How To Write Significance of the Study (With Examples) 

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

significant of the study research example

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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significant of the study research example

Examples

Significance of the Study

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significant of the study research example

The significance of the study underscores the research’s importance, illustrating its impact on existing knowledge and potential applications. It highlights how the findings address gaps, resolve problems, or contribute to advancements in a specific field. By emphasizing the study’s relevance, it demonstrates the broader implications for society, academia, or industry, justifying the research effort and investment.

What is the Significance of the Study?

The significance of the study illustrates the research’s importance, highlighting its impact on existing knowledge and potential applications. It addresses gaps, resolves problems, or contributes to advancements in a specific field. Emphasizing the study’s relevance, it demonstrates broader implications for society, academia, or industry, justifying the research effort and investment.

Significance of the Study Format

When writing the “Significance of the Study” section in a research paper , follow this format to ensure clarity and impact:

1. Introduction

  • Contextual Background: Provide a brief background of the research topic.
  • Research Problem: State the problem the study addresses.

2. Purpose of the Study

  • Objective Statement: Clearly define the main objective of the study.
  • Scope of the Study: Outline what the study covers.

3. Importance to the Field

  • Contribution to Knowledge: Explain how the study will add to existing knowledge.
  • Theoretical Significance: Discuss the study’s theoretical implications.

4. Practical Implications

  • Real-world Application: Describe how the findings can be applied in practical setting .
  • Beneficiaries: Identify who will benefit from the research (e.g., policymakers, practitioners, educators).

5. Advancement of Future Research

  • Foundation for Future Studies: Indicate how the study can serve as a basis for further research.
  • Research Gaps: Highlight any gaps the study aims to fill.

6. Societal Impact

  • Broader Implications: Discuss the potential societal benefits or changes resulting from the study.
  • Public Awareness: Explain how the study can raise awareness or understanding of the issue.

7. Conclusion

  • Summary of Significance: Recap the main points that underline the importance of the study.
  • Call to Action: Encourage specific actions or further studies based on the research findings.
Significance of the Study on Impact of Remote Work on Employee Productivity in the Tech Industry 1. Introduction The rapid shift to remote work due to the COVID-19 pandemic has fundamentally changed the dynamics of workplace productivity, especially within the tech industry. This study aims to examine how remote work influences employee productivity compared to traditional office settings. 2. Purpose of the Study The primary objective of this research is to evaluate the productivity levels of tech employees working remotely versus those working in office environments. The study analyzes various productivity metrics, such as task completion rates, quality of work, and employee satisfaction. 3. Importance to the Field This research contributes significantly to the existing body of knowledge by providing empirical data on the productivity impacts of remote work. It refines theoretical models of workplace productivity and offers new insights into remote work dynamics specific to the tech sector. Understanding these dynamics helps scholars and practitioners alike in shaping effective productivity strategies in the evolving work landscape. 4. Practical Implications The findings from this study have crucial practical implications for tech companies aiming to optimize their remote work policies. By understanding how remote work affects productivity, managers and HR departments can develop strategies to enhance employee performance and well-being in remote settings. These insights can also assist in designing training programs that equip employees with the skills needed for effective remote work. 5. Advancement of Future Research This study sets the stage for future research on long-term remote work trends and their impacts across various industries. It addresses existing gaps by providing a detailed analysis of how remote work influences productivity in the tech sector. Future researchers can build on this work to explore remote work dynamics in other fields and under different conditions. 6. Societal Impact The study highlights the broader societal implications of remote work, such as promoting work-life balance, reducing urban congestion, and lowering environmental pollution. By demonstrating the potential benefits of remote work, this research can influence public policy and corporate strategies towards more sustainable and flexible working conditions, ultimately contributing to societal well-being. 7. Conclusion Understanding the impact of remote work on productivity is essential for developing effective work policies and creating healthier work environments. This study provides valuable insights that can guide tech companies in optimizing their remote work strategies. Future research should explore the long-term effects of remote work across different sectors to provide a comprehensive understanding of its benefits and challenges.

Significance of the Study Examples

  • Significance of the Study: Research Paper
  • Significance of the Study: Qunatitive Research
  • Significance of the Study: Qualitative Research

Research Paper

Significance-of-the-Study-Research-Paper-Edit-Download-Pdf

Qunatitive Research

Significance-of-the-Study-Quantitative-Research-Edit-Download-Pdf

Qualitative Research

Significance-of-the-Study-Qualitative-Research-Edit-Download-Pdf

More Significance of the Study Examples

  • Educational Resources and Student Performance
  • Business Innovation and Competitive Advantage
  • Social Media Influencers and Brand Loyalty
  • Mental Health Benefits of Physical Activ ity
  • Sustainable Food Practices and Consumer Behavior
  • Green Building and Energy Efficiency
  • Technology in Healthcare
  • Employee Engagement and Job Performance
  • Business Strategies and Market Adaptation
  • Mindfulness at Work

Purpose of Writing the Significance of a Study

When writing academic research or scholarly articles, one critical section is the significance of the study . This part addresses the importance and impact of the research, both theoretically and practically. Here are the main purposes of writing the significance of a study:

1. Establishing Relevance

The primary purpose is to explain why the study is relevant. It connects the research to existing literature, highlighting gaps or deficiencies that the current study aims to fill. This helps to justify the research problem and demonstrates the necessity of the study.

2. Highlighting Contributions

This section outlines the contributions the study will make to the field. It discusses how the findings can advance knowledge, theory, or practice. The significance emphasizes new insights, innovative approaches, or advancements that the study will provide.

3. Guiding Further Research

The significance of the study often includes suggestions for future research. By identifying limitations and unexplored areas, it encourages other researchers to pursue related questions. This helps to build a foundation for continuous inquiry and discovery.

4. Demonstrating Practical Applications

Beyond theoretical contributions, the significance of the study highlights practical applications. It shows how the research can solve real-world problems, improve practices, or influence policy-making. This connects academic research to practical outcomes that benefit society.

5. Engaging Stakeholders

Writing the significance of a study engages various stakeholders, including scholars, practitioners, policymakers, and funders. It communicates the value of the research to different audiences, making it easier to garner support, funding, or collaboration.

6. Enhancing Research Impact

A well-articulated significance section enhances the overall impact of the research. It underscores the importance and potential influence of the study, increasing its visibility and recognition in the academic community and beyond.

Benefits of Significance of the Study

Writing the significance of a study offers several benefits that enhance the research’s value and impact. Here are the key benefits:

1. Clarifies Research Value

The significance section clarifies the value of the research by explaining its importance and relevance. It helps readers understand why the study matters and what contributions it aims to make to the field.

2. Justifies the Research Problem

This section provides a rationale for the study by highlighting the research problem’s importance. It justifies the need for the study by identifying gaps in existing literature and explaining how the research will address these gaps.

3. Engages and Motivates Readers

A well-articulated significance section engages and motivates readers, including scholars, practitioners, and policymakers. It draws their interest by showcasing the study’s potential impact and benefits.

4. Secures Funding and Support

Explaining the significance of the study can help secure funding and support from stakeholders. Funding agencies and institutions are more likely to invest in research that demonstrates clear value and potential impact.

5. Guides Research Focus

The significance section helps guide the research focus by clearly defining the study’s contributions and goals. This clarity ensures that the research stays on track and aligns with its intended purpose.

6. Enhances Academic Credibility

Demonstrating the significance of a study enhances the researcher’s academic credibility. It shows a deep understanding of the field and the ability to identify and address important research questions.

7. Encourages Further Research

By identifying gaps and suggesting future research directions, the significance section encourages other researchers to build on the study’s findings. This fosters a continuous cycle of inquiry and discovery in the field.

8. Highlights Practical Applications

The significance section highlights practical applications of the research, showing how it can solve real-world problems. This makes the study more appealing to practitioners and policymakers who are interested in practical solutions.

9. Increases Research Impact

A clear and compelling significance section increases the overall impact of the research. It enhances the study’s visibility and recognition, leading to broader dissemination and application of the findings.

10. Supports Academic and Professional Goals

For researchers, writing a strong significance section supports academic and professional goals. It can contribute to career advancement, publication opportunities, and recognition within the academic community.

How to Write the Significance of the Study

How to Write the Significance of a Study

Writing the significance of a study involves explaining the importance and impact of your research. This section should clearly articulate why your study matters, how it contributes to the field, and what practical applications it may have. Here’s a step-by-step guide to help you write an effective significance of the study:

Start with the Context

Begin by providing a brief overview of the research context. This sets the stage for understanding the importance of your study. Example : “In today’s digital age, digital literacy has become a critical skill for students. As technology continues to integrate into education, understanding its impact on academic performance is essential.”

Identify the Research Gap

Explain the gap in existing literature or the problem your study aims to address. Highlighting this gap justifies the need for your research. Example: “Despite the growing importance of digital literacy, there is limited empirical evidence on its direct impact on high school students’ academic performance. This study seeks to fill this gap by investigating this relationship.”

Explain the Theoretical Contributions

Discuss how your study will contribute to existing theories or knowledge in the field. This shows the academic value of your research. Example : “The findings of this study will contribute to educational theory by providing new insights into how digital literacy skills influence student learning outcomes. It will expand the current understanding of the role of technology in education.”

Highlight Practical Implications

Describe the practical applications of your research. Explain how the findings can be used in real-world settings. Example : “Practically, the results of this study can inform educators and policymakers about the importance of incorporating digital literacy programs into the curriculum. It will help design more effective teaching strategies that enhance students’ digital competencies.”

Mention the Beneficiaries

Identify who will benefit from your study. This could include scholars, practitioners, policymakers, or specific groups affected by the research problem. Example: “This research will benefit educators, school administrators, and policymakers by providing evidence-based recommendations for integrating digital literacy into educational practices. Additionally, students will benefit from improved learning outcomes and better preparedness for the digital world.”

Suggest Future Research

Point out areas for future research that stem from your study. This shows the ongoing relevance and potential for further inquiry. Example : “Future research could explore the long-term effects of digital literacy on career readiness and job performance. Additionally, studies could examine the impact of specific digital literacy interventions on diverse student populations.”

Use Clear and Concise Language

Ensure your writing is clear and concise. Avoid jargon and overly complex sentences to make your significance easily understandable.

What is the significance of a study?

The significance explains the importance, contributions, and impact of the research, highlighting why the study is necessary and how it benefits the field and society.

Why is the significance of a study important?

It justifies the research, engages readers, secures funding, guides the research focus, and highlights practical and theoretical contributions, enhancing the study’s impact and visibility.

How do you identify the significance of a study?

Identify gaps in existing literature, potential contributions to theory and practice, and practical applications that address real-world problems, demonstrating the study’s relevance and importance.

What should be included in the significance of a study?

Include the research context, identified gaps, theoretical contributions, practical applications, beneficiaries, and suggestions for future research to comprehensively explain the study’s importance.

How long should the significance of a study be?

Typically, the significance section should be concise, around 1-2 paragraphs, providing enough detail to clearly convey the study’s importance and contributions.

Can the significance of a study influence funding decisions?

Yes, a well-articulated significance section can attract funding by demonstrating the study’s potential impact and relevance to funding agencies and stakeholders.

How does the significance of a study benefit researchers?

It clarifies the research focus, enhances credibility, guides the research process, and supports academic and professional goals by highlighting the study’s contributions and importance.

Should the significance of a study mention future research?

Yes, mentioning future research directions shows the ongoing relevance of the study and encourages further inquiry, contributing to continuous advancement in the field.

How does the significance of a study relate to the research problem?

The significance justifies the research problem by explaining its importance, highlighting gaps in existing knowledge, and showing how the study addresses these issues.

Can practical applications be part of the significance of a study?

Yes, practical applications are crucial, showing how the research can solve real-world problems, influence practices, and benefit specific groups or society overall.

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What is the Significance of a Study? Examples and Guide

Significance of a study graphic, showing a female scientist reading a book

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.

Graphic showing the broadening significance of a study going from your study, the wider research field, business opportunities through to society as a whole.

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:

Figure from a paper showing the statistical significance of a study using asterisks

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

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

Commercial and Industrial Significance

What are commercial and industrial significance.

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

Simply put:

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

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

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

How are commercial and industrial significance measured?

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

Here are some potential measures of significance:

Commercial significance:

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

Industrial significance:

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

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

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

Commercial significance.

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

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

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

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

Industrial significance

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

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

For example:

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

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

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

Societal Significance

What is the societal significance of a study.

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

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

Studies can help with big issues facing society such as:

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

How is societal significance measured?

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

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

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

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

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

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

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

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

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

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

We examined food waste as an initial investigation and test of this methodology, and there is clear potential for the examination of not only other policy texts related to food waste (e.g., liability protection, tax incentives, etc.; Broad Leib et al., 2020) but related to sustainable fishing (Worm et al., 2006) and energy use (Hawken, 2017). These other areas are of obvious relevance to climate change… AI-Based Text Analysis for Evaluating Food Waste Policies
The continued development of state-of-the art NLP tools tailored to climate policy will allow climate researchers and policy makers to extract meaningful information from this growing body of text, to monitor trends over time and administrative units, and to identify potential policy improvements. BERT Classification of Paris Agreement Climate Action Plans

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

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

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

Writing an academic journal paper

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

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How To Write a Significance Statement for Your Research

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

Updated on May 4, 2023

a life sciences researcher writing a significance statement for her researcher

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?

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  • By DiscoverPhDs
  • August 25, 2020

Significance of the Study

  • 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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Significance of the Study Samples | Writing Tips

When you write a thesis , there is a section there that is allocated for the significance of the study. This article will provide different  significance of the study examples and will discuss tips on how to write this part.

Tips in Writing the Significance of the Study

Here are the tips that may be helpful when writing the significance of the study. These tips will tell you the basic components expected to be seen in the significance of the study content.

1. Refer to the Problem Statement

In writing the significance of the study, always refer to the statement of the problem. This way, you can clearly define the contribution of your study. To simplify, your research should answer this question, “What are the benefits or advantages of the study based on the statement of the problem?”

Start by explaining the problem that your study aimed to solve. For example, if you conducted a research study on obesity rates among elementary school students, you would start by explaining that obesity is a major health concern in the Philippines and discuss why it is important to find ways to address this issue.

2. Write it from General to Particular

Determine the specific contribution of your thesis study to society as well as to the individual. Write it deductively, starting from general to specific. Start your significance of the study broadly then narrow it out to a specific group or person. This is done by looking into the general contribution of your study, such as its importance to society as a whole, then moving towards its contribution to individuals like yourself as a researcher.

Discuss how your study fills a gap in the literature. If you conducted an experiment on the effects of a certain type of food on children, for example, you might start by explaining that no research has been done on this topic before. This section would also include a discussion about why your study is important.

Your problem statement might help you determine the unique contribution of your research. This can be accomplished by ensuring that the aim of the problem and the study’s objectives are identical. For instance, if your research question is “Is there a significant relationship between the use of Facebook Messenger and the performance of students in English spelling? “, you could write as one of the contributions of your study: “The study will identify common errors in spelling and grammar by Messenger users and recommend its appropriate use in a way that can improve performance in spelling.”

You may also read: How to Make a Conceptual Framework

Significance of the Study Samples

Here are some examples to help you draft your own introduction:

Title: Number of Clinical Internship Hours: A Determinant of Student’s Effectiveness and Skill  Acquisition in the Hospital Area for Velez College Students

Significance of the study.

The results of the study will be of great benefit to the following:

College of Nursing Dean . Data given will provide the dean with information on how the number of duty hours in a week affects the student’s academic and RLE performance. The results will enable the dean to improve the scheduling of RLE and different academic subjects. Data gathered will help the dean initiate collaboration among faculty and chairpersons to help plan the advancement of nursing education in relation to the new curriculum.

Clinical Instructors . The results of the study will help the clinical instructors evaluate the quality of care rendered by the nursing students, academic performance, attitude and skills acquired in relation to the number of hours given in a week. Results would also develop the clinical instructor’s teaching-learning and evaluating strategies in enhancing knowledge, skills and attitude to the students in the time frame given.

Students . This study will provide information regarding which time arrangement is effective: 8-hr of clinical internship from the 5-hr clinical internship with additional academic classes. This study will evaluate the academic performance, the student nurse’s attitude and approach, the skills learned in the clinical area, and the quality of care rendered in the given time frame. Data gathered will also help the students improve both academic and clinical performance.

Velez College . This study will improve the school in the development of nursing education. This study will foster new ways of enhancing knowledge, skills, and attitude, thus preparing globally-competitive nurses in the future. This study will also help in the advancement of school management, clinical leadership, and the teaching-evaluation approach.

Title: The Effectiveness of Isuzu’s Blue Power Technology in Fuel Efficiency of Diesel Engines

The generalization of this study would be a great contribution to the vast knowledge in relation to the brand awareness of Isuzu’s Blue Power Euro 4 Technology. Furthermore, the results of this investigation could be highly significant and beneficial for the following:

Current Customers

They refer to consumers that have already bought products from Isuzu. They are considered to be the main beneficiaries of the business. The findings of this study would provide them with adequate information about the product, most especially for those clients that have already bought units with the Blue Power Euro 4 Technology but have no idea of its benefits and advantages.

Potential Customer

They are the consumers that have not yet purchased this brand. This study aims to give them insights and overviews of the product and would help them choose the right variant to purchase.

They are the main beneficiaries of this study, which may help them to improve their marketing strategies. It would provide substantial data to the business that they could make use of in boosting their sales. Moreover, developing brand awareness will cater to more demands and loyalty in the future.

For they also play a vital role in the business and as consumers. This research would give them the idea that such private vehicles exist, which helps them to conserve energy rather than exploit it. Hence, giving back to the community and making it a better place to live.

Proponents of the Study

This refers to the students conducting the study. They will find self-fulfillment and gain knowledge and skills in this study. This study will help and inspire more researchers to be more innovative and creative in their future endeavors.

Future Researchers

This study will serve as a reference for researchers on the subject of research in the field of marketing. This will serve as a guide to further developing the research with the connection to the variables used.

The significance of a study is a key component of a strong scientific paper. By following these tips, you can create a clear and concise explanation of the importance of your work. I hope that these tips and samples will help you create a perfect Significance of the Study for your thesis. Apply these tips to prevent your mind from wandering aimlessly as you draft the significance of the study. It will allow you to focus on the next section of your thesis, helping you finish it on time. Good luck!

guest

good and interesting

ASDASD

thanks for information

Femi Johnson

Very useful. Thanks

davara

Thank you for a very informative article

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  • Writing Tips

How to Discuss the Significance of Your Research

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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  • Knowledge Base

An Easy Introduction to Statistical Significance (With Examples)

Published on January 7, 2021 by Pritha Bhandari . Revised on June 22, 2023.

If a result is statistically significant , that means it’s unlikely to be explained solely by chance or random factors. In other words, a statistically significant result has a very low chance of occurring if there were no true effect in a research study.

The p value , or probability value, tells you the statistical significance of a finding. In most studies, a p value of 0.05 or less is considered statistically significant, but this threshold can also be set higher or lower.

Table of contents

How do you test for statistical significance, what is a significance level, problems with relying on statistical significance, other types of significance in research, other interesting articles, frequently asked questions about statistical significance.

In quantitative research , data are analyzed through null hypothesis significance testing, or hypothesis testing. This is a formal procedure for assessing whether a relationship between variables or a difference between groups is statistically significant.

Null and alternative hypotheses

To begin, research predictions are rephrased into two main hypotheses: the null and alternative hypothesis .

  • A null hypothesis ( H 0 ) always predicts no true effect, no relationship between variables , or no difference between groups.
  • An alternative hypothesis ( H a or H 1 ) states your main prediction of a true effect, a relationship between variables, or a difference between groups.

Hypothesis testin g always starts with the assumption that the null hypothesis is true. Using this procedure, you can assess the likelihood (probability) of obtaining your results under this assumption. Based on the outcome of the test, you can reject or retain the null hypothesis.

  • H 0 : There is no difference in happiness between actively smiling and not smiling.
  • H a : Actively smiling leads to more happiness than not smiling.

Test statistics and p values

Every statistical test produces:

  • A test statistic that indicates how closely your data match the null hypothesis.
  • A corresponding p value that tells you the probability of obtaining this result if the null hypothesis is true.

The p value determines statistical significance. An extremely low p value indicates high statistical significance, while a high p value means low or no statistical significance.

Next, you perform a t test to see whether actively smiling leads to more happiness. Using the difference in average happiness between the two groups, you calculate:

  • a t value (the test statistic) that tells you how much the sample data differs from the null hypothesis,
  • a p value showing the likelihood of finding this result if the null hypothesis is true.

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The significance level , or alpha (α), is a value that the researcher sets in advance as the threshold for statistical significance. It is the maximum risk of making a false positive conclusion ( Type I error ) that you are willing to accept .

In a hypothesis test, the  p value is compared to the significance level to decide whether to reject the null hypothesis.

  • If the p value is  higher than the significance level, the null hypothesis is not refuted, and the results are not statistically significant .
  • If the p value is lower than the significance level, the results are interpreted as refuting the null hypothesis and reported as statistically significant .

Usually, the significance level is set to 0.05 or 5%. That means your results must have a 5% or lower chance of occurring under the null hypothesis to be considered statistically significant.

The significance level can be lowered for a more conservative test. That means an effect has to be larger to be considered statistically significant.

The significance level may also be set higher for significance testing in non-academic marketing or business contexts. This makes the study less rigorous and increases the probability of finding a statistically significant result.

As best practice, you should set a significance level before you begin your study. Otherwise, you can easily manipulate your results to match your research predictions.

It’s important to note that hypothesis testing can only show you whether or not to reject the null hypothesis in favor of the alternative hypothesis. It can never “prove” the null hypothesis, because the lack of a statistically significant effect doesn’t mean that absolutely no effect exists.

When reporting statistical significance, include relevant descriptive statistics about your data (e.g., means and standard deviations ) as well as the test statistic and p value.

There are various critiques of the concept of statistical significance and how it is used in research.

Researchers classify results as statistically significant or non-significant using a conventional threshold that lacks any theoretical or practical basis. This means that even a tiny 0.001 decrease in a p value can convert a research finding from statistically non-significant to significant with almost no real change in the effect.

On its own, statistical significance may also be misleading because it’s affected by sample size. In extremely large samples , you’re more likely to obtain statistically significant results, even if the effect is actually small or negligible in the real world. This means that small effects are often exaggerated if they meet the significance threshold, while interesting results are ignored when they fall short of meeting the threshold.

The strong emphasis on statistical significance has led to a serious publication bias and replication crisis in the social sciences and medicine over the last few decades. Results are usually only published in academic journals if they show statistically significant results—but statistically significant results often can’t be reproduced in high quality replication studies.

As a result, many scientists call for retiring statistical significance as a decision-making tool in favor of more nuanced approaches to interpreting results.

That’s why APA guidelines advise reporting not only p values but also  effect sizes and confidence intervals wherever possible to show the real world implications of a research outcome.

Aside from statistical significance, clinical significance and practical significance are also important research outcomes.

Practical significance shows you whether the research outcome is important enough to be meaningful in the real world. It’s indicated by the effect size of the study.

Clinical significance is relevant for intervention and treatment studies. A treatment is considered clinically significant when it tangibly or substantially improves the lives of patients.

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

  • Normal distribution
  • Descriptive statistics
  • Measures of central tendency
  • Correlation coefficient

Methodology

  • Cluster sampling
  • Stratified sampling
  • Types of interviews
  • Cohort study
  • Thematic analysis

Research bias

  • Implicit bias
  • Cognitive bias
  • Survivorship bias
  • Availability heuristic
  • Nonresponse bias
  • Regression to the mean

Statistical significance is a term used by researchers to state that it is unlikely their observations could have occurred under the null hypothesis of a statistical test . Significance is usually denoted by a p -value , or probability value.

Statistical significance is arbitrary – it depends on the threshold, or alpha value, chosen by the researcher. The most common threshold is p < 0.05, which means that the data is likely to occur less than 5% of the time under the null hypothesis .

When the p -value falls below the chosen alpha value, then we say the result of the test is statistically significant.

A p -value , or probability value, is a number describing how likely it is that your data would have occurred under the null hypothesis of your statistical test .

P -values are usually automatically calculated by the program you use to perform your statistical test. They can also be estimated using p -value tables for the relevant test statistic .

P -values are calculated from the null distribution of the test statistic. They tell you how often a test statistic is expected to occur under the null hypothesis of the statistical test, based on where it falls in the null distribution.

If the test statistic is far from the mean of the null distribution, then the p -value will be small, showing that the test statistic is not likely to have occurred under the null hypothesis.

No. The p -value only tells you how likely the data you have observed is to have occurred under the null hypothesis .

If the p -value is below your threshold of significance (typically p < 0.05), then you can reject the null hypothesis, but this does not necessarily mean that your alternative hypothesis is true.

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

  • Open Access
  • First Online: 03 December 2022

Cite this chapter

You have full access to this open access chapter

significant of the study research example

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

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

19k Accesses

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

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

Part I. Setting the Groundwork

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

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

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

The picture illustrates a description - A confusing aspect of developing appropriate arguments is the absence of consensus definitions of some key terms.

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

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

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

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

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

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

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

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

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

We will use the following definitions:

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

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

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

Significance

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

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

The picture illustrates a description- Significance can be determined before data are gathered. Significance is an attribute of the research problems.

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

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

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

The picture represents a description-What makes a study significant in the theoretical framework and the predictions make clear how it will increase the field's understanding.

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

Contributions

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

The picture represents a description-A study's contribution lies in the value of its findings for revising the hypotheses, making clear what has been learned.

Contributions Emerge from Revisions to your Hypotheses

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

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

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

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

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

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

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

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

Contributions Answer the Question of Generalizability

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

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

The Connection Between Contributions and Generalizability

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

An Example That Illustrates the Connection

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

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

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

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

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

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

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

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

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

Implications

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

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

Implications for Future Research

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

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

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

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

Implications for Practice

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

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

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

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

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

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

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

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

Part III. The Role of Methods in Determining Contributions

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

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

The picture represents a description-The role that methods play in scientific inquiry is to ensure that your hypotheses will be tested appropriately for contributions.

Coherence Across the Phases of Scientific Inquiry

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

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

The picture illustrates a flowchart depicting the chain of coherence that runs through all parts of a research study-methods, results, hypotheses, and discussion.

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

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

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

Methods Enable Significance to Yield Contributions

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

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

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

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

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

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

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

Limitations of a Study

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

Limitations Due to Unfortunate Choices

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

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

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

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

The picture illustrates a description-We suggest you do the hard work of figuring out how the data should be interpreted in light of the limitations and share details.

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

Limitations Due to Missing Variables

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

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

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

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

Dealing with Unexpected Findings

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

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

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

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

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

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

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

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

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

Part V. A Few Suggestions for Structuring Your Discussion Section

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

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

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

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

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

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

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

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

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

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How to Write Significance of the Study in a Project Research Paper

How to Write Significance of the Study in a Project Research Paper

When you write your thesis or research paper, there is a section of your introduction that is allotted to the significance of the study. The purpose of this section is to state why your study was needed and the contribution of your research to your field.

In this guide, you will learn the meaning of the significance of the study in your research paper and how to write one.

What is the Significance of the Study?

The significance of the study is basically a written statement that explains why your research was important. It justifies why your research was needed, the impact of your research in your field, its contribution, and how others (audience) would benefit from it.

Also referred to as the rationale of the study, the significance of the study is important to communicate why your research is important to your reader. It is important to make clear the significance of your study for easy comprehension by the readers.

Tips for writing the significance of the study

Reflect on the Problem Statement When writing this section of your paper, first reflect on what contribution your research is making to your field, the gaps in knowledge in your research field, and why your work should be published.

Your problem statement should be reflected in the introduction of the significance of the study. Your research problem statement can guide you to identify specific contributions your research is making to your field of study.

Write from a general contribution to a specific contribution Write your significance of the study in an inverted pyramid format. Start with your research contribution to society as a whole, and then proceed to narrow it down to a specific individual or group of people.

When writing your statement of study, the length should not be more than 500 words for a thesis and around 200 words for a research paper.

However, note that writing the significance of study depends on your subject area and your content as there is no single way of writing a perfect significance of study.

An Example of Significance of Study

This study's findings will further reveal how management-employee bilateral relationships can be strengthened while improving workplace productivity. The findings would be of major importance in assessing how collective bargaining can be a major tool in improving workplace performance in a developing economy like Nigeria. Collective bargaining would help both management and employees bargain on terms and conditions of service and resolve their grievances without leading to strikes, lock-outs, and other forms of industrial actions. The best approach in negotiating on the bargaining table is to provide employees with the importance of collective bargaining as the best method of settling the industrial conflict, which will improve their productivity and lead to higher organizational performance.

The significance of the study is used in academic writing by students and researchers to communicate the importance of a research problem. This section describes specific contributions made to your field of study and who benefits from it. Also, the extent to which the study matters and its potential benefits to people, researchers, departments and other fields are discussed here. This statement is written at the end of your introduction and should be well attended to.

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Writing the Significance of a Study

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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 the Rationale of the Study in Research (Examples)

significant of the study research example

What is the Rationale of the Study?

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

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

Table of Contents:

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

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

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

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

When is the Rationale for Research Written?

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

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

What to Include in the Study Rationale

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

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

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

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

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

Methodological limitations

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

Contextual limitations

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

Conceptual limitations

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

Study Rationale Examples

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

Background presentation

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

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

Rationale of the study

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

Statement of the problem

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

How long is a study rationale?

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

Consider Using Professional Academic Editing Services

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

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

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  • Population Study Article
  • Published: 10 July 2024

Caregiver-reported emotional-behavioral symptoms in Spanish youth during the COVID-19 pandemic: a longitudinal study

  • Xavier Estrada-Prat 1 , 2 ,
  • Eduardo Estrada 3 ,
  • Jordina Tor 1 , 2 ,
  • Marcela Mezzatesta 1 ,
  • Aritz Aranbarri 1 , 2 ,
  • Alazne Aizpitarte 1 , 2 ,
  • Anna Butjosa 1 , 2 , 4 ,
  • Natalia Albiac 1 ,
  • Marina Fabrega 1 ,
  • Josep Maria Haro 4 , 5 ,
  • Immaculada Insa Pineda 1 ,
  • Jose A. Alda 1 , 2 ,
  • Carles Virgili 6 ,
  • Ester Camprodon 1 , 2 ,
  • Montserrat Dolz 1 , 2 , 4 , 7 ,
  • Charlotte Keating 6 &
  • Esther Via 1 , 2  

Pediatric Research ( 2024 ) Cite this article

Metrics details

COVID-19 pandemic stressors affected youth’s mental health. This longitudinal study aims to explore these effects while considering predictive factors such as age and sex.

An initial sample of 1502 caregivers answered a longitudinal survey evaluating their youths’ (4–17 years of age) emotional/behavioral symptoms using the Pediatric Symptom Checklist (PSC) screening tool. First assessment in May–July 2020 included the prior year’s retrospective (T R ) and since-lockdown-start (T 0 ) PSC, followed by monthly evaluations until February 2021.

A positive screening PSC (PSC+) was reported in 13.09% of cases at T R and 35.01% at T 0, but the likelihood of PSC+ quickly decreased over time. At T 0 , a more pronounced impact was found on children (39.7%) compared to adolescents (25.4%); male children exhibited higher risk for a PSC+ at T 0 and longitudinally than females. Adolescents presented a weaker effect of time-improvement. PSC+ at T R , experienced stressors, and caregiver’s stress/depressive symptoms positively predicted PSC+ at T 0 and longitudinally; adolescents’ unproductive coping style predicted PSC+ at T 0.

The study shows a caregiver-reported increase in emotional/behavioral symptoms in youths during the COVID-19 pandemic, affecting predominantly younger children in the early stages and showing gradual improvement over time, albeit possibly slower in adolescents.

The results show the anticipated surge in emotional and behavioral symptoms during the COVID-19 lockdown in youth reported by caregivers, followed by subsequent amelioration. Of greater significance, the study reveals a heightened impact on young children initially, yet it suggests a slower improvement trajectory in adolescents. The study also identifies risk factors linked to emotional and behavioral symptoms within each age group. Alongside the longitudinal approach, the authors underscore the remarkable inclusion of a significant representation of young children, an unusual feature in such surveys.

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Acknowledgements

All the authors of the study thank staff-members of Hospital Sant Joan de Déu, who provided valuable feedback, particularly Laura Duran and Jesús Lull for their initial support of the study. They also thank all the families that voluntarily participated in the study. This study has been indexed within the COVID-MINDS initiative bringing together longitudinal studies on COVID-19 pandemic mental health impact ( https://www.covidminds.org/ ). Part of this work was presented at the 20th International Congress of the European Society for Child and Adolescent Psychiatry, 29th June to July 1st 2023.

The study is part of the Kids Corona platform of studies at the Hospital Sant Joan de Déu, Barcelona ( https://www.sjdhospitalbarcelona.org/en/kidscorona ). This research was partially funded by the Project Grant PI22/00655 from Health Institute Carlos III, the Stavros Niarchos Foundation (SNF), Banco Santander, and other private donors of Kids Corona at the Hospital Sant Joan de Déu Barcelona. The authors thank the CERCA Program, Generalitat de Catalunya.

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Conceptualization, X.E.-P. and E.V.; methodology, X.E.-P., E.E., J.T., C.V., A.B., A.A., A.A., E.V.; formal analysis, E.E., J.T., C.V., E.V.; data curation, X.E-P., J.T., E.V.; original draft preparation, X.E.-P., J.T., E.V.; writing—review and editing, all authors. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Jordina Tor or Esther Via .

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Estrada-Prat, X., Estrada, E., Tor, J. et al. Caregiver-reported emotional-behavioral symptoms in Spanish youth during the COVID-19 pandemic: a longitudinal study. Pediatr Res (2024). https://doi.org/10.1038/s41390-024-03364-4

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  • Estimated changes in free sugar consumption one year after the UK soft drinks industry levy came into force: controlled interrupted time series analysis of the National Diet and Nutrition Survey (2011–2019)
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  • http://orcid.org/0000-0003-1857-2122 Nina Trivedy Rogers 1 ,
  • http://orcid.org/0000-0002-3957-4357 Steven Cummins 2 ,
  • Catrin P Jones 1 ,
  • Oliver Mytton 3 ,
  • Mike Rayner 4 ,
  • Harry Rutter 5 ,
  • Martin White 1 ,
  • Jean Adams 1
  • 1 MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus , University of Cambridge , Cambridge , UK
  • 2 Department of Public Health, Environments & Society , London School of Hygiene & Tropical Medicine , London , UK
  • 3 Great Ormond Street Institute of Child Health , University College London , London , UK
  • 4 Nuffield Department of Population Health , University of Oxford , Oxford , UK
  • 5 Department of Social and Policy Sciences , , University of Bath , Bath , UK
  • Correspondence to Dr Nina Trivedy Rogers, MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, University of Cambridge, Cambridge, CB2 1TN, UK; nina.rogers{at}mrc-epid.cam.ac.uk

Background The UK soft drinks industry levy (SDIL) was announced in March 2016 and implemented in April 2018, encouraging manufacturers to reduce the sugar content of soft drinks. This is the first study to investigate changes in individual-level consumption of free sugars in relation to the SDIL.

Methods We used controlled interrupted time series (2011–2019) to explore changes in the consumption of free sugars in the whole diet and from soft drinks alone 11 months after SDIL implementation in a nationally representative sample of adults (>18 years; n=7999) and children (1.5–19 years; n=7656) drawn from the UK National Diet and Nutrition Survey. Estimates were based on differences between observed data and a counterfactual scenario of no SDIL announcement/implementation. Models included protein consumption (control) and accounted for autocorrelation.

Results Accounting for trends prior to the SDIL announcement, there were absolute reductions in the daily consumption of free sugars from the whole diet in children and adults of 4.8 g (95% CI 0.6 to 9.1) and 10.9 g (95% CI 7.8 to 13.9), respectively. Comparable reductions in free sugar consumption from drinks alone were 3.0 g (95% CI 0.1 to 5.8) and 5.2 g (95% CI 4.2 to 6.1). The percentage of total dietary energy from free sugars declined over the study period but was not significantly different from the counterfactual.

Conclusion The SDIL led to significant reductions in dietary free sugar consumption in children and adults. Energy from free sugar as a percentage of total energy did not change relative to the counterfactual, which could be due to simultaneous reductions in total energy intake associated with reductions in dietary free sugar.

  • PUBLIC HEALTH

Data availability statement

Data are available in a public, open access repository. Data from the National Diet and Nutrition Survey years 1–11 (2008–09 to 2018–19) can be accessed on the UK Data Service ( https://ukdataservice.ac.uk/ ).

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/jech-2023-221051

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WHAT IS ALREADY KNOWN ON THIS TOPIC

High intakes of free sugars are associated with a range of non-communicable diseases. Sugar sweetened beverages constitute a major source of dietary free sugars in children and adults.

The UK soft drink industry levy (SDIL) led to a reduction in the sugar content in many sugar sweetened beverages and a reduction in household purchasing of sugar from drinks.

No previous study has examined the impact of the SDIL on total dietary consumption of free sugars at the individual level.

WHAT THIS STUDY ADDS

There were declining trends in the intake of dietary free sugar in adults and children prior to the UK SDIL.

Accounting for prior trends, 1 year after the UK SDIL came into force children and adults further reduced their free sugar intake from food and drink by approximately 5 g/day and 11 g/day, respectively. Children and adults reduced their daily free sugar intake from soft drinks alone by approximately 3 g/day and approximately 5 g/day, respectively.

Energy intake from free sugars as a proportion of total energy consumed did not change significantly following the UK SDIL, indicating energy intake from free sugar was reducing simultaneously with overall total energy intake.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

The UK SDIL was associated with significant reductions in consumption of free sugars from soft drinks and across the whole diet and reinforces previous research indicating a reduction in purchasing. This evidence should be used to inform policy when extending or considering other sugar reduction strategies.

Energy intake from free sugars has been falling but levels remain higher than the 5% recommendation set by the WHO. Reductions in dietary sugar in relation to the SDIL may have driven significant reductions in overall energy.

Introduction

High consumption of free sugars is associated with non-communicable diseases. 1 Guidelines from the World Health Organization (WHO) and the UK Scientific Advisory Committee on Nutrition (SACN) suggest limiting free sugar consumption to below 5% of total energy intake to achieve maximum health benefits, 1 2 equivalent to daily maximum amounts of 30 g for adults, 24 g for children (7–10 years) and 19 g for young children (4–6 years). In the UK, consumption of free sugar is well above the recommended daily maximum, although levels have fallen over the last decade. 3 For example, adolescents consume approximately 70 g/day 4 and obtain 12.3% of their energy from free sugars. 3 Sugar sweetened beverages (SSBs) constitute a major source of free sugar in the UK diet, 2 5 and are the largest single source for children aged 11–18 years where they make up approximately one-third of their daily sugar intake. 6 A growing body of evidence has shown a link between consumption of SSBs and higher risk of weight gain, type 2 diabetes, coronary heart disease and premature mortality, 7 such that the WHO recommends taxation of SSBs in order to reduce over-consumption of free sugars and to improve health. 8 To date, >50 countries have introduced taxation on SSBs, which has been associated with a reduction in sales and dietary intake of free sugar from SSBs. 9 Reductions in the prevalence of childhood obesity 10 11 and improvements in dental health outcomes 12 13 have also been reported.

In March 2016 the UK government announced the UK soft drink industry levy (SDIL), a two-tier levy on manufacturers, importers and bottlers of soft drinks which would come into force in March 2018. 14 The levy was designed to incentivise manufacturers to reformulate and reduce the free sugar content of SSBs (see details in online supplemental text 1 ).

Supplemental material

One year after the UK SDIL was implemented there was evidence of a reduction in the sugar content of soft drinks 15 and households on average reduced the amount of sugar purchased from soft drinks by 8 g/week with no evidence of substitution with confectionary or alcohol. 16 However, lack of available data meant it was not possible to examine substitution of purchasing other sugary foods and drinks, which has previously been suggested in some but not all studies. 17 18 Household purchasing only approximates individual consumption because it captures only those products brought into the home, products may be shared unequally between household members, and it does not account for waste.

To examine the effects of the SDIL on total sugar intake at the individual level, in this study we used surveillance data collected using 3- or 4-day food diaries as part of the UK National Diet and Nutrition Survey (NDNS). We aimed to examine changes in absolute and relative consumption of free sugars from soft drinks alone and from both food and drinks (allowing us to consider possible substitutions with other sugary food items), following the announcement and implementation of the UK SDIL.

Data source

We used 11 years of data (2008–2019) from the NDNS. Data collection, sampling design and information on response is described in full elsewhere. 19 In brief, NDNS is a continuous national cross-sectional survey capturing information on food consumption, nutritional status and nutrient intake inside and outside of the home in a representative annual sample of approximately 500 adults and 500 children (1.5–18 years) living in private households in the UK. Participants are sampled throughout the year, such that in a typical month about 40 adults and 40 children participate (further details are shown in online supplemental text 2 ).

Outcomes of interest

Outcomes of interest were absolute and relative changes in the total intake of dietary free sugar from (1) all food and soft drinks combined and (2) from soft drinks alone. A definition of free sugar is given in online supplemental text 3 . Drink categories examined were those that fell within the following NDNS categories: soft drinks – not low calorie; soft drinks – low calorie; semi-skimmed milk; whole milk; skimmed milk; fruit juice, 1% fat milk and other milk and cream. Additionally, we examined absolute and relative changes in percentage energy from free sugar in (1) food and soft drinks and (2) soft drinks alone. While examination of changes in sugar consumption and percentage energy from sugar across the whole diet (food and drink) captures overall substitutions with other sugar-containing products following the UK SDIL, examination of sugar consumption from soft drinks alone provides a higher level of specificity to the SDIL.

Protein intake was selected as a non-equivalent dependent control. It was not a nutritional component specifically targeted by the intervention or other government interventions and therefore is unlikely to be affected by the SDIL but could still be affected by confounding factors such as increases in food prices 20 (see online supplemental text 4 ).

Statistical analysis

Controlled interrupted time series (ITS) analyses were performed to examine changes in the outcomes in relation to the UK SDIL separately in adults and children. We analysed data at the quarterly level over 11 years with the first data point representing dates from April to June 2008 and the last representing dates from January to March 2019. Model specifications are shown in online supplemental text 5 . Where diary date entries extended over two quarters, the earlier quarter was designated as the time point for analysis. Generalised least squares models were used. Autocorrelation in the time series was determined using Durbin–Watson tests and from visualisations of autocorrelation and partial correlation plots. Autocorrelation-moving average correlation structure with order (p) and moving average (q) parameters were used and selected to minimise the Akaike information criterion in each model. Trends in free sugar consumption prior to the announcement of SDIL in April 2016 were used to estimate counterfactual scenarios of what would have happened if the SDIL had not been announced or come into force. Thus, the interruption point was the 3-month period beginning April 2016. Absolute and relative differences in consumption of free sugars/person/day were estimated by calculating the difference between the observed and counterfactual values at quarterly time point 45. To account for non-response and to ensure the sample distribution represented the UK distribution of females and males and age profile, weights provided by NDNS were used and adapted for analysis of adults and children separately. 21 A study protocol has been published 22 and the study is registered ( ISRCTN18042742 ). For changes to the original protocol see online supplemental text 6 . All statistical analyses were performed in R version 4.1.0.

Data from 7999 adults and 7656 children were included across 11 years representing approximately 40 children and 40 adults each month. Table 1 gives descriptive values for the outcomes of interest. Compared with the pre-announcement period, free sugars consumed from all soft drinks reduced by around one-half in children and one-third in adults in the post-announcement period. Total dietary free sugar consumption and percentage of total dietary energy derived from free sugars also declined. Mean protein consumption was relatively stable over both periods in children and adults. The age and sex of the children and adults were very similar in the pre- and post-announcement periods.

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Mean amount of free sugar (g) consumed in children and adults per day during the study period before and after the announcement of the soft drinks industry levy (SDIL)

All estimates of change in free sugar consumption referred to below are based on g/individual/day in the 3-month period beginning January 2019 and compared with the counterfactual scenario of no UK SDIL announcement and implementation.

Change in free sugar consumption (soft drinks only)

In children, consumption of free sugars from soft drinks was approximately 27 g/day at the start of the study period but fell steeply throughout. By the end of the study period mean sugar consumption from soft drinks was approximately 10 g/day ( figure 1 ). Overall, relative to the counterfactual scenario, there was an absolute reduction in daily free sugar consumption from soft drinks of 3.0 g (95% CI 0.1 to 5.8) or a relative reduction of 23.5% (95% CI 46.0% to 0.9%) in children ( table 2 ). In adults, free sugar consumption at the beginning of the study was lower than that of children (approximately 17 g/day) and was declining prior to the SDIL announcement, although less steeply ( figure 1 ). Following the SDIL announcement, free sugar consumption from soft drinks appeared to decline even more steeply. There was an absolute reduction in free sugar consumption from soft drinks of 5.2 g (95% CI 4.2 to 6.1) or a relative reduction of 40.4% (95% CI 32.9% to 48.0%) in adults relative to the counterfactual ( figure 1 , table 2 ).

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Observed and modelled daily consumption (g) of free sugar from drink products per adult/child from April 2008 to March 2019. Red points show observed data and solid red lines (with light red shadows) show modelled data (and 95% CIs) of free sugar consumed from drinks. The dashed red line indicates the counterfactual line based on pre-announcement trends and if the announcement and implementation had not happened. Modelled protein consumption from drinks (control group) was removed from the graph to include resolution but is available in the supplementary section. The first and second dashed lines indicate the announcement and implementation of the soft drinks industry levy (SDIL), respectively.

Change in free sugar consumption in food and drink and energy from free sugar as a proportion of total energy compared with the counterfactual scenario of no announcement and implementation of the UK soft drinks industry levy (SDIL)

Change in total dietary free sugar consumption (food and soft drinks combined)

Consumption of total dietary free sugars in children was approximately 70 g/day at the beginning of the study but this fell to approximately 45 g/day by the end of the study ( figure 2 ). Relative to the counterfactual scenario, there was an absolute reduction in total dietary free sugar consumption of 4.8 g (95% CI 0.6 to 9.1) or relative reduction of 9.7% (95% CI 18.2% to 1.2%) in children ( figure 2 ; table 2 ). In adults, consumption of total dietary free sugar consumption at the beginning of the study was approximately 60 g/day falling to approximately 45 g/day by the end of the study ( figure 2 ). Relative to the counterfactual scenario there was an absolute reduction in total dietary free sugar consumption in adults of 10.9 g (95% CI 7.8 to 13.9) or a relative reduction of 19.8% (95% CI 25.4% to 14.2%). Online supplemental figures show that, relative to the counterfactual, dietary protein consumption and energy from protein was more or less stable across the study period (see online supplemental figures S3–S6 ).

Observed and modelled daily consumption (g) of free sugar from food and drink products per adult/child from April 2008 to March 2019. Red points show observed data and solid red lines (with light red shadows) show modelled data (and 95% CIs) of free sugar consumed from food and drinks. The dashed red line indicates the counterfactual line based on pre-announcement trends and if the announcement and implementation had not happened. Modelled protein consumption from food and drinks (control group) was removed from the graph to include resolution but is available in the supplementary section. The first and second dashed lines indicate the announcement and implementation of the soft drinks industry levy (SDIL), respectively.

Change in energy from free sugar as a proportion of total energy

The percentage of energy from total dietary free sugar decreased across the study period but did not change significantly relative to the counterfactual scenario in children or adults, with relative changes in free sugar consumption of −7.6 g (95% CI −41.7 to 26.5) and −24.3 g (95% CI −54.0 to 5.4), respectively (see online supplemental figure S1 and table 2 ). Energy from free sugar in soft drinks as a proportion of total energy from soft drinks also decreased across the study period but did not change significantly relative to the counterfactual (see online supplemental figure S2 ).

Summary of main findings

This study is the first to examine individual level consumption of free sugars in the total diet (and in soft drinks only) in relation to the UK SDIL. Using nationally representative population samples, we found that approximately 1 year following the UK SDIL came into force there was a reduction in total dietary free sugar consumed by children and adults compared with what would have been expected if the SDIL had not been announced and implemented. In children this was equivalent to a reduction of 4.8 g of free sugars/day from food and soft drinks, of which 3 g/day came from soft drinks alone, suggesting that the reduction of sugar in the diet was primarily due to a reduction of sugar from soft drinks. In adults, reductions in dietary sugar appeared to come equally from food and drink with an 11 g reduction in food and drink combined, of which 5.2 g was from soft drinks only. There was no significant reduction compared with the counterfactual in the percentage of energy intake from free sugars in the total diet or from soft drinks alone in both children and adults, suggesting that energy intake from free sugar was reducing simultaneously with overall total energy intake.

Comparison with other studies and interpretation of results

Our finding of a reduction in consumption of free sugars from soft drinks after accounting for pre-SDIL announcement trends is supported by previous research showing a large reduction in the proportion of available soft drinks with over 5 g of sugar/100 mL, the threshold at which soft drinks become levy liable. 15 Furthermore, efforts of the soft drink industry to reformulate soft drinks were found to have led to significant reductions in the volume and per capita sales of sugar from these soft drinks. 23

Our findings are consistent with recent research showing reductions in purchasing of sugar from soft drinks of approximately 8 g/household/week (equivalent to approximately 3 g/person/week or approximately 0.5 g/person/day) 1 year after the SDIL came into force. 16 The estimates from the current study suggest larger reductions in consumption (eg, 3 g free sugar/day from soft drinks in children) than previously reported for purchasing. Methodological differences may explain these differences in estimated effect sizes. Most importantly, the previous study used data on soft drink purchases that were for consumption in the home only. In contrast, we captured information on consumption (rather than purchasing) in and out of the home. Consumption of food and particularly soft drinks outside of the home in young people (1–21 years) increases with age and makes a substantial contribution to total free sugar intakes, highlighting the importance of recording both in home and out of home sugar consumption. 4 Purchasing and consumption data also treat waste differently; purchase data record what comes into the home and therefore include waste, whereas consumption data specifically aim to capture leftovers and waste and exclude it from consumption estimates. While both studies use weights to make the population samples representative of the UK, there may be differences in the study participant characteristics in the two studies, which may contribute to the different estimates.

Consistent with other studies, 24 we found that across the 11-year study period we observed a downward trend in free sugar and energy intake in adults and children. 3 A decline in consumption of free sugars was observed in the whole diet rather than just soft drinks, suggesting that consumption of free sugar from food was also declining from as early as 2008. One reason might be the steady transition from sugar in the diet to low-calorie artificial sweeteners, which globally have had an annual growth of approximately 5.1% between 2008 and 2015. 25

Public health signalling around the time of the announcement of the levy may also have contributed to the changes we observed. Public acceptability and perceived effectiveness of the SDIL was reported to be high 4 months before and approximately 20 months after the levy came into force. 26 Furthermore, awareness of the SDIL was found to be high among parents of children living in the UK, with most supporting the levy and intending to reduce purchases of SSBs as a result. 27 Health signalling was also found following the implementation of the SSB tax in Mexico, with one study reporting that most adults (65%) were aware of the tax and that those aware of the tax were more likely to think the tax would reduce purchases of SSBs, 28 although a separate study found that adolescents in Mexico were mostly unaware of the tax, 29 suggesting that public health signalling may differ according to age.

In 2016 the UK government announced a voluntary sugar reduction programme as part of its childhood obesity plan (which also included SDIL) with the aim of reducing sugar sold by industry by 5% no later than 2018 and by 20% in time for 2020 through both reformulation and portion size reduction. 30 While the programme only managed to achieve overall sugar reductions of approximately 3.5%, this did include higher reductions in specific products such as yoghurts (−17%) and cereals (−13%) by 2018 which may have contributed to some of the observed reductions in total sugar consumption (particularly from foods) around the time of the SDIL. While there is strong evidence that the UK SDIL led to significant reformulation 15 and reductions in purchases of sugar from soft drinks, 16 the products targeted by the sugar reduction programme were voluntary with no taxes or penalties if targets were not met, possibly leading to less incentive for manufacturers to reformulate products that were high in sugar. The 5-year duration of the voluntary sugar reduction programme also makes it challenging to attribute overall reductions using interruption points that we assigned to the ITS to align with the date of the SDIL announcement. The soft drinks categories in our study included levy liable and non-levy liable drinks because we wanted to examine whether individuals were likely to substitute levy liable drinks for high sugar non-liable options. The decline in sugar consumed overall and in soft drinks in relation to the levy suggests that individuals did not change their diets substantially by substituting more sugary foods and drinks. This is consistent with findings from a previous study that found no changes in relation to the levy in sugar purchased from fruit juice, powder used to make drinks or confectionery. 16

Consistent with previous analyses, 3 our findings showed that there was a downward trend in energy intake from sugar as a proportion of total energy across the duration of the study. While there was no reduction compared with the counterfactual scenario (which was also decreasing), our estimates suggest that, by 2019, on average energy from sugar as a proportion of all energy appears to be in line with the WHO recommendation of 10% but not the more recent guidelines of 5% which may bring additional health benefits. 1 31 This finding may suggest that reductions in energy intake from sugar were reducing in concert with overall energy intake and indeed may have been driving it. However, the magnitude of calories associated with the reduction in free sugars, compared with the counterfactual scenario in both adults and children, was modest and thus potentially too small to reflect significant changes in the percentage of energy from sugar. In children, a daily reduction of 4.8 g sugar equates to approximately 19.2 kilocalories out of an approximate daily intake of approximately 2000 kilocalories which is equivalent to approximately 1% reduction in energy intake. Furthermore, overall measures of dietary energy are also likely to involve a degree of error reducing the level of precision in any estimates.

Our estimates of changes in sugar consumption in relation to SDIL suggest that adults may have experienced a greater absolute reduction in sugar than children, which is not consistent with estimates of the distributional impact of the policy. 32 However, our understanding may be aided by the visualisations afforded by graphical depictions of our ITS graphs. Children’s consumption of sugar at the beginning of the study period, particularly in soft drinks, was higher than in adults but reducing at a steeper trajectory, which will have influenced our estimated counterfactual scenario of what would have happened without the SDIL. This steep downward trajectory could not have continued indefinitely as there is a lower limit for sugar consumption. No account for this potential ‘floor effect’ was made in the counterfactual. Adults had a lower baseline of sugar consumption, but their trajectory of sugar consumption decreased at a gentler trajectory, potentially allowing more scope for improvement over the longer run.

Reductions in the levels of sugar in food and drink may have also impacted different age groups and children and adults differently. For example, the largest single contributor to free sugars in younger children aged 4–10 years is cereal and cereal products, followed by soft drinks and fruit juice. By the age of 11–18 years, soft drinks provide the largest single source (29%) of dietary free sugar. For adults the largest source of free sugars is sugar, preserves and confectionery, followed by non-alcoholic beverages. 5

Strengths and limitations

The main strengths of the study include the use of nationally representative data on individual consumption of food and drink in and out of the home using consistent food diary assessment over a 4-day period, setting it apart from other surveys which have used food frequency questionnaires, 24 hour recall, shortened dietary instruments or a mixture of these approaches across different survey years. 33 The continual collection of data using consistent methods enabled us to analyse dietary sugar consumption and energy quarterly over 11 years (or 45 time points) including the announcement and implementation period of the SDIL. Information on participant age allowed us to examine changes in sugar consumption in adults and children separately. Limited sample sizes restricted our use of weekly or monthly data and prevented us from examining differences between sociodemographic groups. At each time point we used protein consumption in food and drink as a non-equivalent control category, strengthening our ability to adjust for time-varying confounders such as contemporaneous events. The trends in counterfactual scenarios of sugar consumption and energy from free sugar as part of total energy were based on trends from April 2008 to the announcement of the UK SDIL (March 2016); however, it is possible that the direction of sugar consumption may have changed course. Ascribing changes in free sugar consumption to the SDIL should include exploration of other possible interventions that might have led to a reduction in sugar across the population. We are only aware of the wider UK government’s voluntary sugar reduction programme implemented across overlapping timelines (2015–2020) and leading to reductions in sugar consumption that were well below the targets set. 30 In turn, under-reporting of portion sizes and high energy foods, which may be increasingly seen as less socially acceptable, has been suggested as a common error in self-reported dietary intake with some groups including older teenagers and females, especially those who are living with obesity, more likely to underestimate energy intake. 34 35 However, there is no evidence to suggest this would have changed as a direct result of the SDIL. 36

Conclusions

Our findings indicate that the UK SDIL led to reductions in consumption of dietary free sugars in adults and children 1 year after it came into force. Energy from free sugar as a proportion of overall energy intake was falling prior to the UK SDIL but did not change in relation to the SDIL, suggesting that a reduction in sugar may have driven a simultaneous reduction in overall energy intake.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

For NDNS 2008–2013, ethical approval was obtained from the Oxfordshire A Research Ethics Committee (Reference number: 07/H0604/113). For NDNS 2014–2017, ethical approval was given from the Cambridge South NRES Committee (Reference number: 13/EE/0016). Participants gave informed consent to participate in the study before taking part.

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

  • Data supplement 1

X @stevencjcummins

Contributors OM, SC, MR, HR, MW and JA conceptualised and acquired funding for the study. NTR carried out statistical analyses. NTR and JA drafted the manuscript. All authors contributed to the article and approved the submitted version.

As the guarantor, NTR had access to the data, controlled the decision to publish and accepts full responsibility for the work and the conduct of the study.

Funding NTR, OM, MW and JA were supported by the Medical Research Council (grant Nos MC_UU_00006/7). This project was funded by the NIHR Public Health Research programme (grant nos 16/49/01 and 16/130/01) to MW. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, or the Department of Health and Social Care, UK. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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significant of the study research example

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How to Write an Abstract in Research Papers (with Examples)

How to write an abstract

An abstract in research papers is a keyword-rich summary usually not exceeding 200-350 words. It can be considered the “face” of research papers because it creates an initial impression on the readers. While searching databases (such as PubMed) for research papers, a title is usually the first selection criterion for readers. If the title matches their search criteria, then the readers read the abstract, which sets the tone of the paper. Titles and abstracts are often the only freely available parts of research papers on journal websites. The pdf versions of full articles need to be purchased. Journal reviewers are often provided with only the title and abstract before they agree to review the complete paper. [ 1]  

Abstracts in research papers provide readers with a quick insight into what the paper is about to help them decide whether they want to read it further or not. Abstracts are the main selling points of articles and therefore should be carefully drafted, accurately highlighting the important aspects. [ 2]  

This article will help you identify the important components and provide tips on how to write an abstract in research papers effectively

What is an Abstract?  

An abstract in research papers can be defined as a synopsis of the paper. It should be clear, direct, self-contained, specific, unbiased, and concise. These summaries are published along with the complete research paper and are also submitted to conferences for consideration for presentation.  

Abstracts are of four types and journals can follow any of these formats: [ 2]  

  • Structured  
  • Unstructured  
  • Descriptive  
  • Informative  

Structured abstracts are used by most journals because they are more organized and have clear sections, usually including introduction/background; objective; design, settings, and participants (or materials and methods); outcomes and measures; results; and conclusion. These headings may differ based on the journal or the type of paper. Clinical trial abstracts should include the essential items mentioned in the CONSORT (Consolidated Standards Of Reporting Trials) guidelines.  

significant of the study research example

Figure 1. Structured abstract example [3] 

Unstructured abstracts are common in social science, humanities, and physical science journals. They usually have one paragraph and no specific structure or subheadings. These abstracts are commonly used for research papers that don’t report original work and therefore have a more flexible and narrative style.  

significant of the study research example

Figure 2. Unstructured abstract example [3] 

Descriptive abstracts are short (75–150 words) and provide an outline with only the most important points of research papers. They are used for shorter articles such as case reports, reviews, and opinions where space is at a premium, and rarely for original investigations. These abstracts don’t present the results but mainly list the topics covered.  

Here’s a sample abstract . [ 4]  

“Design of a Radio-Based System for Distribution Automation”  

A new survey by the Maryland Public Utilities Commission suggests that utilities have not effectively explained to consumers the benefits of smart meters. The two-year study of 86,000 consumers concludes that the long-term benefits of smart meters will not be realized until consumers understand the benefits of shifting some of their power usage to off-peak hours in response to the data they receive from their meters. The study presents recommendations for utilities and municipal governments to improve customer understanding of how to use the smart meters effectively.  

Keywords: smart meters, distribution systems, load, customer attitudes, power consumption, utilities  

Informative abstracts (structured or unstructured) give a complete detailed summary, including the main results, of the research paper and may or may not have subsections.   

significant of the study research example

Figure 3. Informative abstract example [5] 

Purpose of Abstracts in Research    

Abstracts in research have two main purposes—selection and indexing. [ 6,7]  

  • Selection : Abstracts allow interested readers to quickly decide the relevance of a paper to gauge if they should read it completely.   
  • Indexing : Most academic journal databases accessed through libraries enable you to search abstracts, allowing for quick retrieval of relevant articles and avoiding unnecessary search results. Therefore, abstracts must necessarily include the keywords that researchers may use to search for articles.  

Thus, a well-written, keyword-rich abstract can p ique readers’ interest and curiosity and help them decide whether they want to read the complete paper. It can also direct readers to articles of potential clinical and research interest during an online search.  

significant of the study research example

Contents of Abstracts in Research  

Abstracts in research papers summarize the main points of an article and are broadly categorized into four or five sections. Here are some details on how to write an abstract .   

Introduction/Background and/or Objectives  

This section should provide the following information:  

  • What is already known about the subject?  
  • What is not known about the subject or what does the study aim to investigate?  

The hypothesis or research question and objectives should be mentioned here. The Background sets the context for the rest of the paper and its length should be short so that the word count could be saved for the Results or other information directly pertaining to the study. The objective should be written in present or past simple tense.  

Examples:  

The antidepressant efficacy of desvenlafaxine (DV) has been established in 8-week, randomized controlled trials. The present study examined the continued efficacy of DV across 6 months of maintenance treatment . [ 1]  

Objective: To describe gastric and breast cancer risk estimates for individuals with CDH1 variants.  

Design, Setting, and Participants (or Materials and Methods)  

This section should provide information on the processes used and should be written in past simple tense because the process is already completed.  

A few important questions to be answered include:  

  • What was the research design and setting?  
  • What was the sample size and how were the participants sampled?  
  • What treatments did the participants receive?  
  • What were the data collection and data analysis dates?  
  • What was the primary outcome measure?  

Hazard ratios (HRs) were estimated for each cancer type and used to calculate cumulative risks and risks per decade of life up to age 80 years.  

significant of the study research example

This section, written in either present or past simple tense, should be the longest and should describe the main findings of the study. Here’s an example of how descriptive the sentences should be:  

Avoid: Response rates differed significantly between diabetic and nondiabetic patients.  

Better: The response rate was higher in nondiabetic than in diabetic patients (49% vs 30%, respectively; P<0.01).  

This section should include the following information:  

  • Total number of patients (included, excluded [exclusion criteria])  
  • Primary and secondary outcomes, expressed in words, and supported by numerical data  
  • Data on adverse outcomes  

Example: [ 8]  

In total, 10.9% of students were reported to have favorable study skills. The minimum score was found for preparation for examination domain. Also, a significantly positive correlation was observed between students’ study skills and their Grade Point Average (GPA) of previous term (P=0.001, r=0.269) and satisfaction with study skills (P=0.001, r=0.493).  

Conclusions  

Here, authors should mention the importance of their findings and also the practical and theoretical implications, which would benefit readers referring to this paper for their own research. Present simple tense should be used here.  

Examples: [ 1,8]  

The 9.3% prevalence of bipolar spectrum disorders in students at an arts university is substantially higher than general population estimates. These findings strengthen the oft-expressed hypothesis linking creativity with affective psychopathology.  

The findings indicated that students’ study skills need to be improved. Given the significant relationship between study skills and GPA, as an index of academic achievement, and satisfaction, it is necessary to promote the students’ study skills. These skills are suggested to be reinforced, with more emphasis on weaker domains.  

significant of the study research example

When to Write an Abstract  

In addition to knowing how to write an abstract , you should also know when to write an abstract . It’s best to write abstracts once the paper is completed because this would make it easier for authors to extract relevant parts from every section.  

Abstracts are usually required for: [ 7]    

  • submitting articles to journals  
  • applying for research grants   
  • writing book proposals  
  • completing and submitting dissertations  
  • submitting proposals for conference papers  

Mostly, the author of the entire work writes the abstract (the first author, in works with multiple authors). However, there are professional abstracting services that hire writers to draft abstracts of other people’s work.   

How to Write an Abstract (Step-by-Step Process)  

Here are some key steps on how to write an abstract in research papers: [ 9]  

  • Write the abstract after you’ve finished writing your paper.  
  • Select the major objectives/hypotheses and conclusions from your Introduction and Conclusion sections.  
  • Select key sentences from your Methods section.  
  • Identify the major results from the Results section.  
  • Paraphrase or re-write the sentences selected in steps 2, 3, and 4 in your own words into one or two paragraphs in the following sequence: Introduction/Objective, Methods, Results, and Conclusions. The headings may differ among journals, but the content remains the same.  
  • Ensure that this draft does not contain: a.   new information that is not present in the paper b.   undefined abbreviations c.   a discussion of previous literature or reference citations d.   unnecessary details about the methods used  
  • Remove all extra information and connect your sentences to ensure that the information flows well, preferably in the following order: purpose; basic study design, methodology and techniques used; major findings; summary of your interpretations, conclusions, and implications. Use section headings for structured abstracts.  
  • Ensure consistency between the information presented in the abstract and the paper.  
  • Check to see if the final abstract meets the guidelines of the target journal (word limit, type of abstract, recommended subheadings, etc.) and if all the required information has been included.  

Choosing Keywords for Abstracts  

Keywords [ 2] are the important and repeatedly used words and phrases in research papers and can help indexers and search engines find papers relevant to your requirements. Easy retrieval would help in reaching a wider audience and eventually gain more citations. In the fields of medicine and health, keywords should preferably be chosen from the Medical Subject Headings (MeSH) list of the US National Library of Medicine because they are used for indexing. These keywords need to be different from the words in the main title (automatically used for indexing) but can be variants of the terms/phrases used in the title, abstract, and the main text. Keywords should represent the content of your manuscript and be specific to your subject area.  

Basic tips for authors [ 10,11]  

  • Read through your paper and highlight key terms or phrases that are most relevant and frequently used in your field, to ensure familiarity.  
  • Several journals provide instructions about the length (eg, 3 words in a keyword) and maximum number of keywords allowed and other related rules. Create a list of keywords based on these instructions and include specific phrases containing 2 to 4 words. A longer string of words would yield generic results irrelevant to your field.  
  • Use abbreviations, acronyms, and initializations if these would be more familiar.  
  • Search with your keywords to ensure the results fit with your article and assess how helpful they would be to readers.  
  • Narrow down your keywords to about five to ten, to ensure accuracy.  
  • Finalize your list based on the maximum number allowed.  

  Few examples: [ 12]  

     
Direct observation of nonlinear optics in an isolated carbon nanotube  molecule, optics, lasers, energy lifetime  single-molecule interaction, Kerr effect, carbon nanotube, energy level 
Region-specific neuronal degeneration after okadaic acid administration  neuron, brain, regional-specific neuronal degeneration, signaling  neurodegenerative diseases; CA1 region, hippocampal; okadaic acid; neurotoxins; MAP kinase signaling system; cell death 
Increases in levels of sediment transport at former glacial-interglacial transitions  climate change, erosion, plant effects  quaternary climate change, soil erosion, bioturbation 

Important Tips for Writing an Abstract  

Here are a few tips on how to write an abstract to ensure that your abstract is complete, concise, and accurate. [ 1,2]  

  • Write the abstract last.  
  • Follow journal-specific formatting guidelines or Instructions to Authors strictly to ensure acceptance for publication.  
  • Proofread the final draft meticulously to avoid grammatical or typographical errors.  
  • Ensure that the terms or data mentioned in the abstract are consistent with the main text.  
  • Include appropriate keywords at the end.

Do not include:  

  • New information  
  • Text citations to references  
  • Citations to tables and figures  
  • Generic statements  
  • Abbreviations unless necessary, like a trial or study name  

significant of the study research example

Key Takeaways    

Here’s a quick snapshot of all the important aspects of how to write an abstract . [2]

  • An abstract in research is a summary of the paper and describes only the main aspects. Typically, abstracts are about 200-350 words long.  
  • Abstracts are of four types—structured, unstructured, descriptive, and informative.  
  • Abstracts should be simple, clear, concise, independent, and unbiased (present both favorable and adverse outcomes).  
  • They should adhere to the prescribed journal format, including word limits, section headings, number of keywords, fonts used, etc.  
  • The terminology should be consistent with the main text.   
  • Although the section heading names may differ for journals, every abstract should include a background and objective, analysis methods, primary results, and conclusions.  
  • Nonstandard abbreviations, references, and URLs shouldn’t be included.  
  • Only relevant and specific keywords should be used to ensure focused searches and higher citation frequency.  
  • Abstracts should be written last after completing the main paper.  

Frequently Asked Questions   

Q1. Do all journals have different guidelines for abstracts?  

A1. Yes, all journals have their own specific guidelines for writing abstracts; a few examples are given in the following table. [ 6,13,14,15]  

   
American Psychological Association           
American Society for Microbiology     
The Lancet     
Journal of the American Medical Association               

Q2. What are the common mistakes to avoid when writing an abstract?  

A2. Listed below are a few mistakes that authors may make inadvertently while writing abstracts.  

  • Copying sentences from the paper verbatim  

An abstract is a summary, which should be created by paraphrasing your own work or writing in your own words. Extracting sentences from every section and combining them into one paragraph cannot be considered summarizing.  

  • Not adhering to the formatting guidelines  

Journals have special instructions for writing abstracts, such as word limits and section headings. These should be followed strictly to avoid rejections.  

  • Not including the right amount of details in every section  

Both too little and too much information could discourage readers. For instance, if the Background has very little information, the readers may not get sufficient context to appreciate your research. Similarly, incomplete information in the Methods and a text-heavy Results section without supporting numerical data may affect the credibility of your research.  

  • Including citations, standard abbreviations, and detailed measurements  

Typically, abstracts shouldn’t include these elements—citations, URLs, and abbreviations. Only nonstandard abbreviations are allowed or those that would be more familiar to readers than the expansions.  

  • Including new information  

Abstracts should strictly include only the same information mentioned in the main text. Any new information should first be added to the text and then to the abstract only if necessary or if permitted by the word limit.  

  • Not including keywords  

Keywords are essential for indexing and searching and should be included to increase the frequency of retrieval and citation.  

Q3. What is the difference between abstracts in research papers and conference abstracts? [16]  

A3. The table summarizes the main differences between research and conference abstracts.  

     
Context  Concise summary of ongoing or completed research presented at conferences  Summary of full research paper published in a journal 
Length  Shorter (150-250 words)   Longer (150-350 words) 
Audience  Diverse conference attendees (both experts & people with general interest)  People or other researchers specifically interested in the subject 
Focus  Intended to quickly attract interest; provides just enough information to highlight the significance, objectives, and impact; may briefly state methods and results  Deeper insight into the study; more detailed sections on methodology, results, and broader implications 
Publication venue  Not published independently but included in conference schedules, booklets, etc.  Published with the full research paper in academic journals, conference proceedings, research databases, etc. 
Citations  Allowed  Not allowed 

  Thus, abstracts are essential “trailers” that can market your research to a wide audience. The better and more complete the abstract the more are the chances of your paper being read and cited. By following our checklist and ensuring that all key elements are included, you can create a well-structured abstract that summarizes your paper accurately.  

References  

  • Andrade C. How to write a good abstract for a scientific paper or conference presentation. Indian J Psychiatry . 2011; 53(2):172-175. Accessed June 14, 2024. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3136027/  
  • Tullu MS. Writing the title and abstract for a research paper: Being concise, precise, and meticulous is the key. 2019; 13(Suppl 1): S12-S17. Accessed June 14, 2024. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6398294/  
  • Zawia J. Writing an Academic Paper? Get to know Abstracts vs. Structured Abstracts. Medium. Published October 16, 2023. Accessed June 16, 2024. https://medium.com/@jamala.zawia/writing-an-academic-paper-get-to-know-abstracts-vs-structured-abstracts-11ed86888367  
  • Markel M and Selber S. Technical Communication, 12 th edition. 2018; pp. 482. Bedford/St Martin’s.  
  • Abstracts. Arkansas State University. Accessed June 17, 2024. https://www.astate.edu/a/global-initiatives/online/a-state-online-services/online-writing-center/resources/How%20to%20Write%20an%20Abstract1.pdf  
  • AMA Manual of Style. 11 th edition. Oxford University Press.  
  • Writing an Abstract. The University of Melbourne. Accessed June 16, 2024. https://services.unimelb.edu.au/__data/assets/pdf_file/0007/471274/Writing_an_Abstract_Update_051112.pdf  
  • 10 Good Abstract Examples that will Kickstart Your Brain. Kibin Essay Writing Blog. Published April 5, 2017. Accessed June 17, 2024. https://www.kibin.com/essay-writing-blog/10-good-abstract-examples/  
  • A 10-step guide to make your research paper abstract more effective. Editage Insights. Published October 16, 2013. Accessed June 17, 2024. https://www.editage.com/insights/a-10-step-guide-to-make-your-research-paper-abstract-more-effective  
  • Using keywords to write your title and abstract. Taylor & Francis Author Services. Accessed June 15, 2024. https://authorservices.taylorandfrancis.com/publishing-your-research/writing-your-paper/using-keywords-to-write-title-and-abstract/  
  • How to choose and use keywords in research papers. Paperpal by Editage blog. Published March 10, 2023. Accessed June 17, 2024. https://paperpal.com/blog/researcher-resources/phd-pointers/how-to-choose-and-use-keywords-in-research-papers  
  • Title, abstract and keywords. Springer. Accessed June 16, 2024. https://www.springer.com/it/authors-editors/authorandreviewertutorials/writing-a-journal-manuscript/title-abstract-and-keywords/10285522  
  • Abstract and keywords guide. APA Style, 7 th edition. Accessed June 18, 2024. https://apastyle.apa.org/instructional-aids/abstract-keywords-guide.pdf  
  • Abstract guidelines. American Society for Microbiology. Accessed June 18, 2024. https://asm.org/events/asm-microbe/present/abstract-guidelines  
  • Guidelines for conference abstracts. The Lancet. Accessed June 16, 2024. https://www.thelancet.com/pb/assets/raw/Lancet/pdfs/Abstract_Guidelines_2013.pdf  
  • Is a conference abstract the same as a paper abstract? Global Conference Alliance, Inc. Accessed June 18, 2024. https://globalconference.ca/is-a-conference-abstract-the-same-as-a-paper-abstract/  

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  • Open access
  • Published: 10 July 2024

Ready to leave? – Adolescents’ and parents’ perceptions of transition from paediatric to adult rheumatology care

  • A. Vermé   ORCID: orcid.org/0009-0008-4541-1133 1 , 2 ,
  • Marika Wenemark   ORCID: orcid.org/0000-0002-6281-7783 1 , 3 , 4 ,
  • J. Granhagen Jungner   ORCID: orcid.org/0000-0003-4103-6539 1 ,
  • E. Broström   ORCID: orcid.org/0000-0002-2967-8080 1 &
  • C. Bartholdson   ORCID: orcid.org/0000-0001-5807-3438 1 , 2  

BMC Health Services Research volume  24 , Article number:  795 ( 2024 ) Cite this article

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In Sweden, approximately 2000 children live with Juvenile Idiopathic Arthritis (JIA). About half of them continue to have an active disease and need to transfer to adult rheumatology care. This study aimed to investigate Swedish adolescents’ and parents´ perceptions of readiness for transition from pediatric to adult rheumatology care.

The study was a cross-sectional quantitative study. Patients at the pediatric rheumatology clinic at a university hospital in Sweden and members of The Swedish National Organization for Young Rheumatics aged 14–18 and their parents were invited to participate in the study. Data was collected with the Readiness for Transition Questionnaire (RTQ) focusing on adolescents' transition readiness, adolescents' healthcare behaviors and responsibility, and parental involvement. Data were analyzed with descriptive statistics. Comparative analyses were made using non-parametric tests with significance levels of 0.05 as well as factor analyses and logistic regression.

There were 106 adolescents (85 girls, 20 boys) and 96 parents answering the RTQ. The analysis revealed that many adolescents and parents experienced that the adolescents were ill-prepared to take over responsibility for several healthcare behaviors, such as booking specialty care appointments, calling to renew prescriptions and communicating with medical staff on phone and to transfer to adult care. Parents and adolescents alike stated that it was especially difficult for the adolescents to take responsibility for healthcare behaviors meaning that the adolescents had to have direct interaction with the healthcare professionals (HCPs) at the paediatric rheumatology clinic, for example to renew prescriptions. It was evident that the adolescents who perceived they were ready to take responsibility for the aspects related to direct interaction with HCPs were more overall ready to be transferred to adult care.

Adolescents need more support to feel prepared to transfer to adult care. With the results from this study, we can develop, customize, and optimize transitional care programs in Sweden for adolescents.

Peer Review reports

Juvenile Idiopathic Arthritis (JIA) is a heterogeneous group of disorders categorized into seven subgroups, all of which have inflammatory arthritis as a common denominator [ 1 ]. JIA can arise at any time during childhood, and girls are more likely than boys to be affected [ 2 ]. Yearly, 150–200 children in Sweden are diagnosed with JIA and around 1 500–2 000 children live with the disease [ 3 ]. Approximately half of the adolescents with JIA continue to have an active disease as they enter adulthood, and need to transfer to adult care [ 4 , 5 ]. In Sweden, most adolescents will be transferred to adult care at the age of 18 years. The transfer from paediatric to adult rheumatology care is, for some, perceived as difficult, and can cause anxiety among adolescents and their parents [ 6 ].

There is a distinction between transfer and transition. The term ‛transfer’ refers to an occurrence or series of events when adolescents with ongoing physical and medical issues move from receiving care in a paediatric setting to an adult medical setting. ‘Transition’, on the other hand, is a process that occurs throughout adolescence and aims to educate adolescents to manage their lives and health in relation to their chronic illness. The learning process should start before the adolescent enters puberty, and last until they are old enough to take care of themselves [ 7 ]. The Society for Adolescent Medicine defines transitional care as “the purposeful, planned movement of adolescents and young adults with chronic physical and medical conditions from child-centred to adult-oriented healthcare systems” (p.570) [ 8 ].

Previous research shows that the transition process gives the best results if initiated as soon as the child enters adolescence. It can begin as early as 11 years of age but not later than the age of 14 [ 9 ]. The necessity of starting the process in early adolescence was also demonstrated by McDonagh and colleagues, who examined a coordinated evidence-based approach. Twelve months following the program’s implementation, the youngest group (aged 11) displayed significant gains in knowledge of arthritis, an increase in self-medication, and increased satisfaction with rheumatology care [ 10 ].

In the transition process, it is important to include the parents and to help them adjust to their new role as they will no longer be the ones who have the main responsibility for the adolescent’s healthcare [ 11 ]. During the transition process, healthcare professionals (HCPs) should try to strengthen the adolescent’s independence without undermining the parent’s role [ 12 ]. HCPs, adolescents, and parents must try to create a common view on how the transition process facilitates and strengthens the adolescent’s independence [ 13 ].

There are several methods for measuring readiness for transition targeting adolescents, parents, and HCPs. In the literature, both quantitative [ 14 , 15 , 16 , 17 ] and qualitative [ 18 , 19 , 20 , 21 ] methods are used. In Sweden the Readiness for Transition Questionnaire (RTQ) has recently been used [ 26 ]. Results from previous research measuring readiness show that both adolescents and parents need more knowledge about transition. In a study with 49 patients suffering from JIA and 103 parents, Matsumoto (2021) shows that over half of the adolescents and about one-third of their parents had limited knowledge about what transitional care was, and over half of the adolescents and nearly four-fifths of the parents felt worried to transfer to adult care [ 22 ]. This study also showed that about half of both the adolescents and the parents were not given the opportunity to talk to the doctor about the upcoming transfer to adult care. A major worry was that the medical doctors in adult care would not have adequate knowledge about JIA [ 22 , 23 ]. In another study by Sömnez (2021), of 157 patients with different rheumatology diagnoses and their parents, half of the adolescents and almost all the parents wanted to stay in paediatric care [ 23 ] and were, accordingly, not sufficiently ready for transfer. Moreover, age seems to be an important determinator for perceptions of readiness for transfer from paediatric rheumatology [ 24 ]. Bingham and colleagues found that older children had higher self-reported autonomy in most questions asked regarding accessing medical care [ 25 ]. Other patient characteristics associated with high self-perceived autonomy included having a family member with a similar disease, having a younger parent, and longer disease duration [ 25 ].

Transfer to adult rheumatology is under-researched [ 10 ]. In Sweden, no studies have been made on readiness for transfer to adult care among adolescents with JIA and there is no structured transition program or guidelines for this patient group. In order to tailor and improve transitional care for adolescents with JIA, it is essential to know how ready adolescents and their parents feel about different aspects of the transition and, ultimately, the transfer from paediatric to adult care. Investigation of adolescents’ and parents’ readiness could facilitate understanding of the transition process and create foundations for individualized support.

The aim of this study was to investigate Swedish adolescents with JIA and their parents’ perceptions of readiness for transition from paediatric to adult rheumatology care.

Study design

A cross-sectional quantitative study.

Participants

Data were collected from March 2020 to March 2022. Patients at the paediatric rheumatology clinic at a university hospital in Stockholm and members of the Swedish National Organization for Young Rheumatics were invited, together with their parents, to participate in the study.

Inclusion criteria

Confirmed Juvenile Idiopathic Arthritis, adolescents turning 14 the year of inclusion and adolescents up to 18 years.

Exclusion criteria

Uncertain paediatric rheumatic disease. Non-Swedish speaking adolescents/parents.

Questionnaire

The readiness for transition questionnaire (RTQ) was originally developed and validated by Gilleland [ 15 ] for patient groups with different chronic diagnoses, and is also available in a parental version [ 15 ]. The questionnaire has been translated and culturally adapted into Swedish [ 26 ] using scientific guidelines [ 27 ]. The first part of the RTQ covers four questions about responsibility for healthcare [ 15 ]. Furthermore, the RTQ covers adolescent responsibility and parental involvement in different healthcare-related behaviours, as well as final questions about overall transition readiness and overall readiness for responsibility for healthcare [ 15 ]. Included healthcare-related behaviours are, for example, regular blood samples, taking medications, and being in contact with the clinic. The questions about healthcare-related behaviours have five possible answers for adolescent responsibility: 1 = Not responsible at all; 2 = Sometimes responsible; 3 = Often responsible; 4 = Almost always responsible; and 5 = Not relevant. The same behaviours are also investigated in the section about parental involvement, with response options as follows: 1 = Not involved at all; 2 = Sometimes involved; 3 = Often involved; 4 = Almost always involved; and 5 = Not relevant. The response option Not relevant was added for questions related to healthcare behaviours during the adaptation process [ 26 ]. Response alternatives to the final overall questions are: Not at all ready; Somewhat ready; Mostly ready; and Completely ready.

In the present study, two minor adjustments were made to the Swedish version [ 26 ], in both the adolescent and parent versions: 1) the word “daily” was excluded from the question about daily medications since not all medications are taken daily within paediatric rheumatology, and 2) the example of type of clinics in the question about scheduling specialty care appointments was replaced by clinics more relevant to the patient group. Furthermore, questions ( n  = 5) about health were excluded due to ambiguities in what adolescents include in the health concept, and that the original questionnaire [ 15 ] focused on healthcare and not health.

Data collection

In total, 225 members of the Swedish National Organization for Young Rheumatics and 110 patients from the paediatric rheumatology clinic were invited to participate in the study by a research invitation letter sent to their home addresses. The research invitation letter included information explaining the purpose of the study and separate QR codes for adolescents and parents to access the digital anonymous RTQ. One reminder was sent to the intended study participants at one point.

Ethical approval declarations

The study was approved by the Ethical Review Board in Sweden Dnr 2019–01540.

Data analysis

Data were analysed with descriptive statistical methods calculating percentages, medians, ranges, means, and standard deviations. Comparative analyses were made using non-parametric tests (Mann Whitney U test) with a significance level of 0.05. The two parts concerning adolescent responsibility and parental involvement for different healthcare-related behaviours were combined to obtain a measure of the adolescent’s level of “independent responsibility”. In the combined measure, no distinction was made between the two response options “Often” and “Almost always” since we found it difficult to distinguish between them. The independent responsibility measures are described below:

No responsibility – Adolescent not responsible at all.

Minor responsibility – Adolescent sometimes responsible.

Shared responsibility – Adolescent often responsible with parents often involved.

Major responsibility – Adolescent often responsible with parents sometimes or not at all involved.

Factor analysis (Varimax rotated principal component analysis) was used to investigate the dimensions of the items. Logistic regression was used to analyse what factor(s) explain adolescents feeling almost fully or fully ready to transfer to adult care.

Out of 335 patients receiving the invitation, including an invitation to their parents, 106 adolescents (girls n  = 85, boys n  = 20, one missing) and 96 parents answered the questionnaire. The response rate was 32% for adolescents but unknown for parents since information about the number of parents in each family receiving the invitation is missing. Adolescents’ ages ranged from 13 to 18 years old (Fig.  1 ) with a median age of 16 years (participants who were 13 years old were turning 14 the same year). Sociodemographic questions in RTQ include age and gender but not diagnosis subgroup. Therefore, we do not know which subgroup of JIA the participants had. The clinic treats patients with all types of JIA and therefore it can be assumed, but not certain, that there also were a spread of JIA sub group diagnosis among the respondents.

figure 1

Age distribution in the adolescent group ( n  = 104)

Responsibility and involvement in different healthcare-related behaviours

Adolescents and parents were asked about how much responsibility the adolescents took for different healthcare-related behaviours, and how much the parents were involved in, for example, taking medication, renewing prescriptions, and attending medical appointments (Table  1 ). In general, 16–18-year-old adolescents reported taking more responsibility and having lower parental involvement than 13–15-year-olds. For several behaviours, there were significant differences between the two age groups of adolescents (Table 2 ). When analysing gender, one significant difference emerged; namely, girls reported more responsibility for communication with the clinic on the phone compared to boys (p value = 0.045) (Table 2 ). The adolescents reported themselves as taking greater responsibility than the parents reported them as doing. However, both adolescents and parents reported equally that the adolescents took less responsibility for tasks involving direct contact with the clinic (Table  1 ). Both adolescents and parents reported that the parents were largely involved in healthcare-related behaviours. The younger adolescents (13–15 years) reported that their parents were more involved in healthcare-related behaviours than the older adolescents (16–18 years) reported (Table  1 ).

Adolescents’ and parents' perception of independent responsibility regarding different healthcare-related behaviours

In the combined measure of responsibility with different levels of parental involvement, the analysis showed that direct contact with the healthcare system was most challenging for adolescents (Fig.  2 ). In many of the other healthcare-related behaviours, for example, taking medication, getting regular labs, and explaining the disease to others, the adolescents perceived themselves as taking major responsibility, while perceiving parents as often involved. A small proportion of adolescents perceived themselves as taking major responsibility without parental involvement. The substantial progress in responsibility, compared between the younger and older adolescent groups, was for getting regular labs and attending medical appointments. For the more challenging activities, there was progress between the younger and older age groups, but still, less than 25% of the older adolescents perceived major responsibility, with parents often/sometimes involved.

figure 2

Independent responsibility (a combined measure of adolescent responsibility in relation to parent involvement) for different healthcare-related behaviours

Adolescents’ and parents’ perceptions of overall readiness to transfer to adult care

There was a significant difference ( p value = 0.005) (Table 2 ) between the age groups when reporting perceptions of overall readiness to transfer to adult care. In the younger group (13–15 years), 2% perceived that they were fully ready to transfer to adult care compared to 7% of the adolescents in the older group (16–18 years) (Table 3 ). Moreover, in the younger age group (13–15 years), 48% perceived that they were not ready to transfer to adult care compared to 24% in the older age group (16–18 years). There were no significant gender differences when adolescents reported perceptions on how fully ready they were to transfer to adult care.

Parents’ perceptions are congruent with the younger age group of adolescents. Three percent reported that they perceived their adolescents as being fully ready to transfer and half (49%) of the parental group reported that they did not perceive their adolescents as ready to transfer (Table 3 ).

Factors influencing adolescents’ and parents’ perception of overall readiness to transfer to adult care

A factor analysis revealed two factors with eigenvalues above 1, explaining 63.9% of the variance (Table  4 ). Factor 1 includes variables that have to do with bookings and communication by telephone, conceptualized as “Administration”. Factor 2 includes handling labs/medications and communicating in person, which seem related to engagement and routines of the healthcare, conceptualized as “Engagement”.

The engagement factor gets high scores in the group that feels not ready for transfer and increases for the group that feels rather ready. Thus, it seems that this factor includes the first steps to independent responsibility for healthcare. Adolescents’ and parents’ results are in reasonable agreeance for Factor 2 (Table  5 ). The administrative factor is continuously increasing in the three levels of readiness, and there is a bigger gap between the group that feels rather ready and the group that feels almost/fully ready. Parents especially don’t seem to judge their adolescents as fully ready for transfer until they also show independent responsibility for administrative matters.

Separate logistic regressions for adolescents and parents showed that only Factor 1 (administrative) was significant for explaining being almost/fully ready for transfer when also controlling for Factor 2 (engagement) (Table  6 ).

This cross-sectional quantitative study’s analysis reveals that many adolescents with JIA were ill-prepared to transfer to adult care. The same issue was reported by their parents. Parents and adolescents alike stated that it was difficult for the adolescents to take responsibility for several healthcare-related behaviours connected to adolescents’ direct interaction with the HCPs at the paediatric rheumatology clinic. It was evident that the adolescents who perceived they were ready to take responsibility for the aspects related to direct interaction with HCPs were more ready to be transferred to adult care.

As mentioned above, challenging healthcare-related behaviours for adolescents included them having direct contact with HCPs, e.g., calling to book an appointment or renew prescriptions. The same results have been shown in other studies [ 24 , 26 ]. The reasons for these results are not clear. One could argue that the feeling of uncertainty and the fear of making mistakes could be one explanation. Research has shown that adolescents transitioning from adolescent to adult care felt anxious, uncertain, and fearful [ 28 ], which could reinforce the fear of making mistakes. The two items that involve using the phone – to communicate with HCPs and renew prescriptions – seem especially difficult for adolescents. There may be several reasons why young people find it challenging to contact healthcare providers by phone. One reason may be that the phone hours are during the day when they are at school, which makes it difficult for them to handle the contact on their own without having to leave classes. Another reason may be that adolescents rarely make telephone calls, and are especially uncomfortable talking to adults on the phone. On the other hand, adolescents are used to using their mobile phones for many other things and it is an environment they feel safe in, which could be argued would perhaps contribute to them feeling comfortable to contact healthcare providers. Healthcare clinics caring for adolescents must fulfill their task to be adolescent-friendly and customize accessibility according to adolescents’ preferences. Using digital platforms, including communication pathways such as chats, could be one solution and would increase flexibility regarding contact times with HCPs. The digital opportunities that exist today could, perhaps, also be utilized in the transition work itself. In a study by Miller [ 29 ], it was shown that adolescents who were given the opportunity to use digital transition support by an app on their phone increased their self-confidence in taking care of their illness, and the proportion of those who took responsibility for booking visits to the healthcare system. They also used the app to increase their knowledge of their disease [ 29 ].

The present study also provides us with the knowledge that this group of adolescents did not feel ready to transfer to adult care. Only a small percent (5%) of the adolescents reported that they were fully ready to transfer. Our results demonstrate that neither does it seem to be enough to take responsibility for some possibly simpler behaviours to feel fully ready. We speculate that the challenge is, perhaps above all, to start taking responsibility for ‛adult’ things, like booking and calling, i.e., the behaviours included in factor 1. However, it may be difficult for adolescents to evaluate whether they are ready to be transferred, as the idea of it may be abstract and they may not know what to expect. They might not know geographically where they are going, which medical doctor to see, and how the care is conducted there. Despite years of increased study and policy focus on the topic of transition, there are still unmet requirements for adolescents and their families. As a crucial component of an adolescent’s development, health transitions take place concurrently with, and in relation to, a variety of other significant transitions, like transitioning from childhood to being an adolescent, that has an impact on many different facets of life [ 30 ], and which may complicate the process further.

Additionally, our analysis reveals that the levels of readiness increase with the age of the adolescents. This result was expected and has been described by others [ 30 ], and is most likely associated with the developmental process of going from adolescence to adulthood [ 31 ].

In this study, parents graded the adolescents less ready for the transfer than the adolescents graded themselves. Similar results have been reported in other studies investigating transition among adolescent’s with chronic diseases [ 26 ]. Only 13% of parents reported that their adolescent was almost or fully ready to transfer, which is low even compared to the youngest age group’s own perception of readiness. The results could be related to a variety factors. One possibility is that adults and adolescents interpret “fully ready” different. Some adolescents may, for example, express readiness without realizing the impact of more independent responsibility that their parents may include in their interpretation of readiness. However, the results may also be an effect of parents underestimating the adolescent’s knowledge and ability. This could mean that adolescents never develop abilities to take responsibility if parents, for example, continue to administer medications and communicate with healthcare providers [ 32 ]. It is therefore important for HCPs to enable adolescents to increase their abilities and put them to use to support positive adolescent development. For instance, adolescents could practice asking questions about the care or sensitive topics if they are given the chance to do so while their parents are present. Although the group of boys is small, the results show that boys seem to perceive themselves as ready for transfer to a greater degree than girls. In the present study population, this perhaps can be explained by gender roles and that girls are a little more open about their lack of abilities, knowledge, and about expressing worries about the transfer. However, the girls reported to a larger extent than boys that they take responsibility for talking on the phone with HCPs. In a study by Eaton et al., the opposite was shown since they concluded that girls were more ready to transfer and had less parent involvement than boys [ 33 ]. We speculate that this might be due to culture and/or contextual differences, which makes measuring readiness among adolescents in specific contexts and cultures extra important, to enable support to be tailored according to specific needs. In a Swedish study by Burström et al. [ 26 ], the aims were to investigate levels of readiness for transition in adolescents with congenital heart disease and to compare adolescents’ levels with their parents’ assessments. Similarly to our study, they demonstrated that adolescents scored higher on overall readiness than their parents. However, they did not compare girls’ and boys’ readiness but investigated differences in perceptions between mothers and fathers. The results show that parents, regardless of gender, perceive adolescents’ responsibility equally. However, perceptions of parental involvement differed between parental genders, meaning that mothers to a greater extent than fathers, perceived themselves as involved [ 26 ]. We would argue that this again indicates that differences in perceptions of transition readiness depend on contexts, and that it is important to study the specific population in order to offer tailored support.

Another interesting question about concepts that might have influenced our results, is how the participants interpreted responsibility. If a parent asks an adolescent to call and renew a prescription and the adolescent does so, the adolescent will probably feel that they have taken responsibility, but in fact, the parent was the one responsible for checking that the prescription needed to be renewed and arranging for it to be done. The meaning and interpretation of responsibility for different age groups and parents would be interesting for further studies, to get deeper knowledge about how to communicate about and support independent responsibility for adolescents.

As a final remark, we would argue that to meet adolescents’ and parents’ needs for transition during adolescence, HCPs in both child and adult healthcare must have adequate training. The HCPs need to have good knowledge of adolescents’ normal development and be able to use it in relation to the difficulties that can arise if they also have a chronic illness. It is also important that HCPs are willing to bring up and talk about sensitive topics, for example, sex, alcohol, and relationships. Studies show that structured transition programs can increase both adolescents’ and parents’ confidence regarding the transfer to adult care [ 25 ]. This means that introducing a person-centred transition program does not only mean educating patients and parents, but also ensuring that HCPs have adequate knowledge to enable transition in an optimal and positive way.

Methodological considerations

This study is based on an anonymous survey sent out to adolescents with JIA, with encouragement for their parents to respond to the parent version. However, we do not have information on whether the adolescent lived with a single parent or both parents. The anonymous feature of the survey makes it impossible to link an adolescent to his or her parent(s). Some adolescents may therefore have answered without any parent answering the parent questionnaire and vice versa. Consequently, we do not know how the parents of a specific adolescent responded, and we cannot determine if there is agreement between adolescents and their parents on an individual level. However, our findings indicate that the responses at the group level are consistent. There is also a possibility that both parents chose to participate and answered one questionnaire each. This makes it impossible to calculate a correct response rate for parents as well as compare the results from the adolescent’s and parent’s perspectives in the same family. On the other hand, the advantage of anonymity is that respondents hopefully felt confident to give truthful answers.

When asking the parents about age and gender, some of the parents reported their age and some reported the adolescent’s age. The reports of age and gender are therefore not reliable for parents and not used in the analysis. Furthermore, we did not ask about the age of the adolescent in the parent questionnaire. This means we cannot ensure that the parents’ results correspond to the same age distribution among adolescents as the adolescents’ results.

Another limitation is that background information other than gender and age is not present. This means that we do not know what kind of JIA the patient had. It might have been interesting to be able to see if patients with a milder disease are more prepared for transferring to adult care than those who have a more severe disease or contrariwise. It would have been valuable to ascertain the duration of the adolescents' diagnoses, as this factor might influence their level of responsibility for managing their disease and their readiness for transitioning to adult healthcare. Additionally, investigating the impact of various family structures on the adolescents' ability to assume responsibility for their disease would have been insightful. For instance, the presence of multiple siblings within a family could potentially affect this ability. However, such analyses were not possible in this study due to the lack of relevant background information. As described in the method section, the decision was made to exclude the questions about responsibility for health in the questionnaire. In the original, Gilleland and colleagues use healthcare, and in Burström’s translated Swedish questionnaire, the word health is used [ 26 ]. Since we did not conduct cognitive interviews about what adolescents with JIA refer to and include when thinking about health, we assessed it was more scientifically rigorous to exclude the five questions about health. In future studies, it would be interesting to explore this further in cognitive interviews with adolescents, and thereby find out if it is most suitable to ask about health versus healthcare.

In the combined measure of independent responsibility, no distinction was made between the parent being involved sometimes or not at all. The reason for this is that it seems reasonable that parents are sometimes involved in visits to the clinic or talking to the staff, even if the adolescent takes most of the responsibility. The factor analysis and the two latent factors are based on summaries of the scores (1–4) of the items in each factor. Summarizing ordinal data is not optimal but is used here to give a rough picture of the two different factors in this rather small amount of material. In a future larger study, Rasch analysis could be used to develop a validated measurement scale for independent responsibility.

Lastly, we would like to point out that it is difficult to state the results in the sudy are representative of the population concerned since we have no data on JIA subtypes, for example. Moreover, it is probable that the participants who responded are those who felt most concerned or more comfortable with the subject. However, the results in this study based on the rather large sample of 106 adolescents shows strong indications of levels of readiness in this population. In future research stratified sampling could be used to ensure that each subgroup is adequately represented.

Clinical implications

The results from this study can be used as a foundation for structuring a transition program for adolescents with JIA, including tailoring transition care and creating opportunities for HCPs to focus on the parts of the transition that are perceived as challenging by the adolescents.

Based on the findings of the present study, it is evident that HCPs working in paediatric care have to provide the adolescents and their parents with information and knowledge so that they can feel safe when transferring to adult care. To guarantee an optimal transition from paediatric to adult care, it is imperative to comprehend the special needs of each adolescent, and acknowledge cultural and contextual differences. The RTQ can be used as a screening tool to discover individual needs.

The results of this study show that adolescents need more support to feel ready to take responsibility for specific healthcare-related behaviours and transfer to adult care. The results indicated that the healthcare behaviours most difficult to take responsibility for included adolescents having to make direct contact with healthcare. The parents also perceived that this was the area that was most difficult for the adolescents to take responsibility for. It is important to pay attention to possible gender differences as well as contextual and cultural differences. The RTQ may be a relevant tool to screen for individual needs during the transition process. With the results from this study, we can customize, and thus optimize, transitional care in Sweden for adolescents with JIA.

Availability of data and materials

The datasets supporting the conclusions of this article are included within the article.

Abbreviations

Confidence interval

Factor score

Health Care Professionals

Juvenile Idiopathic Arthritis

Readiness for Transition Questionnaire

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Acknowledgements

We would like to thank all the adolescents and parents who took the time to respond to the questionnaires. We would also like to thank the Swedish National Organization for Young Rheumatics for their collaboration.

Open access funding provided by Karolinska Institute. We are grateful for the financial support from the “Swedish Rheumatic Foundation”, “Association of Rheumatology Nurses in Sweden”, “Norrbacka Eugenia Foundation”, “Swedish Foundation for Child Research”, “SveReFo”, “Crown Princess Lovisa’s Foundation”, “Stig Thune Foundation”, “Sällskapet barnavård”, and research grants from Astrid Lindgrens’ Children’s Hospital. The grant providers were not involved in the study design, data collection and analysis, or preparation of the manuscript.

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Department of Women’s and Children’s Health, Karolinska Institutet, Karolinska Vägen 37A, 7 Floor, 171 76, Stockholm, Sweden

A. Vermé, Marika Wenemark, J. Granhagen Jungner, E. Broström & C. Bartholdson

Astrid Lindgren Children’s Hospital, Karolinska University Hospital, Stockholm, Sweden

A. Vermé & C. Bartholdson

Department of Health, Medicine and Caring Sciences, Faculty of Medicine and Health Sciences, Linköping University, Linköping, Sweden

Marika Wenemark

Unit for Public Health and Statistics, East Region, Linköping, Sweden

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Contributions

CB and AV conceived the initial idea for the study and led the study design, ethics approval, data collection, data analysis, and most writing. CB, AV, and MW performed data analysis. All authors (AV, MW, JGJ, EB, CB) discussed the findings, drafted and approved the final manuscript.

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Correspondence to A. Vermé .

Ethics declarations

Ethics approval and consent to participate.

The study complies with the Declaration of Helsinki and was approved by the Swedish Ethical Review Authority Dnr 2019–01540. All the participants received an information letter together with the questionnaire. In this information letter, it was stated that by answering the questionnaire the participants consented to participate in the anonymous study. The information targeting minors, i.e. below 15 years old, was age-adapted and parents received the same information enabling assisting their children to understand the purpose of the study. It was clearly stated that participating in the study by answering the anonymous questionnaire was voluntary and that it did not influence their care under any circumstances.

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Not applicable.

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The authors declare no competing interests.

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Vermé, A., Wenemark, M., Jungner, J.G. et al. Ready to leave? – Adolescents’ and parents’ perceptions of transition from paediatric to adult rheumatology care. BMC Health Serv Res 24 , 795 (2024). https://doi.org/10.1186/s12913-024-11265-9

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Received : 14 May 2024

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Published : 10 July 2024

DOI : https://doi.org/10.1186/s12913-024-11265-9

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