analyze research paper

Research Paper Analysis: How to Analyze a Research Article + Example

Why might you need to analyze research? First of all, when you analyze a research article, you begin to understand your assigned reading better. It is also the first step toward learning how to write your own research articles and literature reviews. However, if you have never written a research paper before, it may be difficult for you to analyze one. After all, you may not know what criteria to use to evaluate it. But don’t panic! We will help you figure it out!

In this article, our team has explained how to analyze research papers quickly and effectively. At the end, you will also find a research analysis paper example to see how everything works in practice.

• 🔤 Research Analysis Definition

📊 How to Analyze a Research Article

✍️ how to write a research analysis.

• 📝 Analysis Example
• 🔎 More Examples

🔗 References

🔤 research paper analysis: what is it.

A research paper analysis is an academic writing assignment in which you analyze a scholarly article’s methodology, data, and findings. In essence, “to analyze” means to break something down into components and assess each of them individually and in relation to each other. The goal of an analysis is to gain a deeper understanding of a subject. So, when you analyze a research article, you dissect it into elements like data sources , research methods, and results and evaluate how they contribute to the study’s strengths and weaknesses.

📋 Research Analysis Format

A research analysis paper has a pretty straightforward structure. Check it out below!

Research articles usually include the following sections: introduction, methods, results, and discussion. In the following paragraphs, we will discuss how to analyze a scientific article with a focus on each of its parts.

How to Analyze a Research Paper: Purpose

The purpose of the study is usually outlined in the introductory section of the article. Analyzing the research paper’s objectives is critical to establish the context for the rest of your analysis.

When analyzing the research aim, you should evaluate whether it was justified for the researchers to conduct the study. In other words, you should assess whether their research question was significant and whether it arose from existing literature on the topic.

Here are some questions that may help you analyze a research paper’s purpose:

• Why was the research carried out?
• What gaps does it try to fill, or what controversies to settle?
• How does the study contribute to its field?
• Do you agree with the author’s justification for approaching this particular question in this way?

How to Analyze a Paper: Methods

When analyzing the methodology section , you should indicate the study’s research design (qualitative, quantitative, or mixed) and methods used (for example, experiment, case study, correlational research, survey, etc.). After that, you should assess whether these methods suit the research purpose. In other words, do the chosen methods allow scholars to answer their research questions within the scope of their study?

For example, if scholars wanted to study US students’ average satisfaction with their higher education experience, they could conduct a quantitative survey . However, if they wanted to gain an in-depth understanding of the factors influencing US students’ satisfaction with higher education, qualitative interviews would be more appropriate.

When analyzing methods, you should also look at the research sample . Did the scholars use randomization to select study participants? Was the sample big enough for the results to be generalizable to a larger population?

You can also answer the following questions in your methodology analysis:

• Is the methodology valid? In other words, did the researchers use methods that accurately measure the variables of interest?
• Is the research methodology reliable? A research method is reliable if it can produce stable and consistent results under the same circumstances.
• Is the study biased in any way?
• What are the limitations of the chosen methodology?

How to Analyze Research Articles’ Results

You should start the analysis of the article results by carefully reading the tables, figures, and text. Check whether the findings correspond to the initial research purpose. See whether the results answered the author’s research questions or supported the hypotheses stated in the introduction.

To analyze the results section effectively, answer the following questions:

• What are the major findings of the study?
• Did the author present the results clearly and unambiguously?
• Are the findings statistically significant ?
• Does the author provide sufficient information on the validity and reliability of the results?
• Have you noticed any trends or patterns in the data that the author did not mention?

How to Analyze Research: Discussion

Finally, you should analyze the authors’ interpretation of results and its connection with research objectives. Examine what conclusions the authors drew from their study and whether these conclusions answer the original question.

You should also pay attention to how the authors used findings to support their conclusions. For example, you can reflect on why their findings support that particular inference and not another one. Moreover, more than one conclusion can sometimes be made based on the same set of results. If that’s the case with your article, you should analyze whether the authors addressed other interpretations of their findings .

Here are some useful questions you can use to analyze the discussion section:

• What findings did the authors use to support their conclusions?
• How do the researchers’ conclusions compare to other studies’ findings?
• How does this study contribute to its field?
• What future research directions do the authors suggest?
• What additional insights can you share regarding this article? For example, do you agree with the results? What other questions could the researchers have answered?

Now, you know how to analyze an article that presents research findings. However, it’s just a part of the work you have to do to complete your paper. So, it’s time to learn how to write research analysis! Check out the steps below!

1. Introduce the Article

As with most academic assignments, you should start your research article analysis with an introduction. Here’s what it should include:

• The article’s publication details . Specify the title of the scholarly work you are analyzing, its authors, and publication date. Remember to enclose the article’s title in quotation marks and write it in title case .
• The article’s main point . State what the paper is about. What did the authors study, and what was their major finding?
• Your thesis statement . End your introduction with a strong claim summarizing your evaluation of the article. Consider briefly outlining the research paper’s strengths, weaknesses, and significance in your thesis.

Keep your introduction brief. Save the word count for the “meat” of your paper — that is, for the analysis.

2. Summarize the Article

Now, you should write a brief and focused summary of the scientific article. It should be shorter than your analysis section and contain all the relevant details about the research paper.

Here’s what you should include in your summary:

• The research purpose . Briefly explain why the research was done. Identify the authors’ purpose and research questions or hypotheses .
• Methods and results . Summarize what happened in the study. State only facts, without the authors’ interpretations of them. Avoid using too many numbers and details; instead, include only the information that will help readers understand what happened.
• The authors’ conclusions . Outline what conclusions the researchers made from their study. In other words, describe how the authors explained the meaning of their findings.

If you need help summarizing an article, you can use our free summary generator .

3. Write Your Research Analysis

The analysis of the study is the most crucial part of this assignment type. Its key goal is to evaluate the article critically and demonstrate your understanding of it.

We’ve already covered how to analyze a research article in the section above. Here’s a quick recap:

• Analyze whether the study’s purpose is significant and relevant.
• Examine whether the chosen methodology allows for answering the research questions.
• Evaluate how the authors presented the results.
• Assess whether the authors’ conclusions are grounded in findings and answer the original research questions.

Although you should analyze the article critically, it doesn’t mean you only should criticize it. If the authors did a good job designing and conducting their study, be sure to explain why you think their work is well done. Also, it is a great idea to provide examples from the article to support your analysis.

4. Conclude Your Analysis of Research Paper

A conclusion is your chance to reflect on the study’s relevance and importance. Explain how the analyzed paper can contribute to the existing knowledge or lead to future research. Also, you need to summarize your thoughts on the article as a whole. Avoid making value judgments — saying that the paper is “good” or “bad.” Instead, use more descriptive words and phrases such as “This paper effectively showed…”

Need help writing a compelling conclusion? Try our free essay conclusion generator !

5. Revise and Proofread

Last but not least, you should carefully proofread your paper to find any punctuation, grammar, and spelling mistakes. Start by reading your work out loud to ensure that your sentences fit together and sound cohesive. Also, it can be helpful to ask your professor or peer to read your work and highlight possible weaknesses or typos.

📝 Research Paper Analysis Example

We have prepared an analysis of a research paper example to show how everything works in practice.

No Homework Policy: Research Article Analysis Example

This paper aims to analyze the research article entitled “No Assignment: A Boon or a Bane?” by Cordova, Pagtulon-an, and Tan (2019). This study examined the effects of having and not having assignments on weekends on high school students’ performance and transmuted mean scores. This article effectively shows the value of homework for students, but larger studies are needed to support its findings.

Cordova et al. (2019) conducted a descriptive quantitative study using a sample of 115 Grade 11 students of the Central Mindanao University Laboratory High School in the Philippines. The sample was divided into two groups: the first received homework on weekends, while the second didn’t. The researchers compared students’ performance records made by teachers and found that students who received assignments performed better than their counterparts without homework.

The purpose of this study is highly relevant and justified as this research was conducted in response to the debates about the “No Homework Policy” in the Philippines. Although the descriptive research design used by the authors allows to answer the research question, the study could benefit from an experimental design. This way, the authors would have firm control over variables. Additionally, the study’s sample size was not large enough for the findings to be generalized to a larger population.

The study results are presented clearly, logically, and comprehensively and correspond to the research objectives. The researchers found that students’ mean grades decreased in the group without homework and increased in the group with homework. Based on these findings, the authors concluded that homework positively affected students’ performance. This conclusion is logical and grounded in data.

This research effectively showed the importance of homework for students’ performance. Yet, since the sample size was relatively small, larger studies are needed to ensure the authors’ conclusions can be generalized to a larger population.

🔎 More Research Analysis Paper Examples

Do you want another research analysis example? Check out the best analysis research paper samples below:

• Gracious Leadership Principles for Nurses: Article Analysis
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• Quantitative Article Critique in Nursing
• LIVE Program: Quantitative Article Critique
• Evidence-Based Practice Beliefs and Implementation: Article Critique
• “Differential Effectiveness of Placebo Treatments”: Research Paper Analysis
• “Family-Based Childhood Obesity Prevention Interventions”: Analysis Research Paper Example
• “Childhood Obesity Risk in Overweight Mothers”: Article Analysis
• “Fostering Early Breast Cancer Detection” Article Analysis
• Space and the Atom: Article Analysis
• “Democracy and Collective Identity in the EU and the USA”: Article Analysis
• China’s Hegemonic Prospects: Article Review
• Article Analysis: Fear of Missing Out
• Codependence, Narcissism, and Childhood Trauma: Analysis of the Article
• Relationship Between Work Intensity, Workaholism, Burnout, and MSC: Article Review

We hope that our article on research paper analysis has been helpful. If you liked it, please share this article with your friends!

• Analyzing Research Articles: A Guide for Readers and Writers | Sam Mathews
• Summary and Analysis of Scientific Research Articles | San José State University Writing Center
• Analyzing Scholarly Articles | Texas A&M University
• Article Analysis Assignment | University of Wisconsin-Madison
• How to Summarize a Research Article | University of Connecticut
• Critique/Review of Research Articles | University of Calgary
• Art of Reading a Journal Article: Methodically and Effectively | PubMed Central
• Write a Critical Review of a Scientific Journal Article | McLaughlin Library
• How to Read and Understand a Scientific Paper: A Guide for Non-scientists | LSE
• How to Analyze Journal Articles | Classroom

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Research Paper Writing: 6. Results / Analysis

• 1. Getting Started
• 2. Abstract
• 3. Introduction
• 4. Literature Review
• 5. Methods / Materials
• 6. Results / Analysis
• 7. Discussion
• 8. Conclusion
• 9. Reference

Writing about the information

There are two sections of a research paper depending on what style is being written. The sections are usually straightforward commentary of exactly what the writer observed and found during the actual research. It is important to include only the important findings, and avoid too much information that can bury the exact meaning of the context.

The results section should aim to narrate the findings without trying to interpret or evaluate, and also provide a direction to the discussion section of the research paper. The results are reported and reveals the analysis. The analysis section is where the writer describes what was done with the data found.  In order to write the analysis section it is important to know what the analysis consisted of, but does not mean data is needed. The analysis should already be performed to write the results section.

Written explanations

How should the analysis section be written?

• Should be a paragraph within the research paper
• Consider all the requirements (spacing, margins, and font)
• Should be the writer’s own explanation of the chosen problem
• Thorough evaluation of work
• Description of the weak and strong points
• Discussion of the effect and impact
• Includes criticism

How should the results section be written?

• Show the most relevant information in graphs, figures, and tables
• Include data that may be in the form of pictures, artifacts, notes, and interviews
• Clarify unclear points
• Present results with a short discussion explaining them at the end
• Include the negative results
• Provide stability, accuracy, and value

How the style is presented

Analysis section

• Includes a justification of the methods used
• Technical explanation

Results section

• Purely descriptive
• Easily explained for the targeted audience
• Data driven

Example of a Results Section

Publication Manual of the American Psychological Association Sixth Ed. 2010

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How to Analyze a Research Article: Guide & Analysis Examples

Analyzing a scientific paper is a complicated task that requires knowledge and systematic preparation. This process favors patience over haste and offers a deep and nuanced exploration of the presented research. Fully understanding the peculiarities of content analysis may seem complicated, especially when it comes to evaluating the results.

Our team has developed a thorough guide to make your writing process more comfortable and focused. We offer helpful tips and examples to help you create a paper worthy of admiration from college professors. This guide has everything for a stellar and in-depth argument analysis.

🤔 What Is a Research Article Analysis?

🎯 analysis of a paper: main goals.

• 📑 How to Analyze a Research Article

📝 Research Analysis Template: Essay Outline

• ✨ 5 Tips for Writing an Analysis
• ✒️ 3 Research Paper Analysis Examples

🔗 References

A research genre analysis is a genre of academic writing that lets students assess issues and arguments presented in research articles. They review the text’s content and determine its validity through critical thinking . It involves a great deal of topic analysis. After studying the source, they provide an assessment of the claims with evidence that support or disprove them. It’s their job to establish which of the statements are flawed and which are valid. Students also summarize the article and explain its relevance to the field of study.

📑 How to Analyze a Research Article – 4 Key Steps

Research paper analysis is often both educational and complicated. Taking a structured approach to this task makes it a lot easier. This section of our guide discloses the four stages that help better understand the content of a scientific paper. Follow our analysis plan to learn how to write about things like results and methodology analysis .

Research Paper Analysis: Read an Article & Take Notes

You can’t critique a research piece without reading the source material first. Skimming over the paper won’t do, as you’ll miss crucial details for your analysis. Follow these steps to ensure you get the most out of the paper while critically evaluating its contents.

• Read the paper once to have a general understanding of what it’s about. Ensure you are familiar with the topic beyond elementary knowledge. You may also read up on related literature beforehand.
• Read the second time and take notes. Read the entire research paper carefully, paying attention to the results, discussion, and conclusion sections. It’s better to take detailed notes as you read, summarizing each section in your own words.
• Outline the results of the study. Write a short rundown of what the author found during the search.

Research Paper Analysis: Comprehend & Reveal the Methodology

Once you’re done with the first step, it’s time to move on to the second stage of research paper analysis: comprehending and revealing the methodology. You can’t possibly remember everything about the article so that you can revise your notes.

• Explore key terms and concepts of an article . If you don’t fully understand them, take the time to familiarize yourself with them.
• Find the hypothesis or the research question the author decided to tackle . Check the facts, arguments, and logic behind their thinking to view the paper critically.
• Look at the validity of the arguments . Research sources used in the article and assess the credibility of the supporting evidence.
• Identify the study’s methodology . Find out how the author approached the research and what its results were. Once you establish the methodology, evaluate the quality of the information, including the methods of data gathering and analysis.

Research Paper Analysis: Assess the Results

After completing the second part of the analysis, it’s time to assess the research results. Establish if the findings support the paper’s hypothesis and their statistical relevance. Address any limitations of the study . For example, a writing on psychology that uses a small group of participants that cannot be considered representative of a larger population. It may be true that the researcher did this intentionally to skew their findings. However, it’s best to be balanced in your article critique and talk about the strong sides of the paper as well. Look at similar studies and see if they came to the same conclusions.

Research Paper Analysis: Draw Conclusions

After you’ve completed the previous steps, you’re ready to make conclusions about the research paper as a whole. Don’t forget to include the following information when working on this part of the analysis:

• Determine the theoretical and practical meaning of the results. For example, if the paper found a particular treatment effective, emphasize that it should be used more often.
• Consider the applications of the research results. Try to find out how they can be applied to the broader field and what ethical implications they may lead to.
• Show how they relate to the big picture. Finally, your analysis should show how the article expands the knowledge of the subject and what it means to further studies.

Writing a research paper analysis can be demanding. These papers have several characteristics that set them apart from other types of academic writing. We’ve created this simple template to explain the content each part of your assessment should have.

✨ 5 Tips for Writing an Analysis of Paper

Mastering the art of writing a research paper analysis takes time and practice. We’ve decided to provide five great tips that will make this process easier and more enjoyable:

• Take the time to establish the right angle for your analysis. If you can choose its direction, study the paper first and choose the best subject for your work. You can develop several ideas and select the right one later.
• Connect all evidence to your argument. When conducting the analysis, find facts and data supporting your point of view. Explain the connection of each piece of evidence to your statement and showcase what makes it particularly significant.
• Stay balanced. A good analysis covers all facts and looks at them objectively. When confronted with data that clashes with your stance, check it and use evidence to bolster the credibility of your arguments.
• Work on an outline . Good analysis is often grounded in well-structured outline. Write down ideas and topic sentences that connect to various parts of the research sample and its general idea.
• Evaluate all evidence. All evidence has a place in your analysis. Use all of it, even if you come across contradictory facts. Include information that doesn’t fully support the main idea of your analysis and build compelling counterarguments.

️ ✒️ 3 Great Research Paper Analysis Examples

Seeing an example of a finished article can point you in the right direction. Our team has collected seven excellent essays to inspire your subsequent work and show how to approach its structure correctly.

• Analysis of The Five Dysfunctions of a Team Article . This paper concerns the pitfalls of team building in a business environment. In particular, how to overcome this environment’s five most common dysfunctions.
• When Altruism Isn’t Moral by Sally Satel : Article Analysis. The author demonstrates altruistic behavior is not always sufficient to explain human interaction. It discusses what drives people to help others for free or for money.
• Article Analysis Perceptions of ADHD Among Diagnosed Children and Their Parents. In this work, the author evaluates the findings on the perception of ADHD-diagnosed children in developed countries.

Research Article Analysis Topics

Now that you understand how to write a research paper analysis, it’s time to find the right topic for your paper. Below, you’ll find fifteen exciting ideas to inspire your analytical pursuits.

• Review a research paper on the effects of carbon emissions.
• Explore a recent research article on the use of opioids in American healthcare.
• Assess a research paper on the applications of the Large Hadron Collider.
• Discuss quantitative research about mental health rates in developed countries.
• Examine a scientific article about the problems of space exploration .
• Investigate a recent research paper about the rise of surveillance technology.
• Analyze a qualitative research paper on the effectiveness of biofuels as an alternative energy source.
• Study quantitative methods of research on the housing market in Canada.
• Scrutinize a research article about the use of pesticides in food production.
• Evaluate a paper on the efficiency of anti-climate change measures.
• Assess a recent study on the dangers of sugar consumption.
• Survey the latest research on fast food advertising tactics.
• Consider a paper on the most recent developments in string theory .
• Address a recent research article about artificial intelligence.
• Cover research about the benefits of using nuclear power.

We did our best to cover all crucial points of research article analysis and prepare you for this kind of academic work. When you have the time, share our guide with fellow students who can benefit from the content of our work!

• Analyzing Scholarly Articles. – University Writing Center
• How to Write an Analysis (With Examples and Tips). – Indeed
• Complete Guide on Article Analysis (with 1 Analysis Example). – Nerdify, Medium
• How to Read and Understand a Scientific Paper: A Guide for Non-scientists. – Jennifer Raff, LSE
• How to Review a Journal Article. – The Board of Trustees of the University of Illinois
• Critique/Review of Research Articles. – University of Calgary
• How to Summarize a Research Article. – University of Connecticut
• A Guide for Critique of Research Articles – California State Universite, Long Beach

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Analysis in Research Papers

To analyze means to break a topic or concept down into its parts in order to inspect and understand it, and to restructure those parts in a way that makes sense to you. In an analytical research paper, you do research to become an expert on a topic so that you can restructure and present the parts of the topic from your own perspective.

For example, you could analyze the role of the mother in the ancient Egyptian family. You could break down that topic into its parts--the mother's duties in the family, social status, and expected role in the larger society--and research those parts in order to present your general perspective and conclusion about the mother's role.

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Home » Research Paper – Structure, Examples and Writing Guide

Research Paper – Structure, Examples and Writing Guide

Table of Contents

Research Paper

Definition:

Research Paper is a written document that presents the author’s original research, analysis, and interpretation of a specific topic or issue.

It is typically based on Empirical Evidence, and may involve qualitative or quantitative research methods, or a combination of both. The purpose of a research paper is to contribute new knowledge or insights to a particular field of study, and to demonstrate the author’s understanding of the existing literature and theories related to the topic.

Structure of Research Paper

The structure of a research paper typically follows a standard format, consisting of several sections that convey specific information about the research study. The following is a detailed explanation of the structure of a research paper:

The title page contains the title of the paper, the name(s) of the author(s), and the affiliation(s) of the author(s). It also includes the date of submission and possibly, the name of the journal or conference where the paper is to be published.

The abstract is a brief summary of the research paper, typically ranging from 100 to 250 words. It should include the research question, the methods used, the key findings, and the implications of the results. The abstract should be written in a concise and clear manner to allow readers to quickly grasp the essence of the research.

Introduction

The introduction section of a research paper provides background information about the research problem, the research question, and the research objectives. It also outlines the significance of the research, the research gap that it aims to fill, and the approach taken to address the research question. Finally, the introduction section ends with a clear statement of the research hypothesis or research question.

Literature Review

The literature review section of a research paper provides an overview of the existing literature on the topic of study. It includes a critical analysis and synthesis of the literature, highlighting the key concepts, themes, and debates. The literature review should also demonstrate the research gap and how the current study seeks to address it.

The methods section of a research paper describes the research design, the sample selection, the data collection and analysis procedures, and the statistical methods used to analyze the data. This section should provide sufficient detail for other researchers to replicate the study.

The results section presents the findings of the research, using tables, graphs, and figures to illustrate the data. The findings should be presented in a clear and concise manner, with reference to the research question and hypothesis.

The discussion section of a research paper interprets the findings and discusses their implications for the research question, the literature review, and the field of study. It should also address the limitations of the study and suggest future research directions.

The conclusion section summarizes the main findings of the study, restates the research question and hypothesis, and provides a final reflection on the significance of the research.

The references section provides a list of all the sources cited in the paper, following a specific citation style such as APA, MLA or Chicago.

How to Write Research Paper

You can write Research Paper by the following guide:

• Choose a Topic: The first step is to select a topic that interests you and is relevant to your field of study. Brainstorm ideas and narrow down to a research question that is specific and researchable.
• Conduct a Literature Review: The literature review helps you identify the gap in the existing research and provides a basis for your research question. It also helps you to develop a theoretical framework and research hypothesis.
• Develop a Thesis Statement : The thesis statement is the main argument of your research paper. It should be clear, concise and specific to your research question.
• Plan your Research: Develop a research plan that outlines the methods, data sources, and data analysis procedures. This will help you to collect and analyze data effectively.
• Collect and Analyze Data: Collect data using various methods such as surveys, interviews, observations, or experiments. Analyze data using statistical tools or other qualitative methods.
• Organize your Paper : Organize your paper into sections such as Introduction, Literature Review, Methods, Results, Discussion, and Conclusion. Ensure that each section is coherent and follows a logical flow.
• Write your Paper : Start by writing the introduction, followed by the literature review, methods, results, discussion, and conclusion. Ensure that your writing is clear, concise, and follows the required formatting and citation styles.
• Edit and Proofread your Paper: Review your paper for grammar and spelling errors, and ensure that it is well-structured and easy to read. Ask someone else to review your paper to get feedback and suggestions for improvement.
• Cite your Sources: Ensure that you properly cite all sources used in your research paper. This is essential for giving credit to the original authors and avoiding plagiarism.

Research Paper Example

Note : The below example research paper is for illustrative purposes only and is not an actual research paper. Actual research papers may have different structures, contents, and formats depending on the field of study, research question, data collection and analysis methods, and other factors. Students should always consult with their professors or supervisors for specific guidelines and expectations for their research papers.

Research Paper Example sample for Students:

Title: The Impact of Social Media on Mental Health among Young Adults

Abstract: This study aims to investigate the impact of social media use on the mental health of young adults. A literature review was conducted to examine the existing research on the topic. A survey was then administered to 200 university students to collect data on their social media use, mental health status, and perceived impact of social media on their mental health. The results showed that social media use is positively associated with depression, anxiety, and stress. The study also found that social comparison, cyberbullying, and FOMO (Fear of Missing Out) are significant predictors of mental health problems among young adults.

Introduction: Social media has become an integral part of modern life, particularly among young adults. While social media has many benefits, including increased communication and social connectivity, it has also been associated with negative outcomes, such as addiction, cyberbullying, and mental health problems. This study aims to investigate the impact of social media use on the mental health of young adults.

Literature Review: The literature review highlights the existing research on the impact of social media use on mental health. The review shows that social media use is associated with depression, anxiety, stress, and other mental health problems. The review also identifies the factors that contribute to the negative impact of social media, including social comparison, cyberbullying, and FOMO.

Methods : A survey was administered to 200 university students to collect data on their social media use, mental health status, and perceived impact of social media on their mental health. The survey included questions on social media use, mental health status (measured using the DASS-21), and perceived impact of social media on their mental health. Data were analyzed using descriptive statistics and regression analysis.

Results : The results showed that social media use is positively associated with depression, anxiety, and stress. The study also found that social comparison, cyberbullying, and FOMO are significant predictors of mental health problems among young adults.

Discussion : The study’s findings suggest that social media use has a negative impact on the mental health of young adults. The study highlights the need for interventions that address the factors contributing to the negative impact of social media, such as social comparison, cyberbullying, and FOMO.

Conclusion : In conclusion, social media use has a significant impact on the mental health of young adults. The study’s findings underscore the need for interventions that promote healthy social media use and address the negative outcomes associated with social media use. Future research can explore the effectiveness of interventions aimed at reducing the negative impact of social media on mental health. Additionally, longitudinal studies can investigate the long-term effects of social media use on mental health.

Limitations : The study has some limitations, including the use of self-report measures and a cross-sectional design. The use of self-report measures may result in biased responses, and a cross-sectional design limits the ability to establish causality.

Implications: The study’s findings have implications for mental health professionals, educators, and policymakers. Mental health professionals can use the findings to develop interventions that address the negative impact of social media use on mental health. Educators can incorporate social media literacy into their curriculum to promote healthy social media use among young adults. Policymakers can use the findings to develop policies that protect young adults from the negative outcomes associated with social media use.

References :

• Twenge, J. M., & Campbell, W. K. (2019). Associations between screen time and lower psychological well-being among children and adolescents: Evidence from a population-based study. Preventive medicine reports, 15, 100918.
• Primack, B. A., Shensa, A., Escobar-Viera, C. G., Barrett, E. L., Sidani, J. E., Colditz, J. B., … & James, A. E. (2017). Use of multiple social media platforms and symptoms of depression and anxiety: A nationally-representative study among US young adults. Computers in Human Behavior, 69, 1-9.
• Van der Meer, T. G., & Verhoeven, J. W. (2017). Social media and its impact on academic performance of students. Journal of Information Technology Education: Research, 16, 383-398.

Appendix : The survey used in this study is provided below.

Social Media and Mental Health Survey

• How often do you use social media per day?
• Less than 30 minutes
• 30 minutes to 1 hour
• 1 to 2 hours
• 2 to 4 hours
• More than 4 hours
• Which social media platforms do you use?
• Others (Please specify)
• How often do you experience the following on social media?
• Social comparison (comparing yourself to others)
• Cyberbullying
• Fear of Missing Out (FOMO)
• Have you ever experienced any of the following mental health problems in the past month?
• Do you think social media use has a positive or negative impact on your mental health?
• Very positive
• Somewhat positive
• Somewhat negative
• Very negative
• In your opinion, which factors contribute to the negative impact of social media on mental health?
• Social comparison
• In your opinion, what interventions could be effective in reducing the negative impact of social media on mental health?
• Education on healthy social media use
• Counseling for mental health problems caused by social media
• Social media detox programs
• Regulation of social media use

Thank you for your participation!

Applications of Research Paper

Research papers have several applications in various fields, including:

• Advancing knowledge: Research papers contribute to the advancement of knowledge by generating new insights, theories, and findings that can inform future research and practice. They help to answer important questions, clarify existing knowledge, and identify areas that require further investigation.
• Informing policy: Research papers can inform policy decisions by providing evidence-based recommendations for policymakers. They can help to identify gaps in current policies, evaluate the effectiveness of interventions, and inform the development of new policies and regulations.
• Improving practice: Research papers can improve practice by providing evidence-based guidance for professionals in various fields, including medicine, education, business, and psychology. They can inform the development of best practices, guidelines, and standards of care that can improve outcomes for individuals and organizations.
• Educating students : Research papers are often used as teaching tools in universities and colleges to educate students about research methods, data analysis, and academic writing. They help students to develop critical thinking skills, research skills, and communication skills that are essential for success in many careers.
• Fostering collaboration: Research papers can foster collaboration among researchers, practitioners, and policymakers by providing a platform for sharing knowledge and ideas. They can facilitate interdisciplinary collaborations and partnerships that can lead to innovative solutions to complex problems.

When to Write Research Paper

Research papers are typically written when a person has completed a research project or when they have conducted a study and have obtained data or findings that they want to share with the academic or professional community. Research papers are usually written in academic settings, such as universities, but they can also be written in professional settings, such as research organizations, government agencies, or private companies.

Here are some common situations where a person might need to write a research paper:

• For academic purposes: Students in universities and colleges are often required to write research papers as part of their coursework, particularly in the social sciences, natural sciences, and humanities. Writing research papers helps students to develop research skills, critical thinking skills, and academic writing skills.
• For publication: Researchers often write research papers to publish their findings in academic journals or to present their work at academic conferences. Publishing research papers is an important way to disseminate research findings to the academic community and to establish oneself as an expert in a particular field.
• To inform policy or practice : Researchers may write research papers to inform policy decisions or to improve practice in various fields. Research findings can be used to inform the development of policies, guidelines, and best practices that can improve outcomes for individuals and organizations.
• To share new insights or ideas: Researchers may write research papers to share new insights or ideas with the academic or professional community. They may present new theories, propose new research methods, or challenge existing paradigms in their field.

Purpose of Research Paper

The purpose of a research paper is to present the results of a study or investigation in a clear, concise, and structured manner. Research papers are written to communicate new knowledge, ideas, or findings to a specific audience, such as researchers, scholars, practitioners, or policymakers. The primary purposes of a research paper are:

• To contribute to the body of knowledge : Research papers aim to add new knowledge or insights to a particular field or discipline. They do this by reporting the results of empirical studies, reviewing and synthesizing existing literature, proposing new theories, or providing new perspectives on a topic.
• To inform or persuade: Research papers are written to inform or persuade the reader about a particular issue, topic, or phenomenon. They present evidence and arguments to support their claims and seek to persuade the reader of the validity of their findings or recommendations.
• To advance the field: Research papers seek to advance the field or discipline by identifying gaps in knowledge, proposing new research questions or approaches, or challenging existing assumptions or paradigms. They aim to contribute to ongoing debates and discussions within a field and to stimulate further research and inquiry.
• To demonstrate research skills: Research papers demonstrate the author’s research skills, including their ability to design and conduct a study, collect and analyze data, and interpret and communicate findings. They also demonstrate the author’s ability to critically evaluate existing literature, synthesize information from multiple sources, and write in a clear and structured manner.

Characteristics of Research Paper

Research papers have several characteristics that distinguish them from other forms of academic or professional writing. Here are some common characteristics of research papers:

• Evidence-based: Research papers are based on empirical evidence, which is collected through rigorous research methods such as experiments, surveys, observations, or interviews. They rely on objective data and facts to support their claims and conclusions.
• Structured and organized: Research papers have a clear and logical structure, with sections such as introduction, literature review, methods, results, discussion, and conclusion. They are organized in a way that helps the reader to follow the argument and understand the findings.
• Formal and objective: Research papers are written in a formal and objective tone, with an emphasis on clarity, precision, and accuracy. They avoid subjective language or personal opinions and instead rely on objective data and analysis to support their arguments.
• Citations and references: Research papers include citations and references to acknowledge the sources of information and ideas used in the paper. They use a specific citation style, such as APA, MLA, or Chicago, to ensure consistency and accuracy.
• Peer-reviewed: Research papers are often peer-reviewed, which means they are evaluated by other experts in the field before they are published. Peer-review ensures that the research is of high quality, meets ethical standards, and contributes to the advancement of knowledge in the field.
• Objective and unbiased: Research papers strive to be objective and unbiased in their presentation of the findings. They avoid personal biases or preconceptions and instead rely on the data and analysis to draw conclusions.

Advantages of Research Paper

Research papers have many advantages, both for the individual researcher and for the broader academic and professional community. Here are some advantages of research papers:

• Contribution to knowledge: Research papers contribute to the body of knowledge in a particular field or discipline. They add new information, insights, and perspectives to existing literature and help advance the understanding of a particular phenomenon or issue.
• Opportunity for intellectual growth: Research papers provide an opportunity for intellectual growth for the researcher. They require critical thinking, problem-solving, and creativity, which can help develop the researcher’s skills and knowledge.
• Career advancement: Research papers can help advance the researcher’s career by demonstrating their expertise and contributions to the field. They can also lead to new research opportunities, collaborations, and funding.
• Academic recognition: Research papers can lead to academic recognition in the form of awards, grants, or invitations to speak at conferences or events. They can also contribute to the researcher’s reputation and standing in the field.
• Impact on policy and practice: Research papers can have a significant impact on policy and practice. They can inform policy decisions, guide practice, and lead to changes in laws, regulations, or procedures.
• Advancement of society: Research papers can contribute to the advancement of society by addressing important issues, identifying solutions to problems, and promoting social justice and equality.

Limitations of Research Paper

Research papers also have some limitations that should be considered when interpreting their findings or implications. Here are some common limitations of research papers:

• Limited generalizability: Research findings may not be generalizable to other populations, settings, or contexts. Studies often use specific samples or conditions that may not reflect the broader population or real-world situations.
• Potential for bias : Research papers may be biased due to factors such as sample selection, measurement errors, or researcher biases. It is important to evaluate the quality of the research design and methods used to ensure that the findings are valid and reliable.
• Ethical concerns: Research papers may raise ethical concerns, such as the use of vulnerable populations or invasive procedures. Researchers must adhere to ethical guidelines and obtain informed consent from participants to ensure that the research is conducted in a responsible and respectful manner.
• Limitations of methodology: Research papers may be limited by the methodology used to collect and analyze data. For example, certain research methods may not capture the complexity or nuance of a particular phenomenon, or may not be appropriate for certain research questions.
• Publication bias: Research papers may be subject to publication bias, where positive or significant findings are more likely to be published than negative or non-significant findings. This can skew the overall findings of a particular area of research.
• Time and resource constraints: Research papers may be limited by time and resource constraints, which can affect the quality and scope of the research. Researchers may not have access to certain data or resources, or may be unable to conduct long-term studies due to practical limitations.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Using Evidence: Analysis

Beyond introducing and integrating your paraphrases and quotations, you also need to analyze the evidence in your paragraphs. Analysis is your opportunity to contextualize and explain the evidence for your reader. Your analysis might tell the reader why the evidence is important, what it means, or how it connects to other ideas in your writing.

Note that analysis often leads to synthesis , an extension and more complicated form of analysis. See our synthesis page for more information.

Example 1 of Analysis

Without analysis.

Embryonic stem cell research uses the stem cells from an embryo, causing much ethical debate in the scientific and political communities (Robinson, 2011). "Politicians don't know science" (James, 2010, p. 24). Academic discussion of both should continue (Robinson, 2011).

With Analysis (Added in Bold)

Embryonic stem cell research uses the stem cells from an embryo, causing much ethical debate in the scientific and political communities (Robinson, 2011). However, many politicians use the issue to stir up unnecessary emotion on both sides of the issues. James (2010) explained that "politicians don't know science," (p. 24) so scientists should not be listening to politics. Instead, Robinson (2011) suggested that academic discussion of both embryonic and adult stem cell research should continue in order for scientists to best utilize their resources while being mindful of ethical challenges.

Note that in the first example, the reader cannot know how the quotation fits into the paragraph. Also, note that the word both was unclear. In the revision, however, that the writer clearly (a) explained the quotations as well as the source material, (b) introduced the information sufficiently, and (c) integrated the ideas into the paragraph.

Example 2 of Analysis

Trow (1939) measured the effects of emotional responses on learning and found that student memorization dropped greatly with the introduction of a clock. Errors increased even more when intellectual inferiority regarding grades became a factor (Trow, 1939). The group that was allowed to learn free of restrictions from grades and time limits performed better on all tasks (Trow, 1939).

In this example, the author has successfully paraphrased the key findings from a study. However, there is no conclusion being drawn about those findings. Readers have a difficult time processing the evidence without some sort of ending explanation, an answer to the question so what? So what about this study? Why does it even matter?

Trow (1939) measured the effects of emotional responses on learning and found that student memorization dropped greatly with the introduction of a clock. Errors increased even more when intellectual inferiority regarding grades became a factor (Trow, 1939). The group that was allowed to learn free of restrictions from grades and time limits performed better on all tasks (Trow, 1939). Therefore, negative learning environments and students' emotional reactions can indeed hinder achievement.

Here the meaning becomes clear. The study’s findings support the claim the reader is making: that school environment affects achievement.

Analysis Video Playlist

Note that these videos were created while APA 6 was the style guide edition in use. There may be some examples of writing that have not been updated to APA 7 guidelines.

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Analysis is a type of primary research that involves finding and interpreting patterns in data, classifying those patterns, and generalizing the results. It is useful when looking at actions, events, or occurrences in different texts, media, or publications. Analysis can usually be done without considering most of the ethical issues discussed in the overview, as you are not working with people but rather publicly accessible documents. Analysis can be done on new documents or performed on raw data that you yourself have collected.

Here are several examples of analysis:

• Recording commercials on three major television networks and analyzing race and gender within the commercials to discover some conclusion.
• Analyzing the historical trends in public laws by looking at the records at a local courthouse.
• Analyzing topics of discussion in chat rooms for patterns based on gender and age.

Analysis research involves several steps:

• Finding and collecting documents.
• Specifying criteria or patterns that you are looking for.
• Analyzing documents for patterns, noting number of occurrences or other factors.

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

Edward barroga.

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

Glafera Janet Matanguihan

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

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

INTRODUCTION

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

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

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

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

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

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

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

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

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

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

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

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

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

Research questions in quantitative research

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

Hypotheses in quantitative research

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

Research questions in qualitative research

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

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

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

Hypotheses in qualitative research

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

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

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

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

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

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

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

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

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

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

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

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

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

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

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

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

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

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

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

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

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

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

Author Contributions:

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

Critically Analyzing Information Sources: Critical Appraisal and Analysis

• Critical Appraisal and Analysis

Initial Appraisal : Reviewing the source

• What are the author's credentials--institutional affiliation (where he or she works), educational background, past writings, or experience? Is the book or article written on a topic in the author's area of expertise? You can use the various Who's Who publications for the U.S. and other countries and for specific subjects and the biographical information located in the publication itself to help determine the author's affiliation and credentials.
• Has your instructor mentioned this author? Have you seen the author's name cited in other sources or bibliographies? Respected authors are cited frequently by other scholars. For this reason, always note those names that appear in many different sources.
• Is the author associated with a reputable institution or organization? What are the basic values or goals of the organization or institution?

B. Date of Publication

• When was the source published? This date is often located on the face of the title page below the name of the publisher. If it is not there, look for the copyright date on the reverse of the title page. On Web pages, the date of the last revision is usually at the bottom of the home page, sometimes every page.
• Is the source current or out-of-date for your topic? Topic areas of continuing and rapid development, such as the sciences, demand more current information. On the other hand, topics in the humanities often require material that was written many years ago. At the other extreme, some news sources on the Web now note the hour and minute that articles are posted on their site.

C. Edition or Revision

Is this a first edition of this publication or not? Further editions indicate a source has been revised and updated to reflect changes in knowledge, include omissions, and harmonize with its intended reader's needs. Also, many printings or editions may indicate that the work has become a standard source in the area and is reliable. If you are using a Web source, do the pages indicate revision dates?

D. Publisher

Note the publisher. If the source is published by a university press, it is likely to be scholarly. Although the fact that the publisher is reputable does not necessarily guarantee quality, it does show that the publisher may have high regard for the source being published.

E. Title of Journal

Is this a scholarly or a popular journal? This distinction is important because it indicates different levels of complexity in conveying ideas. If you need help in determining the type of journal, see Distinguishing Scholarly from Non-Scholarly Periodicals . Or you may wish to check your journal title in the latest edition of Katz's Magazines for Libraries (Olin Reference Z 6941 .K21, shelved at the reference desk) for a brief evaluative description.

Critical Analysis of the Content

Having made an initial appraisal, you should now examine the body of the source. Read the preface to determine the author's intentions for the book. Scan the table of contents and the index to get a broad overview of the material it covers. Note whether bibliographies are included. Read the chapters that specifically address your topic. Reading the article abstract and scanning the table of contents of a journal or magazine issue is also useful. As with books, the presence and quality of a bibliography at the end of the article may reflect the care with which the authors have prepared their work.

A. Intended Audience

What type of audience is the author addressing? Is the publication aimed at a specialized or a general audience? Is this source too elementary, too technical, too advanced, or just right for your needs?

B. Objective Reasoning

• Is the information covered fact, opinion, or propaganda? It is not always easy to separate fact from opinion. Facts can usually be verified; opinions, though they may be based on factual information, evolve from the interpretation of facts. Skilled writers can make you think their interpretations are facts.
• Does the information appear to be valid and well-researched, or is it questionable and unsupported by evidence? Assumptions should be reasonable. Note errors or omissions.
• Are the ideas and arguments advanced more or less in line with other works you have read on the same topic? The more radically an author departs from the views of others in the same field, the more carefully and critically you should scrutinize his or her ideas.
• Is the author's point of view objective and impartial? Is the language free of emotion-arousing words and bias?

C. Coverage

• Does the work update other sources, substantiate other materials you have read, or add new information? Does it extensively or marginally cover your topic? You should explore enough sources to obtain a variety of viewpoints.
• Is the material primary or secondary in nature? Primary sources are the raw material of the research process. Secondary sources are based on primary sources. For example, if you were researching Konrad Adenauer's role in rebuilding West Germany after World War II, Adenauer's own writings would be one of many primary sources available on this topic. Others might include relevant government documents and contemporary German newspaper articles. Scholars use this primary material to help generate historical interpretations--a secondary source. Books, encyclopedia articles, and scholarly journal articles about Adenauer's role are considered secondary sources. In the sciences, journal articles and conference proceedings written by experimenters reporting the results of their research are primary documents. Choose both primary and secondary sources when you have the opportunity.

D. Writing Style

Is the publication organized logically? Are the main points clearly presented? Do you find the text easy to read, or is it stilted or choppy? Is the author's argument repetitive?

E. Evaluative Reviews

• Locate critical reviews of books in a reviewing source , such as the Articles & Full Text , Book Review Index , Book Review Digest, and ProQuest Research Library . Is the review positive? Is the book under review considered a valuable contribution to the field? Does the reviewer mention other books that might be better? If so, locate these sources for more information on your topic.
• Do the various reviewers agree on the value or attributes of the book or has it aroused controversy among the critics?
• For Web sites, consider consulting this evaluation source from UC Berkeley .

Permissions Information

If you wish to use or adapt any or all of the content of this Guide go to Cornell Library's Research Guides Use Conditions to review our use permissions and our Creative Commons license.

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• Last Updated: Jun 21, 2024 3:08 PM
• URL: https://guides.library.cornell.edu/critically_analyzing

Research Analysis Paper: How to Analyze a Research Article [2024]

Do you need to write a research analysis paper but have no idea how to do that? Then you’re in the right place.

While completing this type of assignment, your key aim is to critically analyze a research article. An article from a serious scientific journal would be a good choice. You can analyze and interpret either quantitative or qualitative research.

Below, you’ll find a how-to guide on research analysis paper writing prepared by our experts. It contains outlining and formatting tips, topics, and examples of research articles analysis.

• Scan the Paper
• Examine the Content
• Check the Format
• Critique & Evaluate
• ✅ Key Questions

🔗 References

🔎 how to analyze a research article.

This analysis will be beneficial for you since it develops your critical thinking and research skills. So, let us present the main steps that should be undertaken to read and evaluate the paper correctly.

Now, let’s figure out what an analysis paper should include. There are several essential elements the reader should identify:

• logical reasons for conducting the study;
• the description of the methodology applied in the research;
• concise and clear report of the findings;
• a logical conclusion based on the results.

You can use free paper samples for college students before you work with your own writing to get a feel of how the analyzing process goes.

Step 1: Scan the Paper

First, briefly look through the found paper and evaluate whether it’s appropriate for your research. Scanning helps you to start the content analysis and get the general idea of the study.

To scan the paper effectively, follow these simple steps:

• Get familiar with the title, abstract , and introduction . Carefully read these parts and make sure you got the author’s point.
• Read the headings of each section and sub-section. But don’t spend time to get familiar with the content.
• Look through the conclusions. Check the overall one and the last sentence of each section.
• Scan the references. Have you read any of these sources before? Highlight them and decide whether they are appropriate for your research or not.

Have you completed these steps of your research paper’s critical analysis? Now, you should be able to answer these questions:

• What kind of a paper is it (qualitative research, quantitative research, a case study, etc.)?
• What is the research paper topic? How is it connected to your subject of study?
• Do you feel like the findings and the conclusions are valid?
• How can the source contribute to your study?
• Is the paper clear and well-written?

After completing this step, you should have a clear image of the text’s general idea. Also, here you can decide whether the given paper is worth further examination.

Step 2: Examine the Content

The next step leads to a deeper understanding of the topic. Here, again, you can try the following course of action to take the maximum benefit from the evaluation of the source.

• Find the author’s thesis. A thesis statement is usually the last sentence of the introduction (or several sentences). It is an essential part of the paper since it reflects the author’s main point. Make sure you determined the thesis statement and understood it.
• Consider the author’s arguments. How does the author support his position? What are the key arguments they present in their research paper? Are they logical? Evaluate whether the points are clear and concise enough for any reader to get. Do they support the author’s thesis?
• Check the evidence. Try to find all the proof provided by the writer. A successful research paper should have valid evidence for every argument. These can be statistics, diagrams, facts taken from documentaries or books, experiments hold by researchers, etc.
• Determine the limits of the study. An author is supposed to set limits to avoid making their research too broad. Find out what are the variables the writer relied on while determining the exact field of study. Keep them in mind when you decide whether the paper accomplished its goals within limits.
• Establish the author’s perspective. What position does the author take? What methods are applied to prove the correctness of the writer’s point? Does it match with your opinion? Why/ why not?

Sometimes, even after the second step of evaluation, the writer’s perspective is not evident. What to do in this case? There are three scenarios:

• Stop investigating the paper and hope that you will not need it for your research.
• Read some background information on the given topic. Then, reread the paper. This might help you to comprehend the general idea.
• Don’t give up and move on to the next step of the evaluation.

Step 3: Check the Format and Presentation

At this stage, analyze the research paper format and the general presentation of the arguments and facts. Start with the evaluation of the sentence levels. In the research paper, there should be a hierarchy of sentences. To trace the research paper structure, take a look at the tips:

• First-level sentences. They include only general statements and present the ideas that will be explored further in the paper.
• Middle-level sentences. These sentences summarize, give a narrower idea, and present specific arguments.
• Deep-level sentences. They contain specific facts and evidence that correspond to the arguments stated in middle-level sentences.

Your research paper analysis should also include format evaluation. This task might be challenging unless you have the formatting style manual open in front of your eyes.

Figure out what citation style the author applied and check whether all the requirements are met. Here is a mini checklist you have to follow:

• in-text citations
• reference list
• font style and size, spacing
• abstract (if needed)
• appendix (if needed)

Step 4: Critique & Evaluate

This step requires attention to every detail in the paper. Identify each of the author’s assumptions and question them. Do you agree with the author’s evidence? How would you support the arguments? What are your opinions regarding the author’s ideas?

For starters:

Try to re-implement the entire paper from your perspective and see how your version differs from the initial work. This trick will help you to determine the strong and weak sides of the work.

Then, move on to criticism. An effective way to evaluate a research paper consists of asking the right questions and assessing the crucial aspects, like:

• The author’s objective and whether it was reached. Did you get the author’s main idea? Did the writer reach their aim and explain the arguments in great detail? Remember that even if the reader is not majoring in the study field, they should understand the objective. Is there something that remained unclear for you? In your opinion, what is the cause of your inability to comprehend the material?
• The role in the broader context. Make sure the author’s arguments and evidence sound adequately in the larger context. Do the writer’s ideas contradict social norms. If so, why? Also, check the sources the author uses for their research. Make sure they are reliable and not outdated.
• Grammar and organization. A professional research paper should not contain any mistakes. Make sure the text is flawless regarding grammar and structure. The ideas have to follow the logical flow; the tone should be academic; the paper should include transitions, summaries should be on point (which is easier to achieve with the help of a paper summarizer ) and so on.
• What the reader learns. The primary aim of an author is to deliver useful information to the reader. Did you, as a reader, find some new insights? Were they relevant and valuable? Consider whether you’ve read something similar before and how the data fit within limits set by the author.

✅ Research Analysis Paper: Key Questions

As you can see, the task requires a lot of time and effort. That is why we’ve prepared a list of questions you should ask while analyzing a research paper. Use them as a ground for critical reading and evaluation.

Research Article Analysis Topics

• Research article analysis: Using Evidence-Based Practice to Prevent Ventilator-Associated Pneumonia .
• Critical analysis of Seligman’s research article on post-traumatic stress disorder.
• Analyze the article on the role of interprofessional communication in healthcare.
• Examine the articles on the controversy of stem cell research.
• Write a critical analysis of a research article on abortion.
• Discuss a research article on nursing and proactive care program.
• Analyze a quantitative research article on the efficiency of methods used in nursing education.
• Critical analysis of the research article on the role of environmental biology.
• Analysis of the articles about primary quantitative and qualitative research.
• Evaluate Goeders and Guerin’s research on the connection between stress and drug use.
• Study Angela F. Clark’s research article on the efficacy of a nursing education program.
• Analyze the research article by Park, Nisch, and Baptiste examining the connection between immigrants’ mental health and the length of stay in the United States.
• Discuss the scholarly articles researching the connection between obesity and depression.
• Analysis of nursing research article on level of education.
• Write a critical analysis of the scholarly article The Effect of Nurse Staffing on Patient Safety Outcomes .
• Examine a recent research article on spinal cord injuries.
• Analyze Ronald F. Wright’s research article examining the specifics of jury selection.
• Study the article by McConnell et al. on the impact of domestic animals on human well-being.
• Critical evaluation and analysis of the article on ethics and informed consent in research.
• Analysis of a research article on preventing hospital falls .
• Write an analysis of the research article studying the challenges of implementing research findings into practice in nursing.
• Examine the article on the thrombosis process by Bruce Furie and Barbara C. Furie.
• Analyze Mendenhall and Doherty’s research on a new diabetes management approach.
• Qualitative research article critique.
• Critical analysis of a research article on the effectiveness of drug round tabards .
• Discuss quantitative research about the barriers to electronic commerce implementation.
• Study the article Health Information Source Use by Jessica Gall Myrick and Michael Hendryx.
• Analyze a research article by Lengyel et al. That studies the amount of sugar in school breakfast .
• Write a critical analysis of the research studying the quality of pain management.
• Examine the research article The Mental Health of Indigenous Peoples in Canada by Sarah E Nelson and Kathi Wilson.
• Analysis of the article Development of a Proactive Care Program .
• Study the article on nursing REST: Break Through to Resilience by Rajamohan et al.
• Critically analyze the research article Quality Management in Healthcare: The Pivotal Desideratum .
• Examine and interpret the academic article In Defense of the Randomized Controlled Trial by Rosen et al.
• Write an analysis of a research article Cardiovascular Changes Resulting from Sexual Activity by Bispo, De Lima Lopes, and De Barros.
• Study the topicality and consistency of Dillner’s article Obstetrician Suspended After Research Inquiry .
• Critical analysis of research article on nosocomial pneumonia .
• Discuss the methods used by Johanna Brenner in her research on intersections and class relations.
• Analyze the research article by Ansari et al. examining the connection between type 2 diabetes and environmental factors.
• Analysis of research article Nurses’ Perceptions of Research Utilization in a Corporate Health Care System .
• Examine the importance of the research Effectiveness of Hand Hygiene Interventions in Reducing Illness Absence .
• Analyze and interpret the article on the toolkit for postgraduate research supervisors by E. Blass & S. Bertone.
• Discuss the utility and credibility of K. Than’s article A Brief History of Twin Studies .
• Write a critical analysis of the article researching the current US gun policy and its effect on the rates of gun violence cases.
• Analysis of articles on evidence-based prevention of surgical site infections.
• Examine the research article Nurses’ Knowledge about Palliative Care by Etafa et al.
• Analyze the research conducted by Sandelowski et al. on the stigmatization of HIV-positive women.
• Discuss the theoretical framework and methodology of a research article on psychological studies.
• Analysis of a research article about sports and creatine .
• Study the presentation of research findings in the scholarly article Leadership Characteristics and Digital Transformation .

Congrats! Now you know how to write a research paper analysis. You are welcome to check out our writing tips available on the website and save a ton of time on your academic papers. Share the link with your peers who may need our advice as well.

• An Introduction to Critical Analysis of Publications in Experimental Biomedical Science, the Research Paper in Basic Medical Sciences: K. Rangachari, modified by D.J. Crankshaw, McMaster University Honours Biology & Pharmacology Program
• Critical Analysis Template: Keiran Rankin and Sara Wolfe, the Writing Centre, Thompson Rivers University
• How to Read a Paper: S. Keshav, David R. Cheriton, School of Computer Science, the University of Waterloo
• How to Read a Research Paper: School of Engineering and Applied Sciences, Harvard University
• Reading Research Effectively, Organizing Your Social Sciences Research Paper: Research Guides at the University of Southern California
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• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• 8. The Discussion
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

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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• Last Updated: Sep 4, 2024 9:40 AM
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Harnessing the power of poetry in academic research – the author’s use of poetry as a tool for analysis

Holly Bennion, PhD graduate at Durham University 9 Sep 2024

This blog post focuses on my approach to using poetry as an analytical tool in a recent empirical study. There is an exciting body of research highlighting the potential for incorporating poetry into the various stages of the research process. Writing and sharing poems can be an effective data collection method, whereby poems are constructed by/with participants to explore their stories, feelings and memories. Poetry can also be used as an analytical/interpretative lens – for example, Carr (2003) created poems to document the experiences of family members of hospitalised relatives, transforming interview transcripts into poetry. Researchers can also use poetry to disseminate educational research and extend the tone and scope of research communication. The growing emergence of poetry in research, underpinned by arts-based research, is also connected to theoretical insights by postmodern, poststructural and feminist theories, which invites transformative and inclusive possibilities for research that goes beyond hegemonic and traditional forms of knowledge (Cutts & Sankofa Waters, 2019).

My PhD research explored children’s experiences and perspectives of belonging and school inclusion. I explored the interconnectivity in discourses on self-identification, otherness and school inclusion in multilingual and multicultural spaces. The methods included focus groups, children’s artwork, co-analysis with participants, and dance and drama workshops. As part of the data analysis process, I chose to experiment with poems. This process involved going back and forth between the transcriptions, the NVivo coding, and looking closely at the participants’ artwork and what they said about it.

To begin the process, I experimented with free-verse poetry, whereby I attempted to use poetry to identify connections between participants’ comments, further identify themes and keywords, and document my own reflections and feelings as I delved into the data.

Then, I began experimenting with structure and specific words and phrases. I used linguistic devices such as repetition to illustrate aspects that the participants felt strongly about or things they mentioned frequently. I experimented with using short, snappy lines or long, stream-of-consciousness lines to imply the tone of voice and the atmosphere of the workshops. I selected six poems to include in my thesis. Below is one example, which takes verbatim the words of the participants:

Something for you

It belongs to me and

I own it, just mine, not sharing

I may share it sometimes

My life, my bed

The first part of this poem reflects Aasab’s comment: ‘belonging is something for you, it’s like a surprise for you and we have to keep it’. I was interested in her view of belonging as a ‘surprise’. The exclamation mark was used to convey her excited tone of voice. The repetition of ‘my’ – ‘my life, my bed, my things’ – was utilised to highlight how participants often distinguished between what is ‘mine’ and ‘yours’.

‘Through poetry, I was liberated from the structured form of academic writing; I could experiment with themes, form, language, tone and imagery to interpret and represent the children’s comments about belonging and school inclusion.’

The notion of material possessions and human–object relationships was significant in the findings. Furman and colleagues (2007) note that poetry can be a powerful tool for communication through the playfulness of metaphor, alliteration and visual elements. Through poetry, I was liberated from the structured form of academic writing; I could experiment with themes, form, language, tone and imagery to interpret and represent the children’s comments about belonging and school inclusion. I found that poetry as an analysis tool gave me enthusiasm for and confidence in my data.

Reflecting on my research approach, I advocate that poetry can serve as a valuable analysis tool for research, and it can be utilised as part of a multi-level approach. Poetry can be a powerful tool for communicating the researcher’s reflections and interpretations of the data and representing the voices of participants in engaging ways. Importantly, I was not seeking to create a single narrative through the poetry. Poetry is open to interpretation; it is evocative and invites emotional engagement. Like my data collection methods – which invited collaboration, imagination and contradictions among participants – the poetry was an interesting tool that enabled multiple narratives, opinions and clarifications for the researcher and audience.

To conclude, I quote poet and academic Neil McBride (2009, p. 43):

‘[Poetry] questions, it leaves frayed edges and loose writes. It draws out the hidden, the spiritual, the underlying rhythms of life that we swamp with information, noise and news channels.’

Holly will be presenting at the  BERA Conference 2024 and WERA Focal Meeting on Monday 9 September at 12:45pm for a symposium panel on ‘Migration and Education across the Four Nations of the UK’. 

Carr, J. (2003). Poetic expressions of vigilance. Qualitative Health Research , 13 (9), 1334–1331. https://doi.org/DOI: 10.1177/1049732303254018

Cutts, Q., & Sankofa Waters, M. (2019). Poetic approaches to qualitative data analysis. Education Publications , 145. https://doi.org/10.1093/acrefore/9780190264093.013.993   

Furman, R., Langer, C., Davis, C. S., Gallardo, H. P., & Kulkarni, S. (2007). Expressive, research and reflective poetry as qualitative inquiry: A study of adolescent identity. Qualitative Research , 7 (3), 301–315. https://doi.org/10.1177/1468794107078511

McBride, N. (2009, December 3). Poetry cornered. Times Higher Education , 1 (925), 42–44.   https://www.timeshighereducation.com/features/poetry-cornered/409334.article

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GPT-fabricated scientific papers on Google Scholar: Key features, spread, and implications for preempting evidence manipulation

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Academic journals, archives, and repositories are seeing an increasing number of questionable research papers clearly produced using generative AI. They are often created with widely available, general-purpose AI applications, most likely ChatGPT, and mimic scientific writing. Google Scholar easily locates and lists these questionable papers alongside reputable, quality-controlled research. Our analysis of a selection of questionable GPT-fabricated scientific papers found in Google Scholar shows that many are about applied, often controversial topics susceptible to disinformation: the environment, health, and computing. The resulting enhanced potential for malicious manipulation of society’s evidence base, particularly in politically divisive domains, is a growing concern.

Swedish School of Library and Information Science, University of Borås, Sweden

Department of Arts and Cultural Sciences, Lund University, Sweden

Division of Environmental Communication, Swedish University of Agricultural Sciences, Sweden

Research Questions

• Where are questionable publications produced with generative pre-trained transformers (GPTs) that can be found via Google Scholar published or deposited?
• What are the main characteristics of these publications in relation to predominant subject categories?
• How are these publications spread in the research infrastructure for scholarly communication?
• How is the role of the scholarly communication infrastructure challenged in maintaining public trust in science and evidence through inappropriate use of generative AI?

research note Summary

• A sample of scientific papers with signs of GPT-use found on Google Scholar was retrieved, downloaded, and analyzed using a combination of qualitative coding and descriptive statistics. All papers contained at least one of two common phrases returned by conversational agents that use large language models (LLM) like OpenAI’s ChatGPT. Google Search was then used to determine the extent to which copies of questionable, GPT-fabricated papers were available in various repositories, archives, citation databases, and social media platforms.
• Roughly two-thirds of the retrieved papers were found to have been produced, at least in part, through undisclosed, potentially deceptive use of GPT. The majority (57%) of these questionable papers dealt with policy-relevant subjects (i.e., environment, health, computing), susceptible to influence operations. Most were available in several copies on different domains (e.g., social media, archives, and repositories).
• Two main risks arise from the increasingly common use of GPT to (mass-)produce fake, scientific publications. First, the abundance of fabricated “studies” seeping into all areas of the research infrastructure threatens to overwhelm the scholarly communication system and jeopardize the integrity of the scientific record. A second risk lies in the increased possibility that convincingly scientific-looking content was in fact deceitfully created with AI tools and is also optimized to be retrieved by publicly available academic search engines, particularly Google Scholar. However small, this possibility and awareness of it risks undermining the basis for trust in scientific knowledge and poses serious societal risks.

Implications

The use of ChatGPT to generate text for academic papers has raised concerns about research integrity. Discussion of this phenomenon is ongoing in editorials, commentaries, opinion pieces, and on social media (Bom, 2023; Stokel-Walker, 2024; Thorp, 2023). There are now several lists of papers suspected of GPT misuse, and new papers are constantly being added. 1 See for example Academ-AI, https://www.academ-ai.info/ , and Retraction Watch, https://retractionwatch.com/papers-and-peer-reviews-with-evidence-of-chatgpt-writing/ . While many legitimate uses of GPT for research and academic writing exist (Huang & Tan, 2023; Kitamura, 2023; Lund et al., 2023), its undeclared use—beyond proofreading—has potentially far-reaching implications for both science and society, but especially for their relationship. It, therefore, seems important to extend the discussion to one of the most accessible and well-known intermediaries between science, but also certain types of misinformation, and the public, namely Google Scholar, also in response to the legitimate concerns that the discussion of generative AI and misinformation needs to be more nuanced and empirically substantiated  (Simon et al., 2023).

Google Scholar, https://scholar.google.com , is an easy-to-use academic search engine. It is available for free, and its index is extensive (Gusenbauer & Haddaway, 2020). It is also often touted as a credible source for academic literature and even recommended in library guides, by media and information literacy initiatives, and fact checkers (Tripodi et al., 2023). However, Google Scholar lacks the transparency and adherence to standards that usually characterize citation databases. Instead, Google Scholar uses automated crawlers, like Google’s web search engine (Martín-Martín et al., 2021), and the inclusion criteria are based on primarily technical standards, allowing any individual author—with or without scientific affiliation—to upload papers to be indexed (Google Scholar Help, n.d.). It has been shown that Google Scholar is susceptible to manipulation through citation exploits (Antkare, 2020) and by providing access to fake scientific papers (Dadkhah et al., 2017). A large part of Google Scholar’s index consists of publications from established scientific journals or other forms of quality-controlled, scholarly literature. However, the index also contains a large amount of gray literature, including student papers, working papers, reports, preprint servers, and academic networking sites, as well as material from so-called “questionable” academic journals, including paper mills. The search interface does not offer the possibility to filter the results meaningfully by material type, publication status, or form of quality control, such as limiting the search to peer-reviewed material.

To understand the occurrence of ChatGPT (co-)authored work in Google Scholar’s index, we scraped it for publications, including one of two common ChatGPT responses (see Appendix A) that we encountered on social media and in media reports (DeGeurin, 2024). The results of our descriptive statistical analyses showed that around 62% did not declare the use of GPTs. Most of these GPT-fabricated papers were found in non-indexed journals and working papers, but some cases included research published in mainstream scientific journals and conference proceedings. 2 Indexed journals mean scholarly journals indexed by abstract and citation databases such as Scopus and Web of Science, where the indexation implies journals with high scientific quality. Non-indexed journals are journals that fall outside of this indexation. More than half (57%) of these GPT-fabricated papers concerned policy-relevant subject areas susceptible to influence operations. To avoid increasing the visibility of these publications, we abstained from referencing them in this research note. However, we have made the data available in the Harvard Dataverse repository.

The publications were related to three issue areas—health (14.5%), environment (19.5%) and computing (23%)—with key terms such “healthcare,” “COVID-19,” or “infection”for health-related papers, and “analysis,” “sustainable,” and “global” for environment-related papers. In several cases, the papers had titles that strung together general keywords and buzzwords, thus alluding to very broad and current research. These terms included “biology,” “telehealth,” “climate policy,” “diversity,” and “disrupting,” to name just a few.  While the study’s scope and design did not include a detailed analysis of which parts of the articles included fabricated text, our dataset did contain the surrounding sentences for each occurrence of the suspicious phrases that formed the basis for our search and subsequent selection. Based on that, we can say that the phrases occurred in most sections typically found in scientific publications, including the literature review, methods, conceptual and theoretical frameworks, background, motivation or societal relevance, and even discussion. This was confirmed during the joint coding, where we read and discussed all articles. It became clear that not just the text related to the telltale phrases was created by GPT, but that almost all articles in our sample of questionable articles likely contained traces of GPT-fabricated text everywhere.

Evidence hacking and backfiring effects

Generative pre-trained transformers (GPTs) can be used to produce texts that mimic scientific writing. These texts, when made available online—as we demonstrate—leak into the databases of academic search engines and other parts of the research infrastructure for scholarly communication. This development exacerbates problems that were already present with less sophisticated text generators (Antkare, 2020; Cabanac & Labbé, 2021). Yet, the public release of ChatGPT in 2022, together with the way Google Scholar works, has increased the likelihood of lay people (e.g., media, politicians, patients, students) coming across questionable (or even entirely GPT-fabricated) papers and other problematic research findings. Previous research has emphasized that the ability to determine the value and status of scientific publications for lay people is at stake when misleading articles are passed off as reputable (Haider & Åström, 2017) and that systematic literature reviews risk being compromised (Dadkhah et al., 2017). It has also been highlighted that Google Scholar, in particular, can be and has been exploited for manipulating the evidence base for politically charged issues and to fuel conspiracy narratives (Tripodi et al., 2023). Both concerns are likely to be magnified in the future, increasing the risk of what we suggest calling evidence hacking —the strategic and coordinated malicious manipulation of society’s evidence base.

The authority of quality-controlled research as evidence to support legislation, policy, politics, and other forms of decision-making is undermined by the presence of undeclared GPT-fabricated content in publications professing to be scientific. Due to the large number of archives, repositories, mirror sites, and shadow libraries to which they spread, there is a clear risk that GPT-fabricated, questionable papers will reach audiences even after a possible retraction. There are considerable technical difficulties involved in identifying and tracing computer-fabricated papers (Cabanac & Labbé, 2021; Dadkhah et al., 2023; Jones, 2024), not to mention preventing and curbing their spread and uptake.

However, as the rise of the so-called anti-vaxx movement during the COVID-19 pandemic and the ongoing obstruction and denial of climate change show, retracting erroneous publications often fuels conspiracies and increases the following of these movements rather than stopping them. To illustrate this mechanism, climate deniers frequently question established scientific consensus by pointing to other, supposedly scientific, studies that support their claims. Usually, these are poorly executed, not peer-reviewed, based on obsolete data, or even fraudulent (Dunlap & Brulle, 2020). A similar strategy is successful in the alternative epistemic world of the global anti-vaccination movement (Carrion, 2018) and the persistence of flawed and questionable publications in the scientific record already poses significant problems for health research, policy, and lawmakers, and thus for society as a whole (Littell et al., 2024). Considering that a person’s support for “doing your own research” is associated with increased mistrust in scientific institutions (Chinn & Hasell, 2023), it will be of utmost importance to anticipate and consider such backfiring effects already when designing a technical solution, when suggesting industry or legal regulation, and in the planning of educational measures.

Recommendations

Solutions should be based on simultaneous considerations of technical, educational, and regulatory approaches, as well as incentives, including social ones, across the entire research infrastructure. Paying attention to how these approaches and incentives relate to each other can help identify points and mechanisms for disruption. Recognizing fraudulent academic papers must happen alongside understanding how they reach their audiences and what reasons there might be for some of these papers successfully “sticking around.” A possible way to mitigate some of the risks associated with GPT-fabricated scholarly texts finding their way into academic search engine results would be to provide filtering options for facets such as indexed journals, gray literature, peer-review, and similar on the interface of publicly available academic search engines. Furthermore, evaluation tools for indexed journals 3 Such as LiU Journal CheckUp, https://ep.liu.se/JournalCheckup/default.aspx?lang=eng . could be integrated into the graphical user interfaces and the crawlers of these academic search engines. To enable accountability, it is important that the index (database) of such a search engine is populated according to criteria that are transparent, open to scrutiny, and appropriate to the workings of  science and other forms of academic research. Moreover, considering that Google Scholar has no real competitor, there is a strong case for establishing a freely accessible, non-specialized academic search engine that is not run for commercial reasons but for reasons of public interest. Such measures, together with educational initiatives aimed particularly at policymakers, science communicators, journalists, and other media workers, will be crucial to reducing the possibilities for and effects of malicious manipulation or evidence hacking. It is important not to present this as a technical problem that exists only because of AI text generators but to relate it to the wider concerns in which it is embedded. These range from a largely dysfunctional scholarly publishing system (Haider & Åström, 2017) and academia’s “publish or perish” paradigm to Google’s near-monopoly and ideological battles over the control of information and ultimately knowledge. Any intervention is likely to have systemic effects; these effects need to be considered and assessed in advance and, ideally, followed up on.

Our study focused on a selection of papers that were easily recognizable as fraudulent. We used this relatively small sample as a magnifying glass to examine, delineate, and understand a problem that goes beyond the scope of the sample itself, which however points towards larger concerns that require further investigation. The work of ongoing whistleblowing initiatives 4 Such as Academ-AI, https://www.academ-ai.info/ , and Retraction Watch, https://retractionwatch.com/papers-and-peer-reviews-with-evidence-of-chatgpt-writing/ . , recent media reports of journal closures (Subbaraman, 2024), or GPT-related changes in word use and writing style (Cabanac et al., 2021; Stokel-Walker, 2024) suggest that we only see the tip of the iceberg. There are already more sophisticated cases (Dadkhah et al., 2023) as well as cases involving fabricated images (Gu et al., 2022). Our analysis shows that questionable and potentially manipulative GPT-fabricated papers permeate the research infrastructure and are likely to become a widespread phenomenon. Our findings underline that the risk of fake scientific papers being used to maliciously manipulate evidence (see Dadkhah et al., 2017) must be taken seriously. Manipulation may involve undeclared automatic summaries of texts, inclusion in literature reviews, explicit scientific claims, or the concealment of errors in studies so that they are difficult to detect in peer review. However, the mere possibility of these things happening is a significant risk in its own right that can be strategically exploited and will have ramifications for trust in and perception of science. Society’s methods of evaluating sources and the foundations of media and information literacy are under threat and public trust in science is at risk of further erosion, with far-reaching consequences for society in dealing with information disorders. To address this multifaceted problem, we first need to understand why it exists and proliferates.

Finding 1: 139 GPT-fabricated, questionable papers were found and listed as regular results on the Google Scholar results page. Non-indexed journals dominate.

Most questionable papers we found were in non-indexed journals or were working papers, but we did also find some in established journals, publications, conferences, and repositories. We found a total of 139 papers with a suspected deceptive use of ChatGPT or similar LLM applications (see Table 1). Out of these, 19 were in indexed journals, 89 were in non-indexed journals, 19 were student papers found in university databases, and 12 were working papers (mostly in preprint databases). Table 1 divides these papers into categories. Health and environment papers made up around 34% (47) of the sample. Of these, 66% were present in non-indexed journals.

Finding 2: GPT-fabricated, questionable papers are disseminated online, permeating the research infrastructure for scholarly communication, often in multiple copies. Applied topics with practical implications dominate.

The 20 papers concerning health-related issues are distributed across 20 unique domains, accounting for 46 URLs. The 27 papers dealing with environmental issues can be found across 26 unique domains, accounting for 56 URLs.  Most of the identified papers exist in multiple copies and have already spread to several archives, repositories, and social media. It would be difficult, or impossible, to remove them from the scientific record.

As apparent from Table 2, GPT-fabricated, questionable papers are seeping into most parts of the online research infrastructure for scholarly communication. Platforms on which identified papers have appeared include ResearchGate, ORCiD, Journal of Population Therapeutics and Clinical Pharmacology (JPTCP), Easychair, Frontiers, the Institute of Electrical and Electronics Engineer (IEEE), and X/Twitter. Thus, even if they are retracted from their original source, it will prove very difficult to track, remove, or even just mark them up on other platforms. Moreover, unless regulated, Google Scholar will enable their continued and most likely unlabeled discoverability.

A word rain visualization (Centre for Digital Humanities Uppsala, 2023), which combines word prominences through TF-IDF 5 Term frequency–inverse document frequency , a method for measuring the significance of a word in a document compared to its frequency across all documents in a collection. scores with semantic similarity of the full texts of our sample of GPT-generated articles that fall into the “Environment” and “Health” categories, reflects the two categories in question. However, as can be seen in Figure 1, it also reveals overlap and sub-areas. The y-axis shows word prominences through word positions and font sizes, while the x-axis indicates semantic similarity. In addition to a certain amount of overlap, this reveals sub-areas, which are best described as two distinct events within the word rain. The event on the left bundles terms related to the development and management of health and healthcare with “challenges,” “impact,” and “potential of artificial intelligence”emerging as semantically related terms. Terms related to research infrastructures, environmental, epistemic, and technological concepts are arranged further down in the same event (e.g., “system,” “climate,” “understanding,” “knowledge,” “learning,” “education,” “sustainable”). A second distinct event further to the right bundles terms associated with fish farming and aquatic medicinal plants, highlighting the presence of an aquaculture cluster.  Here, the prominence of groups of terms such as “used,” “model,” “-based,” and “traditional” suggests the presence of applied research on these topics. The two events making up the word rain visualization, are linked by a less dominant but overlapping cluster of terms related to “energy” and “water.”

The bar chart of the terms in the paper subset (see Figure 2) complements the word rain visualization by depicting the most prominent terms in the full texts along the y-axis. Here, word prominences across health and environment papers are arranged descendingly, where values outside parentheses are TF-IDF values (relative frequencies) and values inside parentheses are raw term frequencies (absolute frequencies).

Finding 3: Google Scholar presents results from quality-controlled and non-controlled citation databases on the same interface, providing unfiltered access to GPT-fabricated questionable papers.

Google Scholar’s central position in the publicly accessible scholarly communication infrastructure, as well as its lack of standards, transparency, and accountability in terms of inclusion criteria, has potentially serious implications for public trust in science. This is likely to exacerbate the already-known potential to exploit Google Scholar for evidence hacking (Tripodi et al., 2023) and will have implications for any attempts to retract or remove fraudulent papers from their original publication venues. Any solution must consider the entirety of the research infrastructure for scholarly communication and the interplay of different actors, interests, and incentives.

We searched and scraped Google Scholar using the Python library Scholarly (Cholewiak et al., 2023) for papers that included specific phrases known to be common responses from ChatGPT and similar applications with the same underlying model (GPT3.5 or GPT4): “as of my last knowledge update” and/or “I don’t have access to real-time data” (see Appendix A). This facilitated the identification of papers that likely used generative AI to produce text, resulting in 227 retrieved papers. The papers’ bibliographic information was automatically added to a spreadsheet and downloaded into Zotero. 6 An open-source reference manager, https://zotero.org .

We employed multiple coding (Barbour, 2001) to classify the papers based on their content. First, we jointly assessed whether the paper was suspected of fraudulent use of ChatGPT (or similar) based on how the text was integrated into the papers and whether the paper was presented as original research output or the AI tool’s role was acknowledged. Second, in analyzing the content of the papers, we continued the multiple coding by classifying the fraudulent papers into four categories identified during an initial round of analysis—health, environment, computing, and others—and then determining which subjects were most affected by this issue (see Table 1). Out of the 227 retrieved papers, 88 papers were written with legitimate and/or declared use of GPTs (i.e., false positives, which were excluded from further analysis), and 139 papers were written with undeclared and/or fraudulent use (i.e., true positives, which were included in further analysis). The multiple coding was conducted jointly by all authors of the present article, who collaboratively coded and cross-checked each other’s interpretation of the data simultaneously in a shared spreadsheet file. This was done to single out coding discrepancies and settle coding disagreements, which in turn ensured methodological thoroughness and analytical consensus (see Barbour, 2001). Redoing the category coding later based on our established coding schedule, we achieved an intercoder reliability (Cohen’s kappa) of 0.806 after eradicating obvious differences.

The ranking algorithm of Google Scholar prioritizes highly cited and older publications (Martín-Martín et al., 2016). Therefore, the position of the articles on the search engine results pages was not particularly informative, considering the relatively small number of results in combination with the recency of the publications. Only the query “as of my last knowledge update” had more than two search engine result pages. On those, questionable articles with undeclared use of GPTs were evenly distributed across all result pages (min: 4, max: 9, mode: 8), with the proportion of undeclared use being slightly higher on average on later search result pages.

To understand how the papers making fraudulent use of generative AI were disseminated online, we programmatically searched for the paper titles (with exact string matching) in Google Search from our local IP address (see Appendix B) using the googlesearch – python library(Vikramaditya, 2020). We manually verified each search result to filter out false positives—results that were not related to the paper—and then compiled the most prominent URLs by field. This enabled the identification of other platforms through which the papers had been spread. We did not, however, investigate whether copies had spread into SciHub or other shadow libraries, or if they were referenced in Wikipedia.

We used descriptive statistics to count the prevalence of the number of GPT-fabricated papers across topics and venues and top domains by subject. The pandas software library for the Python programming language (The pandas development team, 2024) was used for this part of the analysis. Based on the multiple coding, paper occurrences were counted in relation to their categories, divided into indexed journals, non-indexed journals, student papers, and working papers. The schemes, subdomains, and subdirectories of the URL strings were filtered out while top-level domains and second-level domains were kept, which led to normalizing domain names. This, in turn, allowed the counting of domain frequencies in the environment and health categories. To distinguish word prominences and meanings in the environment and health-related GPT-fabricated questionable papers, a semantically-aware word cloud visualization was produced through the use of a word rain (Centre for Digital Humanities Uppsala, 2023) for full-text versions of the papers. Font size and y-axis positions indicate word prominences through TF-IDF scores for the environment and health papers (also visualized in a separate bar chart with raw term frequencies in parentheses), and words are positioned along the x-axis to reflect semantic similarity (Skeppstedt et al., 2024), with an English Word2vec skip gram model space (Fares et al., 2017). An English stop word list was used, along with a manually produced list including terms such as “https,” “volume,” or “years.”

• Artificial Intelligence
• / Search engines

Cite this Essay

Haider, J., Söderström, K. R., Ekström, B., & Rödl, M. (2024). GPT-fabricated scientific papers on Google Scholar: Key features, spread, and implications for preempting evidence manipulation. Harvard Kennedy School (HKS) Misinformation Review . https://doi.org/10.37016/mr-2020-156

• / Appendix B

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This research has been supported by Mistra, the Swedish Foundation for Strategic Environmental Research, through the research program Mistra Environmental Communication (Haider, Ekström, Rödl) and the Marcus and Amalia Wallenberg Foundation [2020.0004] (Söderström).

Competing Interests

The authors declare no competing interests.

The research described in this article was carried out under Swedish legislation. According to the relevant EU and Swedish legislation (2003:460) on the ethical review of research involving humans (“Ethical Review Act”), the research reported on here is not subject to authorization by the Swedish Ethical Review Authority (“etikprövningsmyndigheten”) (SRC, 2017).

This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided that the original author and source are properly credited.

Data Availability

All data needed to replicate this study are available at the Harvard Dataverse: https://doi.org/10.7910/DVN/WUVD8X

Acknowledgements

The authors wish to thank two anonymous reviewers for their valuable comments on the article manuscript as well as the editorial group of Harvard Kennedy School (HKS) Misinformation Review for their thoughtful feedback and input.

The past and present of thought experiments’ research at Glancy: bibliometric review and analysis

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• Published: 07 September 2024
• Volume 3 , article number  142 , ( 2024 )

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• Hartono Bancong 1  

In the development of physical theories, thought experiments play a crucial role. Research on this topic began in 1976 and has continued to the present. This study aims to provide a more complete picture of the progress of thought experiments over the past two decades. To achieve this, this study employs bibliometric mapping methods. A total of 679 published papers were analyzed, including articles (504), conference papers (92), and book chapters (83). This data was retrieved from the Scopus database. The study's findings reveal that research and publications on thought experiments are highly valued and have received significant attention over the past eight years. According to the findings, 90% of the top 20 source titles contributing to thought experiments are from journals in the first and second quartiles (Q1 and Q2). This quartile ranking shows the quality and significant influence of a journal. The geographical distribution indicates that the United States contributes the most to thought experiments research, with 213 documents, 2592 citations, and 47 links. We also identified several prospective keywords that could be the focus of future research, including artificial intelligence, physics education, fiction, God, theology, productive imagination, technology, speculative design, and critical design. Therefore, this study provides a thorough picture of thought experiment research trends and future directions of potential topics that can be the focus of future researchers.

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1 Introduction

Thought experiments (TEs) have a long history in science. Since Ernst Mach, the term TEs, a direct translation of the phrase Gedankenexperimente , has been widely discussed in the philosophy of science [ 18 ]. Thought and experiments are two components of TEs [ 4 , 18 , 29 ]. The thought element involves visualizing an imaginary world based on theory and experience, whereas the experimental aspect entails practical tasks in a physical laboratory, such as manipulating items and related variables. While some authors consider TEs to be mere arguments [ 24 ], others believe TEs are a form of fiction since their function is comparable to literary fiction in that both have a narrative framework by creating scenarios of occurrences from beginning to end [ 13 , 22 ]. However, unlike fiction, which frequently provides contradictory discourses, we believe that TEs should be logically and conceptually cohesive. TEs are structured imaginative actions based on the theory and experience of thought experimenters to achieve certain goals.

The contributions of TEs to the growth of scientific theories, particularly in physics, are essential. Physicists have employed TEs several times throughout history to either come up with new hypotheses or disprove previous ones. As the most representative examples, Newton used the TEs of cannonballs to support his hypothesis that the force of gravity is universal and the principal force of planetary motion, or Galileo used the TEs of free-falling bodies to disprove Aristotle's theory of gravity, which stated that the speed of falling objects is proportional to their weight. Galileo’s falling body, Newton's bucket and cannon, Maxwell's demon, and Schrodinger’s cat are just a few of the well-known TEs in physics [ 4 ]. These are only a few examples of the significant role TEs played in the development of scientific theories.

In the past 10 years, several works have studied TEs from the perspectives of history and philosophy of science [ 7 , 8 , 10 , 30 , 33 ]. Because most existing historical work on TEs focuses on individual TEs or individual accounts of TEs, reassessing the history of the philosophical debate on TEs becomes essential [ 33 ]. In the philosophy of science, historical debates regarding interactions between various philosophers or philosophical explanations across time in developed TEs are sometimes disregarded. Several studies have also used TEs as an imaginative tool in the classroom to teach science subjects. Velentzas and Halkia [ 37 ], for example, used TEs from Newton's Cannon to teach satellite physics. They then assert that TEs, as a teaching tool, can assist students in strengthening their syllogistic abilities and help them conceive scenarios beyond their everyday experience [ 37 ]. El Skaf and Palacios [ 12 ] have also systematically analyzed the epistemic role of TEs from Wheeler's demon and Geroch's engine, which gave rise to black hole thermodynamics. Recently, Bancong et al. [ 2 ] reported that physics teachers in Indonesia have a high awareness of the importance of TEs in learning physics, especially atomic theory and relativity, even though they lack skills in the pedagogic aspects of TEs. Therefore, Indonesian physics teachers also suggest using technology such as virtual reality to help visualize an imaginary world when performing TEs.

Although a number of studies on TEs from various perspectives have been conducted, no study has yet completely examined this field to look at the trend of this topic in recent years. Therefore, it becomes essential to conduct a bibliometric study of TEs over time based on authoritative databases like Scopus. Because of Scopus's comprehensive coverage of scholarly articles in the field of education [ 23 , 27 , 34 ], it was chosen as the database for this study. Scopus is also a popular resource for bibliometric research [ 23 , 28 ]. For this reason, we use data sources from the Scopus database to carry out the bibliometric method. Our study covers journal articles, conference papers, and book chapters from the last 20 years to provide a more complete view.

To highlight the significance of TEs research, we compare its growth to other scientific topics. While many scientific fields have seen growth over the past two decades, TEs research has also shown a unique and sustained increase in interest and publications. This trend contrasts sharply with the decline in research focus on traditional physics experiments [ 41 ]. Similarly, other topics in physics education, such as methodological issues, textbook analysis, and pre-service physics teachers, are also experiencing reduced research interest [ 25 ]. Additionally, the integration of TEs with emerging technologies, such as artificial intelligence, underscores their evolving relevance and potential for future research [ 21 ].

Therefore, this study aims to provide an up-to-date overview of trends in TEs research. The research questions in this study are as follows:

How is the growth of research output on the topic of TEs over the last 20 years?

Which source titles have contributed the most to the publication of papers on TEs in the last 20 years?

Who are the most prominent authors on the topic of TEs in the last 20 years?

Which countries have published the most articles on TEs over the past 20 years?

What are the most relevant keywords that can be found in the studies of TEs over the last 20 years?

2.1 Research design

This study aims to analyze the trends in TEs research over the past 20 years by using a bibliometric mapping method. To ensure a thorough analysis of recent trends and developments, this study focused on studies published between 2003 and 2022. This period was chosen because of significant advancements in research methodologies and bibliometric analysis tools in the early 2000s, as well as the consistent growth and comprehensive coverage of the Scopus database since that time. Bibliometric analysis is a well-known statistical method for examining and analyzing a large amount of scientific data on a certain topic [ 26 , 39 ]. Metrics studied in bibliometric research include annual publications, source titles, authors, institutions, nations, and keywords, covering data from primary, secondary, and tertiary journals over a specific time period. It should be noted that no ethical approval was required for this study as it did not involve humans or animals.

2.2 Data collection

In this study, data were gathered from the Scopus database ( https://www.scopus.com ). Scopus was chosen because it covers a wider range of documents than any other scientific database [ 23 , 28 , 35 ]. Scopus is the world's largest abstracting and indexing database, with 84 million records containing over 18.0 million open access items, including gold, hybrid gold, green, and bronze, as well as 10.9 million conference papers, 25.8 thousand active peer-reviewed journals, and over 7000 publishers [ 14 ]. In addition, Scopus covers a wider range of educational disciplines than other databases, such as the Web of Science (WoS) [ 23 , 27 , 34 ]. As a result, using the Scopus database enables researchers to shed light on areas that may not be covered in WoS.

Electronic data search and retrieval were conducted on February 25, 2023. Keyword search was set to include title, abstract, and keywords. The keyword search was set to include the title, abstract, and keywords. The combination of search strings, operators, and filters used in this study was TITLE-ABS-KEY ("Thought-experiments" AND "Science" OR "Physics"). Quotation marks were used to focus on documents containing this exact phrase, thus ensuring high relevance to the study's scope. The Scopus database retrieved 898 documents related to these keywords with full bibliographical information, including articles (67.04%), paper proceedings (10.13%), book chapters (10.02%), and other types of documents (12.81%). By using the Scopus filter, other types of publications (12.81%), including review articles, were excluded from the list of documents. The exclusion of review articles was intentional to focus on original research contributions that advance the field of TEs directly. Including reviews could confound the analysis as they often summarize existing research rather than introduce new findings. Therefore, concentrating on the three most prevalent types of documents—articles, conference papers, and book chapters—allowed for a clearer interpretation of trends and patterns in original research outputs over the specified period. Additionally, we limited the year of publication to studies published within the last 20 years (2003–2022) to ensure the relevance and currency of our analysis. After using a filtering process to eliminate papers that did not meet the inclusion and exclusion criteria, a total of 679 articles were identified for bibliometric analysis. These articles included 504 articles, 92 book chapters, and 83 conference papers.

2.3 Data analysis

The data analysis process began with acquiring the necessary raw data by downloading it from the Scopus database in either comma-separated value (CSV) or research information system (RIS) format. For data analysis and visualization, we used VOSviewer and Microsoft Excel. VOSviewer, a sophisticated mapping tool, was employed to create collaborative networks for various variables and keywords, while Microsoft Excel was used for descriptive analysis, such as determining the number of articles published each year and identifying the most prolific source titles.

The network graphs in this study were generated using VOSviewer, based on co-authorship, co-occurrence, and citation data from Scopus. The analysis type focused on the co-occurrence of keywords and co-authorship, with a full counting method. Keywords with a minimum of four occurrences were included. The visualization settings in VOSviewer were mainly default, with the attraction parameter set to 2 and the repulsion parameter set to 0. These settings ensured that the most relevant and frequently occurring terms were highlighted, providing a clear overview of research trends and collaborations in the field of TEs over the past 20 years.

In this study, we explored the most productive publishers, the most referenced articles, the most productive authors, the most productive nations, and author keyword occurrences across time. An analysis of co-authorship and co-occurrence was performed at this stage. The analysis of co-authorship provides insights into the interactions between authors. This methodology was also used for metrics related to countries. For country attribution, we included all the countries of all authors involved in each publication, not just the corresponding author. This method ensures that all co-authors' contributions are acknowledged and provides a comprehensive representation of the global distribution of research. Co-occurrence analysis was employed as a means of investigating current keywords and their interrelationships with other phrases associated with TEs. Within this particular framework, the term “node size” refers to the frequency at which a certain keyword appears in comparison to other words. Additionally, interconnected nodes are visually represented by lines known as connections. The link establishes a connection between two nodes, while the width of the link signifies the intensity or potency of the connection between the aforementioned nodes [ 36 , 39 ].

In the context of network map visualization, nodes that exhibit a high degree of association are categorized into clusters. The clustering of items was performed using the Louvain algorithm, a popular method for community detection in large networks due to its efficiency and accuracy in handling large datasets [ 36 , 39 ]. This algorithm was chosen for its ability to uncover modular structures within large networks, which is particularly useful for identifying distinct research themes and collaboration groups in bibliometric data. Subsequently, a distinct color code was assigned to each cluster, wherein nodes within the same cluster exhibit a high degree of homogeneity. Therefore, this bibliometric mapping approach enabled researchers to discern patterns and emerging areas of interest throughout the timeframe spanning from 2003 to 2022. Figure 1 shows the stages in the process of collecting and analyzing data in this study.

The steps in collecting and analyzing the data

3.1 Statistics analysis

In this analysis, we use statistical data to observe differences in the number of articles published each year. The goal is to determine whether the quantity of publications on the topic of TEs has increased or decreased annually. Figure 2 illustrates the number of papers published over the last 20 years (2003–2022). As we can see, there has been an increase in the interest and attention of researchers, scholars, and experts in researching TEs. The growth started in 2004 and continued until 2006. The number of papers published then fluctuated between 2006 and 2015. The increase started again in 2015 and continued until 2021. The number of publications increased significantly in 2021, with 69 articles published. This growth demonstrates that research and publications on TEs are in high demand and have garnered significant attention globally in the last eight years despite a reduction in 2022. Although studies in this area are still ongoing, these findings indicate an annual growth in the writing and publication of TEs on Scopus.

Number of articles published each year

Statistical data are also used to see the number of source titles that have made the greatest contributions to TEs during the last 20 years. A total of 679 papers have been published from various sources with different types of documents in the form of articles (504), conference papers (92), and book chapters (83). According to statistical data in the Scopus database, publication in journals is very significant in publishing research on the topic of TEs, while publication in proceedings and book chapters with the main scope of TEs is not very significant. Therefore, researchers, academics, and experts are advised to submit their articles focused on TEs to journals rather than proceedings and chapter books. Table 1 lists the top 20 sources of scientific research publications covering the topic of TEs from 2003 to 2022.

As seen in Table 1 , 90% of the source titles contributing to the TEs topic are journals, with only one publishing conference proceedings. Philosophical studies ranks first, with 17 documents published in the last 20 years. This is followed by the AIP Conference Proceedings with 15 documents. The American Journal of Physics, Science and Education, and Studies in History and Philosophy of Science Part A have published 11 documents each. Other source titles, such as Synthese (10), Foundations of Science (9), Physics Teacher (9), Journal for General Philosophy of Science (8), and Philosophy of Science (8), also contributed to publishing TEs topics. Minds and Machines and Physics Education each published seven documents. Erkenntnis, European Journal of Physics, Physics Essays, and Religions each published six documents, Acta Analytica published five documents, while Axiomathes, Boston Studies in the Philosophy of and History of Science, and European Journal for Philosophy of Science each published four documents.

3.2 Bibliometric analysis

3.2.1 contributions of authors.

Table 2 shows the 10 most prolific authors based on the total number of published articles from 2003 to 2022. As shown in this list, Stuart is the most significant author with 7 papers (51 citations), followed by Bancong from Universitas Muhammadiyah Makassar, Indonesia, with 5 papers (15 citations). Following Bancong, Fehige from the University of Toronto, Canada, has also published 5 articles. The majority of Fehige’s research focuses on TEs in the context of religion. In contrast to Fehige, Brown, also from the University of Toronto in Canada, has studied TEs through the lens of history and philosophy of science in several of his works (4 documents, 52 citations). Similarly, Buzzoni (3 documents, 15 citations) and El Skaf (3 documents, 29 citations) from Italy, discuss TEs from historical and philosophical perspectives of science. Meanwhile, Halkia and Velentzas from the University of Athens, Greece, have analyzed TEs thoroughly from an educational standpoint, with the number of documents being 4 and 86 citations.

3.2.2 Contributions of country

In the context of the leading countries, authors from 64 different countries/territories published a total of 679 documents. Table 3 lists the top 20 countries in terms of TE contributions based on the number of papers published. As shown, the United States contributes the most to TEs research, with 213 documents, 2592 citations, and 47 links. The number of papers is about three times that of the United Kingdom, which comes second (75 documents, 1016 citations, and 31 links). European countries continue to hold third to sixth place, with Germany publishing 50 documents with 634 citations, followed by Canada (43 documents, 410 citations, and 17 links), Italy (33 documents, 96 citations, 6 links), and the Netherlands (28 documents, 342 citations, and 12 links). This suggests that countries in America and Europe contribute the most to TEs. The Asian country that has contributed the most to TEs is China, with 18 documents, 286 citations, and 11 links, followed by India (14 documents), Japan (12 documents), and South Korea (12 documents), with 97, 111, and 27 citations, respectively. The three countries below these are European countries, with Austria having issued 10 documents related to TEs with a total of 135 citations, followed by Finland (9 documents, 31 citations) and Spain (9 documents, 47 citations).

3.2.3 Keywords

The results of a keyword analysis can be used in further investigation of the topic at hand. This study employs a minimum threshold of two occurrences of keywords in all research articles that were examined using VOSviewer. Figure 3 displays the 253 authors' keywords detected from 1990, which may be categorized into six distinct clusters. Cluster 1 is characterized by a red color, Cluster 2 by a green color, while Cluster 3 is distinguished by a blue color. In addition, Cluster 4 is characterized by a yellow color, Cluster 5 has a purple hue, and Cluster 6 is distinguished by a light blue shade. Each cluster is comprised of interconnected keywords that are visually represented by the same colors. It is important to note that the size and shape of the node are indicative of the frequency of its occurrences [ 36 , 39 ]. In other words, there is a positive correlation between the size of the node and the frequency of occurrences of these terms. Clustering is employed as a means to gain insights or a comprehensive understanding of bibliometric groupings, whereas image mapping serves the purpose of obtaining a holistic depiction of a bibliometric network.

Network visualization of TEs

Figure 3 shows Cluster 1 (red) with 68 items such as thought experiments, intuition, Science, Kant, Aristotle, Galileo, Platonism, personal identity, theology, fiction narrative, moral motivation, and neuroscience. Cluster 2 (green) consists of 57 categories, such as science fiction, philosophy of science, philosophy of physics, philosophical thought, epistemology, knowledge, scientific reasoning, experiments, models, and realism. Cluster 3 (blue) contains 41 items, such as consciousness, Maxwell's demon, Schrodinger's cat, quantum theory, entropy, uncertainty principle, quantum entanglement, quantum information, quantum physics, and Newton's bucket. Furthermore, cluster 4 (yellow) consists of 30 items: physics education, science education, visualization, special theory of relativity, history of physics, problem-solving, exploration, Einstein, relativity, and falsification. Cluster 5 (purple) consists of 29 items: imagination, ontology, physics, truth time, algorithm of discovery, artificial intelligence, ethics, nanotechnology, fiction, philosophy, and technology. Finally, cluster 6 (light blue) contains 16 categories, including popular science, fictionality, narrative, construction, sensation, a priori, story, Mach, memory, productive imagination, and schema.

Keywords in clusters 1 and 2 have a high number of occurrences and a high total link strength. The term thought experiment ranks first with 85 occurrences and a total link strength of 91. This is followed by the term thought experiment with 60 occurrences, a total link strength of 98, and several other keywords. The high number of occurrences and high total link strength indicate that scientific research publications on the topic of TEs in the 2003–2022 range indexed by Scopus have a strong and direct relationship with these keywords. Table 4 displays the ten keywords with the highest occurrence and overall link strength in the last 20 years on the topic of TEs.

VOSviewer, on the other hand, is also used to visualize the progress of keywords over a certain period. Figure 4 illustrates the overlay visualization of the TEs topic in the time range 2003 to 2022.

Overlay visualization of TEs

Figure 4 depicts the annual distribution of the number of articles containing keywords. The various colors represent the publication dates of the related papers where these keywords appear together. The data in Fig. 4 indicate that the most frequently used topics related to TEs from 2010 to 2014 were quantum theory, ethical naturalism, ethical naturalism, quantum mechanics, scientific discovery, and mental models. Then, from 2014 to 2018, keywords such as scientific reasoning, intuition, science education, computer simulation, history of science, and science fiction began to appear in the TEs topic. The hottest topics in TEs research are shown in yellow color, including fiction, artificial intelligence, God, theology, speculative design, critical design, and methods of case. These findings indicate that these keywords have gained popularity in recent years. It can be concluded that scholars have increasingly turned to research on the mentioned topics in recent years.

4 Discussion

The goal of this study is to use the bibliometric mapping method to examine the trend of studies on TEs during the last 20 years (2003–2022). According to the findings of the study, there has been an increase in the interest and attention of researchers, scholars, and professionals in studying TEs. Although research in this area is ongoing, these findings indicate an annual growth in the writing and publication of TEs on Scopus. This growth demonstrates that research and publications on TEs are in high demand and receive significant global attention.

Interestingly, 90% of the top 20 source titles contributing to TEs research are journals in the first quartile (Q1) and second quartile (Q2). Among these, 10 journals are in the highest quartile, Q1, and 8 journals are in Q2. The quartile level indicates that these journals have the highest quality and the greatest influence [ 39 , 40 ]. Furthermore, 7 source titles (Philosophical Studies, Synthese, Foundations of Science, Minds and Machines, Erkenntnis, Acta Analytica, and Axiomathes) that publish TEs topics focus on the field of philosophy. When studying TEs from a philosophical standpoint, researchers, scholars, and professionals have the option of submitting their articles to these journals. Alternatively, if TEs are studied from a historical perspective, journals such as Science and Education, Studies in History and Philosophy of Science Part A, Journal for General Philosophy of Science, Philosophy of Science, Boston Studies in the Philosophy and History of Science, and European Journal for Philosophy of Science are appropriate. Meanwhile, if TEs are studied from an educational perspective, Physics Teacher, Science and Education, Physics Education, American Journal of Physics, and European Journal of Physics are ideal choices for publishing articles. These journals regularly publish articles in physics education studies.

If we look at the authors who have made the greatest contributions to the topic of TEs in the previous 20 years (2003–2022), Stuart is the most significant author with 7 articles (51 citations). Stuart’s work focuses on the history and philosophy of TEs [ 31 , 32 , 33 ], with the first publication in 2014 in the journal Perspectives of Science. In contrast to Stuart, Bancong's work, which ranks second, investigates various TEs from an educational standpoint. His first work, published in 2018, examined TEs in high school physics textbooks [ 3 ], followed by an investigation of how students construct TEs collaboratively [ 4 ], and an identification of factors influencing TEs during problem-solving activities [ 5 ]. Following Bancong, Fehige from the University of Toronto, Canada, has also published 5 articles. Most of his work examines TEs in religious contexts, such as thought experiments, Christianity and science in novalis [ 15 ], thought experiments and theology [ 16 ], and the book of job as a thought experiment: on science, religion, and literature [ 17 ] which was published in the journal Religions in 2019. Brown examines TEs in several of his works in light of the history and philosophy of science [ 6 , 7 ], as do Buzzoni and El Skaf from Italy, who mostly discuss TEs in light of the history and philosophy of science [ 8 , 12 ]. Meanwhile, Halkia and Velentzas from the University of Athens, Greece, have discussed TEs from an educational perspective, such as using TEs from Newton's Cannon for teaching satellite physics [ 37 ] and using TEs from the theory of relativity for teaching relativity theories [ 38 ].

Over the past two decades, authors have examined TEs from diverse perspectives, including history, philosophy, education, and religion. This variety highlights a significant shift in the disciplinary landscape of TE research, which is historically rooted in the philosophy of science [ 18 , 24 ]. The true strength of TEs lies in their adaptability across disciplines, rather than in resolving philosophical disputes. Although TEs were traditionally centered on history and philosophy of science (HPS), recent trends show a growing application in education and technology, particularly in artificial intelligence and speculative design. This shift indicates that TEs have not lost their significance but have instead found new areas of relevance. In HPS, the focus has moved toward understanding the methodological and epistemological implications of TEs, confirming their essential role in scientific reasoning [ 7 , 30 ]. Additionally, in fields such as physics education, TEs are increasingly utilized to explore complex theoretical concepts and enhance educational methodologies [ 2 , 12 ].

Based on the most commonly used keywords in the last 20 years, research on TEs has mostly focused on understanding TEs from a philosophical perspective in the first five years (2003–2007). Thought experiments rethought and reperceived [ 19 ], on thought experiments: is there more to the argument? [ 24 ] and thought experiments [ 9 ] are a few examples. Then, over the next five years (2008–2012), many studies looked at how TEs contributed to physical theories, including the special theory of relativity and quantum theory. The keywords that emerged frequently during this period were quantum theory, scientific discovery, methodology, quantum mechanics, twin earths, falling bodies, and others. In the last ten years, TEs have been studied from various perspectives. For example, in 2013, Velentzas and Halkia [ 38 ] also used TEs as a didactic tool in teaching physics to upper-secondary students. Fehige, on the other hand, began to connect TEs to theology, with a specific focus on the interaction between Christianity and science [ 15 , 16 ]. There are also researchers who continue to study the existence of TEs from a philosophical point of view and claim that TEs are science fiction [ 1 , 20 ]. In recent years, TEs have become increasingly popular in education and have been linked to artificial intelligence. Artificial intelligence, physics education, productive imagination, technology, and speculative design are some of the keywords that appear frequently. This is not surprising because TEs, as experimental activities using mental models, are not easy for students to perform on their own [ 4 , 5 ]. Therefore, technology that can assist students in creating an imaginative world for constructing TEs is required.

Since no studies have charted the trends in TEs research so far, it is difficult to compare the research results obtained with those of others. Nevertheless, several studies that examine trends in physics education reveal that although research on experiments is declining in physics education, TEs are still important to physics teaching and learning [ 41 ]. Hallswoth et al. [ 21 ] have also used artificial intelligence technologies to support TEs in the field of wet biology research, which is dominated by experiments on microbial growth and survival. The use of artificial intelligence in learning is based on the growing interest in artificial intelligence methods in science, technology, and education [ 11 ]. Overall, our study contributes to a more comprehensive understanding of TEs research trends during the last 20 years. In addition, this research also contributes to providing an overview of several potential topics that can be the focus of future researchers, such as the use of artificial intelligence in TEs. By situating our findings within the broader context of previous studies, we provide a clearer picture of how TE research has evolved and where it is heading.

5 Conclusions

This study aims to present a more comprehensive understanding of the trend of studies on TEs during the last 20 years (2003–2022). Research on this topic began in 1976, and its progress has continued to the present. A total of 679 published papers from various sources, including articles (504), conference papers (92), and book chapters (83), were analyzed. The results of the study show that research and publications on TEs are of interest and have received a lot of attention during the last eight years. A significant increase occurred in 2021, with 69 published articles. According to the findings, 95% of the top 20 source titles contributing to TEs are from journals in the first and second quartiles (Q1 and Q2). This quartile ranking shows the quality and significant influence of a journal. The geographical distribution reveals that the United States contributes the most to TEs research, with 213 documents, 2592 citations, and 47 links. We also identified several prospective keywords that could be the focus of future research, including artificial intelligence, physics education, fiction, God, theology, productive imagination, technology, speculative design, and critical design. Therefore, this study contributes to providing a thorough picture of thought experiment research trends and future directions of potential topics that can be the focus of future researchers.

This research has several limitations. The exclusive source of publication data utilized in this study is the Scopus database, which is recognized as one of the most extensive databases in the field. However, it is worth noting that future research endeavors may consider including publication data from other prominent sources such as WoS and Google Scholar. Furthermore, the utilization of the search function in the TITLE-ABS-KEY field, specifically employing the terms "Thought-experiments" AND "Science" OR "Physics," was used for the purpose of data retrieval. However, it is important to acknowledge that this approach is not infallible, as there is a potential for some papers to be overlooked, making the process less than completely accurate. Despite its limitations, this research is often regarded as a pioneering contribution to the field of bibliometric studies on the subject of TEs during the past two decades.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Model orthogonalization and Bayesian forecast mixing via principal component analysis

P. giuliani, k. godbey, v. kejzlar, and w. nazarewicz, phys. rev. research 6 , 033266 – published 9 september 2024.

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• INTRODUCTION
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• ACKNOWLEDGMENTS

One can improve predictability in the unknown domain by combining forecasts of imperfect complex computational models using a Bayesian statistical machine learning framework. In many cases, however, the models used in the mixing process are similar. In addition to contaminating the model space, the existence of such similar, or even redundant, models during the multimodeling process can result in misinterpretation of results and deterioration of predictive performance. In this paper we describe a method based on the principal component analysis that eliminates model redundancy. We show that by adding model orthogonalization to the proposed Bayesian model combination framework, one can arrive at better prediction accuracy and reach excellent uncertainty quantification performance.

• Received 2 July 2024
• Accepted 19 August 2024

DOI: https://doi.org/10.1103/PhysRevResearch.6.033266

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

Published by the American Physical Society

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• 1 Facility for Rare Isotope Beams , Michigan State University , East Lansing, Michigan 48824, USA
• 2 Mathematics and Statistics Department, Skidmore College , Saratoga Springs, New York 12866, USA
• 3 Department of Physics and Astronomy, Michigan State University , East Lansing, Michigan 48824, USA
• * Contact author: [email protected]
• † Contact author: [email protected]
• ‡ Contact author: [email protected]

Article Text

Vol. 6, Iss. 3 — September - November 2024

Subject Areas

• Interdisciplinary Physics
• Nuclear Physics

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Schematic representation of the PCA approach for the model combination. Here, two model classes consist of two and five models, respectively, and are represented as vectors in a space R n . This collection of seven models is approximated in the affine space (gray rectangle) spanned by the constant ϕ 0 term (dashed light-gray arrow) and the two principal components ϕ 1 and ϕ 2 (dashed black arrows).

Illustration of S3 of Table  1 . (a) Forecasts of the binding energy per nucleon produced by 19 different models: one perfect model (black), three good models (blue), five intermediate models (green), and ten bad models (red). The spread of the results comes from the noise terms added. The inset shows the projection ν j ( k ) defined in Eq. ( 7 ) for each of the 19 models onto the first two principal components, clearly identifying the existence of three model classes, with the perfect model and three good models being nearly aligned. (b) Decay of the singular values s j . The inset shows the evolution of the RMSE ( 15 ) for the training (cyan blue squares), validation (yellow stars), and testing (dark red circles) datasets as the number of principal components kept in the expansion ( 8 ) is increased (zero corresponds to ϕ 0 ). The BMC + PCA results are marked by solid lines. The dashed lines show the RMSE obtained when combining all 19 models without projecting on principal components (pure BMC), which shows signs of overfitting: lower RMSE, training dataset; higher RMSE, testing set.

Case study II results. (a) Training (squares), validation (stars), and testing (circles) datasets of binding energies of 629 even-even nuclei used in this paper. The stable isotopes are marked by small black squares. (b) Projections ν 1 and ν 2 of 15 realistic models of the nuclear binding energy into the first two principal components. This representation allows us to visualize intermodel relationships. (c) Similar to Fig.  2  but for the realistic mass models. The colors and symbols follow the same convention as in panel (a), with solid lines representing the BMC + PCA model of Eq. ( 8 ) and dashed lines representing the BMC of Eq. ( 3 ) with f 0 = 0 . (d) Distribution of the weights ω k for the individual models in the expansion ( 9 ) in the unconstrained (top) and simplex-constrained (bottom) settings [see Eq. ( 2 )]. The vertical error bars represent a 95 % region obtained from the sampled posterior.

(a) Predictive posterior distribution for the binding energy per nucleon of the Sn isotopes. The mean prediction and 95 % credible interval of the unconstrained combined model is shown in purple, while the simplex-constrained (simplex) combined model is shown in khaki. The inset shows the detail of the plot for N = 54 , 56 , and 58. (b) ECP for unconstrained and simplex-constrained variants for training (blue), validation (yellow), and testing (red) datasets. The diagonal black line shows a reference of what a perfect statistical coverage would entail, with points above it being conservative, and those below being overconfident.

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