous years, with 128 million more international migrants than in 1990 and over three times the number reported in 1970 (IOM UN Migration 2022 ). The adjustment of these individuals to new countries and organisations varies depending on factors such as language barriers, geopolitical dynamics, cultural differences, and familial status. Therefore, research into working people’s international mobility and adjustment has gained much attention from researchers worldwide.

A review of previous studies on adjustment highlights a predominant focus on cross-cultural issues, including the development of adjustment over time, the influence of prior international experience, cross-cultural training, and intercultural learning (Chenyang 2022 ; Morris et al. 2014 ; Nam et al. 2014 ; Takeuchi and Chen, 2013 ). Additionally, numerous antecedents of expatriate adjustment have been examined, such as personality traits, expatriate-local interactions, family dynamics, and organisational factors (Van Bakel 2019 ; Dang et al. 2022 ; Harari et al. 2018 ; Haslberger and Brewster 2008 ; Kang and Shen 2018 ; Takeuchi 2010 ). Similarly, studies by Hajro et al. ( 2019 ), Schudey et al. ( 2012 ), and Shen and Hall ( 2009 ) explored the influences of individual, organisational, and social variables on migrants’ acculturation, coping mechanisms and integration, as well as repatriate readjustment.

This review makes a unique contribution by focusing on the factors influencing the adjustment of different groups of international employees, namely expatriates and migrants. Through systematic literature mapping, it delineates the scope of existing research on adjustment, its evolution over time, and differences between employee groups. By aligning findings with macro-level migration data, the study identifies research gaps and priorities, which are crucial for enhancing our understanding of adjustment processes and informing future research directions. This unique approach aims to advance research on the adjustment of international employees (IE), thereby contributing to the existing body of knowledge on international human resource management and international business.

The literature reveals a plethora of definitions of IEs based on various factors such as mobility patterns, employment characteristics, education level, support availability, and planned duration of stay in a foreign country. However, these definitions often overlap, and authors tailor unique definitions to suit their research needs (Andresen et al. 2018 ). Common types of IEs include assigned expatriates, self-initiated expatriates (SIEs), sojourners, migrants, international business travellers, short-term assignees, rotational assignees, and international commuters, with SIEs, assigned expatriates, skilled migrants, and skilled immigrants being the most frequently discussed groups in the literature (Andresen et al. 2014 ; McNulty and Selmer 2017 ; Cerdin and Selmer 2014 ; McNulty and Brewster 2017 ).

The adjustment of IEs is multifaceted and varies depending on the type of IE and the circumstances surrounding their becoming IEs (Shaffer et al. 1999 ). According to Waxin and Panaccio ( 2005 ), the intercultural adjustment of expatriates is defined as a ratio of human psychological comfort and knowledge of a foreign culture. However, scholars have offered differing definitions of intercultural adjustment, with terms such as adjustment, adaptation, assimilation, acculturation, and integration often used interchangeably (Harrison et al. 2004 ). In this study, “adjustment” is the standard term to denote realigning one’s needs with new cultural demands after relocating to an unfamiliar cultural environment (Aycan 1997 ; Bhaskar-Shrinivas et al. 2005 ).

Against this backdrop, a hybrid literature review was conducted, combining bibliometric analysis and content analysis of scientific article abstracts published between 1990 and 2022. Generated systematic literature mapping aimed to (1) provide insights into the field’s evolution over time; (2) identify research trends, priorities, and critical areas; (3) pinpoint research gaps for future exploration.

This study contributes to adjustment theory in five key ways. Firstly, it highlights the need to refine the adjustment construct’s definition, conceptual landscape, nomological network, and causal mechanisms. Secondly, it underscores the importance of systematically identifying the boundary conditions of adjustment theory. Thirdly, it tracks evolutionary nuances to anticipate the trajectory of adjustment research. Fourthly, it identifies critical knowledge gaps to inform future research directions. Finally, recommendations for research methods are provided to facilitate the evolution of adjustment theory from an intermediate to a mature state.

The paper has been structured into four parts. The first part defines adjustment together with an overview of its most essential antecedents that can be identified in the literature. It expounds upon the methodology and strategy used in the study. The second part presents the findings of the bibliometric analysis that indicates general information such as publication year, country, and the research sample’s nationality. The third part covers the content analysis of the abstracts with the presentation of the covered themes and research areas. The final part then discusses the main results and limitations and outlines future research areas.

Theoretical background

The adjustment model proposed by Black et al. ( 1991 ) depicts the factors influencing adjustment and refers to the group of assigned expatriates. The authors differentiate between anticipatory and in-country adjustment, representing two stages of the expatriate cross-cultural adjustment process. Anticipatory adjustment, which occurs before the international relocation, is determined by individual factors, such as training and previous experience and organisational factors, such as selection mechanisms and criteria. It is assumed that individuals’ anticipatory adjustment, i.e., their preparation before they embark on the journey to the host country, will ease their adjustment abroad. Black et al. ( 1991 ) highlighted four influencing factors related to in-country adjustment, which takes place upon relocation to the destination country, that relate to the sphere of the individual (self-efficacy, relation skills, and perception skills), job (role clarity, role discretion, role novelty, role conflict), organisation (organisation culture novelty, social support, logistical help, socialisation tactics, socialisation content), and nonwork (culture novelty and family-spouse adjustment). The in-country adjustment process leads to different degrees of adjustment in terms of work, interaction , and general adjustment in the country of destination that can be measured.

Subsequent researchers delving into adjustment and extending the framework proposed by Black et al. ( 1991 ) revealed additional factors influencing anticipatory and in-country adjustment. For instance, Yijälä et al. ( 2012 ) investigated the anticipatory adjustment of highly skilled, self-initiated foreign employees, shedding light on specific challenges and strategies pertinent to this cohort. They differentiate between psychological , socio-psychological , and work-related anticipatory adjustment. Lett and Smith ( 2009 ) distinguished – analogous to Black et al. ( 1991 ) – pre-departure and in-country adjustment and highlight individual , organisational , job , and non-work factors that impact adjustment before and after moving to the destination country.

Ritchie et al. ( 2015 ) expanded on general adjustment following relocation by identifying additional precursors, including job satisfaction, team cohesion, and alignment with organisational values. Additionally, they advocate for the incorporation of control variables related to demographics and individual traits such as gender, family status, parental responsibilities, professional background, tenure, and linguistic abilities (Caligiuri et al. 1998 ; Canhilal et al. 2015 ; Chen 2010 ; Lee et al. 2014 ), a recommendation that subsequent scholars have adopted in their studies. Hippler et al. ( 2014 ) divided their scale into ten factors delineating various aspects or changes that may necessitate adjustment. These factors encompass aspects of the work environment, language proficiency, job or task attributes, recreational activities, urban setting, work-life balance, living accommodations, familial dynamics, local social connections, and communication with those remaining behind. This approach shows that work - related facets of IEs’ adjustment receive the least attention.

After reviewing the antecedents of adjustment proposed by different authors (e.g., Black et al. 1991 ; Caligiuri et al. 1998 ; Chen, 2010 ; Hippler et al. 2014 ; Lee et al. 2014 ; Lett and Smith, 2009 ; Ritchie et al. 2015 ), both similarities and some differences become apparent. Based on this overview, we group the antecedents of IEs’ adjustment (anticipatory and in-country) into the following main groups: individual-, organisation-, and country-related antecedents (see Fig. 1 ).

Model of factors influencing IE adjustment.

The study aims to achieve several objectives: firstly, to offer a comprehensive overview of the evolution of research within the adjustment field over time, including the types of international employees (IEs) whose adjustment is being researched, the terminology utilised to describe ‘adjustment’ in publications, and the research methodologies employed. Secondly, it seeks to identify trends in research topics, delineate research priorities, and highlight critical research areas. Lastly, the study aims to uncover research gaps that necessitate attention in future studies.

The methodology employed in our study, illustrated in Fig. 2 , follows an adapted systematic mapping approach proposed by Petersen et al. ( 2008 ). This approach enables the collation, description, and cataloguing of available evidence, as elucidated by James et al. ( 2016 ). By adopting this approach, we can provide a broad overview of a research field and identify the amount and type of research in this field (Petersen et al. 2008 ; Soaita et al. 2020 ), as elaborated upon in subsequent sections.

Study mapping process.

For analysis purposes, we utilised the Web of Science (WoS) Core Collection database, renowned as one of the premier platforms for scientific citation search, discovery, and analytical information (Li et al. 2018 ). Scholars frequently rely on this database for bibliometric analyses (Vlase and Lähdesmäki 2023 ). With its comprehensive coverage spanning articles from 1900 onwards (Chadegani et al. 2013 ), the WoS database provides a robust foundation for gaining insights into trends in academic research on IEs’ adjustment, a vital component of this study.

To conduct our literature search, we established specific inclusion criteria. We designated the base timeframe for the search period from 1990 to 2022 (July). Within the WoS platform, we focused on the management and business categories, representing the primary disciplines relevant to international employees’ adjustment. Articles were restricted to published in English, the predominant language for international collaboration.

We formulated search terms targeting IEs and an adjustment in identifying relevant articles. For the IE aspect, keywords such as immigrant, migrant, and expatriate were employed. Concerning adjustment, the terms adaptation, assimilation, acculturation, and integration were selected, aligning with the terminology outlined by Harrison et al. ( 2004 ) as synonymous with adjustment. The search terms were combined of the two search fields into a search string using “AND” to search the title, abstracts, or keywords of the articles, i.e. (immigra* OR migra* OR expatriat*) AND (adjust* OR adapt* OR assimilat* OR acculturat* OR integrat*). As an additional criterion, it was stipulated that one of the keywords related to adjustment must be present as an article keyword. Article keywords were meticulously chosen by authors to accurately encapsulate the essence of their paper (Emich et al. 2020 ; Zhang et al. 2016 ). Hence, if authors perceive their article as directly pertinent to adjustment, they are inclined to opt for the term as a keyword.

The search yielded a total of 444 articles. The abstracts of these articles were imported into the MAXQDA software, commonly used for qualitative and mixed methods research. Each abstract was meticulously reviewed to confirm its relevance to IE adjustment. In cases where abstracts lacked clarity and inclusion or exclusion was uncertain, the introduction or conclusion of the paper was consulted for clarification (Petersen et al. 2008 ). Out of the initial pool, 222 articles were identified as unrelated to IE adjustment, focusing instead on consumer acculturation’s impact on product selection, micromarketing issues regarding immigration and acculturation, and differences in labour and capital incomes between immigrants and natives. The final selection of the articles for the study consists of 222 articles.

A hybrid approach combining bibliometric analysis and structured review was adopted to analyse the data and achieve the research objectives, following the framework proposed by Paul and Criado ( 2020 ). Bibliometric analysis provided insights into the evolution of the field and trends in articles on adjustment and their prevalence concerning types of international employees published from 1990 to 2022. Concurrently, structured review techniques, including content analysis, were employed to identify research trends and uncover research gaps (Paul and Criado 2020 ). Content analysis systematically condenses extensive text into categories based on predefined coding rules, facilitating the identification of document trends and patterns (Stemler 2000 ), thus offering a systematic and objective means of describing and quantifying phenomena (Downe-Wamboldt, 1992 ).

The initial coding process involved 50 articles from the corpus of 222, conducted by one author and subsequently reviewed by other authors. The coding system was refined through discussions among the authors, ensuring consensus. Following this, the 50 initial abstracts were re-analysed, and all remaining abstracts were subjected to the established coding rules. (1) Main categories were created for all statistical data: publication year, research method, terminology of ‘adjustment’ used in the articles, country of research, nationality of participants, and type of IE. (2) Deductive categories of anticipatory and in-country adjustment were utilised to examine the antecedents of IE adjustment. Each category was further subdivided into individual-related, organisation-related, and country-related antecedents. Inductive codes were then defined for each identified antecedent and assigned to the deductive categories (refer to Table 1 for details).

All statistical data and specified antecedents underwent coding based on the abstracts. A total of 1522 coding instances were assigned. The total number of codings per category sometimes varied from the total number of articles in the corpus. This discrepancy occurred because not all articles included information relevant to every category, or multiple subcategories within an article were pertinent, resulting in multiple codings. For instance, if an article examined and assigned expatriates and self-initiated expatriates within its sample, two codings were recorded under the IE type category.

The interrelationships among the categories were analysed to identify prevalent themes and underlying patterns of connection.

General information

Field progression over time.

A total of 222 articles spanning from 1990 to 2022 were subjected to analysis (refer to Fig. 3 ). The distribution of articles across each year within this timeframe reveals distinct phases in the evolution of interest in IE adjustment research: before 1999, between 2000 and 2016, and from 2017 onwards. Before 1999, sporadic publications occurred every few years (a total of five), indicating budding interest in the field without establishing it as a full-fledged area of research. From 2000 to 2016, researchers consistently, albeit modestly, addressed IE adjustment, with the number of published articles gradually increasing from two per year to a maximum of 12 in specific years. Notably, since 2017, 27 years after the first publication on IE adjustment, the annual publication count has consistently reached 20 or more, albeit not every year. This sustained growth in publications within the management and business domains reflects rising scholarly interest in IE adjustment. Such findings affirm our initiative to delve into topic diversity, identify research gaps, and contribute to the future advancement of the field.

Number of articles on IE adjustment published per year, 1990–2022.

Types of IEs researched

Coding the type of IEs studied in the articles in the corpus generated 230 codings (see Fig. 4 ). Based on the terminology used in the abstracts by the researchers themselves to elucidate the types of IEs studied in each case, two subcategories of IEs were generated: (a) expatriates (assigned expatriates and self-initiated expatriates) and (b) migrants (migrant workers, immigrants, and skilled/qualified migrants).

Use of the different IE types to name the samples per year.

In comparison, a more significant proportion of articles concentrated on the expatriate cohort (197 articles) than the migrant cohort (33 articles). Specifically, assigned expatriates emerged as the most extensively studied subgroup within the expatriate cohort, with 165 articles dedicated to their adjustment consistently appearing in the scientific literature over the years. Notably, research on the adjustment of assigned expatriates commenced as early as 1990 and has steadily escalated since 2000. The period post-2017 witnessed a sustained and notable volume of articles on assigned expatriates, indicating continued scholarly interest in this area.

Conversely, a significantly smaller number of research publications delved into the adjustment of self-initiated expatriates (SIEs) (32 articles), albeit ranking as the second highest. Interestingly, the earliest article addressing the adjustment of SIEs only emerged in 2008. Although the number of articles SIEs has remained relatively low over the years, there was a notable surge in 2021 with nine articles. Nonetheless, research on SIEs has persisted since 2012, albeit in limited numbers.

The second cohort, migrants, was represented in 33 articles. Among these, the term “immigrant” was predominantly utilised in 20 articles to define the focus group of their research. Four articles specifically focussed on migrant workers, while nine underscored the high skills or qualifications of the migrants in their respective samples. Moreover, research on adjustment primarily concentrated on adjusting IEs to the host country, with no studies additionally analysing the reciprocal adjustment of locals to the cultural changes introduced by IEs.

To summarise, most adjustment research focuses on expatriates, particularly assigned expatriates, with a notable increase in articles over the years. Conversely, studies on all other groups have remained consistent, albeit low, levels. Furthermore, adjustment was predominantly explored unilaterally through the lens of IEs.

Adjustment terminology used

The terms adjustment, acculturation, assimilation, integration, and adaptation have been used to describe IEs’ successful settling in a new host country, new job, or community. Figure 5 shows the adjustment terms used in the scientific literature concerning a specific type of IE.

Use of terminology around “adjustment” according to IE types.

Assimilation is the least utilised term in the literature on IE adjustment, appearing in only two articles. Acculturation, integration, and adaptation were employed more frequently, with 13, 12, and 23 articles, respectively. However, the usage frequency of these terms pales compared to the predominant use of the term adjustment, which was featured in 174 articles.

Furthermore, we analysed the extent to which multiple terms were employed within individual article abstracts. While most authors consistently used only one term in their articles, a minority of articles (9) utilised four of the five adjustment terms in varying combinations. For instance, as the primary term, adjustment was paired with acculturation (1) and integration (1). Acculturation, as the primary term, was coupled with adjustment (1), assimilation (1), or integration (4). Assimilation, as the primary term, was combined with acculturation (1) and integration (2). Notably, the term adaptation was not used concurrently with the other terms. Integration was frequently interchanged with other terms within the same articles (7) (refer to Table 2 for details).

The analysis of bibliometric data also highlights variations in the predominant adjustment terms across different types of international employees. A comparison between expatriates and migrants reveals distinct patterns. Research articles concerning expatriates predominantly utilised the terms adjustment (160 [81.2%]) and adaptation (21 [10.7%]). Conversely, these terms were less prevalent in studies focusing on migrants, accounting for only 14 (42.4%) and 2 (6.1%) instances, respectively. Notably, the term assimilation was exclusively used in studies on migrants (2 instances), while integration (migrants: 10 [30.3%]; expatriates: 2 [1%]) and acculturation (migrants: 11 [33.3%]; expatriates: 7 [3.6%]) were employed more frequently in research related to migrants compared to expatriates.

Research methods

Table 3 presents the research methods outlined in the abstracts of the articles. These methods were categorised based on the research onion framework proposed by Saunders et al. ( 2009 ), distinguishing between methodological choice, time horizon, and strategy. Quantitative research emerged as the most frequently employed methodological choice (124 instances) in IE adjustment research, followed by qualitative research methods (38 instances) and mixed methods (11 instances), with a considerable margin between them. Concerning the time horizon of the research, only 11 articles with a longitudinal design were identified since 1990 in the domain of IE adjustment. Several unique features were observed regarding the research strategy, including case studies (2 instances) and secondary sources (7 instances). Notably, the methodological choice was listed in the abstracts of only 186 (84%) articles.

In summary, quantitative research predominated in both expatriate and migrant groups. However, studies on migrants exhibited a relatively higher proportion of qualitative methods. Additionally, there was slightly more variability in the research methods employed for expatriates than migrants.

Trends in research topics and critical research priorities

Host countries and nationality of participants.

Notably, 154 articles specified the country or countries where the research was conducted, while 96 articles indicated the nationality of the participants. Some articles opted to identify regions rather than specific countries (e.g., Asia or Africa) without providing details on the nationalities of the participants, leading to ambiguity regarding the participants’ origins and the research locations. The information extracted from the articles was categorised based on the type of international employee (IE) under study, as outlined in Table 4 .

Whenever available, the nationalities of the IE samples were classified according to geographic regions defined by the (United Nations 2022 ): Africa, Asia, Europe, Latin America and the Caribbean, North America, and Oceania. Analysis of the abstracts revealed that the samples predominantly comprised IEs from Asian (42 instances), European (24 instances), and North American (14 instances) origins. Conversely, IEs from Africa (1 instance), Latin America and the Caribbean (3 instances), and Oceania (2 instances) were less frequently examined in terms of adjustment. Among the focal regions, Chinese (17 instances), Japanese (12 instances), and American (12 instances) IEs were the most commonly studied. Notably, the Japanese IE group exclusively consisted of assigned expatriates.

A similar trend is observed concerning the host countries where international employees reside. Based on available data, the majority of research on IE adjustment focused on IEs living in Asia (93 instances), Europe (23 instances), and North America (18 instances), with significantly fewer studies conducted in regions such as Africa (8 instances), Latin America and the Caribbean (4 instances), and Oceania (8 instances). Examining individual countries, the data indicate that China (25 instances), Japan (10 instances), and the United States (13 instances) were the primary host countries for IE adjustment research. Among studies focusing on Japan or China as host countries, the articles predominantly referred to expatriates, particularly assigned expatriates (84% and 70%, respectively), rather than migrants.

Overall, the findings suggest that regions such as Africa, Latin America, the Caribbean, and Oceania, along with their nationals, were significantly underrepresented in research on IE adjustment.

Anticipatory adjustment of IEs

Anticipatory adjustment, comprising 34 studies, was most frequently examined in association with assigned expatriates (23 studies) (refer to Table 5 ). Anticipatory adjustment was not a significant focus in studies involving migrant IE groups (4 studies). The two primary factors explored concerning anticipatory adjustment were cross-cultural training to prepare assigned expatriates for their new roles during foreign assignments (9 studies) and previous international experience (11 studies, of which eight referred to assigned expatriates). Other factors, such as language proficiency, motivation to migrate, pre-departure expectations, organisational support and identification, recruitment/selection, and the host country environment, were only explored in limited studies.

In-country adjustment of IEs

Many studies have dealt with adjustment in the host country, which was named 238 times. Factors/antecedents were grouped into individual-, organisation- and country-related groups (refer to Table 6 ). Individual factors were researched most frequently (155), followed by organisational (95) and country-related (78) factors.

Out of individual factors, demographics such as gender and age were explored in 14 articles related to the expatriate group. Personal characteristics, including cultural competence, personality traits, and networks, were the most extensively researched aspect, with 105 studies dedicated to this area. Most of this research targeted assigned expatriates (79 studies), with relatively fewer studies focusing on SIEs and the broader migrant group (14 and 12 studies, respectively). Additionally, there were 22 articles focusing on spouse/family adjustment, examining how family dynamics impacted IE adjustment and considering factors such as support networks, personality traits, host country nationals, and language proficiency. Most of these articles (20 out of 22) were related to assigned expatriates. Individual work-related characteristics, such as organisational commitment, embeddedness, and job satisfaction, were also investigated in 14 studies, with all but two articles referencing the expatriate group.

Regarding organisational factors, particular attention was given to two areas: human resource strategy and management (including leadership, performance management, and organisational support), which were the focus of 35 studies, and employee relations (such as international teamwork, social support networks, and organisational socialisation), which were explored in 30 studies. Additionally, there were studies examining job-related factors (such as role clarity and workplace learning) and the role of the work environment in adjustment (including organisational culture and extrinsic motivation). Most of these articles primarily focused on assigned expatriates, with four-fifths of the articles on HR strategy and management related to this group.

Finally, concerning country-related factors , studies focused mainly on culture (cross-cultural training, cross-cultural communication, and cultural gap, novelty) (43), as well as networks (social support networks, spousal/family support, and host country nationals) (21) and the impact of the host country environment (culture, safety, location, leisure time, etc.) (14) on IE adjustment. Like the previously analysed groups, country-related factors influencing adjustment primarily concentrated on assigned expatriates (59 studies), potentially limiting the generalisation of adjustment patterns to other types of IEs.

In summary, individual, organisational, and country-related factors were predominantly examined through the lens of assigned expatriates. Regarding the distribution of topics by IE type, the analysis revealed that studies on assigned expatriates (49.8%) and SIEs (50%) primarily focused on individual factors. In contrast, most studies on the migrant group emphasised organisational antecedents (40.8%). Country-related factors received comparatively less attention across all IE types, with 24.5% of studies on assigned expatriates, 15.8% on SIEs, and 26.5% on the migrant group exploring these aspects.

By employing a hybrid analysis, which integrates partial bibliometric analysis and abstract content analysis of scientific articles published between 1990 and 2022, we accomplished two of our objectives: (1) furnishing comprehensive insights into the evolution of the field over time, and (2) identifying trends in research topics to grasp research priorities and essential research areas. In the subsequent sections, we will delve into our third objective, (3) uncovering research gaps that warrant attention in future research. Table 7 outlines the principal findings and a proposed research agenda, which we will elucidate below.

Research agenda

General information about the field progression over time indicates that the number of articles per year increased consistently, indicating that the field of IEs adjustment is of rising interest to management and business researchers. Nevertheless, as shown in the following, abstract content analysis of IE adjustment revealed several under-researched avenues for future research.

This analysis underscores a notable emphasis on expatriates in IE adjustment research, particularly assigned expatriates, which constituted approximately 72% of all articles. Conversely, other types of IEs remain relatively underexplored, aligning with previous research highlighting the dearth of scholarly attention on international career transitions for self-initiated IEs (Hajro et al. 2021 ; Yijälä et al. 2012 ; Zikic et al. 2010 ). Given the likelihood of SIEs and migrants receiving less or no support from their employers during relocation and in the host country, they may encounter distinct and potentially heightened adjustment challenges (Brewster et al. 2017 ). Given the escalating global prevalence of SIEs (Collings et al. 2010 ), the limited coverage of 32 articles on the adjustment of this specific group underscores a critical need for further research.

Moreover, standardising terminology for IE types could enhance the development of adjustment research and improve precision. Notably, the term “immigrant” lacks a robust definition compared to terms like “assigned expatriate,” “self-initiated expatriate,” or “skilled migrant.” Consequently, the ambiguity surrounding the delineation of these groups hampers the comparability of research findings. Future studies would benefit from clearly describing the characteristics of the group(s) under investigation, regardless of the label used. Additionally, given the varied definitions of IEs, more comparative research across two or more IE types is warranted to ascertain whether and how they adjust differently to host country circumstances and the underlying reasons.

Finally, regarding sample perspectives, all studies in the corpus exclusively focused on the adjustment of IEs, who typically represent a minority in the host country, to a foreign culture. However, the adjustment of locals to newcomers and the influences they bring from their home countries, which may affect various aspects of local life, warrant a more thorough examination in future research.

Adjustment Terms

As 76% of articles used the term ‘adjustment,’ it might be concluded that this term is the most acceptable for scientists to use in conjunction with IE adjustment. Adaptation (22) was mainly used in connection with expatriates (91%) and – as the only term – and not along with other terms. Interestingly, many publications on adaptation (totalling 19) primarily focused on cross-cultural processes. Although these adaptation studies explicitly employed “adaptation” in their abstracts, they frequently cited sources with synonymous terms in their full text. For instance, three adaptation studies directly referenced acculturation literature sources (e.g., Berry et al. 1988 ) in the complete text, avoiding the explicit use of “acculturation.” Similarly, seven adaptation articles drew on references from the adjustment literature (J. S. Black and Stephens 1989 ; Lazarova et al. 2010 ) as the theoretical foundation for their adaptation research, without employing the term “adjustment” in the full text. In nine articles, the terms “adaptation” and “adjustment” were used interchangeably within the full text (Jyoti and Kour, 2017 ; Zhang et al. 2021 ). Given that conventional literature searches involve seeking relevant texts in databases based on titles, abstracts, and keywords, there exists a risk of parallel development between adaptation research and other adjustment research despite their overlapping content. Thus, future adaptation research should aim to demonstrate the scientific value of the terminological distinction between adaptation and other forms of adjustment. If this distinction is justified, it is crucial to clearly define and delineate these terms or refer to synonymous adjustment terms through cross-references in abstracts or keywords.

Moreover, the bibliometric analysis unveiled variations in dominant adjustment terms across different IE types. When comparing expatriates and migrants, research articles on expatriates predominantly employed the terms “adjustment” and “adaptation,” these terms were notably less utilised for the migrant groups. However, from a content perspective, both terms are equally pertinent and applicable to both groups. This underscores the need for a comprehensive assessment of literature covering both expatriate and migrant IE types, emphasising the importance of scientific exchange between these two research streams in the future.

Research Methods

The limited range of research methods employed in the study is noteworthy. Of the abstracts analysed, 124 indicated quantitative research methods, whereas 38 indicated qualitative methods. Interestingly, while quantitative methods were used across expatriate and migrant groups, qualitative research methods were comparatively more prevalent in studies focusing on migrant groups, albeit in smaller numbers overall. Existing research offers tentative explanations for adjustment; however, adjustment theory remains in a nascent stage, as evidenced by recent efforts at scale redevelopment (Hippler et al. 2014 ), the varied terminology used (Harrison et al. 2004 ), and calls for more significant consideration of context (Szabó 2022 ). Therefore, adjustment theory is currently classified as an intermediate theory. Although research questions permit the formulation of testable hypotheses, the adjustment construct remains preliminary. To achieve methodological congruence, a hybrid approach combining quantitative and qualitative methods is recommended (Edmondson and McManus 2007 ). Quantitative research enables testing associations between variables, while qualitative research facilitates elaboration on phenomena, explanations, and illumination of adjustment constructs and relationships. Incorporating more qualitative research would provide deeper insights into the individual experiences of IEs, given that expatriation/migration is inherently unique. Furthermore, latent class analyses could offer a person-centred perspective on adjustment, exploring different adjustment strategies individuals adopt and their characteristics and antecedents (Morris et al. 2015 ).

The chosen time horizon also reveals explicit limitations in current research practices. Only 5% of the articles indicated the use of a longitudinal design. Given that adjustment is a dynamic process (Banai, 2022 ; Hippler et al. 2015 ), the field could benefit from more longitudinal studies to understand its temporal development, success factors, and obstacles. A broader range of research methods is desirable to address diverse research questions (Sam and Ward 2021 ). Particularly in research on migrants’ adjustment, future studies should strive for more significant methodological variance, as differences in IE types do not inherently dictate differences in research methodology.

Countries of Destination and Sample Nationalities

IEs relocating to and originating from Asia, Europe, and North America were the most researched groups in studies related to IE adjustment. Compared to the absolute number of migrants, which is highest in the destination regions of Europe (87 million), Asia (86 million), and North America (59 million) (IOM UN Migration 2022 ), the host countries in the articles on which the analyses are based reflected the distribution well. Conversely, an analysis of the increase in migration flows from 2000 to 2020 shows that the regions Asia ( + 37 million), Europe ( + 30 million), North America ( + 18 million), and Africa ( + 10 million) (IOM UN Migration, 2022 ) are of the highest relevance. However, the fewest adjustment studies have been conducted in the regions of Africa, as well as Latin America, the Caribbean, and Oceania so far. In particular, the hitherto scarcely explored region of Africa, characterised by a high proportion of migration flow within the region and not across regions as applies to other regions (IOM UN Migration 2022 ), assumes great significance for future adjustment research. Many scholars posit that adjusting to a host culture that is culturally very different proves more difficult for IEs (Li et al. 2013 ; Varela and Gatlin-Watts, 2014 ). However, Selmer ( 2007 ) presents evidence suggesting that adjusting to a similar host culture can be as challenging as adjusting to a different one. Consequently, there should be a focus on the nuances of intraregional migration and adjustment, particularly in Africa.

Based on the information in the article abstracts, the most extensively researched destination countries for IEs were the United States, China, and Japan. Despite the United States being the primary destination for international migrants since 1970 (IOM UN Migration 2022 ), Germany, the second top destination for migrants (IOM UN Migration, 2022 ), was notably underrepresented in the corpus, with only three articles. Similarly, countries like Saudi Arabia (0), Russia (0), the UAE (5), the United Kingdom (5), and France (2) which rank among the countries with the highest migrant populations globally (IOM UN Migration 2022 ; UN DESA, 2022 ), were also underrepresented in adjustment studies. Furthermore, according to the OECD ( 2017 ), Switzerland, Australia, and New Zealand have foreign-born individuals comprising over 20% of their total employment. Nevertheless, research articles on IE adjustment in these destination countries numbered only 2, 6, and 2, respectively. Although Asia is witnessing significant growth in migrants, the proportion of international migrants in the population remains relatively low (1.8%; IOM UN Migration, 2022 ). Historically regarded as a highly homogeneous society with limited global mobility (Andresen et al. 2020 ; Sugimoto, 2014 ), Japan was unexpectedly one of the most studied destination countries for IE adjustment, highlighting the relevance of research in exploring adjustment dynamics in such unique contexts.

Concerning nationality , data indicates that over 40 per cent of all international migrants globally in 2020 hailed from Asia, predominantly from countries like India, China, Bangladesh, Pakistan, the Philippines, and Afghanistan (IOM UN Migration 2022 ). Mexico and Russia are among the largest emigration countries worldwide (UN DESA, 2022 ). However, these regions were scarcely represented in the nationalities studied in the adjustment articles analysed. Despite numerous studies focusing on Chinese IEs (17), other countries were either underrepresented (e.g., the Philippines, 2) or not represented at all (e.g., India, Bangladesh, Pakistan, Afghanistan) in the sampled articles.

Moreover, it is noteworthy that three of the ten GLOBE cultural clusters (House et al. 2004 ) accounted for approximately four-fifths of the destination countries (Confucian Asia, Southern Asia, Anglo) and nationalities (Confucian Asia, Latin Europe, Anglo) studied, with studies based on samples from other cultural clusters such as the Middle East, Sub-Saharan Africa, Latin America, or Eastern Europe being the exception. Future research should systematically examine the combination of nationality and host country to understand the impact of cultural attractiveness on adjustment. While cultural distance measures highlight challenges and losses from cross-cultural interaction, cultural attractiveness focuses on the potential gains from such interaction, even in culturally disparate contexts (Li et al. 2017 ). IEs from countries who perceive the cultural practices of their host country as more valuable than their own may feel attracted to the host country’s cultural practices, which could positively impact their adjustment (Li et al. 2017 ).

To summarise, data accessibility rather than content criteria may have primarily influenced the selection of nationalities and destination countries/regions in previous research. While focusing on countries with high migrant populations and significant migrant inflows may help identify facilitating factors, expanding the scope to include countries with different conditions can help identify equally important barriers. For instance, in countries with few IEs, more personal initiative is required for adjustment, as there are fewer fellow IEs to provide support, and interactions with the native population may be less familiar (Andresen et al. 2020 ). Given that adjustment processes are influenced by social systems that create inequities across individuals and groups, future research should systematically consider the social conditions in different cultures and how these inequities affect IEs’ ability to achieve positive outcomes (Szabó 2022 ). This necessitates a more deliberate sampling approach for destination countries/regions and the nationality of IEs, including “exceptional” destinations and nationalities, and examining the combination of nationality and host country attractiveness in future studies.

Research Themes

Most studies on anticipatory adjustment (68%) focused on assigned expatriates, which is understandable given their affiliation with the same company. Assigned expatriates typically receive support from their organisation before their assignment, facilitating their anticipatory adjustment. However, it is worth noting that all other types of international employees also engage in planning before relocating to another country. Therefore, they will likely undergo some form of individual anticipatory adjustment that could impact their adjustment abroad. Despite this, only seven articles explored the anticipatory adjustment of SIEs, and four studies examined the migrant group. Since SIEs and other migrants typically do not receive financial support from their employers for relocation, studying their anticipatory adjustment could benefit both receiving companies and countries. Hence, there is a need for more research on the anticipatory adjustment of all types of international employees beyond assigned expatriates.

Antecedents of in-country adjustment for international employees were categorised into individual, organisational, and country-level factors. However, some antecedents, such as networks, host country nationals, host country language proficiency, or person-organisation fit, could be attributed to multiple levels depending on the researcher’s perspective. For example, social support networks may not solely be “work-related” at work, even within the workplace environment. Individuals often form close networks with co-workers from various departments based on non-work-related factors like shared interests. Therefore, the impact of these adjustment antecedents on international employee adjustment may extend beyond the organisational level. This highlights the need for research that examines antecedents affecting multiple levels (individual, organisation, country) and stages of international employee adjustment.

Only 14 articles investigated how demographics might affect international employee adjustment; one emphasised the age of international employees, and 13 examined gender (with four focusing on women and seven comparing men with women). It is important to note that no articles addressed adjustment related to transgender or other genders. The lack of understanding regarding how international employees’ demographics or the host country’s environment influence adjustment could lead to poor decision-making and negative consequences for businesses, such as decreased motivation among international employees and disruptions in interactions with customers, suppliers, and colleagues abroad (Olsen and Martins 2009 ). This highlights the need for more research on the effects of international employees’ demographics and the host country’s demographics on adjustment.

A phenomenon not previously explored in existing studies is remote adjustment, which refers to the adjustment process experienced by workers with indirect and often temporary intercultural contact with individuals in geographically separated cultures. This indirect contact occurs virtually through the Internet, where IEs build social networks and seek support. Research by Canhilal et al. ( 2022 ) indicates that these virtual networks and Internet-based support significantly influence IE adjustment.

The concept of remote adjustment may have been particularly accelerated by the COVID-19 pandemic, which brought about widespread changes in workplaces worldwide, especially in technologically advanced countries. With the shift to online work replacing traditional face-to-face interactions, there has been a surge in virtual assignments and international remote work arrangements. As a result, an increasing number of IEs are navigating adjustment challenges in virtual environments. Given the growing prevalence of virtual work arrangements, exploring the adjustment experiences of virtual IEs, particularly in the context of information technologies, becomes essential in the post-COVID era. Understanding how remote adjustment unfolds and identifying effective strategies for supporting virtual IEs will benefit employers and international employees.

Theoretical contributions

To demonstrate the significance of this hybrid review in enriching the adjustment literature, we refer to Mukherjee et al. ( 2022 ) systematisation for delineating the critical pathways to making theoretical contributions. Within theoretical contributions (as outlined by Whetten, 1989 ), our examination reveals that prevailing adjustment research predominantly addresses fundamental theoretical questions. These inquiries encompass defining the adjustment construct, identifying the contributing factors to pre- and post-relocation adjustment phases (the conceptual landscape), delineating the interconnections among these factors (nomological network), and elucidating the underlying causal mechanisms (Mukherjee et al. 2022 ). Whereby the model of Black et al. ( 1991 ) plays a vital role in conceptualising international adjustment as both multifaceted (work and general adjustments together with interactions with host-country nationals) and time-related (anticipatory and in-country adjustments).

A primary theoretical contribution emanating from our analysis is the recognition that while the model proposed by Black et al. ( 1991 ) remains prominent, adjustment research also incorporates other theoretical constructs (such as acculturation, integration, and adaptation, albeit infrequently assimilation), which are often used synonymously. Consequently, regarding construct definition, a pressing need exists for either consolidation or precise demarcation of these constructs. A comprehensive comparison of literature concerning expatriates and migrants, as detailed in the research agenda mentioned earlier, holds promise for theoretically refining the conceptual landscape, nomological network, and causal mechanisms (Mukherjee et al. 2022 ).

Secondly, by delineating knowledge clusters or primary themes in adjustment research (Mukherjee et al. 2022 ), our analysis underscores the underexplored boundaries of adjustment theory, particularly temporal and contextual factors. These boundary conditions encompass discerning variances in adjustment predicated on the identity of the individuals undergoing adjustment (types of IEs, locals), the geographical locations involved (countries of origin and destination), and the timing of adjustment (anticipatory and in-country phases). Studies on expatriation and migration have explored distinct boundary conditions, but the findings need to be synthesised to inform future research on adjustment. Statistical data has revealed that the sampled populations are not fully representative, highlighting some research gaps that must be addressed. It is essential to compare the findings in the context of the “where” boundary condition to understand the topic better.

Thirdly, our systematic analysis underscores elevated researcher interest despite the increasing productivity in IE adjustment research over time by tracing evolutionary nuances to understand the trajectory of adjustment research (Mukherjee et al. 2022 ). However, a notable trend emerges wherein most research has predominantly focused on assigned expatriates, with all other IE categories receiving considerably less scholarly attention. This discrepancy highlights the imperative for a more equitable distribution of research focus across diverse IE cohorts to foster a comprehensive understanding of adjustment phenomena.

The fourth theoretical contribution centres on identifying significant knowledge gaps within adjustment research. Addressing these gaps necessitates a heightened focus on several areas in future studies. Specifically, increased attention should be given to anticipatory adjustment, particularly for migrants but encompassing all types of IEs. Additionally, there should be a more concentrated examination of in-country adjustment, specifically emphasising migrants and various country-related factors such as the cultural appeal of the home versus the host country, economic considerations, and political dynamics. Expanding the scope to include a broader range of countries of origin and destination, demographic variables, remote adjustment, and locals’ attitudes towards IEs’ adjustment or even their adjustment to them is essential.

The theoretical insights gleaned from systematic mapping highlight the necessity for future studies to adopt research methodologies that facilitate the evolution of adjustment theory from an intermediate to a mature stage, advocating for a hybrid research approach.

These findings contribute significantly to international human resource management and business, emphasising the need for additional research involving SIEs and migrants. Given the global rise in their numbers, particularly in less-explored countries and adjustment factors, such research has the potential to deepen our comprehension of the adjustment phenomenon.

Limitations and implications for research

The study is subject to several limitations that warrant acknowledgement. A methodological constraint is inherent in bibliometric analysis, as it primarily involves categorising and organising extensive bibliometric data (Andersen 2019 ). Although the supplementary content analysis of abstracts in this hybrid review offers additional insights into the state of research, it remains somewhat superficial. Future researchers are encouraged to delve deeper into relevant publications to facilitate a more nuanced differentiation of their research questions based on the research fields identified in this review.

Secondly, a limitation arises from our focus on business and management. The selection of articles inherently reflects a somewhat homogeneous perspective on IE adjustment research, with the organisational context typically foregrounded in these studies. Publications in sociology, economics, or psychology could offer additional insights into IE adjustment, such as those related to the macroeconomic context (sociology, economics) or individual antecedents, such as memory and identity (psychology).

Thirdly, our exploration was confined to the WoS database, inevitably influencing the articles. While it is generally acknowledged that there is a significant overlap in content indexed between WoS and Scopus (Pranckutė 2021 ), Donthu et al. ( 2021 ) advocate for selecting “one appropriate database to mitigate the need for that consolidation” (p. 293) and the associated risks of errors, a search in Scopus or Dimensions databases could have broadened the scope, considering they encompass journals not included in WoS.

Fourthly, our study’s search was restricted to English-language articles. Including articles in various languages would introduce research from diverse nations, fostering the exchange of research insights.

Conclusions

Based on a comprehensive review spanning 32 years of theory and research on adjustment, it is evident that studies concerning IE adjustment have seen a remarkable increase over this period. To advance adjustment theory and research further, future research should be deliberate in two key aspects: research design, incorporating purposeful sampling across demographics, types of IE, nationality, and destination countries, and methodological alignment through a hybrid approach that integrates qualitative and quantitative methods; and research focus, involving systematic selection and analysis of host countries alongside their social, political, and technological contexts, comparison of IE adjustment with that of local populations, examination of pre-departure and in-country adjustment among various IE types, and tracking adjustment over time, including remote settings. This proposed research agenda is extensive and essential for progressing intermediate adjustment theory towards maturity.

Data availability

All data generated or analysed during this study are included in this published article [and its supplementary information files].

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Baneviciene, I., Andresen, M. & Kumpikaite-Valiuniene, V. Assessing the status quo of international employees’ adjustment research, 1990–2022: a review and future research agenda. Humanit Soc Sci Commun 11 , 633 (2024). https://doi.org/10.1057/s41599-024-03098-y

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How People with Type 2 Diabetes Can Live Longer

• Life expectancy is known as the number of years a person is expected to live.
• At age 50, life expectancy is 6 years shorter for people with type 2 diabetes than for people without diabetes.
• By meeting type 2 diabetes treatment goals, life expectancy can increase by 3 years, or for some, as much as 10 years.

What did this study examine?

This study measured average increases in life expectancy years for people with type 2 diabetes who met four different treatment goals. Researchers divided study participants into six groups based on sex and three age ranges. People with diabetes can use results to estimate their own likely life expectancy increase.

Terms to know

Body mass index (BMI) is a measure of weight based on height.

Hemoglobin A1C , or A1C , is a blood test that measures average blood sugar over the past 3 months.

Low-density lipoprotein (LDL) cholesterol can build up in the blood vessels, causing damage to vessel walls.

Systolic blood pressure (SBP) measures the force of blood pushing against artery walls as it moves through the body. Blood pressure is measured with a top and bottom number, and SBP refers to the top number.

Study results

Managing weight, blood sugar, blood pressure, and cholesterol can increase life expectancy by 3 years for the average person with type 2 diabetes. For people with the highest levels of BMI, A1C, LDL, and SBP, reducing these levels can potentially increase life expectancy by more than 10 years.

The benefits in life expectancy from meeting treatment goals in this study were highest in adults ages 51 to 60, compared to those 61 and older.

Of the four treatment goals studied, reduced BMI on average was associated with the greatest gain in life expectancy, followed by reduced A1C.

The benefit of weight loss may have been underestimated since it is often connected with other treatment goals in this study. Weight loss must be maintained in the long term to potentially increase life expectancy.

What's important about this study?

Living well with diabetes requires more than blood sugar management. Diabetes management is also connected to weight, blood pressure, and cholesterol. This study shows how people with type 2 diabetes can reduce their risk of complications and extend their lives.

These findings can help people with diabetes and their doctors determine treatment goals with the most impact on life expectancy. Decision makers can use this study to support diabetes programs in the United States.

Diabetes is a chronic disease that affects how your body turns food into energy. About 1 in 10 Americans has diabetes.

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Internet use statistically associated with higher wellbeing, finds new global Oxford study

Links between internet adoption and wellbeing are likely to be positive, despite popular concerns to the contrary, according to a major new international study from researchers at the Oxford Internet Institute, part of the University of Oxford.

The study encompassed more than two million participants psychological wellbeing from 2006-2021 across 168 countries, in relation to internet use and psychological well-being across 33,792 different statistical models and subsets of data, 84.9% of associations between internet connectivity and wellbeing were positive and statistically significant. 

The study analysed data from two million individuals aged 15 to 99 in 168 countries, including Latin America, Asia, and Africa and found internet access and use was consistently associated with positive wellbeing.   

Assistant Professor Matti Vuorre, Tilburg University and Research Associate, Oxford Internet Institute and Professor Andrew Przybylski, Oxford Internet Institute carried out the study to assess how technology relates to wellbeing in parts of the world that are rarely studied.

Professor Przybylski said: 'Whilst internet technologies and platforms and their potential psychological consequences remain debated, research to date has been inconclusive and of limited geographic and demographic scope. The overwhelming majority of studies have focused on the Global North and younger people thereby ignoring the fact that the penetration of the internet has been, and continues to be, a global phenomenon'. 

'We set out to address this gap by analysing how internet access, mobile internet access and active internet use might predict psychological wellbeing on a global level across the life stages. To our knowledge, no other research has directly grappled with these issues and addressed the worldwide scope of the debate.' 

The researchers studied eight indicators of well-being: life satisfaction, daily negative and positive experiences, two indices of social well-being, physical wellbeing, community wellbeing and experiences of purpose.   

Commenting on the findings, Professor Vuorre said, “We were surprised to find a positive correlation between well-being and internet use across the majority of the thousands of models we used for our analysis.”

Whilst the associations between internet access and use for the average country was very consistently positive, the researchers did find some variation by gender and wellbeing indicators: The researchers found that 4.9% of associations linking internet use and community well-being were negative, with most of those observed among young women aged 15-24yrs.

Whilst not identified by the researchers as a causal relation, the paper notes that this specific finding is consistent with previous reports of increased cyberbullying and more negative associations between social media use and depressive symptoms among young women. 

Adds Przybylski, 'Overall we found that average associations were consistent across internet adoption predictors and wellbeing outcomes, with those who had access to or actively used the internet reporting meaningfully greater wellbeing than those who did not'.

'We hope our findings bring some greater context to the screentime debate however further work is still needed in this important area.  We urge platform providers to share their detailed data on user behaviour with social scientists working in this field for transparent and independent scientific enquiry, to enable a more comprehensive understanding of internet technologies in our daily lives.' 

In the study, the researchers examined data from the Gallup World Poll, from 2,414,294 individuals from 168 countries, from 2006-2021.  The poll assessed well-being with face-to-face and phone surveys by local interviewers in the respondents’ native languages.  The researchers applied statistical modelling techniques to the data using wellbeing indicators to test the association between internet adoption and wellbeing outcomes. 

Watch the  American Psychological Association (APA) video  highlighting the key findings from the research.

Download the paper ‘ A multiverse analysis of the associations between internet use and well-being ’ published in the journal Technology, Mind and Behaviour, American Psychological Association.

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New cardiac research will save women's lives by improving detection of heart failure

An important new study has advanced how heart failure is detected in women -- meaning more female patients can be diagnosed and at an earlier stage.

Researchers led by teams from the Universities of East Anglia (UEA), Sheffield and Leeds, have been able to fine-tune how magnetic resonance imaging (MRI) is used to detect heart failure in women's hearts, making it more accurate.

Lead author Dr Pankaj Garg, of the University of East Anglia's Norwich Medical School and a consultant cardiologist at the Norfolk and Norwich University Hospital, said: "By refining the method for women specifically, we were able to diagnose 16.5pc more females with heart failure.

"This could have huge impact in the NHS, which diagnoses around 200,000 patients with heart failure each year.

"This improved method will increase early detection, meaning more women can get life-saving treatment sooner."

In 2022, UEA and the University of Sheffield published research which showed how using MRI scans could be used to detect heart failure and which led to this technique being widely employed by medics.

When a heart starts to fail, it is unable to pump blood out effectively, and so the pressure in the heart rises.

Co-author Dr Gareth Matthews, of the University of East Anglia's Norwich Medical School, said: "Currently one of the best ways of diagnosing heart failure is to measure pressures inside the heart with a tube called a catheter.

"While this is very accurate, it is an invasive procedure, and therefore carries risks for patients, which limits its use.

"For this reason, doctors tend to use echocardiograms, which are based on ultrasound, to assess heart function, but this is inaccurate in up to 50 per cent of cases. Using MRI, we can get much more accurate images of how the heart is working."

The team was able to create an equation which allowed them to non-invasively derive the pressure in the heart using an MRI scanner.

However, previous use of this method wasn't as accurate as the researchers would have liked in diagnosing heart failure in women, especially in early or borderline disease.

Co-author Professor Andy Swift, of the University of Sheffield's School of Medicine and Population Health, said: "Women's hearts are biologically different to men's.

"Our work suggests that in heart failure women's hearts may respond differently in response to increases in pressure."

Heart failure can be classed differently, depending on the amount of blood squeezed out of the main chamber of the heart with every beat, known as the heart's ejection fraction.

Women suffer disproportionately from a type of heart failure where the pumping function of the heart is preserved but the ability of the heart to relax and fill with blood is impaired.

Echocardiography really struggles to diagnose this type of heart failure. The improvements in diagnosis from this new work will enable more of this particular cohort to be diagnosed more accurately and hopefully drive better treatments.

Co-author Dr Peter Swoboda, of the University of Leeds' Faculty of Medicine and Health, said: "The symptoms of heart failure, like breathlessness and fatigue, can have a devastating effect on patients' quality of life.

"We are increasingly recognising the importance of early diagnosis and, early treatment can improve symptoms and life expectancy.

"This research will help diagnose heart failure in women more quickly and get them established on life-saving treatments sooner."

The Government's Health and Social Care Secretary, Victoria Atkins, said: "Heart failure is a devastating condition affecting hundreds of thousands of women in the UK, so this research is a hugely positive development that could make it possible for thousands of people to get diagnosed and treated at an earlier stage.

"For the second year of our Women's Health Strategy for England, I have been clear that we need more research to look at the differences between how conditions affect men and women.

"I am delighted that this government-backed research has met this challenge so that we can get life-saving treatment to women faster."

The research was a collaboration between the University of East Anglia, the University of Leeds, the University of Sheffield, the Norfolk and Norwich University Hospital NHS Foundation Trust, the National Heart Research Institute Singapore, Duke-NUS Medical School in Singapore, Queen Mary University of London, the National Institute for Health and Care Research's Sheffield Biomedical Research Centre, the University of Amsterdam and Kocaeli City Hospital in Turkey.

It was funded by the National Institute for Health and Care Research (NIHR) Sheffield Biomedical Research Centre, the Wellcome Trust, and the National Medical Research Council (NMRC).

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• Ciaran Grafton-Clarke, Gareth Matthews, Rui Li, Hosamadin Assadi, Peter Swoboda, Chris Sawh, Vassilios S Vassiliou, Andrew J Swift, Pankaj Garg. 32 Sex-specific cardiac magnetic resonance pulmonary capillary wedge pressure model predicts outcomes in heart failure: a multi-centre study . European Heart Journal Open , 2024 DOI: 10.1136/heartjnl-2024-BSCMR.29

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Why writing by hand beats typing for thinking and learning

Jonathan Lambert

If you're like many digitally savvy Americans, it has likely been a while since you've spent much time writing by hand.

The laborious process of tracing out our thoughts, letter by letter, on the page is becoming a relic of the past in our screen-dominated world, where text messages and thumb-typed grocery lists have replaced handwritten letters and sticky notes. Electronic keyboards offer obvious efficiency benefits that have undoubtedly boosted our productivity — imagine having to write all your emails longhand.

To keep up, many schools are introducing computers as early as preschool, meaning some kids may learn the basics of typing before writing by hand.

But giving up this slower, more tactile way of expressing ourselves may come at a significant cost, according to a growing body of research that's uncovering the surprising cognitive benefits of taking pen to paper, or even stylus to iPad — for both children and adults.

Is this some kind of joke? A school facing shortages starts teaching standup comedy

In kids, studies show that tracing out ABCs, as opposed to typing them, leads to better and longer-lasting recognition and understanding of letters. Writing by hand also improves memory and recall of words, laying down the foundations of literacy and learning. In adults, taking notes by hand during a lecture, instead of typing, can lead to better conceptual understanding of material.

"There's actually some very important things going on during the embodied experience of writing by hand," says Ramesh Balasubramaniam , a neuroscientist at the University of California, Merced. "It has important cognitive benefits."

While those benefits have long been recognized by some (for instance, many authors, including Jennifer Egan and Neil Gaiman , draft their stories by hand to stoke creativity), scientists have only recently started investigating why writing by hand has these effects.

A slew of recent brain imaging research suggests handwriting's power stems from the relative complexity of the process and how it forces different brain systems to work together to reproduce the shapes of letters in our heads onto the page.

Your brain on handwriting

Both handwriting and typing involve moving our hands and fingers to create words on a page. But handwriting, it turns out, requires a lot more fine-tuned coordination between the motor and visual systems. This seems to more deeply engage the brain in ways that support learning.

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"Handwriting is probably among the most complex motor skills that the brain is capable of," says Marieke Longcamp , a cognitive neuroscientist at Aix-Marseille Université.

Gripping a pen nimbly enough to write is a complicated task, as it requires your brain to continuously monitor the pressure that each finger exerts on the pen. Then, your motor system has to delicately modify that pressure to re-create each letter of the words in your head on the page.

"Your fingers have to each do something different to produce a recognizable letter," says Sophia Vinci-Booher , an educational neuroscientist at Vanderbilt University. Adding to the complexity, your visual system must continuously process that letter as it's formed. With each stroke, your brain compares the unfolding script with mental models of the letters and words, making adjustments to fingers in real time to create the letters' shapes, says Vinci-Booher.

That's not true for typing.

To type "tap" your fingers don't have to trace out the form of the letters — they just make three relatively simple and uniform movements. In comparison, it takes a lot more brainpower, as well as cross-talk between brain areas, to write than type.

Recent brain imaging studies bolster this idea. A study published in January found that when students write by hand, brain areas involved in motor and visual information processing " sync up " with areas crucial to memory formation, firing at frequencies associated with learning.

"We don't see that [synchronized activity] in typewriting at all," says Audrey van der Meer , a psychologist and study co-author at the Norwegian University of Science and Technology. She suggests that writing by hand is a neurobiologically richer process and that this richness may confer some cognitive benefits.

Other experts agree. "There seems to be something fundamental about engaging your body to produce these shapes," says Robert Wiley , a cognitive psychologist at the University of North Carolina, Greensboro. "It lets you make associations between your body and what you're seeing and hearing," he says, which might give the mind more footholds for accessing a given concept or idea.

Those extra footholds are especially important for learning in kids, but they may give adults a leg up too. Wiley and others worry that ditching handwriting for typing could have serious consequences for how we all learn and think.

What might be lost as handwriting wanes

The clearest consequence of screens and keyboards replacing pen and paper might be on kids' ability to learn the building blocks of literacy — letters.

"Letter recognition in early childhood is actually one of the best predictors of later reading and math attainment," says Vinci-Booher. Her work suggests the process of learning to write letters by hand is crucial for learning to read them.

"When kids write letters, they're just messy," she says. As kids practice writing "A," each iteration is different, and that variability helps solidify their conceptual understanding of the letter.

Research suggests kids learn to recognize letters better when seeing variable handwritten examples, compared with uniform typed examples.

This helps develop areas of the brain used during reading in older children and adults, Vinci-Booher found.

"This could be one of the ways that early experiences actually translate to long-term life outcomes," she says. "These visually demanding, fine motor actions bake in neural communication patterns that are really important for learning later on."

Ditching handwriting instruction could mean that those skills don't get developed as well, which could impair kids' ability to learn down the road.

"If young children are not receiving any handwriting training, which is very good brain stimulation, then their brains simply won't reach their full potential," says van der Meer. "It's scary to think of the potential consequences."

Many states are trying to avoid these risks by mandating cursive instruction. This year, California started requiring elementary school students to learn cursive , and similar bills are moving through state legislatures in several states, including Indiana, Kentucky, South Carolina and Wisconsin. (So far, evidence suggests that it's the writing by hand that matters, not whether it's print or cursive.)

Slowing down and processing information

For adults, one of the main benefits of writing by hand is that it simply forces us to slow down.

During a meeting or lecture, it's possible to type what you're hearing verbatim. But often, "you're not actually processing that information — you're just typing in the blind," says van der Meer. "If you take notes by hand, you can't write everything down," she says.

The relative slowness of the medium forces you to process the information, writing key words or phrases and using drawing or arrows to work through ideas, she says. "You make the information your own," she says, which helps it stick in the brain.

Such connections and integration are still possible when typing, but they need to be made more intentionally. And sometimes, efficiency wins out. "When you're writing a long essay, it's obviously much more practical to use a keyboard," says van der Meer.

Still, given our long history of using our hands to mark meaning in the world, some scientists worry about the more diffuse consequences of offloading our thinking to computers.

"We're foisting a lot of our knowledge, extending our cognition, to other devices, so it's only natural that we've started using these other agents to do our writing for us," says Balasubramaniam.

It's possible that this might free up our minds to do other kinds of hard thinking, he says. Or we might be sacrificing a fundamental process that's crucial for the kinds of immersive cognitive experiences that enable us to learn and think at our full potential.

Balasubramaniam stresses, however, that we don't have to ditch digital tools to harness the power of handwriting. So far, research suggests that scribbling with a stylus on a screen activates the same brain pathways as etching ink on paper. It's the movement that counts, he says, not its final form.

Jonathan Lambert is a Washington, D.C.-based freelance journalist who covers science, health and policy.

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Research: What Companies Don’t Know About How Workers Use AI

• Jeremie Brecheisen

Three Gallup studies shed light on when and why AI is being used at work — and how employees and customers really feel about it.

Leaders who are exploring how AI might fit into their business operations must not only navigate a vast and ever-changing landscape of tools, but they must also facilitate a significant cultural shift within their organizations. But research shows that leaders do not fully understand their employees’ use of, and readiness for, AI. In addition, a significant number of Americans do not trust business’ use of AI. This article offers three recommendations for leaders to find the right balance of control and trust around AI, including measuring how their employees currently use AI, cultivating trust by empowering managers, and adopting a purpose-led AI strategy that is driven by the company’s purpose instead of a rules-heavy strategy that is driven by fear.

If you’re a leader who wants to shift your workforce toward using AI, you need to do more than manage the implementation of new technologies. You need to initiate a profound cultural shift. At the heart of this cultural shift is trust. Whether the use case for AI is brief and experimental or sweeping and significant, a level of trust must exist between leaders and employees for the initiative to have any hope of success.

• Jeremie Brecheisen is a partner and managing director of The Gallup CHRO Roundtable.

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