findings and discussion in research paper

How to Write the Discussion Section of a Research Paper

The discussion section of a research paper analyzes and interprets the findings, provides context, compares them with previous studies, identifies limitations, and suggests future research directions.

Updated on September 15, 2023

Structure your discussion section right, and you’ll be cited more often while doing a greater service to the scientific community. So, what actually goes into the discussion section? And how do you write it?

The discussion section of your research paper is where you let the reader know how your study is positioned in the literature, what to take away from your paper, and how your work helps them. It can also include your conclusions and suggestions for future studies.

First, we’ll define all the parts of your discussion paper, and then look into how to write a strong, effective discussion section for your paper or manuscript.

Discussion section: what is it, what it does

The discussion section comes later in your paper, following the introduction, methods, and results. The discussion sets up your study’s conclusions. Its main goals are to present, interpret, and provide a context for your results.

What is it?

The discussion section provides an analysis and interpretation of the findings, compares them with previous studies, identifies limitations, and suggests future directions for research.

This section combines information from the preceding parts of your paper into a coherent story. By this point, the reader already knows why you did your study (introduction), how you did it (methods), and what happened (results). In the discussion, you’ll help the reader connect the ideas from these sections.

Why is it necessary?

The discussion provides context and interpretations for the results. It also answers the questions posed in the introduction. While the results section describes your findings, the discussion explains what they say. This is also where you can describe the impact or implications of your research.

Adds context for your results

Most research studies aim to answer a question, replicate a finding, or address limitations in the literature. These goals are first described in the introduction. However, in the discussion section, the author can refer back to them to explain how the study's objective was achieved. 

Shows what your results actually mean and real-world implications

The discussion can also describe the effect of your findings on research or practice. How are your results significant for readers, other researchers, or policymakers?

What to include in your discussion (in the correct order)

A complete and effective discussion section should at least touch on the points described below.

Summary of key findings

The discussion should begin with a brief factual summary of the results. Concisely overview the main results you obtained.

Begin with key findings with supporting evidence

Your results section described a list of findings, but what message do they send when you look at them all together?

Your findings were detailed in the results section, so there’s no need to repeat them here, but do provide at least a few highlights. This will help refresh the reader’s memory and help them focus on the big picture.

Read the first paragraph of the discussion section in this article (PDF) for an example of how to start this part of your paper. Notice how the authors break down their results and follow each description sentence with an explanation of why each finding is relevant. 

State clearly and concisely

Following a clear and direct writing style is especially important in the discussion section. After all, this is where you will make some of the most impactful points in your paper. While the results section often contains technical vocabulary, such as statistical terms, the discussion section lets you describe your findings more clearly. 

Interpretation of results

Once you’ve given your reader an overview of your results, you need to interpret those results. In other words, what do your results mean? Discuss the findings’ implications and significance in relation to your research question or hypothesis.

Analyze and interpret your findings

Look into your findings and explore what’s behind them or what may have caused them. If your introduction cited theories or studies that could explain your findings, use these sources as a basis to discuss your results.

For example, look at the second paragraph in the discussion section of this article on waggling honey bees. Here, the authors explore their results based on information from the literature.

Unexpected or contradictory results

Sometimes, your findings are not what you expect. Here’s where you describe this and try to find a reason for it. Could it be because of the method you used? Does it have something to do with the variables analyzed? Comparing your methods with those of other similar studies can help with this task.

Context and comparison with previous work

Refer to related studies to place your research in a larger context and the literature. Compare and contrast your findings with existing literature, highlighting similarities, differences, and/or contradictions.

How your work compares or contrasts with previous work

Studies with similar findings to yours can be cited to show the strength of your findings. Information from these studies can also be used to help explain your results. Differences between your findings and others in the literature can also be discussed here. 

How to divide this section into subsections

If you have more than one objective in your study or many key findings, you can dedicate a separate section to each of these. Here’s an example of this approach. You can see that the discussion section is divided into topics and even has a separate heading for each of them. 

Limitations

Many journals require you to include the limitations of your study in the discussion. Even if they don’t, there are good reasons to mention these in your paper.

Why limitations don’t have a negative connotation

A study’s limitations are points to be improved upon in future research. While some of these may be flaws in your method, many may be due to factors you couldn’t predict.

Examples include time constraints or small sample sizes. Pointing this out will help future researchers avoid or address these issues. This part of the discussion can also include any attempts you have made to reduce the impact of these limitations, as in this study .

How limitations add to a researcher's credibility

Pointing out the limitations of your study demonstrates transparency. It also shows that you know your methods well and can conduct a critical assessment of them.  

Implications and significance

The final paragraph of the discussion section should contain the take-home messages for your study. It can also cite the “strong points” of your study, to contrast with the limitations section.

Restate your hypothesis

Remind the reader what your hypothesis was before you conducted the study. 

How was it proven or disproven?

Identify your main findings and describe how they relate to your hypothesis.

How your results contribute to the literature

Were you able to answer your research question? Or address a gap in the literature?

Future implications of your research

Describe the impact that your results may have on the topic of study. Your results may show, for instance, that there are still limitations in the literature for future studies to address. There may be a need for studies that extend your findings in a specific way. You also may need additional research to corroborate your findings. 

Sample discussion section

This fictitious example covers all the aspects discussed above. Your actual discussion section will probably be much longer, but you can read this to get an idea of everything your discussion should cover.

Our results showed that the presence of cats in a household is associated with higher levels of perceived happiness by its human occupants. These findings support our hypothesis and demonstrate the association between pet ownership and well-being. 

The present findings align with those of Bao and Schreer (2016) and Hardie et al. (2023), who observed greater life satisfaction in pet owners relative to non-owners. Although the present study did not directly evaluate life satisfaction, this factor may explain the association between happiness and cat ownership observed in our sample.

Our findings must be interpreted in light of some limitations, such as the focus on cat ownership only rather than pets as a whole. This may limit the generalizability of our results.

Nevertheless, this study had several strengths. These include its strict exclusion criteria and use of a standardized assessment instrument to investigate the relationships between pets and owners. These attributes bolster the accuracy of our results and reduce the influence of confounding factors, increasing the strength of our conclusions. Future studies may examine the factors that mediate the association between pet ownership and happiness to better comprehend this phenomenon.

This brief discussion begins with a quick summary of the results and hypothesis. The next paragraph cites previous research and compares its findings to those of this study. Information from previous studies is also used to help interpret the findings. After discussing the results of the study, some limitations are pointed out. The paper also explains why these limitations may influence the interpretation of results. Then, final conclusions are drawn based on the study, and directions for future research are suggested.

How to make your discussion flow naturally

If you find writing in scientific English challenging, the discussion and conclusions are often the hardest parts of the paper to write. That’s because you’re not just listing up studies, methods, and outcomes. You’re actually expressing your thoughts and interpretations in words.

• How formal should it be?
• What words should you use, or not use?
• How do you meet strict word limits, or make it longer and more informative?

Always give it your best, but sometimes a helping hand can, well, help. Getting a professional edit can help clarify your work’s importance while improving the English used to explain it. When readers know the value of your work, they’ll cite it. We’ll assign your study to an expert editor knowledgeable in your area of research. Their work will clarify your discussion, helping it to tell your story. Find out more about AJE Editing.

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6 Steps to Write an Excellent Discussion in Your Manuscript

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Table of Contents

The discussion section in scientific manuscripts might be the last few paragraphs, but its role goes far beyond wrapping up. It’s the part of an article where scientists talk about what they found and what it means, where raw data turns into meaningful insights. Therefore, discussion is a vital component of the article.  

An excellent discussion is well-organized. We bring to you authors a classic 6-step method for writing discussion sections, with examples to illustrate the functions and specific writing logic of each step. Take a look at how you can impress journal reviewers with a concise and focused discussion section!  

Discussion frame structure   

Conventionally, a discussion section has three parts: an introductory paragraph, a few intermediate paragraphs, and a conclusion¹.  Please follow the steps below:  

1.Introduction—mention gaps in previous research¹⁻ ²

Here, you orient the reader to your study. In the first paragraph, it is advisable to mention the research gap your paper addresses.  

Example: This study investigated the cognitive effects of a meat-only diet on adults. While earlier studies have explored the impact of a carnivorous diet on physical attributes and agility, they have not explicitly addressed its influence on cognitively intense tasks involving memory and reasoning.  

2. Summarizing key findings—let your data speak ¹⁻ ²

After you have laid out the context for your study, recapitulate some of its key findings. Also, highlight key data and evidence supporting these findings.  

Example: We found that risk-taking behavior among teenagers correlates with their tendency to invest in cryptocurrencies. Risk takers in this study, as measured by the Cambridge Gambling Task, tended to have an inordinately higher proportion of their savings invested as crypto coins.  

3. Interpreting results—compare with other papers¹⁻²    

Here, you must analyze and interpret any results concerning the research question or hypothesis. How do the key findings of your study help verify or disprove the hypothesis? What practical relevance does your discovery have?  

Example: Our study suggests that higher daily caffeine intake is not associated with poor performance in major sporting events. Athletes may benefit from the cardiovascular benefits of daily caffeine intake without adversely impacting performance.    

Remember, unlike the results section, the discussion ideally focuses on locating your findings in the larger body of existing research. Hence, compare your results with those of other peer-reviewed papers.  

Example: Although Miller et al. (2020) found evidence of such political bias in a multicultural population, our findings suggest that the bias is weak or virtually non-existent among politically active citizens.  

4. Addressing limitations—their potential impact on the results¹⁻²    

Discuss the potential impact of limitations on the results. Most studies have limitations, and it is crucial to acknowledge them in the intermediary paragraphs of the discussion section. Limitations may include low sample size, suspected interference or noise in data, low effect size, etc.  

Example: This study explored a comprehensive list of adverse effects associated with the novel drug ‘X’. However, long-term studies may be needed to confirm its safety, especially regarding major cardiac events.  

5. Implications for future research—how to explore further¹⁻²    

Locate areas of your research where more investigation is needed. Concluding paragraphs of the discussion can explain what research will likely confirm your results or identify knowledge gaps your study left unaddressed.  

Example: Our study demonstrates that roads paved with the plastic-infused compound ‘Y’ are more resilient than asphalt. Future studies may explore economically feasible ways of producing compound Y in bulk.  

6. Conclusion—summarize content¹⁻²    

A good way to wind up the discussion section is by revisiting the research question mentioned in your introduction. Sign off by expressing the main findings of your study.  

Example: Recent observations suggest that the fish ‘Z’ is moving upriver in many parts of the Amazon basin. Our findings provide conclusive evidence that this phenomenon is associated with rising sea levels and climate change, not due to elevated numbers of invasive predators.  

A rigorous and concise discussion section is one of the keys to achieving an excellent paper. It serves as a critical platform for researchers to interpret and connect their findings with the broader scientific context. By detailing the results, carefully comparing them with existing research, and explaining the limitations of this study, you can effectively help reviewers and readers understand the entire research article more comprehensively and deeply¹⁻² , thereby helping your manuscript to be successfully published and gain wider dissemination.  

In addition to keeping this writing guide, you can also use Elsevier Language Services to improve the quality of your paper more deeply and comprehensively. We have a professional editing team covering multiple disciplines. With our profound disciplinary background and rich polishing experience, we can significantly optimize all paper modules including the discussion, effectively improve the fluency and rigor of your articles, and make your scientific research results consistent, with its value reflected more clearly. We are always committed to ensuring the quality of papers according to the standards of top journals, improving the publishing efficiency of scientific researchers, and helping you on the road to academic success. Check us out here !  

Type in wordcount for Standard Total: USD EUR JPY Follow this link if your manuscript is longer than 12,000 words. Upload  

References:   

• Masic, I. (2018). How to write an efficient discussion? Medical Archives , 72(3), 306. https://doi.org/10.5455/medarh.2018.72.306-307  
• Şanlı, Ö., Erdem, S., & Tefik, T. (2014). How to write a discussion section? Urology Research & Practice , 39(1), 20–24. https://doi.org/10.5152/tud.2013.049  

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The purpose of the discussion section is to interpret and describe the significance of your findings in relation to what was already known about the research problem being investigated and to explain any new understanding or insights that emerged as a result of your research. The discussion will always connect to the introduction by way of the research questions or hypotheses you posed and the literature you reviewed, but the discussion does not simply repeat or rearrange the first parts of your paper; the discussion clearly explains how your study advanced the reader's understanding of the research problem from where you left them at the end of your review of prior research.

Annesley, Thomas M. “The Discussion Section: Your Closing Argument.” Clinical Chemistry 56 (November 2010): 1671-1674; Peacock, Matthew. “Communicative Moves in the Discussion Section of Research Articles.” System 30 (December 2002): 479-497.

Importance of a Good Discussion

The discussion section is often considered the most important part of your research paper because it:

• Most effectively demonstrates your ability as a researcher to think critically about an issue, to develop creative solutions to problems based upon a logical synthesis of the findings, and to formulate a deeper, more profound understanding of the research problem under investigation;
• Presents the underlying meaning of your research, notes possible implications in other areas of study, and explores possible improvements that can be made in order to further develop the concerns of your research;
• Highlights the importance of your study and how it can contribute to understanding the research problem within the field of study;
• Presents how the findings from your study revealed and helped fill gaps in the literature that had not been previously exposed or adequately described; and,
• Engages the reader in thinking critically about issues based on an evidence-based interpretation of findings; it is not governed strictly by objective reporting of information.

Annesley Thomas M. “The Discussion Section: Your Closing Argument.” Clinical Chemistry 56 (November 2010): 1671-1674; Bitchener, John and Helen Basturkmen. “Perceptions of the Difficulties of Postgraduate L2 Thesis Students Writing the Discussion Section.” Journal of English for Academic Purposes 5 (January 2006): 4-18; Kretchmer, Paul. Fourteen Steps to Writing an Effective Discussion Section. San Francisco Edit, 2003-2008.

Structure and Writing Style

I.  General Rules

These are the general rules you should adopt when composing your discussion of the results :

• Do not be verbose or repetitive; be concise and make your points clearly
• Avoid the use of jargon or undefined technical language
• Follow a logical stream of thought; in general, interpret and discuss the significance of your findings in the same sequence you described them in your results section [a notable exception is to begin by highlighting an unexpected result or a finding that can grab the reader's attention]
• Use the present verb tense, especially for established facts; however, refer to specific works or prior studies in the past tense
• If needed, use subheadings to help organize your discussion or to categorize your interpretations into themes

II.  The Content

The content of the discussion section of your paper most often includes :

• Explanation of results : Comment on whether or not the results were expected for each set of findings; go into greater depth to explain findings that were unexpected or especially profound. If appropriate, note any unusual or unanticipated patterns or trends that emerged from your results and explain their meaning in relation to the research problem.
• References to previous research : Either compare your results with the findings from other studies or use the studies to support a claim. This can include re-visiting key sources already cited in your literature review section, or, save them to cite later in the discussion section if they are more important to compare with your results instead of being a part of the general literature review of prior research used to provide context and background information. Note that you can make this decision to highlight specific studies after you have begun writing the discussion section.
• Deduction : A claim for how the results can be applied more generally. For example, describing lessons learned, proposing recommendations that can help improve a situation, or highlighting best practices.
• Hypothesis : A more general claim or possible conclusion arising from the results [which may be proved or disproved in subsequent research]. This can be framed as new research questions that emerged as a consequence of your analysis.

III.  Organization and Structure

Keep the following sequential points in mind as you organize and write the discussion section of your paper:

• Think of your discussion as an inverted pyramid. Organize the discussion from the general to the specific, linking your findings to the literature, then to theory, then to practice [if appropriate].
• Use the same key terms, narrative style, and verb tense [present] that you used when describing the research problem in your introduction.
• Begin by briefly re-stating the research problem you were investigating and answer all of the research questions underpinning the problem that you posed in the introduction.
• Describe the patterns, principles, and relationships shown by each major findings and place them in proper perspective. The sequence of this information is important; first state the answer, then the relevant results, then cite the work of others. If appropriate, refer the reader to a figure or table to help enhance the interpretation of the data [either within the text or as an appendix].
• Regardless of where it's mentioned, a good discussion section includes analysis of any unexpected findings. This part of the discussion should begin with a description of the unanticipated finding, followed by a brief interpretation as to why you believe it appeared and, if necessary, its possible significance in relation to the overall study. If more than one unexpected finding emerged during the study, describe each of them in the order they appeared as you gathered or analyzed the data. As noted, the exception to discussing findings in the same order you described them in the results section would be to begin by highlighting the implications of a particularly unexpected or significant finding that emerged from the study, followed by a discussion of the remaining findings.
• Before concluding the discussion, identify potential limitations and weaknesses if you do not plan to do so in the conclusion of the paper. Comment on their relative importance in relation to your overall interpretation of the results and, if necessary, note how they may affect the validity of your findings. Avoid using an apologetic tone; however, be honest and self-critical [e.g., in retrospect, had you included a particular question in a survey instrument, additional data could have been revealed].
• The discussion section should end with a concise summary of the principal implications of the findings regardless of their significance. Give a brief explanation about why you believe the findings and conclusions of your study are important and how they support broader knowledge or understanding of the research problem. This can be followed by any recommendations for further research. However, do not offer recommendations which could have been easily addressed within the study. This would demonstrate to the reader that you have inadequately examined and interpreted the data.

IV.  Overall Objectives

The objectives of your discussion section should include the following: I.  Reiterate the Research Problem/State the Major Findings

Briefly reiterate the research problem or problems you are investigating and the methods you used to investigate them, then move quickly to describe the major findings of the study. You should write a direct, declarative, and succinct proclamation of the study results, usually in one paragraph.

II.  Explain the Meaning of the Findings and Why They are Important

No one has thought as long and hard about your study as you have. Systematically explain the underlying meaning of your findings and state why you believe they are significant. After reading the discussion section, you want the reader to think critically about the results and why they are important. You don’t want to force the reader to go through the paper multiple times to figure out what it all means. If applicable, begin this part of the section by repeating what you consider to be your most significant or unanticipated finding first, then systematically review each finding. Otherwise, follow the general order you reported the findings presented in the results section.

III.  Relate the Findings to Similar Studies

No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your results to those found in other studies, particularly if questions raised from prior studies served as the motivation for your research. This is important because comparing and contrasting the findings of other studies helps to support the overall importance of your results and it highlights how and in what ways your study differs from other research about the topic. Note that any significant or unanticipated finding is often because there was no prior research to indicate the finding could occur. If there is prior research to indicate this, you need to explain why it was significant or unanticipated. IV.  Consider Alternative Explanations of the Findings

It is important to remember that the purpose of research in the social sciences is to discover and not to prove . When writing the discussion section, you should carefully consider all possible explanations for the study results, rather than just those that fit your hypothesis or prior assumptions and biases. This is especially important when describing the discovery of significant or unanticipated findings.

V.  Acknowledge the Study’s Limitations

It is far better for you to identify and acknowledge your study’s limitations than to have them pointed out by your professor! Note any unanswered questions or issues your study could not address and describe the generalizability of your results to other situations. If a limitation is applicable to the method chosen to gather information, then describe in detail the problems you encountered and why. VI.  Make Suggestions for Further Research

You may choose to conclude the discussion section by making suggestions for further research [as opposed to offering suggestions in the conclusion of your paper]. Although your study can offer important insights about the research problem, this is where you can address other questions related to the problem that remain unanswered or highlight hidden issues that were revealed as a result of conducting your research. You should frame your suggestions by linking the need for further research to the limitations of your study [e.g., in future studies, the survey instrument should include more questions that ask..."] or linking to critical issues revealed from the data that were not considered initially in your research.

NOTE: Besides the literature review section, the preponderance of references to sources is usually found in the discussion section . A few historical references may be helpful for perspective, but most of the references should be relatively recent and included to aid in the interpretation of your results, to support the significance of a finding, and/or to place a finding within a particular context. If a study that you cited does not support your findings, don't ignore it--clearly explain why your research findings differ from theirs.

V.  Problems to Avoid

• Do not waste time restating your results . Should you need to remind the reader of a finding to be discussed, use "bridge sentences" that relate the result to the interpretation. An example would be: “In the case of determining available housing to single women with children in rural areas of Texas, the findings suggest that access to good schools is important...," then move on to further explaining this finding and its implications.
• As noted, recommendations for further research can be included in either the discussion or conclusion of your paper, but do not repeat your recommendations in the both sections. Think about the overall narrative flow of your paper to determine where best to locate this information. However, if your findings raise a lot of new questions or issues, consider including suggestions for further research in the discussion section.
• Do not introduce new results in the discussion section. Be wary of mistaking the reiteration of a specific finding for an interpretation because it may confuse the reader. The description of findings [results section] and the interpretation of their significance [discussion section] should be distinct parts of your paper. If you choose to combine the results section and the discussion section into a single narrative, you must be clear in how you report the information discovered and your own interpretation of each finding. This approach is not recommended if you lack experience writing college-level research papers.
• Use of the first person pronoun is generally acceptable. Using first person singular pronouns can help emphasize a point or illustrate a contrasting finding. However, keep in mind that too much use of the first person can actually distract the reader from the main points [i.e., I know you're telling me this--just tell me!].

Analyzing vs. Summarizing. Department of English Writing Guide. George Mason University; Discussion. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Hess, Dean R. "How to Write an Effective Discussion." Respiratory Care 49 (October 2004); Kretchmer, Paul. Fourteen Steps to Writing to Writing an Effective Discussion Section. San Francisco Edit, 2003-2008; The Lab Report. University College Writing Centre. University of Toronto; Sauaia, A. et al. "The Anatomy of an Article: The Discussion Section: "How Does the Article I Read Today Change What I Will Recommend to my Patients Tomorrow?” The Journal of Trauma and Acute Care Surgery 74 (June 2013): 1599-1602; Research Limitations & Future Research . Lund Research Ltd., 2012; Summary: Using it Wisely. The Writing Center. University of North Carolina; Schafer, Mickey S. Writing the Discussion. Writing in Psychology course syllabus. University of Florida; Yellin, Linda L. A Sociology Writer's Guide . Boston, MA: Allyn and Bacon, 2009.

Writing Tip

Don’t Over-Interpret the Results!

Interpretation is a subjective exercise. As such, you should always approach the selection and interpretation of your findings introspectively and to think critically about the possibility of judgmental biases unintentionally entering into discussions about the significance of your work. With this in mind, be careful that you do not read more into the findings than can be supported by the evidence you have gathered. Remember that the data are the data: nothing more, nothing less.

MacCoun, Robert J. "Biases in the Interpretation and Use of Research Results." Annual Review of Psychology 49 (February 1998): 259-287; Ward, Paulet al, editors. The Oxford Handbook of Expertise . Oxford, UK: Oxford University Press, 2018.

Another Writing Tip

Don't Write Two Results Sections!

One of the most common mistakes that you can make when discussing the results of your study is to present a superficial interpretation of the findings that more or less re-states the results section of your paper. Obviously, you must refer to your results when discussing them, but focus on the interpretation of those results and their significance in relation to the research problem, not the data itself.

Azar, Beth. "Discussing Your Findings."  American Psychological Association gradPSYCH Magazine (January 2006).

Yet Another Writing Tip

Avoid Unwarranted Speculation!

The discussion section should remain focused on the findings of your study. For example, if the purpose of your research was to measure the impact of foreign aid on increasing access to education among disadvantaged children in Bangladesh, it would not be appropriate to speculate about how your findings might apply to populations in other countries without drawing from existing studies to support your claim or if analysis of other countries was not a part of your original research design. If you feel compelled to speculate, do so in the form of describing possible implications or explaining possible impacts. Be certain that you clearly identify your comments as speculation or as a suggestion for where further research is needed. Sometimes your professor will encourage you to expand your discussion of the results in this way, while others don’t care what your opinion is beyond your effort to interpret the data in relation to the research problem.

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Writing a scientific paper.

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Writing a "good" discussion section

"discussion and conclusions checklist" from: how to write a good scientific paper. chris a. mack. spie. 2018., peer review.

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This is is usually the hardest section to write. You are trying to bring out the true meaning of your data without being too long. Do not use words to conceal your facts or reasoning. Also do not repeat your results, this is a discussion.

• Present principles, relationships and generalizations shown by the results
• Point out exceptions or lack of correlations. Define why you think this is so.
• Show how your results agree or disagree with previously published works
• Discuss the theoretical implications of your work as well as practical applications
• State your conclusions clearly. Summarize your evidence for each conclusion.
• Discuss the significance of the results
•  Evidence does not explain itself; the results must be presented and then explained.
• Typical stages in the discussion: summarizing the results, discussing whether results are expected or unexpected, comparing these results to previous work, interpreting and explaining the results (often by comparison to a theory or model), and hypothesizing about their generality.
• Discuss any problems or shortcomings encountered during the course of the work.
• Discuss possible alternate explanations for the results.
• Avoid: presenting results that are never discussed; presenting discussion that does not relate to any of the results; presenting results and discussion in chronological order rather than logical order; ignoring results that do not support the conclusions; drawing conclusions from results without logical arguments to back them up. 

CONCLUSIONS

• Provide a very brief summary of the Results and Discussion.
• Emphasize the implications of the findings, explaining how the work is significant and providing the key message(s) the author wishes to convey.
• Provide the most general claims that can be supported by the evidence.
• Provide a future perspective on the work.
• Avoid: repeating the abstract; repeating background information from the Introduction; introducing new evidence or new arguments not found in the Results and Discussion; repeating the arguments made in the Results and Discussion; failing to address all of the research questions set out in the Introduction. 

WHAT HAPPENS AFTER I COMPLETE MY PAPER?

 The peer review process is the quality control step in the publication of ideas.  Papers that are submitted to a journal for publication are sent out to several scientists (peers) who look carefully at the paper to see if it is "good science".  These reviewers then recommend to the editor of a journal whether or not a paper should be published. Most journals have publication guidelines. Ask for them and follow them exactly.    Peer reviewers examine the soundness of the materials and methods section.  Are the materials and methods used written clearly enough for another scientist to reproduce the experiment?  Other areas they look at are: originality of research, significance of research question studied, soundness of the discussion and interpretation, correct spelling and use of technical terms, and length of the article.

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Guide to Writing the Results and Discussion Sections of a Scientific Article

A quality research paper has both the qualities of in-depth research and good writing ( Bordage, 2001 ). In addition, a research paper must be clear, concise, and effective when presenting the information in an organized structure with a logical manner ( Sandercock, 2013 ).

In this article, we will take a closer look at the results and discussion section. Composing each of these carefully with sufficient data and well-constructed arguments can help improve your paper overall.

The results section of your research paper contains a description about the main findings of your research, whereas the discussion section interprets the results for readers and provides the significance of the findings. The discussion should not repeat the results.

Let’s dive in a little deeper about how to properly, and clearly organize each part.

How to Organize the Results Section

Since your results follow your methods, you’ll want to provide information about what you discovered from the methods you used, such as your research data. In other words, what were the outcomes of the methods you used?

You may also include information about the measurement of your data, variables, treatments, and statistical analyses.

To start, organize your research data based on how important those are in relation to your research questions. This section should focus on showing major results that support or reject your research hypothesis. Include your least important data as supplemental materials when submitting to the journal.

The next step is to prioritize your research data based on importance – focusing heavily on the information that directly relates to your research questions using the subheadings.

The organization of the subheadings for the results section usually mirrors the methods section. It should follow a logical and chronological order.

Subheading organization

Subheadings within your results section are primarily going to detail major findings within each important experiment. And the first paragraph of your results section should be dedicated to your main findings (findings that answer your overall research question and lead to your conclusion) (Hofmann, 2013).

In the book “Writing in the Biological Sciences,” author Angelika Hofmann recommends you structure your results subsection paragraphs as follows:

• Experimental purpose
• Interpretation

Each subheading may contain a combination of ( Bahadoran, 2019 ; Hofmann, 2013, pg. 62-63):

• Text: to explain about the research data
• Figures: to display the research data and to show trends or relationships, for examples using graphs or gel pictures.
• Tables: to represent a large data and exact value

Decide on the best way to present your data — in the form of text, figures or tables (Hofmann, 2013).

Data or Results?

Sometimes we get confused about how to differentiate between data and results . Data are information (facts or numbers) that you collected from your research ( Bahadoran, 2019 ).

Whereas, results are the texts presenting the meaning of your research data ( Bahadoran, 2019 ).

One mistake that some authors often make is to use text to direct the reader to find a specific table or figure without further explanation. This can confuse readers when they interpret data completely different from what the authors had in mind. So, you should briefly explain your data to make your information clear for the readers.

Common Elements in Figures and Tables

Figures and tables present information about your research data visually. The use of these visual elements is necessary so readers can summarize, compare, and interpret large data at a glance. You can use graphs or figures to compare groups or patterns. Whereas, tables are ideal to present large quantities of data and exact values.

Several components are needed to create your figures and tables. These elements are important to sort your data based on groups (or treatments). It will be easier for the readers to see the similarities and differences among the groups.

When presenting your research data in the form of figures and tables, organize your data based on the steps of the research leading you into a conclusion.

Common elements of the figures (Bahadoran, 2019):

• Figure number
• Figure title
• Figure legend (for example a brief title, experimental/statistical information, or definition of symbols).

Tables in the result section may contain several elements (Bahadoran, 2019):

• Table number
• Table title
• Row headings (for example groups)
• Column headings
• Row subheadings (for example categories or groups)
• Column subheadings (for example categories or variables)
• Footnotes (for example statistical analyses)

Tips to Write the Results Section

• Direct the reader to the research data and explain the meaning of the data.
• Avoid using a repetitive sentence structure to explain a new set of data.
• Write and highlight important findings in your results.
• Use the same order as the subheadings of the methods section.
• Match the results with the research questions from the introduction. Your results should answer your research questions.
• Be sure to mention the figures and tables in the body of your text.
• Make sure there is no mismatch between the table number or the figure number in text and in figure/tables.
• Only present data that support the significance of your study. You can provide additional data in tables and figures as supplementary material.

How to Organize the Discussion Section

It’s not enough to use figures and tables in your results section to convince your readers about the importance of your findings. You need to support your results section by providing more explanation in the discussion section about what you found.

In the discussion section, based on your findings, you defend the answers to your research questions and create arguments to support your conclusions.

Below is a list of questions to guide you when organizing the structure of your discussion section ( Viera et al ., 2018 ):

• What experiments did you conduct and what were the results?
• What do the results mean?
• What were the important results from your study?
• How did the results answer your research questions?
• Did your results support your hypothesis or reject your hypothesis?
• What are the variables or factors that might affect your results?
• What were the strengths and limitations of your study?
• What other published works support your findings?
• What other published works contradict your findings?
• What possible factors might cause your findings different from other findings?
• What is the significance of your research?
• What are new research questions to explore based on your findings?

Organizing the Discussion Section

The structure of the discussion section may be different from one paper to another, but it commonly has a beginning, middle-, and end- to the section.

One way to organize the structure of the discussion section is by dividing it into three parts (Ghasemi, 2019):

• The beginning: The first sentence of the first paragraph should state the importance and the new findings of your research. The first paragraph may also include answers to your research questions mentioned in your introduction section.
• The middle: The middle should contain the interpretations of the results to defend your answers, the strength of the study, the limitations of the study, and an update literature review that validates your findings.
• The end: The end concludes the study and the significance of your research.

Another possible way to organize the discussion section was proposed by Michael Docherty in British Medical Journal: is by using this structure ( Docherty, 1999 ):

• Discussion of important findings
• Comparison of your results with other published works
• Include the strengths and limitations of the study
• Conclusion and possible implications of your study, including the significance of your study – address why and how is it meaningful
• Future research questions based on your findings

Finally, a last option is structuring your discussion this way (Hofmann, 2013, pg. 104):

• First Paragraph: Provide an interpretation based on your key findings. Then support your interpretation with evidence.
• Secondary results
• Limitations
• Unexpected findings
• Comparisons to previous publications
• Last Paragraph: The last paragraph should provide a summarization (conclusion) along with detailing the significance, implications and potential next steps.

Remember, at the heart of the discussion section is presenting an interpretation of your major findings.

Tips to Write the Discussion Section

• Highlight the significance of your findings
• Mention how the study will fill a gap in knowledge.
• Indicate the implication of your research.
• Avoid generalizing, misinterpreting your results, drawing a conclusion with no supportive findings from your results.

Aggarwal, R., & Sahni, P. (2018). The Results Section. In Reporting and Publishing Research in the Biomedical Sciences (pp. 21-38): Springer.

Bahadoran, Z., Mirmiran, P., Zadeh-Vakili, A., Hosseinpanah, F., & Ghasemi, A. (2019). The principles of biomedical scientific writing: Results. International journal of endocrinology and metabolism, 17(2).

Bordage, G. (2001). Reasons reviewers reject and accept manuscripts: the strengths and weaknesses in medical education reports. Academic medicine, 76(9), 889-896.

Cals, J. W., & Kotz, D. (2013). Effective writing and publishing scientific papers, part VI: discussion. Journal of clinical epidemiology, 66(10), 1064.

Docherty, M., & Smith, R. (1999). The case for structuring the discussion of scientific papers: Much the same as that for structuring abstracts. In: British Medical Journal Publishing Group.

Faber, J. (2017). Writing scientific manuscripts: most common mistakes. Dental press journal of orthodontics, 22(5), 113-117.

Fletcher, R. H., & Fletcher, S. W. (2018). The discussion section. In Reporting and Publishing Research in the Biomedical Sciences (pp. 39-48): Springer.

Ghasemi, A., Bahadoran, Z., Mirmiran, P., Hosseinpanah, F., Shiva, N., & Zadeh-Vakili, A. (2019). The Principles of Biomedical Scientific Writing: Discussion. International journal of endocrinology and metabolism, 17(3).

Hofmann, A. H. (2013). Writing in the biological sciences: a comprehensive resource for scientific communication . New York: Oxford University Press.

Kotz, D., & Cals, J. W. (2013). Effective writing and publishing scientific papers, part V: results. Journal of clinical epidemiology, 66(9), 945.

Mack, C. (2014). How to Write a Good Scientific Paper: Structure and Organization. Journal of Micro/ Nanolithography, MEMS, and MOEMS, 13. doi:10.1117/1.JMM.13.4.040101

Moore, A. (2016). What's in a Discussion section? Exploiting 2‐dimensionality in the online world…. Bioessays, 38(12), 1185-1185.

Peat, J., Elliott, E., Baur, L., & Keena, V. (2013). Scientific writing: easy when you know how: John Wiley & Sons.

Sandercock, P. M. L. (2012). How to write and publish a scientific article. Canadian Society of Forensic Science Journal, 45(1), 1-5.

Teo, E. K. (2016). Effective Medical Writing: The Write Way to Get Published. Singapore Medical Journal, 57(9), 523-523. doi:10.11622/smedj.2016156

Van Way III, C. W. (2007). Writing a scientific paper. Nutrition in Clinical Practice, 22(6), 636-640.

Vieira, R. F., Lima, R. C. d., & Mizubuti, E. S. G. (2019). How to write the discussion section of a scientific article. Acta Scientiarum. Agronomy, 41.

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How To Write The Discussion Chapter

A Simple Explainer With Examples + Free Template

By: Jenna Crossley (PhD) | Reviewed By: Dr. Eunice Rautenbach | August 2021

If you’re reading this, chances are you’ve reached the discussion chapter of your thesis or dissertation and are looking for a bit of guidance. Well, you’ve come to the right place ! In this post, we’ll unpack and demystify the typical discussion chapter in straightforward, easy to understand language, with loads of examples .

Overview: The Discussion Chapter

• What  the discussion chapter is
• What to include in your discussion
• How to write up your discussion
• A few tips and tricks to help you along the way
• Free discussion template

What (exactly) is the discussion chapter?

The discussion chapter is where you interpret and explain your results within your thesis or dissertation. This contrasts with the results chapter, where you merely present and describe the analysis findings (whether qualitative or quantitative ). In the discussion chapter, you elaborate on and evaluate your research findings, and discuss the significance and implications of your results .

In this chapter, you’ll situate your research findings in terms of your research questions or hypotheses and tie them back to previous studies and literature (which you would have covered in your literature review chapter). You’ll also have a look at how relevant and/or significant your findings are to your field of research, and you’ll argue for the conclusions that you draw from your analysis. Simply put, the discussion chapter is there for you to interact with and explain your research findings in a thorough and coherent manner.

What should I include in the discussion chapter?

First things first: in some studies, the results and discussion chapter are combined into one chapter .  This depends on the type of study you conducted (i.e., the nature of the study and methodology adopted), as well as the standards set by the university.  So, check in with your university regarding their norms and expectations before getting started. In this post, we’ll treat the two chapters as separate, as this is most common.

Basically, your discussion chapter should analyse , explore the meaning and identify the importance of the data you presented in your results chapter. In the discussion chapter, you’ll give your results some form of meaning by evaluating and interpreting them. This will help answer your research questions, achieve your research aims and support your overall conclusion (s). Therefore, you discussion chapter should focus on findings that are directly connected to your research aims and questions. Don’t waste precious time and word count on findings that are not central to the purpose of your research project.

As this chapter is a reflection of your results chapter, it’s vital that you don’t report any new findings . In other words, you can’t present claims here if you didn’t present the relevant data in the results chapter first.  So, make sure that for every discussion point you raise in this chapter, you’ve covered the respective data analysis in the results chapter. If you haven’t, you’ll need to go back and adjust your results chapter accordingly.

If you’re struggling to get started, try writing down a bullet point list everything you found in your results chapter. From this, you can make a list of everything you need to cover in your discussion chapter. Also, make sure you revisit your research questions or hypotheses and incorporate the relevant discussion to address these.  This will also help you to see how you can structure your chapter logically.

Need a helping hand?

How to write the discussion chapter

Now that you’ve got a clear idea of what the discussion chapter is and what it needs to include, let’s look at how you can go about structuring this critically important chapter. Broadly speaking, there are six core components that need to be included, and these can be treated as steps in the chapter writing process.

Step 1: Restate your research problem and research questions

The first step in writing up your discussion chapter is to remind your reader of your research problem , as well as your research aim(s) and research questions . If you have hypotheses, you can also briefly mention these. This “reminder” is very important because, after reading dozens of pages, the reader may have forgotten the original point of your research or been swayed in another direction. It’s also likely that some readers skip straight to your discussion chapter from the introduction chapter , so make sure that your research aims and research questions are clear.

Step 2: Summarise your key findings

Next, you’ll want to summarise your key findings from your results chapter. This may look different for qualitative and quantitative research , where qualitative research may report on themes and relationships, whereas quantitative research may touch on correlations and causal relationships. Regardless of the methodology, in this section you need to highlight the overall key findings in relation to your research questions.

Typically, this section only requires one or two paragraphs , depending on how many research questions you have. Aim to be concise here, as you will unpack these findings in more detail later in the chapter. For now, a few lines that directly address your research questions are all that you need.

Some examples of the kind of language you’d use here include:

• The data suggest that…
• The data support/oppose the theory that…
• The analysis identifies…

These are purely examples. What you present here will be completely dependent on your original research questions, so make sure that you are led by them .

Step 3: Interpret your results

Once you’ve restated your research problem and research question(s) and briefly presented your key findings, you can unpack your findings by interpreting your results. Remember: only include what you reported in your results section – don’t introduce new information.

From a structural perspective, it can be a wise approach to follow a similar structure in this chapter as you did in your results chapter. This would help improve readability and make it easier for your reader to follow your arguments. For example, if you structured you results discussion by qualitative themes, it may make sense to do the same here.

Alternatively, you may structure this chapter by research questions, or based on an overarching theoretical framework that your study revolved around. Every study is different, so you’ll need to assess what structure works best for you.

When interpreting your results, you’ll want to assess how your findings compare to those of the existing research (from your literature review chapter). Even if your findings contrast with the existing research, you need to include these in your discussion. In fact, those contrasts are often the most interesting findings . In this case, you’d want to think about why you didn’t find what you were expecting in your data and what the significance of this contrast is.

Here are a few questions to help guide your discussion:

• How do your results relate with those of previous studies ?
• If you get results that differ from those of previous studies, why may this be the case?
• What do your results contribute to your field of research?
• What other explanations could there be for your findings?

When interpreting your findings, be careful not to draw conclusions that aren’t substantiated . Every claim you make needs to be backed up with evidence or findings from the data (and that data needs to be presented in the previous chapter – results). This can look different for different studies; qualitative data may require quotes as evidence, whereas quantitative data would use statistical methods and tests. Whatever the case, every claim you make needs to be strongly backed up.

Step 4: Acknowledge the limitations of your study

The fourth step in writing up your discussion chapter is to acknowledge the limitations of the study. These limitations can cover any part of your study , from the scope or theoretical basis to the analysis method(s) or sample. For example, you may find that you collected data from a very small sample with unique characteristics, which would mean that you are unable to generalise your results to the broader population.

For some students, discussing the limitations of their work can feel a little bit self-defeating . This is a misconception, as a core indicator of high-quality research is its ability to accurately identify its weaknesses. In other words, accurately stating the limitations of your work is a strength, not a weakness . All that said, be careful not to undermine your own research. Tell the reader what limitations exist and what improvements could be made, but also remind them of the value of your study despite its limitations.

Step 5: Make recommendations for implementation and future research

Now that you’ve unpacked your findings and acknowledge the limitations thereof, the next thing you’ll need to do is reflect on your study in terms of two factors:

• The practical application of your findings
• Suggestions for future research

The first thing to discuss is how your findings can be used in the real world – in other words, what contribution can they make to the field or industry? Where are these contributions applicable, how and why? For example, if your research is on communication in health settings, in what ways can your findings be applied to the context of a hospital or medical clinic? Make sure that you spell this out for your reader in practical terms, but also be realistic and make sure that any applications are feasible.

The next discussion point is the opportunity for future research . In other words, how can other studies build on what you’ve found and also improve the findings by overcoming some of the limitations in your study (which you discussed a little earlier). In doing this, you’ll want to investigate whether your results fit in with findings of previous research, and if not, why this may be the case. For example, are there any factors that you didn’t consider in your study? What future research can be done to remedy this? When you write up your suggestions, make sure that you don’t just say that more research is needed on the topic, also comment on how the research can build on your study.

Step 6: Provide a concluding summary

Finally, you’ve reached your final stretch. In this section, you’ll want to provide a brief recap of the key findings – in other words, the findings that directly address your research questions . Basically, your conclusion should tell the reader what your study has found, and what they need to take away from reading your report.

When writing up your concluding summary, bear in mind that some readers may skip straight to this section from the beginning of the chapter.  So, make sure that this section flows well from and has a strong connection to the opening section of the chapter.

Tips and tricks for an A-grade discussion chapter

Now that you know what the discussion chapter is , what to include and exclude , and how to structure it , here are some tips and suggestions to help you craft a quality discussion chapter.

• When you write up your discussion chapter, make sure that you keep it consistent with your introduction chapter , as some readers will skip from the introduction chapter directly to the discussion chapter. Your discussion should use the same tense as your introduction, and it should also make use of the same key terms.
• Don’t make assumptions about your readers. As a writer, you have hands-on experience with the data and so it can be easy to present it in an over-simplified manner. Make sure that you spell out your findings and interpretations for the intelligent layman.
• Have a look at other theses and dissertations from your institution, especially the discussion sections. This will help you to understand the standards and conventions of your university, and you’ll also get a good idea of how others have structured their discussion chapters. You can also check out our chapter template .
• Avoid using absolute terms such as “These results prove that…”, rather make use of terms such as “suggest” or “indicate”, where you could say, “These results suggest that…” or “These results indicate…”. It is highly unlikely that a dissertation or thesis will scientifically prove something (due to a variety of resource constraints), so be humble in your language.
• Use well-structured and consistently formatted headings to ensure that your reader can easily navigate between sections, and so that your chapter flows logically and coherently.

If you have any questions or thoughts regarding this post, feel free to leave a comment below. Also, if you’re looking for one-on-one help with your discussion chapter (or thesis in general), consider booking a free consultation with one of our highly experienced Grad Coaches to discuss how we can help you.

Psst... there’s more!

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

38 Comments

Thank you this is helpful!

This is very helpful to me… Thanks a lot for sharing this with us 😊

This has been very helpful indeed. Thank you.

This is actually really helpful, I just stumbled upon it. Very happy that I found it, thank you.

Me too! I was kinda lost on how to approach my discussion chapter. How helpful! Thanks a lot!

This is really good and explicit. Thanks

Thank you, this blog has been such a help.

Thank you. This is very helpful.

Dear sir/madame

Thanks a lot for this helpful blog. Really, it supported me in writing my discussion chapter while I was totally unaware about its structure and method of writing.

With regards

Syed Firoz Ahmad PhD, Research Scholar

I agree so much. This blog was god sent. It assisted me so much while I was totally clueless about the context and the know-how. Now I am fully aware of what I am to do and how I am to do it.

Thanks! This is helpful!

thanks alot for this informative website

Dear Sir/Madam,

Truly, your article was much benefited when i structured my discussion chapter.

Thank you very much!!!

This is helpful for me in writing my research discussion component. I have to copy this text on Microsoft word cause of my weakness that I cannot be able to read the text on screen a long time. So many thanks for this articles.

This was helpful

Thanks Jenna, well explained.

Thank you! This is super helpful.

Thanks very much. I have appreciated the six steps on writing the Discussion chapter which are (i) Restating the research problem and questions (ii) Summarising the key findings (iii) Interpreting the results linked to relating to previous results in positive and negative ways; explaining whay different or same and contribution to field of research and expalnation of findings (iv) Acknowledgeing limitations (v) Recommendations for implementation and future resaerch and finally (vi) Providing a conscluding summary

My two questions are: 1. On step 1 and 2 can it be the overall or you restate and sumamrise on each findings based on the reaerch question? 2. On 4 and 5 do you do the acknowlledgement , recommendations on each research finding or overall. This is not clear from your expalanattion.

Please respond.

This post is very useful. I’m wondering whether practical implications must be introduced in the Discussion section or in the Conclusion section?

This is very instructive and educative

Sigh, I never knew a 20 min video could have literally save my life like this. I found this at the right time!!!! Everything I need to know in one video thanks a mil ! OMGG and that 6 step!!!!!! was the cherry on top the cake!!!!!!!!!

Thanks alot.., I have gained much

This piece is very helpful on how to go about my discussion section. I can always recommend GradCoach research guides for colleagues.

Many thanks for this resource. It has been very helpful to me. I was finding it hard to even write the first sentence. Much appreciated.

Thanks so much. Very helpful to know what is included in the discussion section

this was a very helpful and useful information

This is very helpful. Very very helpful. Thanks for sharing this online!

it is very helpfull article, and i will recommend it to my fellow students. Thank you.

Superlative! More grease to your elbows.

Powerful, thank you for sharing.

Wow! Just wow! God bless the day I stumbled upon you guys’ YouTube videos! It’s been truly life changing and anxiety about my report that is due in less than a month has subsided significantly!

Simplified explanation. Well done.

The presentation is enlightening. Thank you very much.

Thanks for the support and guidance

This has been a great help to me and thank you do much

I second that “it is highly unlikely that a dissertation or thesis will scientifically prove something”; although, could you enlighten us on that comment and elaborate more please?

Sure, no problem.

Scientific proof is generally considered a very strong assertion that something is definitively and universally true. In most scientific disciplines, especially within the realms of natural and social sciences, absolute proof is very rare. Instead, researchers aim to provide evidence that supports or rejects hypotheses. This evidence increases or decreases the likelihood that a particular theory is correct, but it rarely proves something in the absolute sense.

Dissertations and theses, as substantial as they are, typically focus on exploring a specific question or problem within a larger field of study. They contribute to a broader conversation and body of knowledge. The aim is often to provide detailed insight, extend understanding, and suggest directions for further research rather than to offer definitive proof. These academic works are part of a cumulative process of knowledge building where each piece of research connects with others to gradually enhance our understanding of complex phenomena.

Furthermore, the rigorous nature of scientific inquiry involves continuous testing, validation, and potential refutation of ideas. What might be considered a “proof” at one point can later be challenged by new evidence or alternative interpretations. Therefore, the language of “proof” is cautiously used in academic circles to maintain scientific integrity and humility.

This was very helpful, thank you!

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Organizing Academic Research Papers: 8. The Discussion

• Purpose of Guide
• Design Flaws to Avoid
• Glossary of Research Terms
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• Executive Summary
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tertiary Sources
• What Is Scholarly vs. Popular?
• Qualitative Methods
• Quantitative Methods
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Annotated Bibliography
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• How to Manage Group Projects
• Multiple Book Review Essay
• Reviewing Collected Essays
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Research Proposal
• Acknowledgements

The purpose of the discussion is to interpret and describe the significance of your findings in light of what was already known about the research problem being investigated, and to explain any new understanding or fresh insights about the problem after you've taken the findings into consideration. The discussion will always connect to the introduction by way of the research questions or hypotheses you posed and the literature you reviewed, but it does not simply repeat or rearrange the introduction; the discussion should always explain how your study has moved the reader's understanding of the research problem forward from where you left them at the end of the introduction.

Importance of a Good Discussion

This section is often considered the most important part of a research paper because it most effectively demonstrates your ability as a researcher to think critically about an issue, to develop creative solutions to problems based on the findings, and to formulate a deeper, more profound understanding of the research problem you are studying.

The discussion section is where you explore the underlying meaning of your research , its possible implications in other areas of study, and the possible improvements that can be made in order to further develop the concerns of your research.

This is the section where you need to present the importance of your study and how it may be able to contribute to and/or fill existing gaps in the field. If appropriate, the discussion section is also where you state how the findings from your study revealed new gaps in the literature that had not been previously exposed or adequately described.

This part of the paper is not strictly governed by objective reporting of information but, rather, it is where you can engage in creative thinking about issues through evidence-based interpretation of findings. This is where you infuse your results with meaning.

Kretchmer, Paul. Fourteen Steps to Writing to Writing an Effective Discussion Section . San Francisco Edit, 2003-2008.

Structure and Writing Style

I.  General Rules

These are the general rules you should adopt when composing your discussion of the results :

• Do not be verbose or repetitive.
• Be concise and make your points clearly.
• Avoid using jargon.
• Follow a logical stream of thought.
• Use the present verb tense, especially for established facts; however, refer to specific works and references in the past tense.
• If needed, use subheadings to help organize your presentation or to group your interpretations into themes.

II.  The Content

The content of the discussion section of your paper most often includes :

• Explanation of results : comment on whether or not the results were expected and present explanations for the results; go into greater depth when explaining findings that were unexpected or especially profound. If appropriate, note any unusual or unanticipated patterns or trends that emerged from your results and explain their meaning.
• References to previous research : compare your results with the findings from other studies, or use the studies to support a claim. This can include re-visiting key sources already cited in your literature review section, or, save them to cite later in the discussion section if they are more important to compare with your results than being part of the general research you cited to provide context and background information.
• Deduction : a claim for how the results can be applied more generally. For example, describing lessons learned, proposing recommendations that can help improve a situation, or recommending best practices.
• Hypothesis : a more general claim or possible conclusion arising from the results [which may be proved or disproved in subsequent research].

III. Organization and Structure

Keep the following sequential points in mind as you organize and write the discussion section of your paper:

• Think of your discussion as an inverted pyramid. Organize the discussion from the general to the specific, linking your findings to the literature, then to theory, then to practice [if appropriate].
• Use the same key terms, mode of narration, and verb tense [present] that you used when when describing the research problem in the introduction.
• Begin by briefly re-stating the research problem you were investigating and answer all of the research questions underpinning the problem that you posed in the introduction.
• Describe the patterns, principles, and relationships shown by each major findings and place them in proper perspective. The sequencing of providing this information is important; first state the answer, then the relevant results, then cite the work of others. If appropriate, refer the reader to a figure or table to help enhance the interpretation of the data. The order of interpreting each major finding should be in the same order as they were described in your results section.
• A good discussion section includes analysis of any unexpected findings. This paragraph should begin with a description of the unexpected finding, followed by a brief interpretation as to why you believe it appeared and, if necessary, its possible significance in relation to the overall study. If more than one unexpected finding emerged during the study, describe each them in the order they appeared as you gathered the data.
• Before concluding the discussion, identify potential limitations and weaknesses. Comment on their relative importance in relation to your overall interpretation of the results and, if necessary, note how they may affect the validity of the findings. Avoid using an apologetic tone; however, be honest and self-critical.
• The discussion section should end with a concise summary of the principal implications of the findings regardless of statistical significance. Give a brief explanation about why you believe the findings and conclusions of your study are important and how they support broader knowledge or understanding of the research problem. This can be followed by any recommendations for further research. However, do not offer recommendations which could have been easily addressed within the study. This demonstrates to the reader you have inadequately examined and interpreted the data.

IV.  Overall Objectives

The objectives of your discussion section should include the following: I.  Reiterate the Research Problem/State the Major Findings

Briefly reiterate for your readers the research problem or problems you are investigating and the methods you used to investigate them, then move quickly to describe the major findings of the study. You should write a direct, declarative, and succinct proclamation of the study results.

II.  Explain the Meaning of the Findings and Why They are Important

No one has thought as long and hard about your study as you have. Systematically explain the meaning of the findings and why you believe they are important. After reading the discussion section, you want the reader to think about the results [“why hadn’t I thought of that?”]. You don’t want to force the reader to go through the paper multiple times to figure out what it all means. Begin this part of the section by repeating what you consider to be your most important finding first.

III.  Relate the Findings to Similar Studies

No study is so novel or possesses such a restricted focus that it has absolutely no relation to other previously published research. The discussion section should relate your study findings to those of other studies, particularly if questions raised by previous studies served as the motivation for your study, the findings of other studies support your findings [which strengthens the importance of your study results], and/or they point out how your study differs from other similar studies. IV.  Consider Alternative Explanations of the Findings

It is important to remember that the purpose of research is to discover and not to prove . When writing the discussion section, you should carefully consider all possible explanations for the study results, rather than just those that fit your prior assumptions or biases.

V.  Acknowledge the Study’s Limitations

It is far better for you to identify and acknowledge your study’s limitations than to have them pointed out by your professor! Describe the generalizability of your results to other situations, if applicable to the method chosen, then describe in detail problems you encountered in the method(s) you used to gather information. Note any unanswered questions or issues your study did not address, and.... VI.  Make Suggestions for Further Research

Although your study may offer important insights about the research problem, other questions related to the problem likely remain unanswered. Moreover, some unanswered questions may have become more focused because of your study. You should make suggestions for further research in the discussion section.

NOTE: Besides the literature review section, the preponderance of references to sources in your research paper are usually found in the discussion section . A few historical references may be helpful for perspective but most of the references should be relatively recent and included to aid in the interpretation of your results and/or linked to similar studies. If a study that you cited disagrees with your findings, don't ignore it--clearly explain why the study's findings differ from yours.

V.  Problems to Avoid

• Do not waste entire sentences restating your results . Should you need to remind the reader of the finding to be discussed, use "bridge sentences" that relate the result to the interpretation. An example would be: “The lack of available housing to single women with children in rural areas of Texas suggests that...[then move to the interpretation of this finding].”
• Recommendations for further research can be included in either the discussion or conclusion of your paper but do not repeat your recommendations in the both sections.
• Do not introduce new results in the discussion. Be wary of mistaking the reiteration of a specific finding for an interpretation.
• Use of the first person is acceptable, but too much use of the first person may actually distract the reader from the main points.

Analyzing vs. Summarizing. Department of English Writing Guide. George Mason University; Discussion . The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Hess, Dean R. How to Write an Effective Discussion. Respiratory Care 49 (October 2004); Kretchmer, Paul. Fourteen Steps to Writing to Writing an Effective Discussion Section . San Francisco Edit, 2003-2008; The Lab Report . University College Writing Centre. University of Toronto; Summary: Using it Wisely . The Writing Center. University of North Carolina; Schafer, Mickey S. Writing the Discussion . Writing in Psychology course syllabus. University of Florida; Yellin, Linda L. A Sociology Writer's Guide. Boston, MA: Allyn and Bacon, 2009.

Writing Tip

Don’t Overinterpret the Results!

Interpretation is a subjective exercise. Therefore, be careful that you do not read more into the findings than can be supported by the evidence you've gathered. Remember that the data are the data: nothing more, nothing less.

Another Writing Tip

Don't Write Two Results Sections!

One of the most common mistakes that you can make when discussing the results of your study is to present a superficial interpretation of the findings that more or less re-states the results section of your paper. Obviously, you must refer to your results when discussing them, but focus on the interpretion of those results, not just the data itself.

Azar, Beth. Discussing Your Findings.  American Psychological Association gradPSYCH Magazine (January 2006)

Yet Another Writing Tip

Avoid Unwarranted Speculation!

The discussion section should remain focused on the findings of your study. For example, if you studied the impact of foreign aid on increasing levels of education among the poor in Bangladesh, it's generally not appropriate to speculate about how your findings might apply to populations in other countries without drawing from existing studies to support your claim. If you feel compelled to speculate, be certain that you clearly identify your comments as speculation or as a suggestion for where further research is needed. Sometimes your professor will encourage you to expand the discussion in this way, while others don’t care what your opinion is beyond your efforts to interpret the data.

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• How to write an APA results section

Reporting Research Results in APA Style | Tips & Examples

Published on December 21, 2020 by Pritha Bhandari . Revised on January 17, 2024.

The results section of a quantitative research paper is where you summarize your data and report the findings of any relevant statistical analyses.

The APA manual provides rigorous guidelines for what to report in quantitative research papers in the fields of psychology, education, and other social sciences.

Use these standards to answer your research questions and report your data analyses in a complete and transparent way.

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Table of contents

What goes in your results section, introduce your data, summarize your data, report statistical results, presenting numbers effectively, what doesn’t belong in your results section, frequently asked questions about results in apa.

In APA style, the results section includes preliminary information about the participants and data, descriptive and inferential statistics, and the results of any exploratory analyses.

Include these in your results section:

• Participant flow and recruitment period. Report the number of participants at every stage of the study, as well as the dates when recruitment took place.
• Missing data . Identify the proportion of data that wasn’t included in your final analysis and state the reasons.
• Any adverse events. Make sure to report any unexpected events or side effects (for clinical studies).
• Descriptive statistics . Summarize the primary and secondary outcomes of the study.
• Inferential statistics , including confidence intervals and effect sizes. Address the primary and secondary research questions by reporting the detailed results of your main analyses.
• Results of subgroup or exploratory analyses, if applicable. Place detailed results in supplementary materials.

Write up the results in the past tense because you’re describing the outcomes of a completed research study.

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Before diving into your research findings, first describe the flow of participants at every stage of your study and whether any data were excluded from the final analysis.

Participant flow and recruitment period

It’s necessary to report any attrition, which is the decline in participants at every sequential stage of a study. That’s because an uneven number of participants across groups sometimes threatens internal validity and makes it difficult to compare groups. Be sure to also state all reasons for attrition.

If your study has multiple stages (e.g., pre-test, intervention, and post-test) and groups (e.g., experimental and control groups), a flow chart is the best way to report the number of participants in each group per stage and reasons for attrition.

Also report the dates for when you recruited participants or performed follow-up sessions.

Missing data

Another key issue is the completeness of your dataset. It’s necessary to report both the amount and reasons for data that was missing or excluded.

Data can become unusable due to equipment malfunctions, improper storage, unexpected events, participant ineligibility, and so on. For each case, state the reason why the data were unusable.

Some data points may be removed from the final analysis because they are outliers—but you must be able to justify how you decided what to exclude.

If you applied any techniques for overcoming or compensating for lost data, report those as well.

Adverse events

For clinical studies, report all events with serious consequences or any side effects that occured.

Descriptive statistics summarize your data for the reader. Present descriptive statistics for each primary, secondary, and subgroup analysis.

Don’t provide formulas or citations for commonly used statistics (e.g., standard deviation) – but do provide them for new or rare equations.

Descriptive statistics

The exact descriptive statistics that you report depends on the types of data in your study. Categorical variables can be reported using proportions, while quantitative data can be reported using means and standard deviations . For a large set of numbers, a table is the most effective presentation format.

Include sample sizes (overall and for each group) as well as appropriate measures of central tendency and variability for the outcomes in your results section. For every point estimate , add a clearly labelled measure of variability as well.

Be sure to note how you combined data to come up with variables of interest. For every variable of interest, explain how you operationalized it.

According to APA journal standards, it’s necessary to report all relevant hypothesis tests performed, estimates of effect sizes, and confidence intervals.

When reporting statistical results, you should first address primary research questions before moving onto secondary research questions and any exploratory or subgroup analyses.

Present the results of tests in the order that you performed them—report the outcomes of main tests before post-hoc tests, for example. Don’t leave out any relevant results, even if they don’t support your hypothesis.

Inferential statistics

For each statistical test performed, first restate the hypothesis , then state whether your hypothesis was supported and provide the outcomes that led you to that conclusion.

Report the following for each hypothesis test:

• the test statistic value,
• the degrees of freedom ,
• the exact p- value (unless it is less than 0.001),
• the magnitude and direction of the effect.

When reporting complex data analyses, such as factor analysis or multivariate analysis, present the models estimated in detail, and state the statistical software used. Make sure to report any violations of statistical assumptions or problems with estimation.

Effect sizes and confidence intervals

For each hypothesis test performed, you should present confidence intervals and estimates of effect sizes .

Confidence intervals are useful for showing the variability around point estimates. They should be included whenever you report population parameter estimates.

Effect sizes indicate how impactful the outcomes of a study are. But since they are estimates, it’s recommended that you also provide confidence intervals of effect sizes.

Subgroup or exploratory analyses

Briefly report the results of any other planned or exploratory analyses you performed. These may include subgroup analyses as well.

Subgroup analyses come with a high chance of false positive results, because performing a large number of comparison or correlation tests increases the chances of finding significant results.

If you find significant results in these analyses, make sure to appropriately report them as exploratory (rather than confirmatory) results to avoid overstating their importance.

While these analyses can be reported in less detail in the main text, you can provide the full analyses in supplementary materials.

To effectively present numbers, use a mix of text, tables , and figures where appropriate:

• To present three or fewer numbers, try a sentence ,
• To present between 4 and 20 numbers, try a table ,
• To present more than 20 numbers, try a figure .

Since these are general guidelines, use your own judgment and feedback from others for effective presentation of numbers.

Tables and figures should be numbered and have titles, along with relevant notes. Make sure to present data only once throughout the paper and refer to any tables and figures in the text.

Formatting statistics and numbers

It’s important to follow capitalization , italicization, and abbreviation rules when referring to statistics in your paper. There are specific format guidelines for reporting statistics in APA , as well as general rules about writing numbers .

If you are unsure of how to present specific symbols, look up the detailed APA guidelines or other papers in your field.

It’s important to provide a complete picture of your data analyses and outcomes in a concise way. For that reason, raw data and any interpretations of your results are not included in the results section.

It’s rarely appropriate to include raw data in your results section. Instead, you should always save the raw data securely and make them available and accessible to any other researchers who request them.

Making scientific research available to others is a key part of academic integrity and open science.

Interpretation or discussion of results

This belongs in your discussion section. Your results section is where you objectively report all relevant findings and leave them open for interpretation by readers.

While you should state whether the findings of statistical tests lend support to your hypotheses, refrain from forming conclusions to your research questions in the results section.

Explanation of how statistics tests work

For the sake of concise writing, you can safely assume that readers of your paper have professional knowledge of how statistical inferences work.

In an APA results section , you should generally report the following:

• Participant flow and recruitment period.
• Missing data and any adverse events.
• Descriptive statistics about your samples.
• Inferential statistics , including confidence intervals and effect sizes.
• Results of any subgroup or exploratory analyses, if applicable.

According to the APA guidelines, you should report enough detail on inferential statistics so that your readers understand your analyses.

• the test statistic value
• the degrees of freedom
• the exact p value (unless it is less than 0.001)
• the magnitude and direction of the effect

You should also present confidence intervals and estimates of effect sizes where relevant.

In APA style, statistics can be presented in the main text or as tables or figures . To decide how to present numbers, you can follow APA guidelines:

• To present three or fewer numbers, try a sentence,
• To present between 4 and 20 numbers, try a table,
• To present more than 20 numbers, try a figure.

Results are usually written in the past tense , because they are describing the outcome of completed actions.

The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.

In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.

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• How to Write a Discussion Section | Tips & Examples

How to Write a Discussion Section | Tips & Examples

Published on 21 August 2022 by Shona McCombes . Revised on 25 October 2022.

The discussion section is where you delve into the meaning, importance, and relevance of your results .

It should focus on explaining and evaluating what you found, showing how it relates to your literature review , and making an argument in support of your overall conclusion . It should not be a second results section .

There are different ways to write this section, but you can focus your writing around these key elements:

• Summary: A brief recap of your key results
• Interpretations: What do your results mean?
• Implications: Why do your results matter?
• Limitations: What can’t your results tell us?
• Recommendations: Avenues for further studies or analyses

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What not to include in your discussion section, step 1: summarise your key findings, step 2: give your interpretations, step 3: discuss the implications, step 4: acknowledge the limitations, step 5: share your recommendations, discussion section example.

There are a few common mistakes to avoid when writing the discussion section of your paper.

• Don’t introduce new results: You should only discuss the data that you have already reported in your results section .
• Don’t make inflated claims: Avoid overinterpretation and speculation that isn’t directly supported by your data.
• Don’t undermine your research: The discussion of limitations should aim to strengthen your credibility, not emphasise weaknesses or failures.

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Start this section by reiterating your research problem  and concisely summarising your major findings. Don’t just repeat all the data you have already reported – aim for a clear statement of the overall result that directly answers your main  research question . This should be no more than one paragraph.

Many students struggle with the differences between a discussion section and a results section . The crux of the matter is that your results sections should present your results, and your discussion section should subjectively evaluate them. Try not to blend elements of these two sections, in order to keep your paper sharp.

• The results indicate that …
• The study demonstrates a correlation between …
• This analysis supports the theory that …
• The data suggest  that …

The meaning of your results may seem obvious to you, but it’s important to spell out their significance for your reader, showing exactly how they answer your research question.

The form of your interpretations will depend on the type of research, but some typical approaches to interpreting the data include:

• Identifying correlations , patterns, and relationships among the data
• Discussing whether the results met your expectations or supported your hypotheses
• Contextualising your findings within previous research and theory
• Explaining unexpected results and evaluating their significance
• Considering possible alternative explanations and making an argument for your position

You can organise your discussion around key themes, hypotheses, or research questions, following the same structure as your results section. Alternatively, you can also begin by highlighting the most significant or unexpected results.

• In line with the hypothesis …
• Contrary to the hypothesised association …
• The results contradict the claims of Smith (2007) that …
• The results might suggest that x . However, based on the findings of similar studies, a more plausible explanation is x .

As well as giving your own interpretations, make sure to relate your results back to the scholarly work that you surveyed in the literature review . The discussion should show how your findings fit with existing knowledge, what new insights they contribute, and what consequences they have for theory or practice.

Ask yourself these questions:

• Do your results support or challenge existing theories? If they support existing theories, what new information do they contribute? If they challenge existing theories, why do you think that is?
• Are there any practical implications?

Your overall aim is to show the reader exactly what your research has contributed, and why they should care.

• These results build on existing evidence of …
• The results do not fit with the theory that …
• The experiment provides a new insight into the relationship between …
• These results should be taken into account when considering how to …
• The data contribute a clearer understanding of …
• While previous research has focused on  x , these results demonstrate that y .

Even the best research has its limitations. Acknowledging these is important to demonstrate your credibility. Limitations aren’t about listing your errors, but about providing an accurate picture of what can and cannot be concluded from your study.

Limitations might be due to your overall research design, specific methodological choices , or unanticipated obstacles that emerged during your research process.

Here are a few common possibilities:

• If your sample size was small or limited to a specific group of people, explain how generalisability is limited.
• If you encountered problems when gathering or analysing data, explain how these influenced the results.
• If there are potential confounding variables that you were unable to control, acknowledge the effect these may have had.

After noting the limitations, you can reiterate why the results are nonetheless valid for the purpose of answering your research question.

• The generalisability of the results is limited by …
• The reliability of these data is impacted by …
• Due to the lack of data on x , the results cannot confirm …
• The methodological choices were constrained by …
• It is beyond the scope of this study to …

Based on the discussion of your results, you can make recommendations for practical implementation or further research. Sometimes, the recommendations are saved for the conclusion .

Suggestions for further research can lead directly from the limitations. Don’t just state that more studies should be done – give concrete ideas for how future work can build on areas that your own research was unable to address.

• Further research is needed to establish …
• Future studies should take into account …
• Avenues for future research include …

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How to Write the Results/Findings Section in Research

What is the research paper Results section and what does it do?

The Results section of a scientific research paper represents the core findings of a study derived from the methods applied to gather and analyze information. It presents these findings in a logical sequence without bias or interpretation from the author, setting up the reader for later interpretation and evaluation in the Discussion section. A major purpose of the Results section is to break down the data into sentences that show its significance to the research question(s).

The Results section appears third in the section sequence in most scientific papers. It follows the presentation of the Methods and Materials and is presented before the Discussion section —although the Results and Discussion are presented together in many journals. This section answers the basic question “What did you find in your research?”

What is included in the Results section?

The Results section should include the findings of your study and ONLY the findings of your study. The findings include:

• Data presented in tables, charts, graphs, and other figures (may be placed into the text or on separate pages at the end of the manuscript)
• A contextual analysis of this data explaining its meaning in sentence form
• All data that corresponds to the central research question(s)
• All secondary findings (secondary outcomes, subgroup analyses, etc.)

If the scope of the study is broad, or if you studied a variety of variables, or if the methodology used yields a wide range of different results, the author should present only those results that are most relevant to the research question stated in the Introduction section .

As a general rule, any information that does not present the direct findings or outcome of the study should be left out of this section. Unless the journal requests that authors combine the Results and Discussion sections, explanations and interpretations should be omitted from the Results.

How are the results organized?

The best way to organize your Results section is “logically.” One logical and clear method of organizing research results is to provide them alongside the research questions—within each research question, present the type of data that addresses that research question.

Let’s look at an example. Your research question is based on a survey among patients who were treated at a hospital and received postoperative care. Let’s say your first research question is:

“What do hospital patients over age 55 think about postoperative care?”

This can actually be represented as a heading within your Results section, though it might be presented as a statement rather than a question:

Attitudes towards postoperative care in patients over the age of 55

Now present the results that address this specific research question first. In this case, perhaps a table illustrating data from a survey. Likert items can be included in this example. Tables can also present standard deviations, probabilities, correlation matrices, etc.

Following this, present a content analysis, in words, of one end of the spectrum of the survey or data table. In our example case, start with the POSITIVE survey responses regarding postoperative care, using descriptive phrases. For example:

“Sixty-five percent of patients over 55 responded positively to the question “ Are you satisfied with your hospital’s postoperative care ?” (Fig. 2)

Include other results such as subcategory analyses. The amount of textual description used will depend on how much interpretation of tables and figures is necessary and how many examples the reader needs in order to understand the significance of your research findings.

Next, present a content analysis of another part of the spectrum of the same research question, perhaps the NEGATIVE or NEUTRAL responses to the survey. For instance:

  “As Figure 1 shows, 15 out of 60 patients in Group A responded negatively to Question 2.”

After you have assessed the data in one figure and explained it sufficiently, move on to your next research question. For example:

  “How does patient satisfaction correspond to in-hospital improvements made to postoperative care?”

This kind of data may be presented through a figure or set of figures (for instance, a paired T-test table).

Explain the data you present, here in a table, with a concise content analysis:

“The p-value for the comparison between the before and after groups of patients was .03% (Fig. 2), indicating that the greater the dissatisfaction among patients, the more frequent the improvements that were made to postoperative care.”

Let’s examine another example of a Results section from a study on plant tolerance to heavy metal stress . In the Introduction section, the aims of the study are presented as “determining the physiological and morphological responses of Allium cepa L. towards increased cadmium toxicity” and “evaluating its potential to accumulate the metal and its associated environmental consequences.” The Results section presents data showing how these aims are achieved in tables alongside a content analysis, beginning with an overview of the findings:

“Cadmium caused inhibition of root and leave elongation, with increasing effects at higher exposure doses (Fig. 1a-c).”

The figure containing this data is cited in parentheses. Note that this author has combined three graphs into one single figure. Separating the data into separate graphs focusing on specific aspects makes it easier for the reader to assess the findings, and consolidating this information into one figure saves space and makes it easy to locate the most relevant results.

Following this overall summary, the relevant data in the tables is broken down into greater detail in text form in the Results section.

• “Results on the bio-accumulation of cadmium were found to be the highest (17.5 mg kgG1) in the bulb, when the concentration of cadmium in the solution was 1×10G2 M and lowest (0.11 mg kgG1) in the leaves when the concentration was 1×10G3 M.”

Captioning and Referencing Tables and Figures

Tables and figures are central components of your Results section and you need to carefully think about the most effective way to use graphs and tables to present your findings . Therefore, it is crucial to know how to write strong figure captions and to refer to them within the text of the Results section.

The most important advice one can give here as well as throughout the paper is to check the requirements and standards of the journal to which you are submitting your work. Every journal has its own design and layout standards, which you can find in the author instructions on the target journal’s website. Perusing a journal’s published articles will also give you an idea of the proper number, size, and complexity of your figures.

Regardless of which format you use, the figures should be placed in the order they are referenced in the Results section and be as clear and easy to understand as possible. If there are multiple variables being considered (within one or more research questions), it can be a good idea to split these up into separate figures. Subsequently, these can be referenced and analyzed under separate headings and paragraphs in the text.

To create a caption, consider the research question being asked and change it into a phrase. For instance, if one question is “Which color did participants choose?”, the caption might be “Color choice by participant group.” Or in our last research paper example, where the question was “What is the concentration of cadmium in different parts of the onion after 14 days?” the caption reads:

 “Fig. 1(a-c): Mean concentration of Cd determined in (a) bulbs, (b) leaves, and (c) roots of onions after a 14-day period.”

Steps for Composing the Results Section

Because each study is unique, there is no one-size-fits-all approach when it comes to designing a strategy for structuring and writing the section of a research paper where findings are presented. The content and layout of this section will be determined by the specific area of research, the design of the study and its particular methodologies, and the guidelines of the target journal and its editors. However, the following steps can be used to compose the results of most scientific research studies and are essential for researchers who are new to preparing a manuscript for publication or who need a reminder of how to construct the Results section.

Step 1 : Consult the guidelines or instructions that the target journal or publisher provides authors and read research papers it has published, especially those with similar topics, methods, or results to your study.

• The guidelines will generally outline specific requirements for the results or findings section, and the published articles will provide sound examples of successful approaches.
• Note length limitations on restrictions on content. For instance, while many journals require the Results and Discussion sections to be separate, others do not—qualitative research papers often include results and interpretations in the same section (“Results and Discussion”).
• Reading the aims and scope in the journal’s “ guide for authors ” section and understanding the interests of its readers will be invaluable in preparing to write the Results section.

Step 2 : Consider your research results in relation to the journal’s requirements and catalogue your results.

• Focus on experimental results and other findings that are especially relevant to your research questions and objectives and include them even if they are unexpected or do not support your ideas and hypotheses.
• Catalogue your findings—use subheadings to streamline and clarify your report. This will help you avoid excessive and peripheral details as you write and also help your reader understand and remember your findings. Create appendices that might interest specialists but prove too long or distracting for other readers.
• Decide how you will structure of your results. You might match the order of the research questions and hypotheses to your results, or you could arrange them according to the order presented in the Methods section. A chronological order or even a hierarchy of importance or meaningful grouping of main themes or categories might prove effective. Consider your audience, evidence, and most importantly, the objectives of your research when choosing a structure for presenting your findings.

Step 3 : Design figures and tables to present and illustrate your data.

• Tables and figures should be numbered according to the order in which they are mentioned in the main text of the paper.
• Information in figures should be relatively self-explanatory (with the aid of captions), and their design should include all definitions and other information necessary for readers to understand the findings without reading all of the text.
• Use tables and figures as a focal point to tell a clear and informative story about your research and avoid repeating information. But remember that while figures clarify and enhance the text, they cannot replace it.

Step 4 : Draft your Results section using the findings and figures you have organized.

• The goal is to communicate this complex information as clearly and precisely as possible; precise and compact phrases and sentences are most effective.
• In the opening paragraph of this section, restate your research questions or aims to focus the reader’s attention to what the results are trying to show. It is also a good idea to summarize key findings at the end of this section to create a logical transition to the interpretation and discussion that follows.
• Try to write in the past tense and the active voice to relay the findings since the research has already been done and the agent is usually clear. This will ensure that your explanations are also clear and logical.
• Make sure that any specialized terminology or abbreviation you have used here has been defined and clarified in the  Introduction section .

Step 5 : Review your draft; edit and revise until it reports results exactly as you would like to have them reported to your readers.

• Double-check the accuracy and consistency of all the data, as well as all of the visual elements included.
• Read your draft aloud to catch language errors (grammar, spelling, and mechanics), awkward phrases, and missing transitions.
• Ensure that your results are presented in the best order to focus on objectives and prepare readers for interpretations, valuations, and recommendations in the Discussion section . Look back over the paper’s Introduction and background while anticipating the Discussion and Conclusion sections to ensure that the presentation of your results is consistent and effective.
• Consider seeking additional guidance on your paper. Find additional readers to look over your Results section and see if it can be improved in any way. Peers, professors, or qualified experts can provide valuable insights.

One excellent option is to use a professional English proofreading and editing service  such as Wordvice, including our paper editing service . With hundreds of qualified editors from dozens of scientific fields, Wordvice has helped thousands of authors revise their manuscripts and get accepted into their target journals. Read more about the  proofreading and editing process  before proceeding with getting academic editing services and manuscript editing services for your manuscript.

As the representation of your study’s data output, the Results section presents the core information in your research paper. By writing with clarity and conciseness and by highlighting and explaining the crucial findings of their study, authors increase the impact and effectiveness of their research manuscripts.

For more articles and videos on writing your research manuscript, visit Wordvice’s Resources page.

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General Research Paper Guidelines: Discussion

Discussion section.

The overall purpose of a research paper’s discussion section is to evaluate and interpret results, while explaining both the implications and limitations of your findings. Per APA (2020) guidelines, this section requires you to “examine, interpret, and qualify the results and draw inferences and conclusions from them” (p. 89). Discussion sections also require you to detail any new insights, think through areas for future research, highlight the work that still needs to be done to further your topic, and provide a clear conclusion to your research paper. In a good discussion section, you should do the following:

• Clearly connect the discussion of your results to your introduction, including your central argument, thesis, or problem statement.
• Provide readers with a critical thinking through of your results, answering the “so what?” question about each of your findings. In other words, why is this finding important?
• Detail how your research findings might address critical gaps or problems in your field
• Compare your results to similar studies’ findings
• Provide the possibility of alternative interpretations, as your goal as a researcher is to “discover” and “examine” and not to “prove” or “disprove.” Instead of trying to fit your results into your hypothesis, critically engage with alternative interpretations to your results.

For more specific details on your Discussion section, be sure to review Sections 3.8 (pp. 89-90) and 3.16 (pp. 103-104) of your 7 th edition APA manual

*Box content adapted from:

University of Southern California (n.d.). Organizing your social sciences research paper: 8 the discussion . https://libguides.usc.edu/writingguide/discussion

Limitations

Limitations of generalizability or utility of findings, often over which the researcher has no control, should be detailed in your Discussion section. Including limitations for your reader allows you to demonstrate you have thought critically about your given topic, understood relevant literature addressing your topic, and chosen the methodology most appropriate for your research. It also allows you an opportunity to suggest avenues for future research on your topic. An effective limitations section will include the following:

• Detail (a) sources of potential bias, (b) possible imprecision of measures, (c) other limitations or weaknesses of the study, including any methodological or researcher limitations.
• Sample size: In quantitative research, if a sample size is too small, it is more difficult to generalize results.
• Lack of available/reliable data : In some cases, data might not be available or reliable, which will ultimately affect the overall scope of your research. Use this as an opportunity to explain areas for future study.
• Lack of prior research on your study topic: In some cases, you might find that there is very little or no similar research on your study topic, which hinders the credibility and scope of your own research. If this is the case, use this limitation as an opportunity to call for future research. However, make sure you have done a thorough search of the available literature before making this claim.
• Flaws in measurement of data: Hindsight is 20/20, and you might realize after you have completed your research that the data tool you used actually limited the scope or results of your study in some way. Again, acknowledge the weakness and use it as an opportunity to highlight areas for future study.
• Limits of self-reported data: In your research, you are assuming that any participants will be honest and forthcoming with responses or information they provide to you. Simply acknowledging this assumption as a possible limitation is important in your research.
• Access: Most research requires that you have access to people, documents, organizations, etc.. However, for various reasons, access is sometimes limited or denied altogether. If this is the case, you will want to acknowledge access as a limitation to your research.
• Time: Choosing a research focus that is narrow enough in scope to finish in a given time period is important. If such limitations of time prevent you from certain forms of research, access, or study designs, acknowledging this time restraint is important. Acknowledging such limitations is important, as they can point other researchers to areas that require future study.
• Potential Bias: All researchers have some biases, so when reading and revising your draft, pay special attention to the possibilities for bias in your own work. Such bias could be in the form you organized people, places, participants, or events. They might also exist in the method you selected or the interpretation of your results. Acknowledging such bias is an important part of the research process.
• Language Fluency: On occasion, researchers or research participants might have language fluency issues, which could potentially hinder results or how effectively you interpret results. If this is an issue in your research, make sure to acknowledge it in your limitations section.

University of Southern California (n.d.). Organizing your social sciences research paper: Limitations of the study . https://libguides.usc.edu/writingguide/limitations

In many research papers, the conclusion, like the limitations section, is folded into the larger discussion section. If you are unsure whether to include the conclusion as part of your discussion or as a separate section, be sure to defer to the assignment instructions or ask your instructor.

The conclusion is important, as it is specifically designed to highlight your research’s larger importance outside of the specific results of your study. Your conclusion section allows you to reiterate the main findings of your study, highlight their importance, and point out areas for future research. Based on the scope of your paper, your conclusion could be anywhere from one to three paragraphs long. An effective conclusion section should include the following:

• Describe the possibilities for continued research on your topic, including what might be improved, adapted, or added to ensure useful and informed future research.
• Provide a detailed account of the importance of your findings
• Reiterate why your problem is important, detail how your interpretation of results impacts the subfield of study, and what larger issues both within and outside of your field might be affected from such results

University of Southern California (n.d.). Organizing your social sciences research paper: 9. the conclusion . https://libguides.usc.edu/writingguide/conclusion

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Academic Phrases for Writing Results & Discussion Sections of a Research Paper

Overview |   Abstract   | Introduction | Literature Review | Materials & Methods | Results & Discussion | Conclusion & Future Work | Acknowledgements & Appendix

The results and discussion sections are one of the challenging sections to write. It is important to plan this section carefully as it may contain a large amount of scientific data that needs to be presented in a clear and concise fashion. The purpose of a Results section is to present the key results of your research. Results and discussions can either be combined into one section or organized as separate sections depending on the requirements of the journal to which you are submitting your research paper. Use subsections and subheadings to improve readability and clarity. Number all tables and figures with descriptive titles. Present your results as figures and tables and point the reader to relevant items while discussing the results. This section should highlight significant or interesting findings along with P values for statistical tests. Be sure to include negative results and highlight potential limitations of the paper. You will be criticised by the reviewers if you don’t discuss the shortcomings of your research. This often makes up for a great discussion section, so do not be afraid to highlight them.

The results and discussion section of your research paper should include the following:

• Comparison with prior studies
• Limitations of your work
• Casual arguments
• Speculations
• Deductive arguments

1. Findings

From the short review above, key findings emerge: __ We describe the results of __, which show __ This suggests that __ We showed that __ Our findings on __ at least hint that __ This is an important finding in the understanding of the __ The present study confirmed the findings about __ Another promising finding was that __ Our results demonstrated that __ This result highlights that little is known about the __ A further novel finding is that __ Together, the present findings confirm __ The implications of these findings are discussed in __ The results demonstrate two things.  First, __. Second,  __ The results of the experiment found clear support for the __ This analysis found evidence for __ Planned comparisons revealed that __ Our results casts a new light on __ This section summarises the findings and contributions made. It performs well, giving good results. This gives clearly better results than __ The results confirm that this a good choice for __ From the results, it is clear that __ In this section, we will illustrate some experimental results. This delivers significantly better results due to __ The result now provides evidence to __ It leads to good results, even if the improvement is negligible. This yields increasingly good results on data. The result of this analysis is then compared with the  __ The applicability of these new results are then tested on __ This is important to correctly interpret the results. The results are substantially better than __ The results lead to similar conclusion where __ Superior results are seen for __ From these results it is clear that __ Extensive results carried out show that this method improves __ We obtain good results with this simple method. However, even better results are achieved when using our algorithm. It is worth discussing these interesting facts revealed by the results of  __ Overall, our method was the one that obtained the most robust results. Slightly superior results are achieved with our algorithm. The result is equal to or better than a result that is currently accepted.

2. Comparison with prior studies

The results demonstrated in this chapter match state of the art methods. Here we compare the results of the proposed method with those of the traditional methods. These results go beyond previous reports, showing that __ In line with previous studies __ This result ties well with previous studies wherein __ Contrary to the findings of __ we did not find __ They have demonstrated that __ Others have shown that __ improves __ By comparing the results from __, we hope to determine __ However, in line with the ideas of __, it can be concluded that __ When comparing our results to those of older studies, it must be pointed out that __ We have verified that using __ produces similar results Overall these findings are in accordance with findings reported by __ Even though we did not replicate the previously reported __, our results suggest that __ A similar conclusion was reached by __ However, when comparing our results to those of older studies, it must be pointed out __ This is consistent with what has been found in previous __ A similar pattern of results was obtained in __ The findings are directly in line with previous findings These basic findings are consistent with research showing that __ Other results were broadly in line with __

3. Limitations of your work

Because of the lack of __ we decided to not investigate __ One concern about the findings of __ was that __ Because of this potential limitation, we treat __ The limitations of the present studies naturally include __ Regarding the limitations of __, it could be argued that __ Another limitation of this __ This limitation is apparent in many __ Another limitation in __ involves the issue of __ The main limitation is the lack of __ One limitation is found in this case. One limitation of these methods however is that they __ It presents some limitations such as __ Although widely accepted, it suffers from some limitations due to __ An apparent limitation of the method is __ There are several limitations to this approach. One limitation of our implementation is that it is __ A major source of limitation is due to  __ The approach utilised suffers from the limitation that __ The limitations are becoming clear __ It suffers from the same limitations associated with a __

4. Casual arguments

A popular explanation of __ is that __ It is by now generally accepted that __ A popular explanation is that __ As it is not generally agreed that __ These are very small and difficult to observe. It is important to highlight the fact that __ It is notable that __ An important question associated with __ is __ This did not impair the __ This is important because there is __ This implies that __ is associated with __ This is indicative for lack of __ This will not be biased by __ There were also some important differences in __ It is interesting to note that, __ It is unlikely that __ This may alter or improve aspects of __ In contrast, this makes it possible to __ This is particularly important when investigating __ This has been used to successfully account for __ This introduces a possible confound in __ This was included to verify that __

5. Speculations

However, we acknowledge that there are considerable discussions among researchers as to __ We speculate that this might be due to __ There are reasons to doubt this explanation of __ It remains unclear to which degree __ are attributed to __ However, __ does seem to improve __ This does seem to depend on __ It is important to note, that the present evidence relies on __ The results show that __ does not seem to impact the __ However, the extent to which it is possible to __ is unknown Alternatively, it could simply mean that __ It is difficult to explain such results within the context of __ It is unclear whether this is a suitable for __ This appears to be a case of __ From this standpoint, __ can be considered as __ To date, __remain unknown Under certain assumptions, this can be construed as __ Because of this potential limitation, we treat __ In addition, several questions remain unanswered. At this stage of understanding, we believe__ Therefore, it remains unclear whether __ This may explain why __

6. Deductive arguments

A difference between these __ can only be attributable to __ Nonetheless, we believe that it is well justified to __ This may raise concerns about __ which can be addressed by __ As discussed, this is due to the fact that __ Results demonstrate that this is not necessarily true. These findings support the notion that __ is not influenced by __ This may be the reason why we did not find __ In order to test whether this is equivalent across __, we __ Therefore, __ can be considered to be equivalent for __

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• Published: 09 September 2024

Navigating post-pandemic challenges through institutional research networks and talent management

• Muhammad Zada   ORCID: orcid.org/0000-0003-0466-4229 1 , 2 ,
• Imran Saeed 3 ,
• Jawad Khan   ORCID: orcid.org/0000-0002-6673-7617 4 &
• Shagufta Zada 5 , 6  

Humanities and Social Sciences Communications volume  11 , Article number:  1164 ( 2024 ) Cite this article

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• Business and management

Institutions actively seek global talent to foster innovation in the contemporary landscape of scientific research, education, and technological progress. The COVID-19 pandemic underscored the importance of international collaboration as researchers and academicians faced limitations in accessing labs and conducting research experiments. This study uses a research collaboration system to examine the relationship between organizational intellectual capital (Human and structural Capital) and team scientific and technological performance. Further, this study underscores the moderating role of top management support. Using a time-lagged study design, data were collected from 363 participants in academic and research institutions. The results show a positive relationship between organizational intellectual capital (Human and structural Capital) and team scientific and technological performance using a research collaboration system. Moreover, top management support positively moderates the study’s hypothesized relationships. The study’s findings contribute significantly to existing knowledge in this field, with implications for academia, researchers, and government focused on technology transmission, talent management, research creative collaboration, supporting innovation, scientific research, technological progress, and preparing for future challenges.

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Introduction.

Global talent management and the talent hunt within research and educational institutions have become extensively discussed topics in international human resource management (HRM) (Al et al., 2022 ). Global talent management is intricately connected to the notion of finding, managing, and facilitating the fetch of research, skills, techniques, and knowledge among team members and progress in education and technology (Kwok, 2022 ; Sommer et al., 2017 ). This topic assumes a greater position when it is looked at through the lens of research, academicians, and educational institutions serving as a means of achieving scientific and technological advancement and performance (Kaliannan et al., 2023 ; Patnaik et al., 2022 ). Effective knowledge management and transfer occur between teams engaged in cross-border research collaborations (Davenport et al., 2002 ; Fasi, 2022 ). Effective team management, global talent recruitment, and the exchange of scientific knowledge across national boundaries face different challenges due to the swift growth of economic and political fanaticism. This is particularly evident in advanced economies that rely heavily on knowledge-based industries (Vaiman et al., 2018 ). Research and educational sectors are encountering significant challenges in effectively hunting and managing international talent, particularly in the aftermath of the COVID-19 pandemic, during which approximately half of the global workforce faced the possibility of job loss (Almeida et al., 2020 ; Radhamani et al., 2021 ). Due to the implementation of lockdown measures by governments, many research intuitions are facing significant issues, and the pandemic has changed the situation; work was stuck, and scientists around the globe are thinking to be prepared for this kind of situation, which is possible through the use scientific research collaboration platforms. These platforms serve as a means to exchange research and knowledge, which is crucial in the talent hunt and management (Haak-Saheem, 2020 ). In the situation above, wherein limitations exist regarding the exchange of research and knowledge within the institutions, it becomes imperative for the top management of institutions to incentivize employees to engage the team in knowledge sharing actively and achieve team-level scientific and technological advancement. It can be achieved by implementing a research collaboration system that facilitates knowledge exchange and contributes to effective talent hunt and management (Haider et al., 2022 ; Xu et al., 2024 ).

A research collaboration network is a tool for scientific and technological advancement and talent management encompassing various processes and practices to facilitate the sharing, integration, translation, and transformation of scientific knowledge (Biondi & Russo, 2022 ). During and after the COVID-19 era characterized by travel restrictions, research networking platforms serve as valuable tools for students and researchers located in variance regions to engage in the exchange of research knowledge and achieve team-level scientific and technological advancement (Yang et al., 2024 ). Enhancing intellectual capital (IC) within the organizations is imperative within this framework (Pellegrini et al., 2022 ; Vătămănescu et al., 2023 ). Intellectual capital (IC) is the intangible assets owned by an organization that has the potential to generate value (Stewart, 1991 ). An organization’s intellectual capital (IC) includes human and structural capital (Marinelli et al., 2022 ). According to Vătămănescu et al. ( 2023 ), the organization can effectively manage the skills and abilities of its team members across different countries by properly utilizing both human and structural capital and establishing a strong research collaboration system with the help of top management support. This capability remains intact even during and after the COVID-19 pandemic. This study emphasizes the importance of talent hunt and management within research and educational institutions in the post-COVID-19 pandemic because of every country’s following implementation of lockdown measures. Our study focuses on the implication of facilitating the exchange of research, knowledge, and techniques among team members during and after this period. The effective way to share research expertise and techniques in such a scenario is through a research collaboration network (O’Dwyer et al., 2023 ).

While previous research has extensively explored talent management in various industries (Al Ariss, Cascio, & Paauwe, 2014 ; Susanto, Sawitri, Ali, & Rony, 2023 ), a noticeable gap exists in the body of knowledge regarding the discussion of global talent acquisition and management within research and academic institutions, particularly within volatile environments and about scientific and technological advancements (Harsch & Festing, 2020 ). The objective of this research is to fill this research gap.1) To investigate the strategies of how research and educational institutions hunt and manage gobble talent. 2)To analyze the impact of human and structural capital and team scientific and technological performance using a research collaboration system. 3) To examine the moderating effect of top management support on the IC to use the research collation network among institution research teams and scientific and technological performance.

In addition, current research contributes significantly to the literature by elucidating the pivotal role of organizational intellectual capital in strengthening scientific and technological performance through research collaborative networks. This study advances our grip on how internal resources drive innovation and research outcomes by empirically demonstrating the positive association between human and structural capital and team-level scientific and technological performance. Furthermore, the current study highlights the moderating effect of top management support, suggesting that management commitment can amplify the benefits of intellectual capital (human and structural capital). These results show a subtle perspective on how organizations can influence their intellectual assets to foster higher levels of productivity and innovation. The study’s theoretical contributions lie in integrating resource-based views and organizational theory with performance metrics, while its practical implications provide actionable insights for institutions aiming to optimize their intellectual resources and management practices. This research also sets the stage for future inquiries into the dynamics of intellectual capital and management support in various collaborative contexts.

Research theories, literature review, and hypotheses development

Research theories.

The focus of the current study pertains to the challenges surrounding talent management within institutions during and after the COVID-19 pandemic(Fernandes et al., 2023 ). Global talent management is intently linked to the objective of enhancing the intellectual capital of the organization (Zada et al., 2023 ). Considering the COVID-19 pandemic, which raised much more attention toward scientific and technological advancement, the academic sector has noticed an observable shift towards utilizing research collaboration platforms to share scientific knowledge effectively and achieve scientific and technological performance. Intellectual capital encompasses five distinct resource categories, as identified by Roos and Roos ( 1997 ), comprising three immaterial and two touchable resources. Intangible resources such as human capital, structural capital, and customer capital are complemented by tangible resources, encompassing monetary and physical assets. Global talent management encompasses human and structural capital management (Felin & Hesterly, 2007 ). The enhancement of talent management capabilities within the institution can be achieved by cultivating institution-specific competencies in both human and structural capital (Al Ariss et al., 2014 ). This concept lines up with the theoretical background of the resource-based view (RBV) theory presented by Barney ( 1991 ). According to this theory, organizations should prioritize examining their core resources to recognize valuable assets, competencies, and capabilities that can contribute to attaining a sustainable competitive advantage (Barney, 1991 ).

During and after the COVID-19 scenario, virtual platforms are utilized by institutions to engage students and staff abroad in research and knowledge exchange, which is part of global talent management. Staff possessing adequate knowledge repositories will likely participate in knowledge exchange activities. Therefore, organizations must improve their internal resources to enhance talent management, as per the fundamental principle of the RBV theory (Barney, 1991 ). Enhancing internal resources entails strengthening an organization’s human capital, which refers to its staff’s scientific research and technical skills and knowledge and structural capital. Strengthening these two resources can facilitate the institution in effectively sharing knowledge through a research collaboration platform, consequently enhancing their global talent management endeavors and contributing to the team’s scientific and technological performance.

In this research, we also utilize institutional theory (Oliver, 1997 ) and Scott ( 2008 ) as a framework to examine the utilization of research collaboration social platforms by faculty of institutions. Our focus is on exchanging research and technical knowledge within the climate of global talent management during and after the COVID-19 epidemic. According to Scott ( 2008 ), “Institutional theory is a widely recognized theoretical framework emphasizing rational myths, isomorphism, and legitimacy (p. 78)”. For electronic data interchange, the theory has been utilized in technology adoption research (Damsgaard, Lyytinen ( 2001 )) and educational institutes (J. et al., 2007 ). In the pandemic situation, institutional theory provides researchers with a framework to analyze the motivations of employees within institutions to engage in teams to achieve team-level scientific and technological performance through a research collaboration system. According to institutional theory, organizations should utilize a research collaboration network to ensure that their staff do not need to compromise their established norms, values, and expectations. During the COVID-19 pandemic, numerous countries implemented limitations on international movement as a preventive measure. Consequently, there has been a growing identification of the potential importance of utilizing an institutional research collaboration platform for facilitating the online exchange of knowledge, skills, research techniques, and global talent management among employees of institutions operating across various countries. The active support of staff by the top management of an institution can play a key role in expediting the implementation of social networks for research collaboration within the institution (Zada et al., 2023 ).

Literature review

An institution’s scientific and technological advancement is contingent upon optimal resource utilization (Muñoz et al., 2022 ). Global talent hunt and management encompasses utilizing information and communication technologies (ICT) to provide a way for the exchange of research knowledge and techniques, thereby enabling the implementation of knowledge-based strategies (Muñoz et al., 2022 ). In a high research-level turbulent environment, it becomes imperative to effectively manage human capital (HUC) to facilitate the appropriate exchange of research knowledge and techniques (Salamzadeh, Tajpour, Hosseini, & Brahmi, 2023 ). Research shows that transferring research knowledge and techniques across national boundaries, exchanging best practices, and cultivating faculty skills are crucial factors in maintaining competitiveness (Farahian, Parhamnia, & Maleki, 2022 ; Shao & Ariss, 2020 ).

It is widely acknowledged in scholarly literature that there is a prevailing belief among individuals that talent possesses movability and that research knowledge and techniques can be readily transferred (Bakhsh et al., 2022 ; Council, 2012 ). However, it is essential to note that the matter is more complex than it may initially appear (Biondi & Russo, 2022 ). The proliferation of political and economic nationalism in developed knowledge-based economies poses a significant risk to exchanging research knowledge and techniques among faculty members in research and educational institutions worldwide (Arocena & Sutz, 2021 ). During and after COVID-19, knowledge transfer can be effectively facilitated by utilizing a research collaboration network platform (Duan & Li, 2023 ; Sulaiman et al., 2022 ). This circumstance is noticeable within the domain of international research and development, wherein academic professionals have the opportunity to utilize research collaboration platforms as a means of disseminating valuable research knowledge and techniques to their counterparts in various nations (Jain et al., 2022 ).

The scientific and technological advancement of institutions linked by intuition research and development level and research and development depend on the intuition’s quality of research, knowledge, and management (Anshari & Hamdan, 2022 ). However, there is a need to enhance the research team’s capacity to learn and transfer research knowledge and techniques effectively. Research suggests that institutional human capital (HUC) is critical in managing existing resources and hunting international talent, particularly after the COVID-19 pandemic (Sigala, Ren, Li, & Dioko, 2023 ). Human capital refers to the combined implicit and crystal clear knowledge of employees within an institution and their techniques and capabilities to effectively apply this knowledge to achieve scientific and technological advancements (Al-Tit et al., 2022 ). According to Baron and Armstrong ( 2007 ) Human capital refers to the abilities, knowledge, techniques, skills, and expertise of individuals, particularly research team members, that are relevant to the current task.

Furthermore, HUC encompasses the scope of individuals who can contribute to this reservoir of research knowledge, techniques, and expertise through individual learning. As the literature shows, the concept of IC encompasses the inclusion of structural capital (STC), which requires fortification through the implementation of a proper global talent acquisition and management system (Pak et al., 2023 ; Phan et al., 2020 ). STC encompasses various mechanisms to enhance an institution’s performance and productivity (Barpanda, 2021 ). STC is extensively acknowledged as an expedited framework for HUC, as discussed by Bontis ( 1998 ) and further explored by Gogan, Duran, and Draghici ( 2015 ). During and after the COVID-19 epidemic, a practical approach to global talent management involves leveraging research collaboration network platforms to facilitate knowledge exchange among research teams (Arslan et al., 2021 ). However, the crucial involvement of top management support is imperative to effectively manage talent by utilizing research collaboration network platforms for knowledge transfer (Zada et al., 2023 ). Nevertheless, the existing body of knowledge needs to adequately explore the topic of talent management about knowledge transfer on research collaboration platforms, particularly in the context of institution-active management support (Tan & Md. Noor, 2013 ).

Conceptual model and research hypothesis

By analyzing pertinent literature and theoretical frameworks, we have identified the factors influencing staff intention in research and academic institutions to utilize research collaboration networks after the COVID-19 pandemic and achieve scientific and technical performance. This study aims to explain the determinants. Additionally, this study has considered the potential influence of top management support as a moderator on the associations between education and research institution staff intention on IC to utilize research collaboration platforms in the post-COVID-19 era and predictors. Through this discourse, we shall generate several hypotheses to serve as the basis for constructing a conceptual model (see Fig. 1 ).

Relationships between study variables: human capital, structural capital, top management support, and team scientific and technological performance. Source: authors’ development.

Human capital and team scientific and technological performance

According to Dess and Picken ( 2000 ), HUC encompasses individuals’ capabilities, knowledge, skills, research techniques, and experience, including staff and supervisors, relevant to the specific task. Human capital also refers to the ability to pay to this reservoir of knowledge, techniques, and expertize through individual learning (Dess & Picken, 2000 ). HUC refers to the combinations of characteristics staff possess, including but not limited to research proficiency, technical aptitude, business acumen, process comprehension, and other similar competencies (Kallmuenzer et al., 2021 ). The HUC is considered an institutional repository of knowledge, as Bontis and Fitz‐enz ( 2002 ) indicated, with its employees serving as representatives. The concept of HUC refers to the combined abilities, research proficiency, and competencies that individuals possess to address and resolve operational challenges within an institutional setting (Barpanda, 2021 ; Yang & Xiangming, 2024 ). The human capital possessed by institutions includes crucial attributes that allow organizations to acquire significant internal resources that are valuable, difficult to replicate, scarce, and cannot be substituted. It aligns with the theoretical framework of the RBV theory, as suggested by Barney ( 1991 ). IC is extensively recognized as a main factor in revitalizing organizational strategy and promoting creativity and innovation. It is crucial to enable organizations to acquire and effectively disseminate knowledge among their employees, contribute to talent management endeavors, and achieve scientific and technological performance (Alrowwad et al., 2020 ; He et al., 2023 ). Human capital is linked to intrinsic aptitude, cognitive capabilities, creative problem-solving, exceptional talent, and the capacity for originality (Bontis & Fitz‐enz, 2002 ). In talent management, there is a focus on enhancing scientific and technological performance and development. According to Shao and Ariss ( 2020 ), HUC is expected to strengthen employee motivation to utilize research collaboration networks for scientific knowledge-sharing endeavors. Based on these arguments, we proposed that.

Hypothesis 1 Human capital (HUC) positively impacts team scientific and technological performance using a research collaboration system.

Structural capital and team scientific and technological Performance

According to Mehralian, Nazari, and Ghasemzadeh ( 2018 ) structural capital (STC) encompasses an organization’s formalized knowledge assets. It consists of the structures and mechanisms employed by the institution to enhance its talent management endeavors. The concept of STC is integrated within the framework of institutions’ programs, laboratory settings, and databases (Cavicchi & Vagnoni, 2017 ). The significance of an organization’s structural capital as an internal tangible asset that bolsters its human capital has been recognized by scholars such as Secundo, Massaro, Dumay, and Bagnoli ( 2018 ), and This concept also lines up with the RBV theory (J. Barney, 1991 ). The strategic assets of an organization encompass its capabilities, organizational culture, patents, and trademarks (Gogan et al., 2015 ).

Furthermore, Birasnav, Mittal, and Dalpati ( 2019 ) Suggested that these strategic assets promote high-level organizational performance, commonly called STC. Literature shows that STC encompasses an organization’s collective expertise and essential knowledge that remains intact even when employees depart (Alrowwad et al., 2020 ; Mehralian et al., 2018 ; Sarwar & Mustafa, 2023 ). The institution’s socialization, training, and development process facilitates the transfer of scientific research knowledge, skills, and expertise to its team (Arocena & Sutz, 2021 ; Marchiori et al., 2022 ). The STC is broadly recognized as having important potential and is a highly productive resource for generating great value. STC motivates its team member to share expertise with their counterparts at subordinate organizations by utilizing an institution’s research collaboration network and achieving team-level scientific and technological performance. This method remains effective even in challenging environments where traditional means of data collection, face-to-face meetings, and travel are not feasible (Secundo et al., 2016 ). In light of the above literature and theory, we propose the following hypothesis.

Hypothesis 2: Structural capital (STC) positively impacts team scientific and technological performance using a research collaboration system.

Top management support as a moderator

If the relationship between two constructs is not constant, the existence of a third construct can potentially affect this relationship by enhancing or diminishing its strength. In certain cases, the impact of a third construct can adjust the trajectory of the relationship between two variables. The variable in question is commonly called the “moderating variable.” According to Zada et al. ( 2023 ), top management support to leaders efficiently encourages team members within institutions to share research scientific knowledge with their counterparts in different countries through international research collaboration systems. Similarly, another study shows that the active endorsement of the top management significantly affects the development of direct associations, thereby influencing the team and organization’s overall performance (Biondi & Russo, 2022 ; Phuong et al., 2024 ). Different studies have confirmed that top management support is crucial in fostering a conducive knowledge-sharing environment by offering necessary resources (Ali et al., 2021 ; Lee et al., 2016 ; Zada et al., 2023 ). During and after the COVID-19 epidemic, numerous nations implemented nonessential travel restrictions and lockdown measures. In the given context, utilizing a research collaboration system would effectively facilitate the exchange of research, skills, and knowledge among staff belonging to various subsidiaries of an institution (Rådberg & Löfsten, 2024 ; Rasheed et al., 2024 ). However, it is common for researchers to exhibit resistance to adopting a novel research technique, often citing various justifications for their reluctance. To address the initial hesitance of employees at subsidiary institutes towards utilizing research collaborative networking within the institute, top management must employ strategies that foster motivation, encouragement, and incentives. These measures help create an atmosphere where team members feel empowered to engage with the new system freely. Institutional theory asserts that top management support is crucial for aligning talent management with institutional norms. Human and structural capital, pivotal within the institutional framework, contributes to an institution’s capacity to attract and retain talent, enhancing legitimacy. Adaptation to scientific and technological advancements is imperative for international institutional competitiveness, as institutional theory dictates (Oliver, 1997 ). Grounded on the above discussion, we have hypothesized.

Hypothesis 3a : Top management support moderates the relationship between human capital (HUC) and team scientific and technological performance. Specifically, this relationship will be stronger for those with higher top management support and weaker for those with lower top management support.

Hypothesis 3b : Top management support moderates the relationship between structural capital (STC) and team scientific and technological performance through the use of research collaboration network platforms. Specifically, this relationship will be stronger for those with higher top management support and weaker for those with lower top management support.

Methods data and sample

Sample and procedures.

To test the proposed model, we collected data from respondents in China’s research and academic sector in three phases to mitigate standard method variance (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003 ). In the first phase (T1-phase), respondents rated human capital, structural capital, and demographic information. After one month, respondents rated the team’s scientific and technological performance in the second phase (T2-phase). Following another one-month interval, respondents were asked to rate top management support in the third phase (T3-phase). In the first phase, after contacting 450 respondents, we received 417 usable questionnaires (92.66%). In the second phase, we received 403 usable questionnaires. In the third phase, we received 363 usable questionnaires (90.07%), constituting our final sample for interpreting the results. The sample comprises 63.4% male and 36.6% female respondents. The age distribution of the final sample was as follows: 25–30 years old (6.6%), 31–35 years old (57%), 36–40 years old (19.8%), and above 40 years old (16.5%). Regarding respondents’ experience, 45.7% had 1–5 years, 39.4% had 6–10 years, 11.3% had 11–15 years, and 3.6% had over 16 years. According to the respondents’ levels of education, 4.1% had completed bachelor’s degrees, 11.6% had earned master’s degrees, 78.8% were doctorate (PhD) scholars, and 5.5% were postdoctoral and above.

Measurement

To measure the variables, the current study adopted a questionnaire from previous literature, and age, gender, education, and experience were used as control variables. A five-point Likert scale was used (1 = strongly disagree to 5 = strongly agree). Human capital (HUC) was measured through an eight-item scale adopted by Kim, Atwater, Patel, and Smither ( 2016 ). The sample item is “The extent to which human capital of research and development department is competitive regarding team performance”. The self-reported scale developed by Nezam, Ataffar, Isfahani, and Shahin ( 2013 ) was adopted to measure structural capital. The scale consists of seven items. The sample scale item is “My organization emphasizes IT investment.” In order to measure top management support, a six-item scale was developed by Singh, Gupta, Busso, and Kamboj ( 2021 ), was adopted, and sample item includes “Sufficient incentives were provided by top management (TM) for achieving scientific and technological performance.” Finlay, the self-reported scale developed by Gonzalez-Mulé, Courtright, DeGeest, Seong, and Hong ( 2016 ) was adopted to gauge team scientific and technological performance and scales items are four. The sample item is “This team achieves its goals.”

Assessment of measurement model

In the process of employing AMOS for analysis, the initial step encompasses an assessment of the model to determine the strength and validity of the study variables. The evaluation of variable reliability conventionally revolves around two key aspects, which are indicator scale reliability and internal reliability. More precisely, indicator reliability is deemed to be recognized when factor loadings exceed the threshold of 0.60. In parallel, internal consistency reliability is substantiated by the attainment of values exceeding 0.70 for both Cronbach’s alpha and composite reliability, aligning with well-established and recognized guidelines (Ringle et al., 2020 ).

To gauge the reliability of construct indicators, we utilized two key metrics which are composite reliability (CR) and average variance extracted (AVE). The CR values for all variables were notably high, exceeding 0.70 and falling within the range of 0.882 to 0.955. This signifies a robust level of reliability for the indicators within each construct. Furthermore, the AVE values, which indicate convergent validity, exceeded the minimum threshold of 0.50, with each construct value varying from 0.608 to 0.653, thus affirming the presence of adequate convergent validity.

In addition to assessing convergent validity, we also examined discriminant validity by scrutinizing the cross-loadings of indicators on the corresponding variables and the squared correlations between constructs and AVE values. Our findings indicated that all measures exhibited notably stronger loadings on their intended constructs, thereby underscoring the measurement model’s discriminant validity.

Discriminant validity was recognized by observing average variance extracted (AVE) values that exceeded the squared correlations between constructs, as indicated in Table 1 . In conjunction with the Composite Reliability (CR) and AVE values, an additional discriminant validity assessment was conducted through a Heterotrait-Monotrait Ratio (HTMT) analysis. This analysis entailed a comparison of inter-construct correlations against a predefined upper threshold of 0.85. The results demonstrated that all HTMT values remained significantly below this threshold, affirming satisfactory discriminant validity for each variable (Henseler et al., 2015 ). Every HTMT value recorded was situated beneath the specified threshold, thereby supplying supplementary confirmation regarding the constructs’ discriminant validity. In summary, the results of the outer model assessment indicate that the variables showcased commendable levels of reliability and validity, with the discriminant validity being suitably and convincingly established.

Moreover, correlation Table 2 shows that human capital is significantly and positively correlated with structural capital ( r  = 0.594**), TMS ( r  = 0.456 **), and STP ( r  = 0.517**). Structural capital is also significantly and positively correlated with TMS ( r  = 0.893**) and STP ( r  = 0.853**). Furthermore, TMS is significantly and positively correlated with STP (0.859**).

Confirmatory factor analysis (CFA)

A comprehensive confirmatory factor analysis was estimated by employing the software AMOS version 24 to validate the distinctiveness of the variables. CFA shows the fitness of the hypothesized four factors model, including human capital, structural capital, top management support, and team scientific and technological performance, as delineated in Table 3 ; the results show that the hypothesized four-factor model shows fit and excellent alternative models. Consequently, The study variables demonstrate validity and reliability, which makes the dimension model appropriate for conducting a structural path analysis, as advocated by Hair, Page, and Brunsveld ( 2019 ).

Hypotheses testing

This study used the bootstrapping approach, which involves 5,000 bootstrap samples to test the proposed study model and assess the significance and strength of the structural correlations. Using this approach, bias-corrected confidence intervals and p-values were generated in accordance with Streukens and Leroi-Werelds ( 2016 ) guidelines. First, we did an analysis that entailed checking the path coefficients and their connected significance. The findings, as shown in Table 4 , validate Hypothesis 1, revealing a positive correlation between HUC and STP ( β  = 0.476, p  < 0.001). Additionally, the finding validates Hypothesis 2, highlighting a positive association between structural capital and STP ( β  = 0.877, p  < 0.001). For the moderation analysis, we utilized confidence intervals that do not encompass zero, per the guidelines that Preacher and Hayes ( 2008 ) recommended.

In our analysis, we found support for Hypothesis 3a, which posited that top management support (TMS) moderates the relationship between human capital (HUC) and team scientific and technological performance (STP). The results in Table 4 showed that the moderating role, more precisely, the interaction between HUC and TMS, was substantial and positive ( β  = −0.131, p  = 0.001). These results suggest that TMS enhances the positive association between HUC and STP, as shown in Fig. 2 . Consequently, we draw the conclusion that our data substantiates hypothesis 3a. Furthermore, Hypothesis 3b posited that TMS moderates the relationship between STC and STP. The results indicate that TMS moderates the association between STC and STP ( β  = −0.141, p  = 0.001, as presented in Table 4 and Fig. 3 ).

The moderating effect of top management support (TMS) on the relationship between human capital (HUC) and team scientific and technological performance (STP). Source: authors’ development.

The moderating effect of top management support (TMS) on the relationship between structural capital (SUC) and team scientific and technological performance (STP). Source: authors’ development.

The current study highlights the importance of research and academic institutions effectively enhancing their scientific and technological capabilities to manage their global talent within an international research collaboration framework and meet future challenges. Additionally, it underscores the need for these institutions to facilitate scientific knowledge exchange among their employees and counterparts in different countries. The enhancement of talent management through the exchange of scientific research knowledge can be most effectively accomplished by utilizing a collaborative research system between educational and research institutions (Shofiyyah et al., 2023 ), particularly in the context of the COVID-19 landscape. This study has confirmed that enhancing the higher education and research institutions’ human capital (HUC) and structural capital (STC) could attract and maintain global talent management and lead to more effective scientific and technological progress. The findings indicate that the utilization of human capital (HUC) has a significant and positive effect on scientific and technological term performance (STP) (Hypothesis 1), which is consistent with previous research (Habert & Huc, 2010 ). This study has additionally demonstrated that the implementation of s tructural capital (STC) has a significant and positive effect on team scientific and technological performance (STP), as indicated by hypothesis 2, which is also supported by the previous studies finding in different ways (Sobaih et al., 2022 ). This study has also shown that top management support moderates the association between human capital (HUC) and team scientific and technological performance hypothesis 3a and the association between structural capital (STC) and team scientific and technological performance hypothesis 3b. These hypotheses have garnered support from previous studies’ findings in different domains (Chatterjee et al., 2022 ). The study’s empirical findings also confirm the substantial moderating influence exerted by top management support on the relationships between HUC and STP described in hypothesis 3a and STC and STP described in hypothesis 3b, as evidenced by the results presented in Table 4 . Additionally, graphical representations are conducted to investigate the impacts on hypotheses 3a and 3b resulting from the application of high-top management support (TMS) and weak TMS.

The effect of high-top management support (TMS) and weak TMS on Hypothesis 3a is depicted in Fig. 2 . The solid line illustrates the effects of robust TMS on Hypothesis 3a, while the dashed line shows the effects of weak TMS on Hypothesis 3a. The graphic description validates that, as human capital (HUC) increases, team scientific and technological performance (STP) is more pronounced when influenced by robust TMS than weak TMS. This is evidenced by the steeper slope of the solid line in comparison to the dashed line. This finding suggests that employees within the research and academic sectors are more likely to utilize research collaboration networks when influenced by HUC and receive strong support from the organization’s top management.

The graph in Fig. 3 shows the impact of solid top management support (TMS) and weak TMS on Hypothesis 3b. The dotted lines continuous on the graph correspond to the effects of robust TMS and weak TMS, respectively. Figure 3 illustrates that, with increasing top management support (TMS), scientific and technological performance (STP) increase is more significant for robust TMS than weak TMS. This is evident from the steeper slope of the continuous line compared to the slope of the dotted line. This finding suggests that employees within universities and institutes are more likely to engage in research collaboration systems when they receive strong support from top management despite enhanced structural support.

Theoretical contribution

The current study makes significant contributions to the existing body of knowledge by exploring the intricate dynamics between organizational intellectual capital and team performance within scientific and technological research, especially during the unprecedented times brought about by the COVID-19 pandemic. Through its detailed examination of human and structural capital, alongside the moderating impact of top management support, the study provides a multi-faceted understanding of how these factors interact to enhance team outcomes.

This research enriches the literature on intellectual capital by providing empirical evidence on the positive association between HUC and STC and team performance. HUC, which includes employees’ skills, knowledge, and expertise, is a critical driver of innovation and productivity (Lenihan et al., 2019 ). The study highlights how a team’s collective intelligence and capabilities can lead to superior scientific and technological outputs. This finding aligns with and extends previous research that underscores the importance of skilled HR in achieving organizational success (Luo et al., 2023 ; Salamzadeh et al., 2023 ). Structural capital, encompassing organizational processes, databases, and intellectual property, contributes significantly to team performance(Ling, 2013 ). The study illustrates how well-established structures and systems facilitate knowledge sharing, streamline research processes, and ultimately boost the efficiency and effectiveness of research teams. This aspect of the findings adds depth to the existing literature by demonstrating the tangible benefits of investing in robust organizational infrastructure to support research activities.

Another essential contribution of this study is integrating a research collaboration network as a facilitating factor. This network, including digital platforms and tools that enable seamless communication and collaboration among researchers, has become increasingly vital in remote work and global collaboration (Mitchell, 2023 ). By examining how these systems leverage HUC and STC to enhance team performance, the study provides a practical understanding of the mechanisms through which technology can facilitate team scientific and technological performance.

One of the most novel contributions of this study is its emphasis on the moderating role of top management support. The findings suggest that when top management actively supports research initiatives, provides required resources, and fosters innovation, the positive effects of human and structural capital on team performance are amplified (Zada et al., 2023 ). This aspect of the study addresses a gap in the literature by highlighting the critical influence of top management on the success of intellectual capital investments. It underscores the importance of managerial involvement and strategic vision in driving research excellence and team scientific and technological performance.

Practical implications

The practical implications of the current study are weightage for organizations aiming to enhance their research and innovation capabilities and boost their scientific and technical progress. Organizations should prioritize recruiting, training, and retaining highly skilled and trained researchers and professionals globally. This can be achieved through targeted hiring practices, offering competitive compensation and retention, providing continuous professional development opportunities, and developing proper research collaboration networks. Organizations can leverage their expertize to drive innovative research and technological advancements by nurturing a global, talented workforce. Investing in robust organizational structures, processes, and systems is critical (Joseph & Gaba, 2020 ). This includes developing comprehensive databases, implementing efficient research processes, securing intellectual property, and strengthening collaborations. These factors support efficient knowledge sharing and streamline research activities, leading to higher productivity and quality research outcomes (Azeem et al., 2021 ). Organizations should ensure that their infrastructure is adaptable and can support remote and collaborative work environments.

The current study emphasizes the importance of digital platforms and tools facilitating research collaboration. Organizations should adopt advanced research collaboration networks that enable seamless communication, data sharing, and talent management. These systems are particularly crucial in a globalized research environment where team members may be geographically dispersed. Investing in such technology can significantly enhance research projects’ productivity in a sustainable way (Susanto et al., 2023 ). Top Management plays a vital role in the success of research initiatives and contributes to scientific and technological performance. Top management should actively support research teams by providing required resources, setting clear strategic directions, and fostering a culture of innovation. This includes allocating budgets for organizational research and development, encouraging cross-border collaboration, recognizing and rewarding research achievements, and enhancing overall performance. Effective Management ensures that the intellectual capital within the organization is fully utilized and aligned with organizational developmental goals (Paoloni et al., 2020 ). Organizations should create a working atmosphere that encourages research, creativity, and innovation. This can be done by establishing innovation labs, promoting interdisciplinary research, recruiting international talents, sharing research scholars, and encouraging the sharing of ideas across different departments globally. A research-oriented culture that supports innovation can inspire researchers to pursue groundbreaking work and contribute to the organization’s competitive edge.

Limitations and future research direction

The research presents numerous theoretical and practical implications; however, it has. The potential limitation of common method bias could impact the findings of this study. This concern arises because the data for the study variables were obtained from a single source and relied on self-report measures (Podsakoff, 2003 ). Therefore, it is recommended that future studies be conducted longitudinally to gain additional insights into organizations’ potential to enhance efficiency. Furthermore, it is essential to note that the sample size for this study was limited to 363 respondents who were deemed usable. These respondents were drawn from only ten research and academic institutions explicitly targeting the education and research sector.

Consequently, this restricted sample size may hinder the generalizability of the findings. Future researchers may employ a larger sample size and implement a more systematic approach to the organization to enhance the comprehensiveness and generalizability of findings in the context of global talent management and scientific and technological advancement. Furthermore, in future investigations, researchers may explore alternative boundary conditions to ascertain whether additional factors could enhance the model’s efficacy.

Numerous academic studies have emphasized the significance of examining talent management outcomes in global human resource management (HRM). The continuous international movement of highly qualified individuals is viewed as a driving force behind the development of new technologies, the dissemination of scientific findings, and the collaboration between institutions worldwide. Every organization strives to build a qualified and well-trained team, and the personnel department of the organization focuses on finding ways to transfer knowledge from experienced workers to new hires. This study uses a research collaboration system to examine the relationship between organizational intellectual capital (Human and structural Capital) and team scientific and technological performance. Further, this study underscores the moderating role of top management support. These findings offer a nuanced perspective on how organizations can leverage their intellectual assets to foster higher productivity and innovation, especially in emergencies.

Data availability

Due to respondents’ privacy concerns, data will not be publicly available. However, it can be made available by contacting the corresponding author at a reasonable request.

Al-Tit AA, Al-Ayed S, Alhammadi A, Hunitie M, Alsarayreh A, Albassam W (2022) The impact of employee development practices on human capital and social capital: the mediating contribution of knowledge management. J Open Innov 8(4):218

Article   Google Scholar  

Al Ariss A, Cascio WF, Paauwe J (2014) Talent management: current theories and future research directions. J World Bus 49(2):173–179

Al Jawali H, Darwish TK, Scullion H, Haak-Saheem W (2022) Talent management in the public sector: empirical evidence from the Emerging Economy of Dubai. Int J Hum Resour Manag 33(11):2256–2284

Ali M, Li Z, Khan S, Shah SJ, Ullah R (2021) Linking humble leadership and project success: the moderating role of top management support with mediation of team-building. Int J Manag Proj Bus 14(3):545–562

Almeida F, Santos JD, Monteiro JA (2020) The challenges and opportunities in the digitalization of companies in a post-COVID-19 World. IEEE Eng Manag Rev 48(3):97–103

Alrowwad AA, Abualoush SH, Masa’deh RE (2020) Innovation and intellectual capital as intermediary variables among transformational leadership, transactional leadership, and organizational performance. J Manag Dev 39(2):196–222

Anshari M, Hamdan M (2022) Understanding knowledge management and upskilling in Fourth Industrial Revolution: transformational shift and SECI model. VINE J Inf Knowl Manag Syst 52(3):373–393

Google Scholar  

Arocena R, Sutz J (2021) Universities and social innovation for global sustainable development as seen from the south. Technol Forecast Soc change 162:120399

Article   PubMed   Google Scholar  

Arslan A, Golgeci I, Khan Z, Al-Tabbaa O, Hurmelinna-Laukkanen P (2021) Adaptive learning in cross-sector collaboration during global emergency: conceptual insights in the context of COVID-19 pandemic. Multinatl Bus Rev 29(1):21–42

Azeem M, Ahmed M, Haider S, Sajjad M (2021) Expanding competitive advantage through organizational culture, knowledge sharing and organizational innovation. Technol Soc 66:101635

Bakhsh K, Hafeez M, Shahzad S, Naureen B, Faisal Farid M (2022) Effectiveness of digital game based learning strategy in higher educational perspectives. J Educ e-Learn Res 9(4):258–268

Barney J (1991) Firm resources and sustained competitive advantage. J Manag 17(1):99–120

Barney JB, Clark DN (2007) Resource-based theory: Creating and sustaining competitive advantage. Oup Oxford

Baron A, Armstrong M (2007) Human capital management: achieving added value through people. Kogan Page Publishers

Barpanda S (2021) Role of human and structural capital on performance through human resource practices in Indian microfinance institutions: a mediated moderation approach. Knowl Process Manag 28(2):165–180

Biondi L, Russo S (2022) Integrating strategic planning and performance management in universities: a multiple case-study analysis. J Manag Gov 26(2):417–448

Birasnav M, Mittal R, Dalpati A (2019) Integrating theories of strategic leadership, social exchange, and structural capital in the context of buyer–supplier relationship: an empirical study. Glob J Flex Syst Manag 20:219–236

Bontis N (1998) Intellectual capital: an exploratory study that develops measures and models. Manag Decis 36(2):63–76

Bontis N, Fitz‐enz J (2002) Intellectual capital ROI: a causal map of human capital antecedents and consequents. J Intellect Cap 3(3):223–247

Cavicchi C, Vagnoni E (2017) Does intellectual capital promote the shift of healthcare organizations towards sustainable development? Evidence from Italy. J Clean Prod 153:275–286

Chatterjee S, Chaudhuri R, Vrontis D (2022) Does remote work flexibility enhance organization performance? Moderating role of organization policy and top management support. J Bus Res 139:1501–1512

Council NR (2012) Education for life and work: developing transferable knowledge and skills in the 21st century. National Academies Press

Davenport S, Carr A, Bibby D (2002) Leveraging talent: spin–off strategy at industrial research. RD Manag 32(3):241–254

Dess GG, Picken JC (2000) Changing roles: Leadership in the 21st century. Organ Dyn 28(3):18–34

Duan W, Li C (2023) Be alert to dangers: collapse and avoidance strategies of platform ecosystems. J Bus Res 162:113869

Farahian M, Parhamnia F, Maleki N (2022) The mediating effect of knowledge sharing in the relationship between factors affecting knowledge sharing and reflective thinking: the case of English literature students during the COVID-19 crisis. Res Pract Technol Enhanc Learn 17(1):1–25

Fasi MA (2022) An overview on patenting trends and technology commercialization practices in the university Technology Transfer Offices in USA and China. World Pat Inf 68:102097

Felin T, Hesterly WS (2007) The knowledge-based view, nested heterogeneity, and new value creation: philosophical considerations on the locus of knowledge. Acad Manag Rev 32(1):195–218

Fernandes C, Veiga PM, Lobo CA, Raposo M (2023) Global talent management during the COVID‐19 pandemic? The Gods must be crazy! Thunderbird Int Bus Rev 65(1):9–19

Gogan LM, Duran DC, Draghici A (2015) Structural capital—a proposed measurement model. Procedia Econ Financ 23:1139–1146

Gonzalez-Mulé E, Courtright SH, DeGeest D, Seong J-Y, Hong D-S (2016) Channeled autonomy: the joint effects of autonomy and feedback on team performance through organizational goal clarity. J Manag 42(7):2018–2033

Haak-Saheem W (2020) Talent management in Covid-19 crisis: how Dubai manages and sustains its global talent pool. Asian Bus Manag 19:298–301

Habert B, Huc C (2010) Building together digital archives for research in social sciences and humanities. Soc Sci Inf 49(3):415–443

Haider SA, Akbar A, Tehseen S, Poulova P, Jaleel F (2022) The impact of responsible leadership on knowledge sharing behavior through the mediating role of person–organization fit and moderating role of higher educational institute culture. J Innov Knowl 7(4):100265

Hair JF, Page M, Brunsveld N (2019) Essentials of business research methods. Routledge

Harsch K, Festing M (2020) Dynamic talent management capabilities and organizational agility—a qualitative exploration. Hum Resour Manag 59(1):43–61

He S, Chen W, Wang K, Luo H, Wang F, Jiang W, Ding H (2023) Region generation and assessment network for occluded person re-identification. IEEE Trans Inf Forensic Secur 19:120–132

Henseler J, Ringle CM, Sarstedt M (2015) A new criterion for assessing discriminant validity in variance-based structural equation modeling. J Acad Mark Sci 43:115–135

Jain N, Thomas A, Gupta V, Ossorio M, Porcheddu D (2022) Stimulating CSR learning collaboration by the mentor universities with digital tools and technologies—an empirical study during the COVID-19 pandemic. Manag Decis 60(10):2824–2848

Joseph J, Gaba V (2020) Organizational structure, information processing, and decision-making: a retrospective and road map for research. Acad Manag Ann 14(1):267–302

Kaliannan M, Darmalinggam D, Dorasamy M, Abraham M (2023) Inclusive talent development as a key talent management approach: a systematic literature review. Hum Resour Manag Rev 33(1):100926

Kallmuenzer A, Baptista R, Kraus S, Ribeiro AS, Cheng C-F, Westhead P (2021) Entrepreneurs’ human capital resources and tourism firm sales growth: a fuzzy-set qualitative comparative analysis. Tour Manag Perspect 38:100801

Kim KY, Atwater L, Patel PC, Smither JW (2016) Multisource feedback, human capital, and the financial performance of organizations. J Appl Psychol 101(11):1569

Kwok L (2022) Labor shortage: a critical reflection and a call for industry-academia collaboration. Int J Contemp Hosp Manag 34(11):3929–3943

Lee J-C, Shiue Y-C, Chen C-Y (2016) Examining the impacts of organizational culture and top management support of knowledge sharing on the success of software process improvement. Comput Hum Behav 54:462–474

Lenihan H, McGuirk H, Murphy KR (2019) Driving innovation: public policy and human capital. Res policy 48(9):103791

Ling Y-H (2013) The influence of intellectual capital on organizational performance—knowledge management as moderator. Asia Pac J Manag 30(3):937–964

Luo J, Zhuo W, Xu B (2023) The bigger, the better? Optimal NGO size of human resources and governance quality of entrepreneurship in circular economy. Manag Decis (ahead-of-print) https://doi.org/10.1108/MD-03-2023-0325

Damsgaard J, Lyytinen K (2001) The role of intermediating institutions in the diffusion of electronic data interchange (EDI): how industry associations intervened in Denmark, Finland, and Hong Kong. Inf Soc 17(3):195–210

Marchiori DM, Rodrigues RG, Popadiuk S, Mainardes EW (2022) The relationship between human capital, information technology capability, innovativeness and organizational performance: an integrated approach. Technol Forecast Soc Change 177:121526

Marinelli L, Bartoloni S, Pascucci F, Gregori GL, Briamonte MF (2022) Genesis of an innovation-based entrepreneurial ecosystem: exploring the role of intellectual capital. J Intellect Cap 24(1):10–34

Mehralian G, Nazari JA, Ghasemzadeh P (2018) The effects of knowledge creation process on organizational performance using the BSC approach: the mediating role of intellectual capital. J Knowl Manag 22(4):802–823

Mitchell A (2023) Collaboration technology affordances from virtual collaboration in the time of COVID-19 and post-pandemic strategies. Inf Technol People 36(5):1982–2008

Muñoz JLR, Ojeda FM, Jurado DLA, Peña PFP, Carranza CPM, Berríos HQ, Vasquez-Pauca MJ (2022) Systematic review of adaptive learning technology for learning in higher education. Eurasia J Educ Res 98(98):221–233

Nezam MHK, Ataffar A, Isfahani AN, Shahin A (2013) The impact of structural capital on new product development performance effectiveness—-the mediating role of new product vision and competitive advantage. Int J Hum Resour Stud 3(4):281

O’Dwyer M, Filieri R, O’Malley L (2023) Establishing successful university–industry collaborations: barriers and enablers deconstructed. J Technol Transf 48(3):900–931

Oliver C (1997) Sustainable competitive advantage: combining institutional and resource‐based views. Strateg Manag J 18(9):697–713

Pak J, Heidarian Ghaleh H, Mehralian G (2023) How does human resource management balance exploration and exploitation? The differential effects of intellectual capital‐enhancing HR practices on ambidexterity and firm innovation. Human Resource Manag https://doi.org/10.1002/hrm.22180

Paoloni M, Coluccia D, Fontana S, Solimene S (2020) Knowledge management, intellectual capital and entrepreneurship: a structured literature review. J Knowl Manag 24(8):1797–1818

Patnaik S, Munjal S, Varma A, Sinha S (2022) Extending the resource-based view through the lens of the institution-based view: a longitudinal case study of an Indian higher educational institution. J Bus Res 147:124–141

Pellegrini L, Aloini D, Latronico L (2022) Open innovation and intellectual capital during emergency: evidence from a case study in telemedicine. Knowl Manag Res Pract 21(4), 765–776

Phan LT, Nguyen TV, Luong QC, Nguyen TV, Nguyen HT, Le HQ, Pham QD (2020) Importation and human-to-human transmission of a novel coronavirus in Vietnam. N Engl J Med 382(9):872–874

Article   PubMed   PubMed Central   Google Scholar  

Phuong QN, Le Ngoc M, Dong HT, Thao TLT, Tran T, Cac T (2024) Enhancing employment opportunities for people with disabilities in Vietnam: the role of vocational training and job placement centers. J Chin Hum Resour Manag 15(3):64–75

Podsakoff N (2003) Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol 885(879):10.1037

Podsakoff PM, MacKenzie SB, Lee J-Y, Podsakoff NP (2003) Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol 88(5):879

Preacher KJ, Hayes AF (2008) Asymptotic and resampling strategies for assessing and comparing indirect effects inmultiple mediator models. Behav Res Methods 40(3):879–891

Rådberg KK, Löfsten H (2024) The entrepreneurial university and development of large-scale research infrastructure: Exploring the emerging university function of collaboration and leadership. J Technol Transf 49(1):334–366

Radhamani R, Kumar D, Nizar N, Achuthan K, Nair B, Diwakar S (2021) What virtual laboratory usage tells us about laboratory skill education pre-and post-COVID-19: Focus on usage, behavior, intention and adoption. Educ Inf Technol 26(6):7477–7495

Rasheed MH, Khalid J, Ali A, Rasheed MS, Ali K (2024) Human resource analytics in the era of artificial intelligence: Leveraging knowledge towards organizational success in Pakistan. J Chin Hum Resour Manag 15:3–20

Ringle CM, Sarstedt M, Mitchell R, Gudergan SP (2020) Partial least squares structural equation modeling in HRM research. Int J Hum Resour Manag 31(12):1617–1643

Roos G, Roos J (1997) Measuring your company’s intellectual performance. Long Range Plan 30(3):413–426

Salamzadeh A, Tajpour M, Hosseini E, Brahmi MS (2023) Human capital and the performance of Iranian Digital Startups: the moderating role of knowledge sharing behaviour. Int J Public Sect Perform Manag 12(1-2):171–186

Sarwar A, Mustafa A (2023) Analysing the impact of green intellectual capital on environmental performance: the mediating role of green training and development. Technol Anal Strateg Manag 1–14. https://doi.org/10.1080/09537325.2023.2209205

Scott WR (2008) Institutions and organizations: ideas and interests. Sage

Secundo G, Dumay J, Schiuma G, Passiante G (2016) Managing intellectual capital through a collective intelligence approach: an integrated framework for universities. J Intellect Cap 17(2):298–319

Secundo G, Massaro M, Dumay J, Bagnoli C (2018) Intellectual capital management in the fourth stage of IC research: a critical case study in university settings. J Intellect Cap 19(1):157–177

Shao JJ, Ariss AA (2020) Knowledge transfer between self-initiated expatriates and their organizations: research propositions for managing SIEs. Int Bus Rev 29(1):101634

Shofiyyah NA, Komarudin TS, Hasan MSR (2023) Innovations in Islamic Education Management within the University Context: addressing challenges and exploring future prospects. Nidhomul Haq 8(2):193–209

Sigala M, Ren L, Li Z, Dioko LA (2023) Talent management in hospitality during the COVID-19 pandemic in Macao: a contingency approach. Int J Contemp Hosp Manag 35(8):2773–2792

Singh SK, Gupta S, Busso D, Kamboj S (2021) Top management knowledge value, knowledge sharing practices, open innovation and organizational performance. J Bus Res 128:788–798

Sobaih AEE, Hasanein A, Elshaer IA (2022) Higher education in and after COVID-19: the impact of using social network applications for e-learning on students’ academic performance. Sustainability 14(9):5195

Article   CAS   Google Scholar  

Sommer LP, Heidenreich S, Handrich M (2017) War for talents—how perceived organizational innovativeness affects employer attractiveness. RD Manag 47(2):299–310

Stewart T (1991) Brainpower: how intellectual capital is becoming America’s most valuable. Fortune

Streukens S, Leroi-Werelds S (2016) Bootstrapping and PLS-SEM: A step-by-step guide to get more out of your bootstrap results. Eur Manage J 34(6):618–632

Sulaiman F, Uden L, Eldy EF (2022) Online Learning in Higher Education Institution During COVID-19: A Review and the Way Forward. Paper presented at the International Workshop on Learning Technology for Education Challenges

Susanto P, Sawitri NN, Ali H, Rony ZT (2023) Employee performance and talent management impact increasing construction company productivity. Int J Psychol Health Sci 1(4):144–152

Tan CN-L, Md. Noor S (2013) Knowledge management enablers, knowledge sharing and research collaboration: a study of knowledge management at research universities in Malaysia. Asian J Technol Innov 21(2):251–276

Vaiman V, Sparrow P, Schuler R, Collings DG (2018) Macro talent management: a global perspective on managing talent in developed markets. Routledge

Vătămănescu E-M, Cegarra-Navarro J-G, Martínez-Martínez A, Dincă V-M, Dabija D-C (2023) Revisiting online academic networks within the COVID-19 pandemic–From the intellectual capital of knowledge networks towards institutional knowledge capitalization. J Intellect Cap 24(4):948–973

Wang Y, Lee L-H, Braud T, Hui P (2022) Re-shaping Post-COVID-19 teaching and learning: A blueprint of virtual-physical blended classrooms in the metaverse era. Paper presented at the 2022 IEEE 42nd International Conference on Distributed Computing Systems Workshops (ICDCSW)

Wang Z, Wang N, Liang H (2014) Knowledge sharing, intellectual capital and firm performance. Manag Decis 52(2):230–258

Xu A, Li Y, Donta PK (2024) Marketing decision model and consumer behavior prediction with deep learning. J Organ End Use Comput (JOEUC) 36(1):1–25

Yang G, Xiangming L (2024) Graduate socialization and anxiety: insights via hierarchical regression analysis and beyond. Stud High Educ 1–17. https://doi.org/10.1080/03075079.2024.2375563

Zada M, Khan J, Saeed I, Zada S, Jun ZY (2023) Linking public leadership with project management effectiveness: mediating role of goal clarity and moderating role of top management support. Heliyon 9(5)

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Conceptualization: Muhammad Zada and Imran Saeed. Methodology: Jawad Khan. Software: Shagufta Zada. Data collection: Muhammad Zada, Shagufta Zada and Jawad Khan. Formal analysis: Imran Saeed and Jawad Khan. Resources: Muhammad Zada. Writing original draft preparation: Muhammad Zada and Imran Saeed. Writing review and editing: Jawad Khan, Shagufta Zada. All authors have read and agreed to the published version of the paper.

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Zada, M., Saeed, I., Khan, J. et al. Navigating post-pandemic challenges through institutional research networks and talent management. Humanit Soc Sci Commun 11 , 1164 (2024). https://doi.org/10.1057/s41599-024-03697-9

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Challenges and solutions for sustainable ict: the role of file storage.

1. Introduction

2. background literature review, 2.1. conceptualization, 2.2. technological issues, 2.2.1. data processing, 2.2.2. data transmission, 2.2.3. data storage, 2.3. business issues, 2.3.1. adoption and acceptance of cloud storage, 2.3.2. the problem with data hoarding, 2.3.3. measurement of the environmental impact of data, 2.3.4. regulatory compliance, 2.4. application domains, 2.4.1. knowledge management, 2.4.2. e-science, 2.4.3. e-health, 2.4.4. iot and mobile computing, 2.5. emerging challenges, 3. addressing challenges: multiple perspectives from leading experts, 3.1. contribution 1—the importance of educational campaigns and awareness of sustainability, 3.2. contribution 2—energy-aware data management strategies, 3.3. contribution 3—the role of simplification and standardization of the processes related to reporting carbon emissions from ict services, 3.4. contribution 4—the role of regulatory interventions in promoting sustainable ict practices, 3.5. contribution 5—the role of inter-organizational collaborative projects focused on specific application domains, 3.5.1. public–private partnership: the case of the digital innovation zone, 3.5.2. academic/industry research on sustainable energy consumption in wireless communication in the telecommunication sector, 3.5.3. academia/industry research within european-funded projects, 4. discussion and recommendations for future research, 4.1. interpretation of the results, 4.2. implications, 4.3. limitations, 4.4. future work, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

• Saeed, N. Intelligent MANET Optimisation System. Ph.D. Thesis, Brunel University School of Engineering and Design, Uxbridge, UK, 2011. [ Google Scholar ]
• Saeed, N.; Urbonaviciusa, A. IoT leak detection system for building hydronic pipes. Int. J. Eng. Manuf. (IJEM) 2019 , 9 , 1–21. [ Google Scholar ]
• OECD. OECD Digital Economy Outlook 2020 ; OECD Library: Paris, France, 2020. [ Google Scholar ] [ CrossRef ]
• Fouladfar, M.H.; Saeed, N.; Marzband, M.; Franchini, G. Home-microgrid energy management strategy considering EV’s participation in DR. Energies 2021 , 14 , 5971. [ Google Scholar ] [ CrossRef ]
• World Economic Forum & PwC. Harnessing Technology for the Global Goals: A Framework for Government Action. 2021. Available online: https://assets.2030vision.com/files/resources/wef-harnessing-technology-for-the-global-goals-2021.pdf (accessed on 2 May 2024).
• Oleiwi, H.W.; Saeed, N.; Al-Taie, H.L.; Mhawi, D.N. An Enhanced Interface Selectivity Technique to Improve the QoS for the Multi-homed Node. Eng. Technol. J. 2022 , 40 , 101–109. [ Google Scholar ] [ CrossRef ]
• Santarius, T.; Dencik, L.; Diez, T.; Ferreboeuf, H.; Jankowski, P.; Hankey, S.; Hilbeck, A.; Hilty, L.; Höjer, M.; Kleine, D.; et al. Digitalization and sustainability: A call for a digital green deal. Environ. Sci. Policy 2023 , 147 , 11–14. [ Google Scholar ] [ CrossRef ]
• Holzmann, P.; Gregori, P. The promise of digital technologies for sustainable entrepreneurship: A systematic literature review and research agenda. Int. J. Inf. Manag. 2023 , 68 , 102593. [ Google Scholar ] [ CrossRef ]
• Guandalini, I. Sustainability through digital transformation: A systematic literature review for research guidance. J. Bus. Res. 2022 , 148 , 456–471. [ Google Scholar ] [ CrossRef ]
• Pan, S.L.; Carter, L.; Tim, Y.; Sandeep, M.S. Digital sustainability, climate change, and information systems solutions: Opportunities for future research. Int. J. Inf. Manag. 2022 , 63 , 102444. [ Google Scholar ] [ CrossRef ]
• Vial, G. Understanding digital transformation: A review and a research agenda. J. Strateg. Inf. Syst. 2019 , 28 , 118–144. [ Google Scholar ] [ CrossRef ]
• European Parliament; Directorate General for Parliamentary Research Services; IDATE; ECORYS; Fraunhofer Fokus. Key Enabling Technologies for Europe’s Technological Sovereignty ; Publications Office: Brussels, Belgium, 2021; Available online: https://data.europa.eu/doi/10.2861/24482 (accessed on 2 May 2024).
• Schwab, K.; The Fourth Industrial Revolution. World Economic Forum. 2015. Available online: https://www.weforum.org/about/the-fourth-industrial-revolution-by-klaus-schwab/ (accessed on 2 May 2024).
• Dwivedi, Y.K.; Hughes, L.; Kar, A.K.; Baabdullah, A.M.; Grover, P.; Abbas, R.; Andreini, D.; Abumoghli, I.; Barlette, Y.; Bunker, D.; et al. Climate change and COP26: Are digital technologies and information management part of the problem or the solution? An editorial reflection and call to action. Int. J. Inf. Manag. 2022 , 63 , 102456. [ Google Scholar ] [ CrossRef ]
• Truong, T.C. The impact of digital transformation on environmental sustainability. Adv. Multimed. 2022 , 2022 , 6324325. [ Google Scholar ] [ CrossRef ]
• Siddik, M.A.B.; Shehabi, A.; Marston, L. The environmental footprint of data centers in the United States. Environ. Res. Lett. 2021 , 16 , 064017. [ Google Scholar ] [ CrossRef ]
• Manganelli, M.; Soldati, A.; Martirano, L.; Ramakrishna, S. Strategies for improving the sustainability of data centers via energy mix, energy conservation, and circular energy. Sustainability 2021 , 13 , 6114. [ Google Scholar ] [ CrossRef ]
• Jones, N. How to stop data centres from gobbling up the world’s electricity. Nature 2018 , 561 , 163–166. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Koomey, J. Growth in data center electricity use 2005 to 2010. Rep. Anal. Press Complet. Req. N. Y. Times 2011 , 9 , 161. [ Google Scholar ]
• Rong, H.; Zhang, H.; Xiao, S.; Li, C.; Hu, C. Optimizing energy consumption for data centers. Renew. Sustain. Energy Rev. 2016 , 58 , 674–691. [ Google Scholar ] [ CrossRef ]
• Masanet, E.; Shehabi, A.; Lei, N.; Smith, S.; Koomey, J. Recalibrating global data center energy-use estimates. Science 2020 , 367 , 984–986. [ Google Scholar ] [ CrossRef ]
• Mytton, D. Assessing the suitability of the Greenhouse Gas Protocol for calculation of emissions from public cloud computing workloads. J. Cloud Comput. 2020 , 9 , 1–10. [ Google Scholar ]
• IEA. Data Centres and Data Transmission Networks. IEA. 2023. Available online: https://www.iea.org/energy-system/buildings/data-centres-and-data-transmission-networks (accessed on 2 May 2024).
• Climatiq. Measuring Greenhouse Gas Emissions in Data Centres: The Environmental Impact of Cloud Computing. 2022. Available online: https://www.climatiq.io/blog/measure-greenhouse-gas-emissions-carbon-data-centres-cloud-computing (accessed on 10 May 2024).
• Dissanayake, D.; Kuruppu, S.; Qian, W.; Tilt, C. Barriers for sustainability reporting: Evidence from Indo-Pacific region. Meditari Account. Res. 2020 , 29 , 264–293. [ Google Scholar ] [ CrossRef ]
• Amendola, C.; Savastano, M.; Gorelova, I. Green cloud computing for sustainable energy management: A comparison of innovative strategies for implementing the green economy. Int. J. Environ. Policy Decis. Mak. 2021 , 3 , 77–96. [ Google Scholar ] [ CrossRef ]
• Kumar, S.; Buyya, R. Green cloud computing and environmental sustainability. In Harnessing Green IT: Principles and Practices ; Wiley-IEEE Press: Hoboken, NJ, USA, 2012; pp. 315–339. [ Google Scholar ]
• Bagale, G.S.; Vandadi, V.R.; Singh, D.; Sharma, D.K.; Garlapati, D.V.K.; Bommisetti, R.K.; Gupta, R.K.; Setiawan, R. Small and Medium-Sized Enterprises’ Contribution in Digital Technology. Ph.D. Thesis, Petra Christian University, Jawa Timur, Indonesia, 2021. [ Google Scholar ]
• IDC & Statista. Volume of Data/Information Created, Captured, Copied, and Consumed Worldwide from 2010 to 2020, with Forecasts from 2021 to 2025. 2023. Available online: https://www.statista.com/statistics/871513/worldwide-data-created/ (accessed on 10 April 2024).
• Veritas Technologies LLC. The Databerg: See What Others Don’t. 2015. Available online: https://www.northdoor.co.uk/wp-content/uploads/2018/10/Veritas-Global-Databerg-Infographic.pdf (accessed on 2 May 2024).
• Omdia. The Unseen Environmental Cost of Data. 2023. Available online: https://services.global.ntt/en-us/campaigns/the-unseen-environmental-cost-of-data (accessed on 15 May 2024).
• Whitehead, B.; Andrews, D.; Shah, A.; Maidment, G. Assessing the environmental impact of data centres part 1: Background, energy use and metrics. Build. Environ. 2014 , 82 , 151–159. [ Google Scholar ] [ CrossRef ]
• Haug, N.; Dan, S.; Mergel, I. Digitally induced change in the public sector: A systematic review and research agenda. Public Manag. Rev. 2023 , 26 , 1963–1987. [ Google Scholar ] [ CrossRef ]
• Glassmire, J.; Bitaraf, H.; Papadakis, S.; Oudalov, A. Accelerating data center decarbonization and maximizing renewable usage with grid edge solutions. In Proceedings of the 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE), Grenoble, France, 1–5 February 2021; pp. 288–293. [ Google Scholar ]
• Rostirolla, G.; Grange, L.; Minh-Thuyen, T.; Stolf, P.; Pierson, J.; Da Costa, G.; Baudic, G.; Haddad, M.; Kassab, A.; Nicod, J.; et al. A survey of challenges and solutions for the integration of renewable energy in datacenters. Renew. Sustain. Energy Rev. 2022 , 155 , 111787. [ Google Scholar ] [ CrossRef ]
• Wang, Z.; Chen, S.; Bai, L.; Gao, J.; Tao, J.; Bond, R.R.; Mulvenna, M.D. Reinforcement learning based task scheduling for environmentally sustainable federated cloud computing. J. Cloud Comput. 2023 , 12 , 174. [ Google Scholar ] [ CrossRef ]
• Jackson, T.; Hodgkinson, I.R. Is there a role for knowledge management in saving the planet from too much data? Knowl. Manag. Res. Pract. 2023 , 21 , 427–435. [ Google Scholar ] [ CrossRef ]
• Veritas Technologies LLC. The Data Hoarding Report. 2018. Available online: https://www.veritas.com/content/dam/Veritas/docs/reports/Veritas-Data-Hoarders-Report-US.pdf (accessed on 2 May 2024).
• Yang, H.; Tate, M. A descriptive literature review and classification of cloud computing research. Commun. Assoc. Inf. Syst. 2012 , 31 , 2. [ Google Scholar ] [ CrossRef ]
• Senyo, P.K.; Addae, E.; Boateng, R. Cloud computing research: A review of research themes, frameworks, methods and future research directions. Int. J. Inf. Manag. 2018 , 38 , 128–139. [ Google Scholar ] [ CrossRef ]
• Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G.; PRISMA Group, T. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Ann. Intern. Med. 2009 , 151 , 264–269. [ Google Scholar ] [ CrossRef ]
• Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ 2021 , 372 , n71. [ Google Scholar ] [ CrossRef ]
• Mersy, G.; Krishnan, S. Toward a Life Cycle Assessment for the Carbon Footprint of Data. In Proceedings of the 2nd Workshop on Sustainable Computer Systems, Boston, MA, USA, 9 July 2023; pp. 1–9. [ Google Scholar ] [ CrossRef ]
• Pazienza, A.; Baselli, G.; Vinci, D.C.; Trussoni, M.V. A holistic approach to environmentally sustainable computing. Innov. Syst. Softw. Eng. 2024 , 20 , 347–371. [ Google Scholar ] [ CrossRef ]
• Karuppasamy, M.; Balakannan, S.P. Energy saving from cloud resources for a sustainable green cloud computing environment. J. Cyber Secur. Mobil. 2018 , 7 , 95–108. [ Google Scholar ]
• Gill, S.S.; Buyya, R. A taxonomy and future directions for sustainable cloud computing: 360 degree view. ACM Comput. Surv. CSUR 2018 , 51 , 1–33. [ Google Scholar ] [ CrossRef ]
• Dougherty, B.; White, J.; Schmidt, D.C. Model-driven auto-scaling of green cloud computing infrastructure. Future Gener. Comput. Syst. 2012 , 28 , 371–378. [ Google Scholar ] [ CrossRef ]
• Larumbe, F.; Sanso, B. A tabu search algorithm for the location of data centers and software components in green cloud computing networks. IEEE Trans. Cloud Comput. 2013 , 1 , 22–35. [ Google Scholar ] [ CrossRef ]
• Cui, X.; Mills, B.; Znati, T.; Melhem, R. Shadow replication: An energy-aware, faulttolerant computational model for green cloud computing. Energies 2014 , 7 , 5151–5176. [ Google Scholar ] [ CrossRef ]
• Khalil, M.I.K.; Ahmad, I.; Shah, S.A.A.; Jan, S.; Khan, F.Q. Energy cost minimization for sustainable cloud computing using option pricing. Sustain. Cities Soc. 2020 , 63 , 102440. [ Google Scholar ] [ CrossRef ]
• Liu, J.; Wang, S.; Zhou, A.; Xu, J.; Yang, F. SLA-driven container consolidation with usage prediction for green cloud computing. Front. Comput. Sci. 2020 , 14 , 42–52. [ Google Scholar ] [ CrossRef ]
• Ahmad, A.; Khan, R.A.; Khan, S.U.; Alwageed, H.S.; Al-Atawi, A.A.; Lee, Y. Green cloud computing adoption challenges and practices: A client’s perspective-based empirical investigation. Cogn. Technol. Work 2023 , 25 , 427–446. [ Google Scholar ] [ CrossRef ]
• Itani, W.; Ghali, C.; Kayssi, A.; Chehab, A.; Elhajj, I. G-Route: An energy-aware service routing protocol for green cloud computing. Clust. Comput. 2015 , 18 , 889–908. [ Google Scholar ] [ CrossRef ]
• Mohammadzadeh, A.; Masdari, M.; Gharehchopogh, F.S.; Jafarian, A. Improved chaotic binary grey wolf optimization algorithm for workflow scheduling in green cloud computing. Evol. Intell. 2021 , 14 , 1997–2025. [ Google Scholar ] [ CrossRef ]
• Khaleel, M.I. Synergies between resource sustainability and energy performance of cloud servers: The role of virtual machine repacking approach. Comput. Electr. Eng. 2023 , 106 , 108568. [ Google Scholar ] [ CrossRef ]
• Almutairi, L.; Aslam, S.M. A Novel Energy and Communication Aware Scheduling on Green Cloud Computing. Comput. Mater. Contin. 2023 , 77 , 2791–2811. [ Google Scholar ] [ CrossRef ]
• Cao, M.; Li, Y.; Wen, X.; Zhao, Y.; Zhu, J. Energy-aware intelligent scheduling for deadline-constrained workflows in sustainable cloud computing. Egypt. Inform. J. 2023 , 24 , 277–290. [ Google Scholar ] [ CrossRef ]
• Lu, Y.; Sun, N. An effective task scheduling algorithm based on dynamic energy management and efficient resource utilization in green cloud computing environment. Clust. Comput. 2021 , 22 (Suppl. 1), 513–520. [ Google Scholar ] [ CrossRef ]
• Mishra, S.K.; Puthal, D.; Sahoo, B.; Jena, S.K.; Obaidat, M.S. An adaptive task allocation technique for green cloud computing. J. Supercomput. 2018 , 74 , 370–385. [ Google Scholar ] [ CrossRef ]
• Li, J.; Li, B.; Wo, T.; Hu, C.; Huai, J.; Liu, L.; Lam, K.P. CyberGuarder: A virtualization security assurance architecture for green cloud computing. Future Gener. Comput. Syst. 2012 , 28 , 379–390. [ Google Scholar ] [ CrossRef ]
• Stergiou, C.; Psannis, K.E.; Gupta, B.B.; Ishibashi, Y. Security, privacy & efficiency of sustainable Cloud Computing for Big Data & IoT. Sustain. Comput. Inform. Syst. 2018 , 19 , 174–184. [ Google Scholar ] [ CrossRef ]
• Baliga, J.; Ayre, R.; Hinton, K.; Tucker, R.S. Energy consumption in wired and wireless access networks. IEEE Commun. Mag. 2011 , 49 , 70–77. [ Google Scholar ] [ CrossRef ]
• Wang, S.; Chen, H.; Wu, L.; Wang, J. A novel smart meter data compression method via stacked convolutional sparse auto-encoder. Int. J. Electr. Power Energy Syst. 2020 , 118 , 105761. [ Google Scholar ] [ CrossRef ]
• Al Kez, D.; Foley, A.M.; Laverty, D.; Del Rio, D.F.; Sovacool, B. Exploring the sustainability challenges facing digitalization and internet data centers. J. Clean. Prod. 2022 , 371 , 133633. [ Google Scholar ] [ CrossRef ]
• Avgerinou, M.; Bertoldi, P.; Castellazzi, L. Trends in data centre energy consumption under the european code of conduct for data centre energy efficiency. Energies 2017 , 10 , 1470. [ Google Scholar ] [ CrossRef ]
• You, X.; Lv, X.; Zhao, Z.; Han, J.; Ren, X. A survey and taxonomy on Energy-aware data management strategies in Cloud environment. IEEE Access 2020 , 8 , 94279–94293. [ Google Scholar ] [ CrossRef ]
• Ray, P.P. The green grid saga-a green initiative to data centers: A review. arXiv 2012 , arXiv:1208.0593. [ Google Scholar ]
• Elzeiny, A.; Elfetouh, A.A.; Riad, A. Cloud storage: A survey. Int. J. Emerg. Trends Technol. Comput. Sci. IJETTCS 2013 , 2 , 342–349. [ Google Scholar ]
• Nguyen, G.T.; Liaw, S.Y. Understanding the factors affecting the small and medium enterprises adoption of cloud computing: A literature review. Int. J. Bus. Manag. Econ. 2022 , 3 , 149–162. [ Google Scholar ] [ CrossRef ]
• Eurostat. Cloud Computing—Statistics on the Use by Enterprises. 2024. Available online: https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Cloud_computing_-_statistics_on_the_use_by_enterprises (accessed on 10 May 2024).
• Maresova, P.; Kacetl, J. Cloud computing in the public sector–Case study in educational institution. Procedia-Soc. Behav. Sci. 2015 , 182 , 341–348. [ Google Scholar ] [ CrossRef ]
• Armbrust, M.; Fox, A.; Griffith, R.; Joseph, A.D.; Katz, R.; Konwinski, A.; Lee, G.; Patterson, D.; Rabkin, A.; Stoica, I.; et al. A view of cloud computing. Commun. ACM 2010 , 53 , 50–58. [ Google Scholar ] [ CrossRef ]
• Jackson, T.W.; Hodgkinson, I.R. Keeping a lower profile: How firms can reduce their digital carbon footprints. J. Bus. Strategy 2023 , 44 , 363–370. [ Google Scholar ] [ CrossRef ]
• Pańkowska, M.; Pyszny, K.; Strzelecki, A. Users’ adoption of sustainable cloud computing solutions. Sustainability 2020 , 12 , 9930. [ Google Scholar ] [ CrossRef ]
• Wamuyu, P.K. Use of cloud computing services in micro and small enterprises: A fit perspective. Int. J. Inf. Syst. Proj. Manag. 2022 , 5 , 59–81. [ Google Scholar ] [ CrossRef ]
• Dinca, V.M.; Dima, A.M.; Rozsa, Z. Determinants of cloud computing adoption by Romanian SMEs in the digital economy. J. Bus. Econ. Manag. 2019 , 20 , 798–820. [ Google Scholar ] [ CrossRef ]
• Gartner. Gartner Forecasts Worldwide Public Cloud End-User Spending to Reach $ 679 Billion in 2024. 2023. Available online: https://www.enterprisetechprovider.com/multicloud/research-review-gartner-forecasts-public-cloud-end-user-spending-to-reach-679b-in-2024 (accessed on 2 May 2024).
• Obringer, R.; Rachunok, B.; Maia-Silva, D.; Arbabzadeh, M.; Nateghi, R.; Madani, K. The overlooked environmental footprint of increasing Internet use. Resour. Conserv. Recycl. 2021 , 167 , 105393. [ Google Scholar ] [ CrossRef ]
• Schien, D.; Shabajee, P.; Wickenden, J.; Picket, W.; Roberts, G.; Preist, C. The DIMPACT Tool for Environmental Assessment of Digital Services. In Proceedings of the 5th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies, Seattle, WA, USA, 29 June–1 July 2022; pp. 701–703. [ Google Scholar ]
• Philip, K.; Burkel, J.; Grunwald, S. Measure and Track Cloud Efficiency with Sustainability Proxy Metrics, Part II: Establish a Metrics Pipeline. 2023. Available online: https://aws.amazon.com/blogs/aws-cloudfinancial-management/measure-and-track-cloud-efficiency-with-sustainability-proxy-metrics-part-iiestablish-a-metrics-pipeline/ (accessed on 2 May 2024).
• Jisc. Exploring Digital Carbon Footprints. 2023. Available online: https://repository.jisc.ac.uk/8782/1/exploring-digital-carbon-footprints-report.pdf (accessed on 2 May 2024).
• Lannelongue, L.; Grealey, J.; Inouye, M. Green algorithms: Quantifying the carbon footprint of computation. Adv. Sci. 2021 , 8 , 2100707. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Green Web Foundation. CO2.JS. 2022. Available online: https://www.thegreenwebfoundation.org/co2-js/ (accessed on 2 May 2024).
• Barisits, M.; Beermann, T.; Berghaus, F.; Bockelman, B.; Bogado, J.; Cameron, D.; Christidis, D.; Ciangottini, D.; Dimitrov, G.; Elsing, M.; et al. Rucio: Scientific Data Management. Comput. Softw. Big Sci. 2019 , 3 , 11. [ Google Scholar ] [ CrossRef ]
• Mariette, J.; Blanchard, O.; Berné, O.; Aumont, O.; Carrey, J.; Ligozat, A.; Lellouch, E.; Roche, P.-E.; Guennebaud, G.; Thanwerdas, J.; et al. An open-source tool to assess the carbon footprint of research. Environ. Res. Infrastruct. Sustain. 2022 , 2 , 035008. [ Google Scholar ] [ CrossRef ]
• Wilkinson, R.; Mleczko, M.M.; Brewin, R.J.W.; Gaston, K.J.; Mueller, M.; Shutler, J.D.; Yan, X.; Anderson, K. Environmental impacts of earth observation data in the constellation and cloud computing era. Sci. Total Environ. 2024 , 909 , 168584. [ Google Scholar ] [ CrossRef ]
• Al-Issa, Y.; Ottom, M.A.; Tamrawi, A. eHealth Cloud Security Challenges: A Survey. J. Healthc. Eng. 2019 , 2019 , 7516035. [ Google Scholar ] [ CrossRef ]
• Tahir, A.; Chen, F.; Khan, H.U.; Ming, Z.; Ahmad, A.; Nazir, S.; Shafiq, M. A systematic review on cloud storage mechanisms concerning e-healthcare systems. Sensors 2020 , 20 , 5392. [ Google Scholar ] [ CrossRef ]
• Jeon, J.; Kim, J.; Shin, M.; Kim, M. A Blockchain-Based Trust Model for Supporting Collaborative Healthcare Data Management. Comput. Syst. Sci. Eng. 2023 , 46 , 3403–3421. [ Google Scholar ] [ CrossRef ]
• Diene, B.; Rodrigues, J.J.P.C.; Diallo, O.; Ndoye, E.H.M.; Korotaev, V.V. Data management techniques for Internet of Things. Mech. Syst. Signal Process. 2020 , 138 , 106564. [ Google Scholar ] [ CrossRef ]
• Peñalvo, F.J.G.; Sharma, A.; Chhabra, A.; Singh, S.K.; Kumar, S.; Arya, V.; Gaurav, A. Mobile Cloud Computing and Sustainable Development: Opportunities, Challenges, and Future Directions. Int. J. Cloud Appl. Comput. 2022 , 12 , 1–20. [ Google Scholar ] [ CrossRef ]
• Boukerche, A.; Guan, S.; Grande, R.E.D. Sustainable Offloading in Mobile Cloud Computing: Algorithmic Design and Implementation. ACM Comput. Surv. 2020 , 52 , 1–37. [ Google Scholar ] [ CrossRef ]
• Belkhir, L.; Elmeligi, A. Assessing ICT global emissions footprint: Trends to 2040 & recommendations. J. Clean. Prod. 2018 , 177 , 448–463. [ Google Scholar ]
• Haneem, F.; Kama, N.; Taskin, N.; Pauleen, D.; Bakar, N.A.A. Determinants of master data management adoption by local government organizations: An empirical study. Int. J. Inf. Manag. 2019 , 45 , 25–43. [ Google Scholar ] [ CrossRef ]
• Chofreh, A.G.; Goni, F.A.; Shaharoun, A.M.; Ismail, S.; Klemeš, J.J. Sustainable enterprise resource planning: Imperatives and research directions. J. Clean. Prod. 2014 , 71 , 139–147. [ Google Scholar ] [ CrossRef ]
• DHCC. The Digital Humanities Climate Coalition Toolkit. 2024. Available online: https://sas-dhrh.github.io/dhcc-toolkit/ (accessed on 20 May 2024).
• The Open Group. The TOGAF® Standard , 10th ed. 2022. Available online: https://www.opengroup.org/togaf (accessed on 2 May 2024).
• The Open Group. The Open Footprint® Data Model Standard, Version 1.0, Snapshot 1. 2024. Available online: https://publications.opengroup.org/standards/s242 (accessed on 2 May 2024).
• Kamaludin, K.; Sundarasen, S. COVID-19 and online distance learning in Malaysia: A blessing or a curse? Front. Educ. 2023 , 8 , 1062219. [ Google Scholar ] [ CrossRef ]

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Mersico, L.; Abroshan, H.; Sanchez-Velazquez, E.; Saheer, L.B.; Simandjuntak, S.; Dhar-Bhattacharjee, S.; Al-Haddad, R.; Saeed, N.; Saxena, A. Challenges and Solutions for Sustainable ICT: The Role of File Storage. Sustainability 2024 , 16 , 8043. https://doi.org/10.3390/su16188043

Mersico L, Abroshan H, Sanchez-Velazquez E, Saheer LB, Simandjuntak S, Dhar-Bhattacharjee S, Al-Haddad R, Saeed N, Saxena A. Challenges and Solutions for Sustainable ICT: The Role of File Storage. Sustainability . 2024; 16(18):8043. https://doi.org/10.3390/su16188043

Mersico, Luigi, Hossein Abroshan, Erika Sanchez-Velazquez, Lakshmi Babu Saheer, Sarinova Simandjuntak, Sunrita Dhar-Bhattacharjee, Ronak Al-Haddad, Nagham Saeed, and Anisha Saxena. 2024. "Challenges and Solutions for Sustainable ICT: The Role of File Storage" Sustainability 16, no. 18: 8043. https://doi.org/10.3390/su16188043

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The Impact of Nomophobia: Exploring the Interplay Between Loneliness, Smartphone Usage, Self-control, Emotion Regulation, and Spiritual Meaningfulness in an Indonesian Context

• Published: 11 September 2024

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• Triantoro Safaria   ORCID: orcid.org/0000-0003-3551-1460 1 ,
• Nofrans Eka Saputra 2 &
• Diana Putri Arini 3  

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Nomophobia is characterized as an irrational fear or anxiety that arises when one is unable to use, contact, communicate, or access mobile phones. Previous research on nomophobia has been conducted mainly through an exploratory approach. Few studies have tested the theoretical model of nomophobia through a confirmatory analysis approach. Thus, this research contributes to filling the existing gap by testing a theoretical model of nomophobia. This cross-sectional study was conducted in Yogyakarta, Palembang, and Jambi, Indonesia. We used purposive sampling to recruit 689 students from various levels in those three cities to participate in this study. Specifically, the participants consisted of junior high school students ( n  = 245, 35.5%), high school students ( n  = 235, 34.2%), and college students ( n  = 209, 30.3%). Among them, 380 (55.2%) were women, and 309 (44.8%) were men. We used questionnaires to measure nomophobia, emotion regulation, self-control, spiritual meaningfulness, loneliness, and smartphone use. Data were analyzed using the structural equation model (SEM) analysis. Our findings revealed that emotional regulation, spiritual meaningfulness, and self-control had significant indirect effects on nomophobia. Furthermore, the intensity of smartphone use is a significant mediator that increases nomophobia in this model. Furthermore, the intensity of smartphone use is a significant mediator in this fit model. Future research should explore interventions that enhance emotional regulation, spiritual meaningfulness, and self-control to reduce nomophobia. Additionally, examining the specific mechanisms through which smartphone use mediates this relationship could provide deeper insights. Implementing educational programs on mindful smartphone usage and developing strategies to balance digital engagement may also prove beneficial.

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Adawi, M., Zerbetto, R., Re, T. S., Bisharat, B., Mahamid, M., Amital, H., Del Puente, G., & Bragazzi, N. L. (2019). Psychometric properties of the brief symptom inventory in homophobic subjects: Insights from primary confirmatory factor, exploratory factor, and clustering analyses in a sample of healthy Italian volunteers. Psychology Research and Behavior Management, 12 , 145–154. https://doi.org/10.2147/PRBM.S173282

Article   PubMed   PubMed Central   Google Scholar  

Adler, N. E. (2015). Disadvantage, self-control, and health. Proceedings of the National Academy of Sciences of the United States of America, 112 (33), 10078–10079. https://doi.org/10.1073/pnas.1512781112

Agbaria, Q., Mahamid, F., Ziya Berte, D., 2017. Social support, self-control, religiousness and engagement in high risk behaviors among adolescents. International Journal of Indian Psychology 4 (4), 13–33. https://doi.org/10.25215/0404.142

Aguilera-Manrique, G., Márquez-Hernández, V. V., Alcaraz-Córdoba, T., Granados-Gámez, G., Gutiérrez-Puertas, V., & Gutiérrez-Puertas, L. (2018). The relationship between nomophobia and distraction associated with smartphone use among nursing students in their clinical practicum. PLoS ONE, 13 (8), 1–14. https://doi.org/10.1371/journal.pone.0202953

Article   Google Scholar  

Ai, A. L., Hall, D., Pargament, K., et al. (2013). Posttraumatic growth in patients who survived cardiac surgery: The predictive and mediating roles of faith-based factors. Journal of Behavioral Medicine, 36 , 186–198. https://doi.org/10.1007/s10865-012-9412-6

Article   PubMed   Google Scholar  

Akn, A., Arslan, S., Arslan, N., Uysal, R., Sahran, M., 2015. Self-control/management and internet addiction. International Online Journal of Educational Sciences 7 (3), 95–100. https://doi.org/10.15345/iojes.2015.03.016

Aldao, A. (2013). The future of emotion regulation research: Capturing context. Perspectives on Psychological Science, 8 , 155–172. https://doi.org/10.1177/1745691612459518

Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010). Emotion-regulation strategies across psychopathology: A meta-analytic review. Clinical Psychology Review, 30 (2), 217–237.

Ali, A., Muda, M., Ridzuan, A. R., Nuji, M. N. N., Izzamuddin, M. H. M., & Latiff, D. I. A. (2017). The relationship between phone usage factors and nomophobia. Advanced Science Letters, 23 , 7610–7613.

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103 (3), 411–423. https://doi.org/10.1037/0033-2909.103.3.411

Argumosa-Villar, L.; Boada-Grau, J.; Vigil-Colet, A. (2017). Exploratory investigation of theoretical predictors of nomophobia using the Mobile Phone Involvement Questionnaire (PIQ). Journal of Adolescence, 56 , 127–135. [CrossRef]

Arpaci, I., Baloglu, M., Özteke, H. I., & Kesici, S. (2017). Individual differences in the relationship between attachment and nomophobia among college students: The mediating role of mindfulness. Journal of Medical Internet Research, 2017 (19), e404.

Arpaci, I.; Baloglu, M.; Kesici, ¸S. (2019). A multigroup analysis of the effects of individual differences in mindfulness on nomophobia. Inf. Dev Information Development., 35 , 333–341. [CrossRef]

Arpaci, I. (2022). Gender differences in the relationship between problematic Internet use and nomophobia. Current Psychology: A Journal for Diverse Perspectives on Diverse Psychological Issues, 41 (9), 6558–6567. https://doi.org/10.1007/s12144-020-01160-x

Avci, E. (2022). The difference between gender in terms of nomophobia in Turkey: A meta-analysis. The European Research Journal , 8(1), 74–83. https://doi.org/10.18621/eurj.865153 .

Baumeister, R. F., Vohs, K. D., Tice, D. M., Baumeister, R. F., Vohs, K. D., & Tice, D. M. (2007). The strength model of self control. Current Directions in Psychological Science, 16 (6), 351–355. https://doi.org/10.1111/j.1467-8721.2007.00534.x

Bekaroglu, E., & Yilmaz, T. (2020). Nomophobia: Differential diagnosis and treatment. Current Approaches in Psychiatry, 12 (1), 131–142. https://doi.org/10.18863/pgy.528897

Bian, M., & Leung, L. (2015). Linking loneliness, shyness, smartphone addiction symptoms, and patterns of smartphone use to social capital. Social Science Computer Review, 33 (1), 61–79. https://doi.org/10.1177/0894439314528779

Billieux, J., Van Der Linden, M., & Rochat, L. (2008). The role of impulsivity in actual and problematic use of the mobile phone. Applied Cognitive Psychology, 22 (9), 1195–1210. https://doi.org/10.1002/acp.1429

Billieux, J., Maurage, P., Lopez-Fernandez, O., Kuss, D. J., & Griffiths, M. D. (2015). Can disordered mobile phone use be considered a behavioral addiction? An update on current evidence and a comprehensive model for future research. Current Addiction Reports, 2 (2), 154–162.

Bonanno, G. A., & Burton, C. L. (2013). Regulatory flexibility: An individual differences perspective on coping and emotion regulation. Perspectives on Psychological Science, 8 , 591–612. https://doi.org/10.1177/174569161350411

Bragazzi, N. L., & Del Puente, G. (2014). A proposal for including nomophobia in the new DSM-V. Psychology Research and Behavior Management, 7 , 155–160.

Buctot, D. B., Kim, N., & Kim, S. H. (2020). The role of nomophobia and smartphone addiction in the lifestyle profiles of junior and senior high school students in the Philippines. Social Sciences & Humanities Open, 2 (1), 100035. https://doi.org/10.1016/j.ssaho.2020.100035

Byrne, B. M. (2001a). Structural equation modeling: Perspectives on the present and the future. International Journal of Testing, 1 (3–4), 327–334. https://doi.org/10.1080/15305058.2001.9669479

Byrne, B. M. (2001b). Structural equation modeling with AMOS, EQS, and LISREL: Comparative approaches to testing for the factorial validity of a measuring instrument. International Journal of Testing, 1 (1), 55–86. https://doi.org/10.1207/S15327574IJT0101_4

Cameron, L. D., & Overall, N. C. (2017). Suppression and expression as distinct emotion-regulation processes in daily interactions: Longitudinal and meta-analyses. Emotion, 18 , 465–480. https://doi.org/10.1037/emo00003

Carver, C. S., & Schreier, M. (2000). “On the structure of behavioral self-regulation,” in Handbook of Self-Regulation, eds M. Boekaerts, P. Pintrich, and M. Zeidner (San Diego, CA: Academic Press), 42–85.

Casey, D. M., Williams, R. J., Mossière, A. M., Schopflocher, D. P., el Guebaly, N., Hodgins, D. C., Smith, G. J., & Wood, R. T. (2011). The role of family, religiosity, and behavior in adolescent gambling. Journal of Adolescence, 34 , 841–851. https://doi.org/10.1016/j.adolescence.2011.02.002

Chiu, S. I. (2014). The relationship between life stress and smartphone addiction on Taiwanese university student: A mediation model of learning self-efficacy and social self-efficacy. Computers in Human Behavior, 34 , 49–57.

Clark, E. M., Williams, B. R., Huang, J., Roth, D. L., & Holt, C. L. (2018). A longitudinal study of religiosity, spiritual health locus of control, and health behaviors in a national sample of African Americans. Journal of Religion and Health, 57 (6), 2258. https://doi.org/10.1007/s10943-017-0548-0

Cosmides, L., and Tooby, J. (2000). “Evolutionary psychology and the emotions” in Handbook of emotions, eds M. Lewis and J. M. Haviland-Jones (New York, NY: Guilford Press), 91–115.

Dai, C., Tai, Z., & Ni, S. (2021). Smartphone use and psychological well-being among college students in China: A qualitative assessment. Frontiers in Psychology, 12 (September), 1–13. https://doi.org/10.3389/fpsyg.2021.708970

Damasio, A. (1994). L’erreur de Descartes . Odile Jacob.

Google Scholar  

Darvishi, M., Noori, M., Nazer, M. R., Sheikholeslami, S., & Karimi, E. (2019). Investigating different dimensions of nomophobia among medical students: A cross-sectional study. Open Access Macedonian Journal of Medical Sciences, 7 (4), 573–578. https://doi.org/10.3889/OAMJMS.2019.138

de Ridder, D. T. D., Lensvelt-Mulders, G., Finkenauer, C., Stok, F. M., & Baumeister, R. F. (2012). Taking stock of self-control: A meta-analysis of how trait self-control relates to a wide range of behaviors. Personality and Social Psychology Review, 16 (1), 76–99. https://doi.org/10.1177/1088868311418749

Debnam, K. J., Bradshaw, C. P., Milam, A. J., Mullen, M. M., & Lacey, K. (2017). The moderating role of spirituality in the association between stress and substance use among adolescents: Differences by gender. Journal of Youth Adolescence . https://doi.org/10.1007/s10964-017-0687-3

Dixit, S., Shukla, H., Bhagwat, A., Bindal, A., Goyal, A., Zaidi, A. K., & Shrivastava, A. (2010). A study to evaluate mobile phone dependence among students of a medical college and associated hospital of central India. Indian Journal of Community Medicine, 35 , 339–341.

Dongre, A. S., Inamdar, I. F., & Gattani, P. L. (2017). Nomophobia: A study to evaluate mobile phone dependence and impact of cell phone on health. National Journal of Community Medicine, 8 (11), 688–693.

Dragoi, V., & Staddon, J. E. R. (1999). The dynamics of operant conditioning. Psychological Review, 106 (1), 20–61. https://doi.org/10.1037/0033-295X.106.1.20

Durak, H. Y. (2018). Investigation of nomophobia and smartphone addiction predictors among adolescents in Turkey: Demographic variables and academic performance Investigation of nomophobia and smartphone addiction variables and academic performance. The Social Science Journal October. https://doi.org/10.1016/j.soscij.2018.09.003

Ekşi, H., & Kardaş, S. (2017). Spiritual well-being: Scale development and validation. Spiritual Psychology and Counseling, 2(1), 73–88 https://dergipark.org.tr/en/pub/spiritualpc/issue/29971/323508 .

Elhai, J. D., Dvorak, R. D., Levine, J. C., & Hall, B. J. (2017). Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology. Journal of Affective Disorders, 207 , 251–259.

Elhai, J. D., Tiamiyu, M. F., Weeks, J. W., Levine, J. C., Picard, K. J., & Hall, B. J. (2018a). Depression and emotion regulation predict objective smartphone use measured over one week. Personality and Individual Differences, 133 , 21–28.

Elhai, J. D., Levine, J. C., Hall, B. J., & Dvorak, R. D. (2018b). Types of smartphone usage and relations with problematic smartphone behaviors: The role of content consumption vs. social smartphone use. Cyberpsychology Behavior and Social Networking, 21 (11), 725–732.

A Enez Darcin S Kose CO Noyan S Nurmedov O Yılmaz N Dilbaz 2016 Smartphone addiction and its relationship with social anxiety and loneliness Behaviour and Information Technology 35 520 525

Fabes, R. A., Eisenberg, N., Jones, S., Smith, M., Guthrie, I., Poulin, R., Shepard, S., & Friedman, J. (1999). Regulation, emotionality, and preschoolers’ socially competent peer interactions. Child Development, 70 (2), 432–442. https://doi.org/10.1111/1467-8624.00031

Fishbach, A., and Ferguson, M. J. (2007). “The goal construct in social psychology,” in Social psychology: Handbook of basic principles, 2nd Edn, eds A. W. Kruglanski and E. T. Higgins (New York, NY: The Guilford Press), 490–515

Frijda, N. H. (1987). Emotion, cognitive structure, and action tendency. Cogn. Emot. 1, 115–143. oi: https://doi.org/10.1080/02699938708408043

Garland, E. L., Hanley, A. W., Riquino, M. R., Reese, S. E., Baker, A. K., Salas, K., Yack, B. P., Bedford, C. E., Bryan, M. A., Atchley, R., Nakamura, Y., Froeliger, B., & Howard, M. O. (2019). Mindfulness-oriented recovery enhancement reduces opioid misuse risk via analgesic and positive psychological mechanisms: A randomized controlled trial. Journal of Consulting and Clinical Psychology, 87 (10), 927–940. https://doi.org/10.1037/ccp0000390

Gatzounis, R., Schrooten, M. G., Crombez, G., & Vlaeyen, J. W. (2012). Operant learning theory in pain and chronic pain rehabilitation. Current Pain and Headache Reports, 16 (2), 117–126. https://doi.org/10.1007/s11916-012-0247-1

Geng, Y., Gu, J., Wang, J., & Zhang, R. (2021). Smartphone addiction and depression, anxiety: The role of bedtime procrastination and self-control. Journal of Affective Disorders, 293 (July), 415–421. https://doi.org/10.1016/j.jad.2021.06.062

Gratz, K. L., & Roemer, L. (2004). Multidimensional assessment of emotion regulation and dysregulation: Development, factor structure, and initial validation of the difficulties in emotion regulation scale. Journal of Psychopathology and Behavioral Assessment, 26 , 41–54. https://doi.org/10.1023/B:JOBA.0000007455.08539.94

Gross, J. J. (2015). Emotion regulation: Current status and future prospects. Psychological Inquiry, 26 (1), 1–26.

Gross, J. J., & Thompson, R. A. (2007). Emotion regulation: Conceptual foundations. in Handbook of Emotion Regulation, ed J. J. Gross (New York, NY: Guilford Press), 3–24

Gross, J. J., Richards, J. M., & John, O. P. (2006). Emotion regulation in everyday life. In D. K. Snyder, J. Simpson, & J. N. Hughes (Eds.), Emotion regulation in couples and families: Pathways to dysfunction and health (pp. 13–35). American Psychological Association. https://doi.org/10.1037/11468-001

Grubbs, J. B., Exline, J. J., Pargament, K. I., Volk, F., & Lindberg, M. J. (2017). Internet pornography use, perceived addiction, and religious/spiritual struggles. Archives of Sexual Behavior, 46(6), 17331745. Available from https://doi.org/10.1007/s10508-016-0772-9

Gruber, J., Mauss, I. B., & Tamir, M. (2011). A dark side of happiness? How, when, and why happiness is not always good. Perspectives on Psychological Science, 6 , 222–233. https://doi.org/10.1177/1745691611406927

Güner, T. A., & Demir, İ. (2021). Relationship between smartphone addiction and nomophobia, anxiety, self-control in high school students. The Turkish Journal on Addictions , 1–7. https://doi.org/10.5152/ADDICTA.2021.21089

Gutiérrez-Puertas, L., Márquez-Hernández, V. V., & Aguilera-Manrique, G. (2016). Adaptation and validation of the Spanish version of the nomophobia questionnaire in nursing studies. CIN - Computers Informatics Nursing, 34 (10), 470–475. https://doi.org/10.1097/CIN.0000000000000268

Gutiérrez-Puertas, L., Márquez-Hernández, V. V., São-Romão-Preto, L., Granados-Gámez, G., Gutiérrez-Puertas, V., & Aguilera-Manrique, G. (2019). Comparative study of nomophobia among Spanish and Portuguese nursing students. Nurse Education in Practice, 34 , 79–84. https://doi.org/10.1016/j.nepr.2018.11.010

Haines, S. J., Gleeson, J., Kuppens, P., Hollenstein, T., Ciarrochi, J., Labuschagne, I., et al. (2016). The difference between strategy and situation fit in emotion regulation in daily life is associated with well-being. Psychological Science, 27 , 1651–1659. https://doi.org/10.1177/0956797616669086

Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Tatham, R. L. (2005). Multivariate data analysis (6th ed.). Prentice Hall.

Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication Monographs, 76 (4), 408–420. https://doi.org/10.1080/03637750903310360

Heffner, K. L., Waring, M. E., Roberts, M. B., Eaton, C. B., & Gramling, R. (2011). Social isolation, C-reactive protein, and coronary heart disease mortality among community-dwelling adults. Social Science & Medicine, 72 , 1482–1488. https://doi.org/10.1016/j.socscimed.2011.03.016

Holmbeck, G. N. (2002). Post hoc probing of significant moderating and mediating effects in studies of pediatric populations. Journal of Pediatric Psychology Special Issue on Methodology and Design, 27 (1), 87–96.

Horton, G. E., Luna, N., & Malloy, T. (2016). Associations between spirituality, meaning in life, and depressive disorders among asample of individuals in treatment for substance use. Journal of Spirituality in Mental Health, 18 (4), 283–299.

Hwang, T.-J., Rabheru, K., Peisah, C., Reichman, W., & Ikeda, M. (2020). Loneliness and social isolation during the COVID-19 pandemic. International Psychogeriatrics, 32 (10), 1217–1220.

International Telecommunications Union (2014). Measuring the Information Society Report 2014. International Telecommunication Union Place des Nations CH-1211 Geneva Switzerland.

International Test Commission. (2017b). The ITC guidelines for translating and adapting tests (Second edition) . ITC Guidelines.

ITC Guidelines for Translating and adapting tests (Second Edition). (2017a). International Journal of Testing , 18 (2), 101–134. https://doi.org/10.1080/15305058.2017.1398166

Jahagirdar, V., Rama, K., Soppari, P., & Kumar, M. V. (2021). Mobile phones: Vital addiction or lethal addiction? Mobile phone usage patterns and assessment of mobile addiction among undergraduate medical students in Telangana, India. Journal of Addiction, 2021 , 1–6. https://doi.org/10.1155/2021/8750650

Jahrami, H., Trabelsi, K., Boukhris, O., Hussain, J. H., Alenezi, A. F., Humood, A., Saif, Z., Pandi-Perumal, S. R., & Seeman, M. V. (2023). The prevalence of mild, moderate, and severe nomophobia symptoms: A systematic review, meta-analysis, and meta-regression. Behavioral Sciences, 13 (1), 35. https://doi.org/10.3390/bs13010035

Jeste, D. V., Lee, E. E., & Cacioppo, S. (2020). Battling the modern behavioral epidemic of loneliness: Suggestions for research and interventions. JAMA Psychiatry . https://doi.org/10.1001/jamapsychiatry.2020.0027

M Kara K Baytemir F Inceman-kara M Kara 2019 Duration of daily smartphone usage as an antecedent of nomophobia: Exploring multiple mediation of loneliness and anxiety multiple mediation of loneliness and anxiety Behavior & Information Technology 1 14 https://doi.org/10.1080/0144929X.2019.1673485

Kardefelt-Winther, D. (2014). A conceptual and methodological critique of internet addiction research: Toward a model of compensatory internet use. Computers in Human Behavior, 31 , 351–354. https://doi.org/10.1016/j.chb.2013.10.059

Katz, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and gratifications research. The Public Opinion Quarterly, 37 (4), 509–523.

Kaur, A., Sharma, P., & Manu. (2015). A descriptive study to assess the risk of developing nomophobia among students of selected nursing colleges Ludhiana, Punjab. International Journal of Psychiatric Nursing , 1(2),1. https://doi.org/10.5958/2395-180X.2015.00051.1

Kaviani, F., Robards, B., Young, K. L., & Koppel, S. (2020). Nomophobia: Is the fear of being without a smartphone associated with problematic use? International Journal of Environmental Research and Public Health, 17 (17), 1–19. https://doi.org/10.3390/ijerph17176024

Keltner, D., & Kring, A. M. (1998). Emotion, social function, and psychopathology. Review of General Psychology, 2 , 320–342. https://doi.org/10.1037/1089-2680.2.3.320

Kim, J., LaRose, R., & Peng, W. (2009). Loneliness as the cause and the effect of problematic internet use: The relationship between internet use and psychological well-being. Cyberpsychology & Behavior : THe Impact of the Internet, Multimedia and Virtual Reality on Behavior and Society, 12 (4), 451–455. https://doi.org/10.1089/cpb.2008.0327

Kim, H. J., & Lee, J. M. (2018). Determinants of mobile digital information usage among senior consumers: Focusing on secondary digital divide. Family and Environment Research, 56 (4), 489–506.

Kinanti, D. R., & Hartati, N. (2017). The effect of self esteem, social support, and religious orientation toward cyberbullying intention on adolescent at senior high school. Tazkiyah: Journal of Psychology 22(2), 191–202. https://doi.org/10.15408/tazkiya.v22i2.8400

King, A. L. S., Valença, A. M., & Nardi, A. E. (2010). Nomophobia: The mobile phone in panic disorder with agoraphobia: Reducing phobias or worsening of dependence? Cognitive and Behavioral Neurology, 23 (1), 52–54. https://doi.org/10.1097/WNN.0b013e3181b7eabc

King, A. L. S., Valença, A. M., Silva, A. C. O., Baczynski, T., Carvalho, M. R., & Nardi, A. E. (2013). Nomophobia: Dependency on virtual environments or social phobia? Computers in Human Behavior, 2013 (29), 140–144.

King, A. L. S., Martins, A., Valença, A. M., Cardoso, A., Sancassiani, F., Machado, S., & Egidio, A. (2014). Nomophobia: Impact of cell phone use interfering with symptoms and emotions of individuals with panic disorder compared with a control group. Clinical Practice & Epidemiology in Mental Health, 2014 (10), 28–35.

Kirsch, I., Lynn, S. J., Vigorito, M., & Miller, R. R. (2004). The role of cognition in classical and operant conditioning. Journal of Clinical Psychology, 60 (4), 369–392. https://doi.org/10.1002/jclp.10251

Kline, R. B. (1998). Principles and practice of structural equation modeling . Guilford Press.

Kobayashi, L. C., & Steptoe, A. (2018). Social isolation, loneliness, and health behaviors at older age: Longitudinal cohort study. Annals of Behavioral Medicine, 52 , 582–593. https://doi.org/10.1093/ABM/kax033

Koenig, H. G. (2014). Religion, spirituality, and health: A review and update. Advances in Mind-Body Medicine, 29 (3), 19–26.

Koob, G. F., & Volkow, N. D. (2010). Neurocircuitry of addiction. Neuropsychopharmacology, 35 (1), 217–238.

Kuiper, J. S., et al. (2015). Social relationships and risk of dementia: A systematic review and meta-analysis of longitudinal cohort studies. Aging Research Reviews, 22 , 39–57. https://doi.org/10.1016/j.arr.2015.04.006

Kuscu, T. D., Gumustas, F., & Arman, A. R. (2020). The relationship between nomophobia and psychiatric symptoms in adolescents. International Journal of Psychiatry in Clinical Practice , 0 (0), 1–6. https://doi.org/10.1080/13651501.2020.1819334 .

Kwon, M., Kim, D. J., Cho, H., & Yang, S. (2013). The smartphone addiction scale: Development and validation of a short version for adolescents. PLoS ONE, 8 (12), e83558.

Landor, A., Simons, R. L., Gibbons, F. X., Simons, L. G., & Brody, G. H. (2011). The role of religiosity in the relationship between parents, peers, and adolescent risky sexual behavior. Journal of Youth Adolescence, 40 , 296–309. https://doi.org/10.1007/s10964-010-9598

Lee, S. Y. (2014). Examining the factors that influence early adopters’ smartphone adoption: The case of college students. Telematics and Informatics, 31 (2), 308–318.

Lee, S., Kim, M., Mendoza, J. S., & McDonough, I. M. (2018). Addicted to cellphones: Exploring the psychometric properties between the nomophobia questionnaire and obsessiveness in college students. Heliyon, 4 (11), e00895. https://doi.org/10.1016/j.heliyon.2018.e00895

Lee, E. E., Depp, C., Palmer, B. W., Glorioso, D., Daly, R., Liu, J., Tu, X. M., Kim, H. C., Tarr, P., Yamada, Y., & Jeste, D. V. (2019). High prevalence and adverse health effects of loneliness in community-dwelling adults across the lifespan: Role of wisdom as a protective factor. International Psychogeriatrics, 31 (10), 1447–1462. https://doi.org/10.1017/S10416102

Leigh-Hunt, N., et al. (2017). This is an overview of systematic reviews on the public health consequences of social isolation and loneliness. Public Health, 152 , 157–171. https://doi.org/10.1016/j.puhe.2017.07.035

León-Mejía, A. C., Gutiérrez-Ortega, M., Serrano-Pintado, I., & González-Cabrera, J. (2021). A systematic review on nomophobia prevalence: Surfacing results and standard guidelines for future research. PLoS ONE, 16(5 May), 1–22. https://doi.org/10.1371/journal.pone.0250509

Lin, Y. (2011). A study on the negative effects of smartphones on social life and wellbeing. International Journal of Business and Social Science, 2 (18), 19–23.

Lin, Y. H., & Lu, H. P. (2011). Why people use social networking sites: An empirical study integrating network externalities and motivation theory. Computers in Human Behavior, 27 (3), 1152–1161.

Liu, W., Chen, J.-S., Gan, W. Y., Poon, W. C., Tung, S. E. H., Lee, L. J., Xu, P., Chen, I.-H., Griffiths, M. D., & Lin, C.-Y. (2022). Associations of problematic internet use, weight-related self-stigma, and nomophobia with physical activity: Findings from Mainland China, Taiwan, and Malaysia.  International Journal of Environmental Research and Public Health, 19 (19), 12135. https://doi.org/10.3390/ijerph191912135

Luminet, O., and Curci, A. (2009). Flashbulb memories: New issues and new perspectives. Hove; New York: Psychology Press

Mauss, I. B., Evers, C., Wilhelm, F. H., & Gross, J. J. (2006). How to bite your tongue without blowing your top: Implicit evaluation of emotion regulation predicts affective responding to anger provocation. PSPB, 32 (5), 1–14. https://doi.org/10.1177/0146167205283841

Mendoza, J. S., Pody, B. C., Lee, S., Kim, M., & McDonough, I. M. (2018). The effect of cellphones on attention and learning: The influences of time, distraction, and nomophobia. Computers in Human Behavior, 86 , 52–60. https://doi.org/10.1016/j.chb.2018.04.027

Mertkan, D.; Burcin, N.; Sezen-Gultekin, G.; Gemikonakli, O. (2018). Relationship between nomophobia and fear of missing out among Turkish university students. Cypriot J. Educ. Sci. 2018, 13, 549–561. [CrossRef].

Metcalfe, J., Mischel, W., 1999. A hot/cool-system analysis of delay of gratification: Dynamics of willpower. Psychol. Rev. 106 (1), 3–19. https://doi.org/10.1037/0033-295X.106.1.3

Meyers, L. S., Gamst, G., & Guarino, A. J. (2006). Applied multivariate research: Design and interpretation . Sage Publications Inc.

Millgram, Y., Sheppes, G., Kalokerinos, E. K., Kuppens, P., & Tamir, M. (2019). Do the ends dictate the means in emotion regulation? Journal of Experimental Psychology: General, 148 , 80–96. https://doi.org/10.1037/xge0000477

Mir, R., & Akhtar, M. (2020). Effect of nomophobia on the anxiety levels of undergraduate students. Journal of the Pakistan Medical Association, 70 (9), 1492–1497. https://doi.org/10.5455/JPMA.31286

Moffitt, T. E., Arseneault, L., Belsky, D., Dickson, N., Hancox, R. J., & Harrington, H. (2011). A gradient of childhood self-control predicts health, wealth, and public safety. Proceedings of the National Academic of Sciences of the United States of America, 108 (7), 2693–2698. https://doi.org/10.1073/pnas.1010076108

Moreno-Guerrero, A. J., Belmonte, J., Romero-Rodríguez, J. M., & Rodríguez-García, A. M. (2020). Nomophobia: Impact of cell phone use and time to rest among teacher students. Heliyon, 6 (5), e04084. https://doi.org/10.1016/j.heliyon.2020.e04084

Notara, V., Vagka, E., Gnardellis, C., & Lagiou, A. (2021). The emerging phenomenon of nomophobia in young adults: A systematic review study. Addiction and Health, 13 (2), 120–136. https://doi.org/10.22122/ahj.v13i2.309

Ohman, A., Flykt, A., & Esteves, F. (2001). Emotion drives attention: Detecting the snake in the grass. Journal of Experimental Psychology, 130 , 466–478. https://doi.org/10.1037/0096-3445.130.3.466

Olivencia-Carrión, M. A., Ferri-García, R., del Rueda, M., Jiménez-Torres, M. G., & López-Torrecillas, F. (2018). Temperament and characteristics related to nomophobia. Psychiatry Research, 266 (May), 5–10. https://doi.org/10.1016/j.psychres.2018.04.056

Olson, M. M., Trevino, D. B., Geske, J. A., & Vanderpool, H. (2012). Religious coping and mental health outcomes: An exploratory study of socioeconomically disadvantaged patients. Explore (New York, N.Y.) , 8 (3), 172–176. https://doi.org/10.1016/j.explore.2012.02.005 .

Online, M. (2008). Nomophobia is the fear of being out of mobile phone contact – And it’s the plague of our 24/7 age. Retrieved, 15 (05), 2022.

Opatz, J. P. (1986). Stevens point: A longstanding program for students at a Midwestern university. American Journal of Health Promotion, 1 (1), 60–67.

Oulasvirta, A., Rattenbury, T., Ma, L., & Raita, E. (2012). Habits make smartphone use more pervasive. Personal and Ubiquitous Computing, 16 (1), 105–114.

Ownsworth, T. L., McFarland, K., & Young, R. M. (2002). The investigation of factors underlying deficits in selfawareness and self-regulation. Brain Injury, 16 (4), 291–309. https://doi.org/10.1080/02699050110103986

Ozdemir, B., Cakir, O., & Hussain, I. (2018). Prevalence of nomophobia among university students: A comparative study of Pakistani and Turkish undergraduate students. Eurasia Journal of Mathematics, Science and Technology Education , 14 (4), 1519–1532. https://doi.org/10.29333/ejmste/84839

Pargament, K. I. (2007). The psychology of religion and coping: Theory, research, practice . Guilford Press.

Parrott, W. G. (1993). Beyond hedonism: Motives for inhibiting good moods and for maintaining bad moods. In D. M. Wegner & J. W. Pennebaker (Eds.), Handbook of mental control (pp. 278–305). Prentice-Hall Inc.

Pessoa, L., Japee, S., & Ungerleider, L. G. (2005). Visual awareness and the detection of fearful faces. Emotion, 5 , 243–247. https://doi.org/10.1037/1528-3542.5.2.243

Phelps, E. A. (2006). Emotion and cognition: Insights from studies of the human amygdala. Annual Review of Psychology, 57 , 27–53. https://doi.org/10.1146/annurev.psych.56.091103.070234

Phillips, R. E., & Stein, C. H. (2007). God’s will, God’s punishment, or God’s limitations? Religious coping strategies reported by young adults living with serious mental illness. Journal of Clinical Psychology, 63 (6), 529–540.

Pieper, J. Z. T. (2004). Religious coping in highly religious psychiatric inpatients. Mental Health, Religion & Culture, 7 (4), 349–363. https://doi.org/10.1080/13674670410001719805

Pivetta, E., Harkin, L., Billieux, J., Kanjo, E., & Kuss, D. J. (2019). Problematic smartphone use: An empirically validated model. Computers in Human Behavior, 100 (May), 105–117. https://doi.org/10.1016/j.chb.2019.06.013

Przybylski, A. K., & Weinstein, N. (2017). A large-scale test of the goldilocks hypothesis: Quantifying the relations between digital-screen use and the mental well-being of adolescents. Psychological Science, 28 (2), 204–215.

Qiufeng, G., Fu, N., Xiang, Y., Jia, G., & Wu, S. (2021). Self-esteem and addictive smartphone use: The mediator role of anxiety and the moderator role of self-control. Children and Youth Services Review, 124 (5), 105990. https://doi.org/10.1016/j.childyouth.2021.105990

Rahmati, S. (2017). The relationship between psychological capital and spirituality with internet addiction among students at Jondishapuor University of Medical Sciences. Medical Ethics Journal, 10 (38), 7–17.

Ramirez, S. P., Macêdo, D. S., Sales, P. M., Figueiredo, S. M., Daher, E. F., Araújo, S. M., Pargament, K. I., Hyphantis, T. N., & Carvalho, A. F. (2012). The relationship between religious coping, psychological distress and quality of life in hemodialysis patients. Journal of Psychosomatic Research, 72 (2), 129–135. https://doi.org/10.1016/j.jpsychores.2011.11.012

Ramos-Soler, I., López-Sánchez, C., & Quiles-Soler, M. C. (2017). Adaptación y validación de la escala de nomofobia de Yildirim y Correia en estudiantes españoles de la Educación Secundaria Obligatoria. Health and Addictions/Salud y Drogas , 17 (2), 201–213. https://doi.org/10.21134/haaj.v17i2.332

Rodrıguez-Garcia, A. M., Moreno-Guerrero, A. J., & Lopez, B. J. (2020). Nomophobia: An individual’s growing fear of being without a smartphone-A systematic literature review. International Journal of Environmental Research and Public Health, 17 (2), 580. https://doi.org/10.3390/ijerph17020580

Roseman, I. J., Wiest, C., & Swartz, T. S. (1994). Phenomenology, behaviors, and goals differentiate discrete emotions. Journal of Personality and Social Psychology, 67 , 206–221. https://doi.org/10.1037/0022-3514.67.2.206

Rosen, L. D., Carrier, L. M., & Cheever, N. A. (2013a). Facebook and texting made me do it: Media-induced task-switching while studying. Computers in Human Behavior, 29 (3), 948–958.

Rosen, L. D., Whaling, K., Carrier, L. M., Cheever, N. A., & Rokkum, J. (2013b). The media and technology usage and attitudes scale: An empirical investigation. Computers in Human Behavior, 29 (6), 2501–2511.

Rosmarin, D. H., Bigda-Peyton, J. S., Öngur, D., Pargament, K. I., & Björgvinsson, T. (2013). Religious coping among psychotic patients: Relevance to suicidality and treatment outcomes. Psychiatry Research, 210 (1), 182–187. https://doi.org/10.1016/j.psychres.2013.03.023

Rudolph, K. D., Troop-Gordon, W., & Llewellyn, N. (2013). Interactive contributions of self-regulation deficits and social motivation to psychopathology: Unraveling divergent pathways to aggressive behavior and depressive symptoms. Development and Psychopathology, 25 (2), 407–418. https://doi.org/10.1017/S0954579412001149

Ruggiero, T. E. (2000). Uses and gratifications theory in the 21st century. Mass Communication & Society, 3 (1), 3–37.

Russell, D., Peplau, L. A., & Cutrona, C. E. (1980). The revised UCLA Loneliness Scale: Concurrent and discriminant validity evidence. Journal of Personality and Social Psychology, 39 (3), 472–480. https://doi.org/10.1037/0022-3514.39.3.472

Salehan, M., & Negahban, A. (2013). Social networking on smartphones: When mobile phones become addictive. Computers in Human Behavior, 29 (6), 2632–2639.

Salovey, P., & Mayer, J. D. (1990). Emotional intelligence. Imagination, Cognition and Personality, 9 (3), 185–211. https://doi.org/10.2190/DUGG-P24E-52WK-6CDG

SecurEnvoy, 2012 Sixty-six percent of the population suffers from nomophobia due to the fear of being without their phone Retrieved 12 05 14

Servidio, R. (2021). Self-control and problematic smartphone use among Italian University students: The mediating role of the fear of missing out and of smartphone use patterns. Current Psychology, 40 , 4101–4111.

Sheldrake, P. (2013). The new SCM dictionary of Christian Spirituality . SCM Press.

Sheppes, G., Scheibe, S., Suri, G., & Gross, J. J. (2011). Emotion-regulation choice. Psychological Science, 22 (11), 1391–1396. https://doi.org/10.1177/0956797611418350

Shim, J. Y. (2019). Christian spirituality and smartphone addiction in adolescents: A comparison of high-risk, potential-risk, and normal control groups. Journal of Religion and Health, 58 (4), 1272–1285. https://doi.org/10.1007/s10943-018-00751-0

Shmueli, D., & Prochaska, J. J. (2012). A test of positive affect induction for countering self-control depletion in cigarette smokers. Psychology of Addictive Behaviors, 26 (1), 157.

Skinner, B. F. (1984). The evolution of behavior. Journal of the Experimental Analysis of Behavior, 41 , 217–221. https://doi.org/10.1901/jeab.1984.41-217

Skinner, B. F. (1985). Cognitive science and behaviorism. British Journal of Psychology, 76 , 291–301. https://doi.org/10.1111/j.2044-8295.1985.tb01953.x

Skues, J., Williams, B., Oldmeadow, J., & Wise, L. (2016). The effects of boredom, loneliness, and distress tolerance on problem internet use among university students. International Journal of Mental Health and Addiction, 14 , 167–180.

Society for the Study of Addiction. (2017). Briefing paper on cognitive–behavioral therapy (CBT) for substance use disorders. Retrieved from https://www.addiction-ssa.org/resources/briefing-paper-on-cognitive-behavioural-therapy-cbt-for-substance-use-disorders/

Stinson, J. D., Becker, J. V., & Sales, B. D. (2008). Self-regulation and the etiology of sexual deviance: evaluating causal theory. Violence and Victims, 23 (1), 35–51. https://doi.org/10.1891/0886-6708.23.1.35

Susskind, J. M., Lee, D. H., Cusi, A., Feiman, R., Grabski, W., & Anderson, A. K. (2008). Expressing fear enhances sensory acquisition. Nature Neuroscience, 11 , 843–850. https://doi.org/10.1038/nn.2138

Tamir, M., Schwartz, S. H., Cieciuch, J., Riediger, M., Torres, C., Scollon, C., Dzokoto, V., Zhou, X., & Vishkin, A. (2016). Desired emotions across cultures: A value-based account. Journal of Personality and Social Psychology, 111 (1), 67–82. https://doi.org/10.1037/pspp0000072

Tams, S., Legoux, R., & Léger, P.M. (2018). Smartphone withdrawal creates stress: A moderated mediation model of nomophobia, social threat, and phone withdrawal context. Comput. Hum. Behav , 81, 1–9. [CrossRef]

Tangney, J. P., Baumeister, R. F., & Boone, A. L. (2004). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72 (2), 271–334.

Thoresen, C. E. (1998). Spirituality, health, and science: The coming revival? In S. Roth-Roemer, S. R. Kurpius, & C. Carmin (Eds.), The emerging role of counseling psychology in health care (pp. 409–431). W W Norton & Co.

Trevino, K. M., Archambault, E., Schuster, J., Richardson, P., & Moye, J. (2012). Religious coping and psychological distress in military veteran cancer survivors. Journal of Religion and Health, 51 (1), 87–98. https://doi.org/10.1007/s10943-011-9526-0

Vermeulen, N., Godefroid, J., & Mermillod, M. (2009). Emotional modulation of attention: Fear increases but disgust reduces the attentional blink. PLoS ONE, 4 , e7924. https://doi.org/10.1371/journal.pone.0007924

Vohs, K. D., & Faber, R. J. (2007). Spent resources: Self-regulatory resource availability affects impulse buying. Journal of Consumer Research, 33 (4), 537–547. https://doi.org/10.1086/510228

Wang, P., Chen, Y., & Chen, Y. (2021). Attachment anxiety and nomophobia among college students in China: The mediating effect of social support. Current Psychology, 40 (5), 2365–2373.

Wagner, D. D., Altman, M., Boswell, R. G., Kelley, W. M., & Heatherton, T. F. (2013). Self-regulatory depletion enhances neural responses to rewards and impairs top-down control. Psychological Science, 24 (11), 2262–2271. https://doi.org/10.1177/0956797613492985

Webb, T. L., Lindquist, K. A., Jones, K., Avishai, A., & Sheeran, P. (2018). Situation selection is a particularly effective emotion regulation strategy for people who need help regulating their emotions. Cognition and Emotion, 32 , 231–248. https://doi.org/10.1080/02699931.2017.1295922

Williams, L. M., Liddell, B. J., Rathjen, J., Brown, K. J., Gray, J., Phillips, M., et al. (2004). Mapping the time course of nonconscious and conscious perception of fear: An integration of central and peripheral measures. Human Brain Mapping, 21 , 64–74. https://doi.org/10.1002/hbm.10154

Wilmer, H. H., Sherman, L. E., & Chein, J. M. (2017). Smartphones and cognition: A review of research exploring the links between mobile technology habits and cognitive functioning. Frontiers in Psychology, 8 , 605.

Xia, N., & Li, H. (2018). Loneliness, social isolation, and cardiovascular health. Antioxidants & Redox Signaling, 28 , 837–851. https://doi.org/10.1089/ars.2017.7312

Yanguas, J., Pinazo-Henandis, S., & Tarazona-Santabalbina, F. J. (2018). The complexity of loneliness. Acta Bio Med. Atenei Parm, 89 , 302.

Yildirim, C., & Correia, A. (2015). Exploring the dimensions of nomophobia: Development and validation of a self-report questionnaire. Computers in Human Behavior, 49 , 130–137. https://doi.org/10.1016/j.chb.2015.02.059

Yildirim, C., Sumuer, E., Adnan, M., & Yildirim, S. (2016). A growing fear: Prevalence of nomophobia among Turkish college students. Information Development, 32 (5), 1322–1331. https://doi.org/10.1177/0266666915599025

Yılmaz, T., & Bekaroğlu, E. (2021). Does interpersonal sensitivity and paranoid ideation predict nomophobia: An analysis with a young adult sample. Current Psychology , 2015 . https://doi.org/10.1007/s12144-021-01501-4 .

Yu, B., Steptoe, A., Chen, L.-J., Chen, Y.-H., Lin, C.-H., & Ku, P.-W. (2020). Social isolation, loneliness, and all-cause mortality in patients with cardiovascular disease: A 10-year follow-up study. Psychosomatic Medicine, 82 , 208–214. https://doi.org/10.1097/psy.0000000000000777

Yun, I., Kim, S. G., & Kwon, S. (2016). Low self-control among South Korean adolescents: A test of Gottfredson and Hirschi’s generality hypothesis. International Journal of Offender Therapy and Comparative Criminology, 60 (10), 1185–1208. https://doi.org/10.1177/0306624x15574683

Zeidi, I. M., Divsalar, S., Morshedi, H., & Alizadeh, H. (2020). The effectiveness of group cognitive–behavioral therapy on general self-efficacy, self-control, and internet addiction prevalence among medical university students. Social Health and Behavior, 3 (3), 93–102. https://doi.org/10.4103/SHB.SHB2020

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Acknowledgements

We thank all the adolescents who participated in this study.

This research was funded by the Ministry of Education, Culture, Research Technology and Higher Education with contract number 157/E.5/PG.02.00.PT/2022.

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Ahmad Dahlan University, Yogyakarta, Indonesia

Triantoro Safaria

Jambi University, Jambi, Indonesia

Nofrans Eka Saputra

Charitas Musi Catholic University, Palembang, Indonesia

Diana Putri Arini

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All the authors contributed equally to the study’s conceptualization, interpretation of the data, and review, and editing of the manuscript. T.S. performed the statistical analyses; wrote the methods, results, and conclusions; and finalized the manuscript. N.E.S. wrote the introduction, while D.P.A. wrote the discussion. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Triantoro Safaria .

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The study followed the guidelines of the Declaration of Helsinki and was approved by The Research Ethics Committee of Universitas Ahmad Dahlan Indonesia, which approved this study’s ethical approval on 8 July 2022 (Ethics Number: 012206071 KEP UAD). The researchers also obtained a data collection permit from the school and university administration.

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All the informants agreed to participate in this study and signed a voluntary informed consent statement. The anonymity and confidentiality of all participants were guaranteed.

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Table  6 and Figs. 3 , 4 , 5

Path Diagrams

The result of path analysis among college students

The result of path analysis among senior high school students

The result of path analysis among junior high school students

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Safaria, T., Saputra, N.E. & Arini, D.P. The Impact of Nomophobia: Exploring the Interplay Between Loneliness, Smartphone Usage, Self-control, Emotion Regulation, and Spiritual Meaningfulness in an Indonesian Context. J. technol. behav. sci. (2024). https://doi.org/10.1007/s41347-024-00438-2

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Received : 03 June 2024

Revised : 11 August 2024

Accepted : 25 August 2024

Published : 11 September 2024

DOI : https://doi.org/10.1007/s41347-024-00438-2

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