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Research Summary – Structure, Examples and Writing Guide

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Research Summary

Definition:

A research summary is a brief and concise overview of a research project or study that highlights its key findings, main points, and conclusions. It typically includes a description of the research problem, the research methods used, the results obtained, and the implications or significance of the findings. It is often used as a tool to quickly communicate the main findings of a study to other researchers, stakeholders, or decision-makers.

Structure of Research Summary

The Structure of a Research Summary typically include:

• Introduction : This section provides a brief background of the research problem or question, explains the purpose of the study, and outlines the research objectives.
• Methodology : This section explains the research design, methods, and procedures used to conduct the study. It describes the sample size, data collection methods, and data analysis techniques.
• Results : This section presents the main findings of the study, including statistical analysis if applicable. It may include tables, charts, or graphs to visually represent the data.
• Discussion : This section interprets the results and explains their implications. It discusses the significance of the findings, compares them to previous research, and identifies any limitations or future directions for research.
• Conclusion : This section summarizes the main points of the research and provides a conclusion based on the findings. It may also suggest implications for future research or practical applications of the results.
• References : This section lists the sources cited in the research summary, following the appropriate citation style.

How to Write Research Summary

Here are the steps you can follow to write a research summary:

• Read the research article or study thoroughly: To write a summary, you must understand the research article or study you are summarizing. Therefore, read the article or study carefully to understand its purpose, research design, methodology, results, and conclusions.
• Identify the main points : Once you have read the research article or study, identify the main points, key findings, and research question. You can highlight or take notes of the essential points and findings to use as a reference when writing your summary.
• Write the introduction: Start your summary by introducing the research problem, research question, and purpose of the study. Briefly explain why the research is important and its significance.
• Summarize the methodology : In this section, summarize the research design, methods, and procedures used to conduct the study. Explain the sample size, data collection methods, and data analysis techniques.
• Present the results: Summarize the main findings of the study. Use tables, charts, or graphs to visually represent the data if necessary.
• Interpret the results: In this section, interpret the results and explain their implications. Discuss the significance of the findings, compare them to previous research, and identify any limitations or future directions for research.
• Conclude the summary : Summarize the main points of the research and provide a conclusion based on the findings. Suggest implications for future research or practical applications of the results.
• Revise and edit : Once you have written the summary, revise and edit it to ensure that it is clear, concise, and free of errors. Make sure that your summary accurately represents the research article or study.
• Add references: Include a list of references cited in the research summary, following the appropriate citation style.

Example of Research Summary

Here is an example of a research summary:

Title: The Effects of Yoga on Mental Health: A Meta-Analysis

Introduction: This meta-analysis examines the effects of yoga on mental health. The study aimed to investigate whether yoga practice can improve mental health outcomes such as anxiety, depression, stress, and quality of life.

Methodology : The study analyzed data from 14 randomized controlled trials that investigated the effects of yoga on mental health outcomes. The sample included a total of 862 participants. The yoga interventions varied in length and frequency, ranging from four to twelve weeks, with sessions lasting from 45 to 90 minutes.

Results : The meta-analysis found that yoga practice significantly improved mental health outcomes. Participants who practiced yoga showed a significant reduction in anxiety and depression symptoms, as well as stress levels. Quality of life also improved in those who practiced yoga.

Discussion : The findings of this study suggest that yoga can be an effective intervention for improving mental health outcomes. The study supports the growing body of evidence that suggests that yoga can have a positive impact on mental health. Limitations of the study include the variability of the yoga interventions, which may affect the generalizability of the findings.

Conclusion : Overall, the findings of this meta-analysis support the use of yoga as an effective intervention for improving mental health outcomes. Further research is needed to determine the optimal length and frequency of yoga interventions for different populations.

References :

• Cramer, H., Lauche, R., Langhorst, J., Dobos, G., & Berger, B. (2013). Yoga for depression: a systematic review and meta-analysis. Depression and anxiety, 30(11), 1068-1083.
• Khalsa, S. B. (2004). Yoga as a therapeutic intervention: a bibliometric analysis of published research studies. Indian journal of physiology and pharmacology, 48(3), 269-285.
• Ross, A., & Thomas, S. (2010). The health benefits of yoga and exercise: a review of comparison studies. The Journal of Alternative and Complementary Medicine, 16(1), 3-12.

Purpose of Research Summary

The purpose of a research summary is to provide a brief overview of a research project or study, including its main points, findings, and conclusions. The summary allows readers to quickly understand the essential aspects of the research without having to read the entire article or study.

Research summaries serve several purposes, including:

• Facilitating comprehension: A research summary allows readers to quickly understand the main points and findings of a research project or study without having to read the entire article or study. This makes it easier for readers to comprehend the research and its significance.
• Communicating research findings: Research summaries are often used to communicate research findings to a wider audience, such as policymakers, practitioners, or the general public. The summary presents the essential aspects of the research in a clear and concise manner, making it easier for non-experts to understand.
• Supporting decision-making: Research summaries can be used to support decision-making processes by providing a summary of the research evidence on a particular topic. This information can be used by policymakers or practitioners to make informed decisions about interventions, programs, or policies.
• Saving time: Research summaries save time for researchers, practitioners, policymakers, and other stakeholders who need to review multiple research studies. Rather than having to read the entire article or study, they can quickly review the summary to determine whether the research is relevant to their needs.

Characteristics of Research Summary

The following are some of the key characteristics of a research summary:

• Concise : A research summary should be brief and to the point, providing a clear and concise overview of the main points of the research.
• Objective : A research summary should be written in an objective tone, presenting the research findings without bias or personal opinion.
• Comprehensive : A research summary should cover all the essential aspects of the research, including the research question, methodology, results, and conclusions.
• Accurate : A research summary should accurately reflect the key findings and conclusions of the research.
• Clear and well-organized: A research summary should be easy to read and understand, with a clear structure and logical flow.
• Relevant : A research summary should focus on the most important and relevant aspects of the research, highlighting the key findings and their implications.
• Audience-specific: A research summary should be tailored to the intended audience, using language and terminology that is appropriate and accessible to the reader.
• Citations : A research summary should include citations to the original research articles or studies, allowing readers to access the full text of the research if desired.

When to write Research Summary

Here are some situations when it may be appropriate to write a research summary:

• Proposal stage: A research summary can be included in a research proposal to provide a brief overview of the research aims, objectives, methodology, and expected outcomes.
• Conference presentation: A research summary can be prepared for a conference presentation to summarize the main findings of a study or research project.
• Journal submission: Many academic journals require authors to submit a research summary along with their research article or study. The summary provides a brief overview of the study’s main points, findings, and conclusions and helps readers quickly understand the research.
• Funding application: A research summary can be included in a funding application to provide a brief summary of the research aims, objectives, and expected outcomes.
• Policy brief: A research summary can be prepared as a policy brief to communicate research findings to policymakers or stakeholders in a concise and accessible manner.

Advantages of Research Summary

Research summaries offer several advantages, including:

• Time-saving: A research summary saves time for readers who need to understand the key findings and conclusions of a research project quickly. Rather than reading the entire research article or study, readers can quickly review the summary to determine whether the research is relevant to their needs.
• Clarity and accessibility: A research summary provides a clear and accessible overview of the research project’s main points, making it easier for readers to understand the research without having to be experts in the field.
• Improved comprehension: A research summary helps readers comprehend the research by providing a brief and focused overview of the key findings and conclusions, making it easier to understand the research and its significance.
• Enhanced communication: Research summaries can be used to communicate research findings to a wider audience, such as policymakers, practitioners, or the general public, in a concise and accessible manner.
• Facilitated decision-making: Research summaries can support decision-making processes by providing a summary of the research evidence on a particular topic. Policymakers or practitioners can use this information to make informed decisions about interventions, programs, or policies.
• Increased dissemination: Research summaries can be easily shared and disseminated, allowing research findings to reach a wider audience.

Limitations of Research Summary

Limitations of the Research Summary are as follows:

• Limited scope: Research summaries provide a brief overview of the research project’s main points, findings, and conclusions, which can be limiting. They may not include all the details, nuances, and complexities of the research that readers may need to fully understand the study’s implications.
• Risk of oversimplification: Research summaries can be oversimplified, reducing the complexity of the research and potentially distorting the findings or conclusions.
• Lack of context: Research summaries may not provide sufficient context to fully understand the research findings, such as the research background, methodology, or limitations. This may lead to misunderstandings or misinterpretations of the research.
• Possible bias: Research summaries may be biased if they selectively emphasize certain findings or conclusions over others, potentially distorting the overall picture of the research.
• Format limitations: Research summaries may be constrained by the format or length requirements, making it challenging to fully convey the research’s main points, findings, and conclusions.
• Accessibility: Research summaries may not be accessible to all readers, particularly those with limited literacy skills, visual impairments, or language barriers.

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Muhammad Hassan

Researcher, Academic Writer, Web developer

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• How to Write a Summary | Guide & Examples

How to Write a Summary | Guide & Examples

Published on 25 September 2022 by Shona McCombes . Revised on 12 May 2023.

Summarising , or writing a summary, means giving a concise overview of a text’s main points in your own words. A summary is always much shorter than the original text.

There are five key steps that can help you to write a summary:

• Read the text
• Break it down into sections
• Identify the key points in each section
• Write the summary
• Check the summary against the article

Writing a summary does not involve critiquing or analysing the source. You should simply provide an accurate account of the most important information and ideas (without copying any text from the original).

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Table of contents

When to write a summary, step 1: read the text, step 2: break the text down into sections, step 3: identify the key points in each section, step 4: write the summary, step 5: check the summary against the article, frequently asked questions.

There are many situations in which you might have to summarise an article or other source:

• As a stand-alone assignment to show you’ve understood the material
• To keep notes that will help you remember what you’ve read
• To give an overview of other researchers’ work in a literature review

When you’re writing an academic text like an essay , research paper , or dissertation , you’ll integrate sources in a variety of ways. You might use a brief quote to support your point, or paraphrase a few sentences or paragraphs.

But it’s often appropriate to summarize a whole article or chapter if it is especially relevant to your own research, or to provide an overview of a source before you analyse or critique it.

In any case, the goal of summarising is to give your reader a clear understanding of the original source. Follow the five steps outlined below to write a good summary.

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You should read the article more than once to make sure you’ve thoroughly understood it. It’s often effective to read in three stages:

• Scan the article quickly to get a sense of its topic and overall shape.
• Read the article carefully, highlighting important points and taking notes as you read.
• Skim the article again to confirm you’ve understood the key points, and reread any particularly important or difficult passages.

There are some tricks you can use to identify the key points as you read:

• Start by reading the abstract . This already contains the author’s own summary of their work, and it tells you what to expect from the article.
• Pay attention to headings and subheadings . These should give you a good sense of what each part is about.
• Read the introduction and the conclusion together and compare them: What did the author set out to do, and what was the outcome?

To make the text more manageable and understand its sub-points, break it down into smaller sections.

If the text is a scientific paper that follows a standard empirical structure, it is probably already organised into clearly marked sections, usually including an introduction, methods, results, and discussion.

Other types of articles may not be explicitly divided into sections. But most articles and essays will be structured around a series of sub-points or themes.

Now it’s time go through each section and pick out its most important points. What does your reader need to know to understand the overall argument or conclusion of the article?

Keep in mind that a summary does not involve paraphrasing every single paragraph of the article. Your goal is to extract the essential points, leaving out anything that can be considered background information or supplementary detail.

In a scientific article, there are some easy questions you can ask to identify the key points in each part.

If the article takes a different form, you might have to think more carefully about what points are most important for the reader to understand its argument.

In that case, pay particular attention to the thesis statement —the central claim that the author wants us to accept, which usually appears in the introduction—and the topic sentences that signal the main idea of each paragraph.

Now that you know the key points that the article aims to communicate, you need to put them in your own words.

To avoid plagiarism and show you’ve understood the article, it’s essential to properly paraphrase the author’s ideas. Do not copy and paste parts of the article, not even just a sentence or two.

The best way to do this is to put the article aside and write out your own understanding of the author’s key points.

Examples of article summaries

Let’s take a look at an example. Below, we summarise this article , which scientifically investigates the old saying ‘an apple a day keeps the doctor away’.

An article summary like the above would be appropriate for a stand-alone summary assignment. However, you’ll often want to give an even more concise summary of an article.

For example, in a literature review or research paper, you may want to briefly summarize this study as part of a wider discussion of various sources. In this case, we can boil our summary down even further to include only the most relevant information.

Citing the source you’re summarizing

When including a summary as part of a larger text, it’s essential to properly cite the source you’re summarizing. The exact format depends on your citation style , but it usually includes an in-text citation and a full reference at the end of your paper.

You can easily create your citations and references in APA or MLA using our free citation generators.

APA Citation Generator MLA Citation Generator

Finally, read through the article once more to ensure that:

• You’ve accurately represented the author’s work
• You haven’t missed any essential information
• The phrasing is not too similar to any sentences in the original.

If you’re summarising many articles as part of your own work, it may be a good idea to use a plagiarism checker to double-check that your text is completely original and properly cited. Just be sure to use one that’s safe and reliable.

A summary is a short overview of the main points of an article or other source, written entirely in your own words.

Save yourself some time with the free summariser.

A summary is always much shorter than the original text. The length of a summary can range from just a few sentences to several paragraphs; it depends on the length of the article you’re summarising, and on the purpose of the summary.

With the summariser tool you can easily adjust the length of your summary.

You might have to write a summary of a source:

• As a stand-alone assignment to prove you understand the material
• For your own use, to keep notes on your reading
• To provide an overview of other researchers’ work in a literature review
• In a paper , to summarise or introduce a relevant study

To avoid plagiarism when summarising an article or other source, follow these two rules:

• Write the summary entirely in your own words by   paraphrasing the author’s ideas.
• Reference the source with an in-text citation and a full reference so your reader can easily find the original text.

An abstract concisely explains all the key points of an academic text such as a thesis , dissertation or journal article. It should summarise the whole text, not just introduce it.

An abstract is a type of summary , but summaries are also written elsewhere in academic writing . For example, you might summarise a source in a paper , in a literature review , or as a standalone assignment.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

McCombes, S. (2023, May 12). How to Write a Summary | Guide & Examples. Scribbr. Retrieved 29 April 2024, from https://www.scribbr.co.uk/working-sources/how-to-write-a-summary/

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How to Write a Summary — Researcher's Guide

Table of Contents

Writing a summary can be a bit challenging if you're not familiar with the process. Thankfully, by following a few key steps, you can master the art of writing a summary effectively. In this article, we will explore the essential elements of summary writing, from understanding the basics to editing and proofreading your work. So, let's dive in and learn how to write a summary that captures the essence of your source material while keeping it concise and readable.

What is a Summary in research?

A summary is a condensed version of a longer text that captures its main points and ideas. It should provide a clear overview without getting into excessive detail. By understanding this foundational concept, you can effectively navigate the process of summary writing.

Now, there are several strategies you can follow to get an effective summary. Let’s dive into some of them.

Identify the Key Points of Your Source Material

To create an accurate summary, you must identify and extract the key points from your source material. This involves thorough reading or reviewing the text and highlighting the most important information. By doing so, you'll be able to effectively convey the main ideas and arguments in your summary.

One effective way to identify the key points is to read the source material multiple times. As you read, make sure to highlight or underline the sentences or paragraphs that stand out to you. These are likely to contain the most significant information. You can use AI research assistants to read and understand your source materials which saves plenty of your reading time.

Another helpful strategy is to take notes while reading. Jot down the main ideas and arguments as you encounter them. This not only helps you remember the key points but also allows you to organize your thoughts and structure your summary effectively.

Additionally, pay attention to any headings or subheadings in the source material. These can often indicate important sections or topics that should be included in your summary.

It's important to remember that summarizing is not about copying and pasting sentences from the source material. Instead, it involves condensing the information and presenting it in your own words. This requires a thorough understanding of the key points and the ability to express them concisely. Once you have identified the key points, you can begin crafting your summary.

Choose Your Words Carefully

When writing a summary, every word counts. It is essential to choose your words carefully to convey the message accurately. Aim for concise and clear language without sacrificing important details. By utilizing precise vocabulary and avoiding unnecessary jargon, you can ensure that your summary accurately represents the original text.

One important aspect to consider when choosing your words is the intended audience . Are you summarizing a scientific article for a group of experts in the field, or are you summarizing a news article for a general audience? Tailoring your language to suit the needs and understanding of your readers is crucial in effectively conveying your message.

Another factor to keep in mind is the tone of the original text. Is it formal and academic, or is it more conversational and informal? Adapting your language to match the tone of the original text can help maintain the intended meaning and style.

Furthermore, it is essential to pay attention to the context of the original text. Understanding the background and purpose of the work can provide valuable insights into how to summarize it effectively. By considering the broader context, you can ensure that your summary captures the main ideas and key points without omitting crucial information.

Additionally, when choosing your words, it is crucial to avoid personal biases or interpretations. A summary should present an objective overview of the original text, focusing on the author's ideas rather than your own opinions. By remaining impartial and objective, you can provide a fair and accurate representation of the message. While brevity is important, it is equally crucial to include enough information.

Moreover, a well-crafted summary should include the most significant details and ideas to provide a comprehensive understanding of your research work. Selecting the most relevant and impactful details will help readers grasp the main points without getting lost in unnecessary information.

Create an Outline Before Writing

Organizing your thoughts before you begin writing can significantly enhance the quality of your summary. Create a clear outline that follows the structure of your source material. By logically dividing your summary into sections, you'll ensure a coherent flow and make it easier for your readers to follow along.

Keep Your Summary Concise

A summary should capture the essence of the original text without unnecessary elaboration. Aim to condense the information into its most crucial points, omitting extraneous details. Keep your sentences clear and to the point, maintaining a concise and focused writing style.

Use the Right Tone and Voice

The tone and voice of your summary should match the original source material. Take note of the style from the source and reflect it in your writing. Whether the source material is formal or informal, academic or creative, ensuring consistency in tone and voice is key to an effective summary.

Check for Clarity and Readability

After completing your summary, take the time to review it for clarity and readability. Ensure that your sentences flow smoothly, providing a seamless reading experience. Pay attention to grammar, punctuation, and sentence structure, as these elements contribute to the overall clarity of your summary.

Make Sure You Include All the Important Points

While summarizing, it's vital to include all the necessary information. Double-check your summary against the source material to ensure that you haven't overlooked any important points. By capturing the essence of the original text accurately, you'll provide your readers with a comprehensive overview.

Edit and Proofread Your Summary

Before finalizing your summary, always take the time to edit and proofread. Trim down any unnecessary words or phrases and refine your sentences for clarity and conciseness. Additionally, check for spelling and grammatical errors. By investing effort into this final step, you'll ensure your summary is polished and professional.

Tips for Writing an Effective Summary

Lastly, here are some essential tips to keep in mind as you embark on your summary-writing journey:

• Focus on conveying the central theme and main points.
• Avoid personal opinions or interpretations.
• Use your own words while faithfully representing the source material.
• Read aloud your summary to ensure clarity and coherence.
• Seek feedback from peers or mentors to improve your summarizing skills.

By incorporating these tips into your summary-writing process, you'll be well-equipped to create an effective summary that captures the essence of your source material.

In conclusion

Writing a summary requires an understanding of the basics, careful word choice, and a concise writing style. By following the steps outlined in this article and utilizing the provided tips, you can develop the necessary skills to write a good research summary.

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Finding and summarizing research articles - apa format, introduction.

Writing a summary or abstract teaches you how to condense information and how to read an article more effectively and with better understanding. Research articles usually contain these parts: Title/Author Information, Abstract, Introduction, Methodology, Result or Findings, Discussion or Conclusion, and References. To gain a better understanding of an article, try reading the abstract and the discussion or conclusion first and then read the entire article.

Finding an Article

PsycINFO Research Database The American Psychological Association’s (APA) renowned resource for abstracts of scholarly journal articles, book chapters, books, and dissertations, the largest resource devoted to peer-reviewed literature in behavioral science and mental health.

PsycINFO Tutorial

Journal Article Request If you can't find the free full text version of a research article, please complete and submit this form. An Learning Commons staff member will then place an interlibrary loan request on your behalf.

Summarizing an Article

The following websites offer advice and instruction on summarizing articles:

Andrews University: Guidelines for Writing an Article Summary

UConn: How to Summarize a Research Article

Resources for APA Style

APA (7th ed.) Formatting and Style Guide Purdue Online Writing Lab (OWL)

APA Style Website American Psychological Association

Books in the Learning Commons

Publication Manual of the American Psychological Association (7th ed.): BF76.7 .P83

Sample APA Citations

In-text citation.

If the author’s name is included within the text, follow the name with (year)

            Example: Jones (2009) found that diabetes symptoms improve with exercise.

If the author’s name is not included within the text, follow the sentence with (Last Name, year).

            Example: Increased exercise resulted in diminished diabetes symptoms (Jones, 2009).

Reference Citation

Author’s last name, A. A., & Author’s last name, B.B. (year).Title of article. Title of Journal , volume (issue), page number – page number. https://doi.org/xxxxx

Iscoe, K. E., & Riddell, M. C. (2011). Continuous moderate-intensity exercise with or without intermittent high-intensity work: Effects on acute and late glycaemia in athletes with Type 1 diabetes mellitus. Diabetic Medicine , 28 (7), 824-832. https://doi.org/10.1111/j.1464-5491.2011.03274.x

• Research Summary: What Is It & How To Write One

Introduction

A research summary is a requirement during academic research and sometimes you might need to prepare a research summary during a research project for an organization.

Most people find a research summary a daunting task as you are required to condense complex research material into an informative, easy-to-understand article most times with a minimum of 300-500 words.

In this post, we will guide you through all the steps required to make writing your research summary an easier task. 

What is a Research Summary?

A research summary is a piece of writing that summarizes the research of a specific topic into bite-size easy-to-read and comprehend articles. The primary goal is to give the reader a detailed outline of the key findings of a research.

It is an unavoidable requirement in colleges and universities. To write a good research summary, you must understand the goal of your research, as this would help make the process easier. 

A research summary preserves the structure and sections of the article it is derived from.

Research Summary or Abstract: What’s The Difference?

The Research Summary and Abstract are similar, especially as they are both brief, straight to the point, and provide an overview of the entire research paper. However, there are very clear differences.

To begin with, a Research summary is written at the end of a research activity, while the Abstract is written at the beginning of a research paper. 

A Research Summary captures the main points of a study, with an emphasis on the topic, method , and discoveries, an Abstract is a description of what your research paper would talk about and the reason for your research or the hypothesis you are trying to validate.

Let us take a deeper look at the difference between both terms.

What is an Abstract?

An abstract is a short version of a research paper. It is written to convey the findings of the research to the reader. It provides the reader with information that would help them understand the research, by giving them a clear idea about the subject matter of a research paper. It is usually submitted before the presentation of a research paper.

What is a Summary?

A summary is a short form of an essay, a research paper, or a chapter in a book. A research summary is a narration of a research study, condensing the focal points of research to a shorter form, usually aligned with the same structure of the research study, from which the summary is derived.

What Is The Difference Between an Abstract and a Summary?

An abstract communicates the main points of a research paper, it includes the questions, major findings, the importance of the findings, etc.

An abstract reflects the perceptions of the author about a topic, while a research summary reflects the ideology of the research study that is being summarized.

Getting Started with a Research Summary

Before commencing a research summary, there is a need to understand the style and organization of the content you plan to summarize. There are three fundamental areas of the research that should be the focal point:

• When deciding on the content include a section that speaks to the importance of the research, and the techniques and tools used to arrive at your conclusion.
• Keep the summary well organized, and use paragraphs to discuss the various sections of the research.
• Restrict your research to 300-400 words which is the standard practice for research summaries globally. However, if the research paper you want to summarize is a lengthy one, do not exceed 10% of the entire research material.

Once you have satisfied the requirements of the fundamentals for starting your research summary, you can now begin to write using the following format:

• Why was this research done?   – A clear description of the reason the research was embarked on and the hypothesis being tested.
• Who was surveyed? – Your research study should have details of the source of your information. If it was via a survey, you should document who the participants of the survey were and the reason that they were selected.
• What was the methodology? – Discuss the methodology, in terms of what kind of survey method did you adopt. Was it a face-to-face interview, a phone interview, or a focus group setting?
• What were the key findings? – This is perhaps the most vital part of the process. What discoveries did you make after the testing? This part should be based on raw facts free from any personal bias.
• Conclusion – What conclusions did you draw from the findings?
• Takeaways and action points – This is where your views and perception can be reflected. Here, you can now share your recommendations or action points.
• Identify the focal point of the article –  In other to get a grasp of the content covered in the research paper, you can skim the article first, in a bid to understand the most essential part of the research paper. 
• Analyze and understand the topic and article – Writing a summary of a research paper involves being familiar with the topic –  the current state of knowledge, key definitions, concepts, and models. This is often gleaned while reading the literature review. Please note that only a deep understanding ensures efficient and accurate summarization of the content.
• Make notes as you read – Highlight and summarize each paragraph as you read. Your notes are what you would further condense to create a draft that would form your research summary.

How to Structure Your Research Summary

• Title – This highlights the area of analysis, and can be formulated to briefly highlight key findings.
• Abstract – this is a very brief and comprehensive description of the study, required in every academic article, with a length of 100-500 words at most. 
• Introduction – this is a vital part of any research summary, it provides the context and the literature review that gently introduces readers to the subject matter. The introduction usually covers definitions, questions, and hypotheses of the research study. 
• Methodology –This section emphasizes the process and or data analysis methods used, in terms of experiments, surveys, sampling, or statistical analysis. 
• Results section – this section lists in detail the results derived from the research with evidence obtained from all the experiments conducted.
• Discussion – these parts discuss the results within the context of current knowledge among subject matter experts. Interpretation of results and theoretical models explaining the observed results, the strengths of the study, and the limitations experienced are going to be a part of the discussion. 
• Conclusion – In a conclusion, hypotheses are discussed and revalidated or denied, based on how convincing the evidence is.
• References – this section is for giving credit to those who work you studied to create your summary. You do this by providing appropriate citations as you write.

Research Summary Example 1

Below are some defining elements of a sample research summary.

Title – “The probability of an unexpected volcanic eruption in Greenwich”

Introduction – this section would list the catastrophic consequences that occurred in the country and the importance of analyzing this event. 

Hypothesis –  An eruption of the Greenwich supervolcano would be preceded by intense preliminary activity manifesting in advance, before the eruption.

Results – these could contain a report of statistical data from various volcanic eruptions happening globally while looking critically at the activity that occurred before these events. 

Discussion and conclusion – Given that Greenwich is now consistently monitored by scientists and that signs of an eruption are usually detected before the volcanic eruption, this confirms the hypothesis. Hence creating an emergency plan outlining other intervention measures and ultimately evacuation is essential. 

Research Summary Example 2

Below is another sample sketch.

Title – “The frequency of extreme weather events in the UK in 2000-2008 as compared to the ‘60s”

Introduction – Weather events bring intense material damage and cause pain to the victims affected.

Hypothesis – Extreme weather events are more frequent in recent times compared to the ‘50s

Results – The frequency of several categories of extreme events now and then are listed here, such as droughts, fires, massive rainfall/snowfalls, floods, hurricanes, tornadoes, etc.

Discussion and conclusion – Several types of extreme events have become more commonplace in recent times, confirming the hypothesis. This rise in extreme weather events can be traced to rising CO2 levels and increasing temperatures and global warming explain the rising frequency of these disasters. Addressing the rising CO2 levels and paying attention to climate change is the only to combat this phenomenon.

A research summary is the short form of a research paper, analyzing the important aspect of the study. Everyone who reads a research summary has a full grasp of the main idea being discussed in the original research paper. Conducting any research means you will write a summary, which is an important part of your project and would be the most read part of your project.

Having a guideline before you start helps, this would form your checklist which would guide your actions as you write your research summary. It is important to note that a Research Summary is different from an Abstract paper written at the beginning of a research paper, describing the idea behind a research paper.

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How to write a summary of a research paper (with template)

by Diana Ribeiro Last updated Jul 20, 2020 | Published on Jun 27, 2020 Writing Skills 0 comments

In our daily work as medical writers, we have to read many scholarly articles and extract the main information from them. Having a process to retrieve that information and create a short summary that you can easily access will save you precious time. That’s why I decided to guide you through my process of summarising a research article and created a handy template.

Having short summaries of academic papers is useful to create news articles, press releases, social media posts, blog articles, or curated news reports, like the one I write weekly for my newsletter subscribers .

What’s the importance of summarising research articles?

If you don’t have a system to extract the main information from a scholarly paper, you may have to re-read it repeatedly, looking for that piece of information you know it’s there. Sure, you can use a highlighter pen to mark the main points, but sometimes what happens is that you end up with yellow walls of text. Or green. Or even a rainbow. Which may be pretty, but it’s quite useless as a retrieval system.

What also happens when you highlight text is that you end up with a diverse array of writing styles, none of them being your own. This way, when you try to write a text with information from multiple sources, you have to search for the information and write it in a consistent style.

In this article, I’ll show you how to retrieve the most relevant information from a scientific paper, how to write it in a compelling way, and how to present it in a news-worthy style that’s easily adaptable to your audience. Ready?

Three steps to summarise a research paper

1. scan and extract the main points.

First things first, so you have to read the paper. But that doesn’t mean you have to read it from start to finish. Start by scanning the article for its main points.

Here’s the essential information to extract from the research paper you have in front of you:

• Authors, year, doi
• Study question: look in the introduction for a phrase like “the aim of this study was”
• Hypothesis tested
• Study methods: design, participants, materials, procedure, what was manipulated (independent variables), what was measured (dependent variables), how data were analysed.
• Findings: from the results section; fill this before you look at the discussion section, if possible. Write bullet points.
• Interpretation: how did the authors interpreted their findings? Use short sentences, in your own words.

After extracting the key information , revisit the article and read it more attentively, to see if you missed something. Add some notes to your summary, but take care to avoid plagiarism. Write notes in your own words. If you can’t do that at this moment, use quotation marks to indicate that your note came straight from the study. You can rewrite it later, when you have a better grasp of the study.

2. Use a journalistic approach for the first draft

Some sources advise you to keep the same structure as the scientific article, but I like to use the journalistic approach of news articles and flush out the more relevant information first, followed by the details. This is more enticing for readers, making them want to continue reading. Yes, I know that your reader may be just you, but I know I have lost myself in some of the things I’ve written, so…keep it interesting, even for a future self 😊.

This is the main information you have to put together:

Title of the article: I like to keep the original article title for the summary, because it’s easier to refer back to the original article if I need to. Sometimes I add a second title, just for me, if the article title is too obscure or long.

• 1 st paragraph: Answer the 5 W’s in 3-4 sentences.

Who? (the authors)

What? (main finding)

When and where? (journal, date of publication)

Why? (relevance)

This should be a standalone paragraph, meaning that the reader should be able to take out the main information even if they just read this paragraph.

• Subsequent paragraphs: In 2-3 paragraphs or less, provide context and more information about the research done. If you’re not sure if a detail is important or not, you can include it here and edit it out in the next step.

3. Polish the rough edges

In this stage, you’re going to make a quick edit, checking for completeness and accuracy. Make sure you’ve included all the main points without repeating yourself. Double-check all the numbers. Stay focused on the research questions to avoid tangents. Avoid using jargon and the passive voice whenever possible.

Final summary

Using this approach, you’ll end up with a short summary of your article that you can use to craft other types of writing, such as press releases, news articles, social media blurbs, and many others.

The advantages of summarising research articles are that you can better understand what the article is about, and you’ll have a text written by you, so it’s easier to adapt and you avoid unintentional plagiarism.

That’s it! My guide to write a research paper summary 😊

I’ve created a handout with all the information in this blog post plus a fill-in-the-blanks template that you can use to summarise research articles, you can download it using the form below. You’ll be signed up to my mailing list, and receive a weekly roundup of news in the biomedical industry as a bonus!

If you have any comments or questions, please let me know in the comment box below.

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And subscribe to the biopharma newsletter 🙂

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About Diana Ribeiro

Diana Ribeiro  is a pharmacist and  freelance medical writer based in Cascais, Portugal.  Before starting her career in medical writing, Diana worked 10+ years in hospital and community pharmacies, where she helped patients and healthcare professionals with drug management and information. Nowadays, she helps pharma, biotech, and meddev companies communicate with their audiences in a clear, accurate, and compelling way. Diana is an active member of the European Medical Writers Association, where she volunteers for the webinar team. You can find more about her on  LinkedIn .

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Writing a Summary – Explanation & Examples

Published by Alvin Nicolas at October 17th, 2023 , Revised On October 17, 2023

In a world bombarded with vast amounts of information, condensing and presenting data in a digestible format becomes invaluable. Enter summaries. 

A summary is a brief and concise account of the main points of a larger body of work. It distils complex ideas, narratives, or data into a version that is quicker to read and easier to understand yet still retains the essence of the original content.

Importance of Summaries

The importance of summarising extends far beyond just making reading more manageable. In academic settings, summaries aid students in understanding and retaining complex materials, from textbook chapters to research articles. They also serve as tools to showcase one’s grasp of the subject in essays and reports. 

In professional arenas, summaries are pivotal in business reports, executive briefings, and even emails where key points need to be conveyed quickly to decision-makers. Meanwhile, summarising skills come into play in our personal lives when we relay news stories to friends, recap a movie plot, or even scroll through condensed news or app notifications on our smartphones.

Why Do We Write Summaries?

In our modern information age, the sheer volume of content available can be overwhelming. From detailed research papers to comprehensive news articles, the quest for knowledge is often met with lengthy and complex resources. This is where the power of a well-crafted summary comes into play. But what drives us to create or seek out summaries? Let’s discuss.

Makes Important Things Easy to Remember

At the heart of summarisation is the goal to understand. A well-written summary aids in digesting complex material. By distilling larger works into their core points, we reinforce the primary messages, making them easier to remember. This is especially crucial for students who need to retain knowledge for exams or professionals prepping for a meeting based on a lengthy report.

Simplification of Complex Topics

Not everyone is an expert in every field. Often, topics come laden with jargon, intricate details, and nuanced arguments. Summaries act as a bridge, translating this complexity into accessible and straightforward content. This is especially beneficial for individuals new to a topic or those who need just the highlights without the intricacies.

Aid in Researching and Understanding Diverse Sources

Researchers, writers, and academics often wade through many sources when working on a project. This involves finding sources of different types, such as primary or secondary sources , and then understanding their content. Sifting through each source in its entirety can be time-consuming. Summaries offer a streamlined way to understand each source’s main arguments or findings, making synthesising information from diverse materials more efficient.

Condensing Information for Presentation or Sharing

In professional settings, there is often a need to present findings, updates, or recommendations to stakeholders. An executive might not have the time to go through a 50-page report, but they would certainly appreciate a concise summary highlighting the key points. Similarly, in our personal lives, we often summarise movie plots, book stories, or news events when sharing with friends or family.

Characteristics of a Good Summary

Crafting an effective summary is an art. It’s more than just shortening a piece of content; it is about capturing the essence of the original work in a manner that is both accessible and true to its intent. Let’s explore the primary characteristics that distinguish a good summary from a mediocre one:

Conciseness

At the core of a summary is the concept of brevity. But being concise doesn’t mean leaving out vital information. A good summary will:

• Eliminate superfluous details or repetitive points.
• Focus on the primary arguments, events, or findings.
• Use succinct language without compromising the message.

Objectivity

Summarising is not about infusing personal opinions or interpretations. A quality summary will:

• Stick to the facts as presented in the original content.
• Avoid introducing personal biases or perspectives.
• Represent the original author’s intent faithfully.

A summary is meant to simplify and make content accessible. This is only possible if the summary itself is easy to understand. Ensuring clarity involves:

• Avoiding jargon or technical terms unless they are essential to the content. If they are used, they should be clearly defined.
• Structuring sentences in a straightforward manner.
• Making sure ideas are presented in a way that even someone unfamiliar with the topic can grasp the primary points.

A jumble of ideas, no matter how concise, will not make for a good summary. Coherence ensures that there’s a logical flow to the summarised content. A coherent summary will:

• Maintain a logical sequence, often following the structure of the original content.
• Use transition words or phrases to connect ideas and ensure smooth progression.
• Group related ideas together to provide structure and avoid confusion.

Steps of Writing a Summary

The process of creating a compelling summary is not merely about cutting down content. It involves understanding, discerning, and crafting. Here is a step-by-step guide to writing a summary that encapsulates the essence of the original work:

Reading Actively

Engage deeply with the content to ensure a thorough understanding.

• Read the entire document or work first to grasp its overall intent and structure.
• On the second read, underline or highlight the standout points or pivotal moments.
• Make brief notes in the margins or on a separate sheet, capturing the core ideas in your own words.

Identifying the Main Idea

Determine the backbone of the content, around which all other details revolve.

• Ask yourself: “What is the primary message or theme the author wants to convey?”
• This can often be found in the title, introduction, or conclusion of a piece.
• Frame the main idea in a clear and concise statement to guide your summary.

List Key Supporting Points

Understand the pillars that uphold the main idea, providing evidence or depth to the primary message.

• Refer back to the points you underlined or highlighted during your active reading.
• Note major arguments, evidence, or examples that the author uses to back up the main idea.
• Prioritise these points based on their significance to the main idea.

Draft the Summary

Convert your understanding into a condensed, coherent version of the original.

• Start with a statement of the main idea.
• Follow with the key supporting points, maintaining logical order.
• Avoid including trivial details or examples unless they’re crucial to the primary message.
• Use your own words, ensuring you are not plagiarising the original content.

Fine-tune your draft to ensure clarity, accuracy, and brevity.

• Read your draft aloud to check for flow and coherence.
• Ensure that your summary remains objective, avoiding any personal interpretations or biases.
• Check the length. See if any non-essential details can be removed without sacrificing understanding if it is too lengthy.
• Ensure clarity by ensuring the language is straightforward, and the main ideas are easily grasped.

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Dos and Don’ts of Summarising Key Points

Summarising, while seemingly straightforward, comes with its nuances. Properly condensing content demands a balance between brevity and fidelity to the original work. To aid in crafting exemplary summaries, here is a guide on the essential dos and don’ts:

Use your Own Words

This ensures that you have truly understood the content and are not merely parroting it. It also prevents issues of plagiarism.

Tip: After reading the original content, take a moment to reflect on it. Then, without looking at the source, write down the main points in your own words.

Attribute Sources Properly

Giving credit is both ethical and provides context to readers, helping them trace back to the original work if needed. How to cite sources correctly is a skill every writer should master.

Tip: Use signal phrases like “According to [Author/Source]…” or “As [Author/Source] points out…” to seamlessly incorporate attributions.

Ensure Accuracy of the Summarised Content

A summary should be a reliable reflection of the original content. Distorting or misrepresenting the original ideas compromises the integrity of the summary.

Tip: After drafting your summary, cross-check with the original content to ensure all key points are represented accurately and ensure you are referencing credible sources .

Avoid Copy-Pasting Chunks of Original Content

This not only raises plagiarism concerns but also shows a lack of genuine engagement with the material.

Tip: If a particular phrase or sentence from the original is pivotal and cannot be reworded without losing its essence, use block quotes , quotation marks, and attribute the source.

Do not Inject your Personal Opinion

A summary should be an objective reflection of the source material. Introducing personal biases or interpretations can mislead readers.

Tip: Stick to the facts and arguments presented in the original content. If you find yourself writing “I think” or “In my opinion,” reevaluate the sentence.

Do not Omit Crucial Information

While a summary is meant to be concise, it shouldn’t be at the expense of vital details that are essential to understanding the original content’s core message.

Tip: Prioritise information. Always include the main idea and its primary supports. If you are unsure whether a detail is crucial, consider its impact on the overall message.

Examples of Summaries

Here are a few examples that will help you get a clearer view of how to write a summary. 

Example 1: Summary of a News Article

Original Article: The article reports on the recent discovery of a rare species of frog in the Amazon rainforest. The frog, named the “Emerald Whisperer” due to its unique green hue and the soft chirping sounds it makes, was found by a team of researchers from the University of Texas. The discovery is significant as it offers insights into the biodiversity of the region, and the Emerald Whisperer might also play a pivotal role in understanding the ecosystem balance.

Summary: Researchers from the University of Texas have discovered a unique frog, termed the “Emerald Whisperer,” in the Amazon rainforest. This finding sheds light on the region’s biodiversity and underscores the importance of the frog in ecological studies.

Example 2: Summary of a Research Paper

Original Paper: In a study titled “The Impact of Urbanisation on Bee Populations,” researchers conducted a year-long observation on bee colonies in three urban areas and three rural areas. Using specific metrics like colony health, bee productivity, and population size, the study found that urban environments saw a 30% decline in bee populations compared to rural settings. The research attributes this decline to factors like pollution, reduced green spaces, and increased temperatures in urban areas.

Summary: A study analysing the effects of urbanisation on bee colonies found a significant 30% decrease in bee populations in urban settings compared to rural areas. The decline is linked to urban factors such as pollution, diminished greenery, and elevated temperatures.

Example 3: Summary of a Novel

Original Story: In the novel “Winds of Fate,” protagonist Clara is trapped in a timeless city where memories dictate reality. Throughout her journey, she encounters characters from her past, present, and imagined future. Battling her own perceptions and a menacing shadow figure, Clara seeks an elusive gateway to return to her real world. In the climax, she confronts the shadow, which turns out to be her own fear, and upon overcoming it, she finds her way back, realising that reality is subjective.

Summary: “Winds of Fate” follows Clara’s adventures in a surreal city shaped by memories. Confronting figures from various phases of her life and battling a symbolic shadow of her own fear, Clara eventually discovers that reality’s perception is malleable and subjective.

Frequently Asked Questions

How long is a summary.

A summary condenses a larger piece of content, capturing its main points and essence.  It is usually one-fourth of the original content.

What is a summary?

A summary is a concise representation of a larger text or content, highlighting its main ideas and points. It distils complex information into a shorter form, allowing readers to quickly grasp the essence of the original material without delving into extensive details. Summaries prioritise clarity, brevity, and accuracy.

When should I write a summary?

Write a summary when you need to condense lengthy content for easier comprehension and recall. It’s useful in academic settings, professional reports, presentations, and research to highlight key points. Summaries aid in comparing multiple sources, preparing for discussions, and sharing essential details of extensive materials efficiently with others.

How can I summarise a source without plagiarising?

To summarise without plagiarising: Read the source thoroughly, understand its main ideas, and then write the summary in your own words. Avoid copying phrases verbatim. Attribute the source properly. Use paraphrasing techniques and cross-check your summary against the original to ensure distinctiveness while retaining accuracy. Always prioritise understanding over direct replication.

What is the difference between a summary and an abstract?

A summary condenses a text, capturing its main points from various content types like books, articles, or movies. An abstract, typically found in research papers and scientific articles, provides a brief overview of the study’s purpose, methodology, results, and conclusions. Both offer concise versions, but abstracts are more structured and specific.

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Critical thinking is the disciplined art of analysing and evaluating information or situations by applying a range of intellectual skills. It goes beyond mere memorisation or blind acceptance of information, demanding a deeper understanding and assessment of evidence, context, and implications.

A credible source can be trusted to provide accurate, reliable, and unbiased information. Credible sources are essential for various purposes, including academic research, journalism, decision-making, and gaining knowledge on various topics.

A tertiary source is an information source that compiles, analyses, and synthesises both primary and secondary sources.

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Scholarly Articles

• Scholarly article sections
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• Reading scholarly articles practice
• Handouts: Reading & Evaluating
• How do I summarize a scholarly article?
• How do I find scholarly articles?
• Wrapping up scholarly articles

One strategy is to write down a quick summary of your understanding of the article right after you read it. This could be on a sticky note or in an email draft or a Word document, depending on what works best for you. Try writing down, in your own words:

• What problem the researcher was approaching
• What they did to study the problem
• What they found

This might look something like:

[Researchers] studied [topic] by [method] and found that [results]. Limitations included [limitations of study]. The authors suggest future research on [questions raised].

Dwyer et. al studied how college students' perceive pizza delivery. They surveyed local pizzerias to determine the amount of pizza delivered to a large public university in the United States over an entire academic year and found that most of the orders were large (for campus events), indicating a decline in student excitement about pizza. Dwyer et. al did not gain any data directly from students, which is recommended for further research.

You might also want to include:

• An important quote if necessary (including page numbers)
• A short reflection of how this source fits in with your topic and your other sources (does it present a new or conflicting point of view? etc.)
• A short reflection of how you might use it in your work (as background info, etc.)
• A short evaluation (is the author credible? etc.)
• The citation/reference

These notes are sometimes called " synthesis notes ." You can repeat this process with each source, and even build out an " annotated bibliography " if that works for you.

Consider reaching out to the SLCC Student Reading & Writing Center for more assistance.

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• Last Updated: Jul 26, 2023 11:01 AM
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• Published: 18 April 2024

Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research

• James Shaw 1 , 13 ,
• Joseph Ali 2 , 3 ,
• Caesar A. Atuire 4 , 5 ,
• Phaik Yeong Cheah 6 ,
• Armando Guio Español 7 ,
• Judy Wawira Gichoya 8 ,
• Adrienne Hunt 9 ,
• Daudi Jjingo 10 ,
• Katherine Littler 9 ,
• Daniela Paolotti 11 &
• Effy Vayena 12  

BMC Medical Ethics volume  25 , Article number:  46 ( 2024 ) Cite this article

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The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice. In this paper we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022.

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, research ethics committee members and other actors to engage with challenges and opportunities specifically related to research ethics. In 2022 the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations, 16 governance presentations, and a series of small group and large group discussions. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. In this paper, we highlight central insights arising from GFBR 2022.

We describe the significance of four thematic insights arising from the forum: (1) Appropriateness of building AI, (2) Transferability of AI systems, (3) Accountability for AI decision-making and outcomes, and (4) Individual consent. We then describe eight recommendations for governance leaders to enhance the ethical governance of AI in global health research, addressing issues such as AI impact assessments, environmental values, and fair partnerships.

Conclusions

The 2022 Global Forum on Bioethics in Research illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

Peer Review reports

Introduction

The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice [ 1 , 2 , 3 ]. Beyond the growing number of AI applications being implemented in health care, capabilities of AI models such as Large Language Models (LLMs) expand the potential reach and significance of AI technologies across health-related fields [ 4 , 5 ]. Discussion about effective, ethical governance of AI technologies has spanned a range of governance approaches, including government regulation, organizational decision-making, professional self-regulation, and research ethics review [ 6 , 7 , 8 ]. In this paper, we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health research, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022. Although applications of AI for research, health care, and public health are diverse and advancing rapidly, the insights generated at the forum remain highly relevant from a global health perspective. After summarizing important context for work in this domain, we highlight categories of ethical issues emphasized at the forum for attention from a research ethics perspective internationally. We then outline strategies proposed for research, innovation, and governance to support more ethical AI for global health.

In this paper, we adopt the definition of AI systems provided by the Organization for Economic Cooperation and Development (OECD) as our starting point. Their definition states that an AI system is “a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. AI systems are designed to operate with varying levels of autonomy” [ 9 ]. The conceptualization of an algorithm as helping to constitute an AI system, along with hardware, other elements of software, and a particular context of use, illustrates the wide variety of ways in which AI can be applied. We have found it useful to differentiate applications of AI in research as those classified as “AI systems for discovery” and “AI systems for intervention”. An AI system for discovery is one that is intended to generate new knowledge, for example in drug discovery or public health research in which researchers are seeking potential targets for intervention, innovation, or further research. An AI system for intervention is one that directly contributes to enacting an intervention in a particular context, for example informing decision-making at the point of care or assisting with accuracy in a surgical procedure.

The mandate of the GFBR is to take a broad view of what constitutes research and its regulation in global health, with special attention to bioethics in Low- and Middle- Income Countries. AI as a group of technologies demands such a broad view. AI development for health occurs in a variety of environments, including universities and academic health sciences centers where research ethics review remains an important element of the governance of science and innovation internationally [ 10 , 11 ]. In these settings, research ethics committees (RECs; also known by different names such as Institutional Review Boards or IRBs) make decisions about the ethical appropriateness of projects proposed by researchers and other institutional members, ultimately determining whether a given project is allowed to proceed on ethical grounds [ 12 ].

However, research involving AI for health also takes place in large corporations and smaller scale start-ups, which in some jurisdictions fall outside the scope of research ethics regulation. In the domain of AI, the question of what constitutes research also becomes blurred. For example, is the development of an algorithm itself considered a part of the research process? Or only when that algorithm is tested under the formal constraints of a systematic research methodology? In this paper we take an inclusive view, in which AI development is included in the definition of research activity and within scope for our inquiry, regardless of the setting in which it takes place. This broad perspective characterizes the approach to “research ethics” we take in this paper, extending beyond the work of RECs to include the ethical analysis of the wide range of activities that constitute research as the generation of new knowledge and intervention in the world.

Ethical governance of AI in global health

The ethical governance of AI for global health has been widely discussed in recent years. The World Health Organization (WHO) released its guidelines on ethics and governance of AI for health in 2021, endorsing a set of six ethical principles and exploring the relevance of those principles through a variety of use cases. The WHO guidelines also provided an overview of AI governance, defining governance as covering “a range of steering and rule-making functions of governments and other decision-makers, including international health agencies, for the achievement of national health policy objectives conducive to universal health coverage.” (p. 81) The report usefully provided a series of recommendations related to governance of seven domains pertaining to AI for health: data, benefit sharing, the private sector, the public sector, regulation, policy observatories/model legislation, and global governance. The report acknowledges that much work is yet to be done to advance international cooperation on AI governance, especially related to prioritizing voices from Low- and Middle-Income Countries (LMICs) in global dialogue.

One important point emphasized in the WHO report that reinforces the broader literature on global governance of AI is the distribution of responsibility across a wide range of actors in the AI ecosystem. This is especially important to highlight when focused on research for global health, which is specifically about work that transcends national borders. Alami et al. (2020) discussed the unique risks raised by AI research in global health, ranging from the unavailability of data in many LMICs required to train locally relevant AI models to the capacity of health systems to absorb new AI technologies that demand the use of resources from elsewhere in the system. These observations illustrate the need to identify the unique issues posed by AI research for global health specifically, and the strategies that can be employed by all those implicated in AI governance to promote ethically responsible use of AI in global health research.

RECs and the regulation of research involving AI

RECs represent an important element of the governance of AI for global health research, and thus warrant further commentary as background to our paper. Despite the importance of RECs, foundational questions have been raised about their capabilities to accurately understand and address ethical issues raised by studies involving AI. Rahimzadeh et al. (2023) outlined how RECs in the United States are under-prepared to align with recent federal policy requiring that RECs review data sharing and management plans with attention to the unique ethical issues raised in AI research for health [ 13 ]. Similar research in South Africa identified variability in understanding of existing regulations and ethical issues associated with health-related big data sharing and management among research ethics committee members [ 14 , 15 ]. The effort to address harms accruing to groups or communities as opposed to individuals whose data are included in AI research has also been identified as a unique challenge for RECs [ 16 , 17 ]. Doerr and Meeder (2022) suggested that current regulatory frameworks for research ethics might actually prevent RECs from adequately addressing such issues, as they are deemed out of scope of REC review [ 16 ]. Furthermore, research in the United Kingdom and Canada has suggested that researchers using AI methods for health tend to distinguish between ethical issues and social impact of their research, adopting an overly narrow view of what constitutes ethical issues in their work [ 18 ].

The challenges for RECs in adequately addressing ethical issues in AI research for health care and public health exceed a straightforward survey of ethical considerations. As Ferretti et al. (2021) contend, some capabilities of RECs adequately cover certain issues in AI-based health research, such as the common occurrence of conflicts of interest where researchers who accept funds from commercial technology providers are implicitly incentivized to produce results that align with commercial interests [ 12 ]. However, some features of REC review require reform to adequately meet ethical needs. Ferretti et al. outlined weaknesses of RECs that are longstanding and those that are novel to AI-related projects, proposing a series of directions for development that are regulatory, procedural, and complementary to REC functionality. The work required on a global scale to update the REC function in response to the demands of research involving AI is substantial.

These issues take greater urgency in the context of global health [ 19 ]. Teixeira da Silva (2022) described the global practice of “ethics dumping”, where researchers from high income countries bring ethically contentious practices to RECs in low-income countries as a strategy to gain approval and move projects forward [ 20 ]. Although not yet systematically documented in AI research for health, risk of ethics dumping in AI research is high. Evidence is already emerging of practices of “health data colonialism”, in which AI researchers and developers from large organizations in high-income countries acquire data to build algorithms in LMICs to avoid stricter regulations [ 21 ]. This specific practice is part of a larger collection of practices that characterize health data colonialism, involving the broader exploitation of data and the populations they represent primarily for commercial gain [ 21 , 22 ]. As an additional complication, AI algorithms trained on data from high-income contexts are unlikely to apply in straightforward ways to LMIC settings [ 21 , 23 ]. In the context of global health, there is widespread acknowledgement about the need to not only enhance the knowledge base of REC members about AI-based methods internationally, but to acknowledge the broader shifts required to encourage their capabilities to more fully address these and other ethical issues associated with AI research for health [ 8 ].

Although RECs are an important part of the story of the ethical governance of AI for global health research, they are not the only part. The responsibilities of supra-national entities such as the World Health Organization, national governments, organizational leaders, commercial AI technology providers, health care professionals, and other groups continue to be worked out internationally. In this context of ongoing work, examining issues that demand attention and strategies to address them remains an urgent and valuable task.

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, REC members and other actors to engage with challenges and opportunities specifically related to research ethics. Each year the GFBR meeting includes a series of case studies and keynotes presented in plenary format to an audience of approximately 100 people who have applied and been competitively selected to attend, along with small-group breakout discussions to advance thinking on related issues. The specific topic of the forum changes each year, with past topics including ethical issues in research with people living with mental health conditions (2021), genome editing (2019), and biobanking/data sharing (2018). The forum is intended to remain grounded in the practical challenges of engaging in research ethics, with special interest in low resource settings from a global health perspective. A post-meeting fellowship scheme is open to all LMIC participants, providing a unique opportunity to apply for funding to further explore and address the ethical challenges that are identified during the meeting.

In 2022, the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations (both short and long form) reporting on specific initiatives related to research ethics and AI for health, and 16 governance presentations (both short and long form) reporting on actual approaches to governing AI in different country settings. A keynote presentation from Professor Effy Vayena addressed the topic of the broader context for AI ethics in a rapidly evolving field. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. The 2-day forum addressed a wide range of themes. The conference report provides a detailed overview of each of the specific topics addressed while a policy paper outlines the cross-cutting themes (both documents are available at the GFBR website: https://www.gfbr.global/past-meetings/16th-forum-cape-town-south-africa-29-30-november-2022/ ). As opposed to providing a detailed summary in this paper, we aim to briefly highlight central issues raised, solutions proposed, and the challenges facing the research ethics community in the years to come.

In this way, our primary aim in this paper is to present a synthesis of the challenges and opportunities raised at the GFBR meeting and in the planning process, followed by our reflections as a group of authors on their significance for governance leaders in the coming years. We acknowledge that the views represented at the meeting and in our results are a partial representation of the universe of views on this topic; however, the GFBR leadership invested a great deal of resources in convening a deeply diverse and thoughtful group of researchers and practitioners working on themes of bioethics related to AI for global health including those based in LMICs. We contend that it remains rare to convene such a strong group for an extended time and believe that many of the challenges and opportunities raised demand attention for more ethical futures of AI for health. Nonetheless, our results are primarily descriptive and are thus not explicitly grounded in a normative argument. We make effort in the Discussion section to contextualize our results by describing their significance and connecting them to broader efforts to reform global health research and practice.

Uniquely important ethical issues for AI in global health research

Presentations and group dialogue over the course of the forum raised several issues for consideration, and here we describe four overarching themes for the ethical governance of AI in global health research. Brief descriptions of each issue can be found in Table  1 . Reports referred to throughout the paper are available at the GFBR website provided above.

The first overarching thematic issue relates to the appropriateness of building AI technologies in response to health-related challenges in the first place. Case study presentations referred to initiatives where AI technologies were highly appropriate, such as in ear shape biometric identification to more accurately link electronic health care records to individual patients in Zambia (Alinani Simukanga). Although important ethical issues were raised with respect to privacy, trust, and community engagement in this initiative, the AI-based solution was appropriately matched to the challenge of accurately linking electronic records to specific patient identities. In contrast, forum participants raised questions about the appropriateness of an initiative using AI to improve the quality of handwashing practices in an acute care hospital in India (Niyoshi Shah), which led to gaming the algorithm. Overall, participants acknowledged the dangers of techno-solutionism, in which AI researchers and developers treat AI technologies as the most obvious solutions to problems that in actuality demand much more complex strategies to address [ 24 ]. However, forum participants agreed that RECs in different contexts have differing degrees of power to raise issues of the appropriateness of an AI-based intervention.

The second overarching thematic issue related to whether and how AI-based systems transfer from one national health context to another. One central issue raised by a number of case study presentations related to the challenges of validating an algorithm with data collected in a local environment. For example, one case study presentation described a project that would involve the collection of personally identifiable data for sensitive group identities, such as tribe, clan, or religion, in the jurisdictions involved (South Africa, Nigeria, Tanzania, Uganda and the US; Gakii Masunga). Doing so would enable the team to ensure that those groups were adequately represented in the dataset to ensure the resulting algorithm was not biased against specific community groups when deployed in that context. However, some members of these communities might desire to be represented in the dataset, whereas others might not, illustrating the need to balance autonomy and inclusivity. It was also widely recognized that collecting these data is an immense challenge, particularly when historically oppressive practices have led to a low-trust environment for international organizations and the technologies they produce. It is important to note that in some countries such as South Africa and Rwanda, it is illegal to collect information such as race and tribal identities, re-emphasizing the importance for cultural awareness and avoiding “one size fits all” solutions.

The third overarching thematic issue is related to understanding accountabilities for both the impacts of AI technologies and governance decision-making regarding their use. Where global health research involving AI leads to longer-term harms that might fall outside the usual scope of issues considered by a REC, who is to be held accountable, and how? This question was raised as one that requires much further attention, with law being mixed internationally regarding the mechanisms available to hold researchers, innovators, and their institutions accountable over the longer term. However, it was recognized in breakout group discussion that many jurisdictions are developing strong data protection regimes related specifically to international collaboration for research involving health data. For example, Kenya’s Data Protection Act requires that any internationally funded projects have a local principal investigator who will hold accountability for how data are shared and used [ 25 ]. The issue of research partnerships with commercial entities was raised by many participants in the context of accountability, pointing toward the urgent need for clear principles related to strategies for engagement with commercial technology companies in global health research.

The fourth and final overarching thematic issue raised here is that of consent. The issue of consent was framed by the widely shared recognition that models of individual, explicit consent might not produce a supportive environment for AI innovation that relies on the secondary uses of health-related datasets to build AI algorithms. Given this recognition, approaches such as community oversight of health data uses were suggested as a potential solution. However, the details of implementing such community oversight mechanisms require much further attention, particularly given the unique perspectives on health data in different country settings in global health research. Furthermore, some uses of health data do continue to require consent. One case study of South Africa, Nigeria, Kenya, Ethiopia and Uganda suggested that when health data are shared across borders, individual consent remains necessary when data is transferred from certain countries (Nezerith Cengiz). Broader clarity is necessary to support the ethical governance of health data uses for AI in global health research.

Recommendations for ethical governance of AI in global health research

Dialogue at the forum led to a range of suggestions for promoting ethical conduct of AI research for global health, related to the various roles of actors involved in the governance of AI research broadly defined. The strategies are written for actors we refer to as “governance leaders”, those people distributed throughout the AI for global health research ecosystem who are responsible for ensuring the ethical and socially responsible conduct of global health research involving AI (including researchers themselves). These include RECs, government regulators, health care leaders, health professionals, corporate social accountability officers, and others. Enacting these strategies would bolster the ethical governance of AI for global health more generally, enabling multiple actors to fulfill their roles related to governing research and development activities carried out across multiple organizations, including universities, academic health sciences centers, start-ups, and technology corporations. Specific suggestions are summarized in Table  2 .

First, forum participants suggested that governance leaders including RECs, should remain up to date on recent advances in the regulation of AI for health. Regulation of AI for health advances rapidly and takes on different forms in jurisdictions around the world. RECs play an important role in governance, but only a partial role; it was deemed important for RECs to acknowledge how they fit within a broader governance ecosystem in order to more effectively address the issues within their scope. Not only RECs but organizational leaders responsible for procurement, researchers, and commercial actors should all commit to efforts to remain up to date about the relevant approaches to regulating AI for health care and public health in jurisdictions internationally. In this way, governance can more adequately remain up to date with advances in regulation.

Second, forum participants suggested that governance leaders should focus on ethical governance of health data as a basis for ethical global health AI research. Health data are considered the foundation of AI development, being used to train AI algorithms for various uses [ 26 ]. By focusing on ethical governance of health data generation, sharing, and use, multiple actors will help to build an ethical foundation for AI development among global health researchers.

Third, forum participants believed that governance processes should incorporate AI impact assessments where appropriate. An AI impact assessment is the process of evaluating the potential effects, both positive and negative, of implementing an AI algorithm on individuals, society, and various stakeholders, generally over time frames specified in advance of implementation [ 27 ]. Although not all types of AI research in global health would warrant an AI impact assessment, this is especially relevant for those studies aiming to implement an AI system for intervention into health care or public health. Organizations such as RECs can use AI impact assessments to boost understanding of potential harms at the outset of a research project, encouraging researchers to more deeply consider potential harms in the development of their study.

Fourth, forum participants suggested that governance decisions should incorporate the use of environmental impact assessments, or at least the incorporation of environment values when assessing the potential impact of an AI system. An environmental impact assessment involves evaluating and anticipating the potential environmental effects of a proposed project to inform ethical decision-making that supports sustainability [ 28 ]. Although a relatively new consideration in research ethics conversations [ 29 ], the environmental impact of building technologies is a crucial consideration for the public health commitment to environmental sustainability. Governance leaders can use environmental impact assessments to boost understanding of potential environmental harms linked to AI research projects in global health over both the shorter and longer terms.

Fifth, forum participants suggested that governance leaders should require stronger transparency in the development of AI algorithms in global health research. Transparency was considered essential in the design and development of AI algorithms for global health to ensure ethical and accountable decision-making throughout the process. Furthermore, whether and how researchers have considered the unique contexts into which such algorithms may be deployed can be surfaced through stronger transparency, for example in describing what primary considerations were made at the outset of the project and which stakeholders were consulted along the way. Sharing information about data provenance and methods used in AI development will also enhance the trustworthiness of the AI-based research process.

Sixth, forum participants suggested that governance leaders can encourage or require community engagement at various points throughout an AI project. It was considered that engaging patients and communities is crucial in AI algorithm development to ensure that the technology aligns with community needs and values. However, participants acknowledged that this is not a straightforward process. Effective community engagement requires lengthy commitments to meeting with and hearing from diverse communities in a given setting, and demands a particular set of skills in communication and dialogue that are not possessed by all researchers. Encouraging AI researchers to begin this process early and build long-term partnerships with community members is a promising strategy to deepen community engagement in AI research for global health. One notable recommendation was that research funders have an opportunity to incentivize and enable community engagement with funds dedicated to these activities in AI research in global health.

Seventh, forum participants suggested that governance leaders can encourage researchers to build strong, fair partnerships between institutions and individuals across country settings. In a context of longstanding imbalances in geopolitical and economic power, fair partnerships in global health demand a priori commitments to share benefits related to advances in medical technologies, knowledge, and financial gains. Although enforcement of this point might be beyond the remit of RECs, commentary will encourage researchers to consider stronger, fairer partnerships in global health in the longer term.

Eighth, it became evident that it is necessary to explore new forms of regulatory experimentation given the complexity of regulating a technology of this nature. In addition, the health sector has a series of particularities that make it especially complicated to generate rules that have not been previously tested. Several participants highlighted the desire to promote spaces for experimentation such as regulatory sandboxes or innovation hubs in health. These spaces can have several benefits for addressing issues surrounding the regulation of AI in the health sector, such as: (i) increasing the capacities and knowledge of health authorities about this technology; (ii) identifying the major problems surrounding AI regulation in the health sector; (iii) establishing possibilities for exchange and learning with other authorities; (iv) promoting innovation and entrepreneurship in AI in health; and (vi) identifying the need to regulate AI in this sector and update other existing regulations.

Ninth and finally, forum participants believed that the capabilities of governance leaders need to evolve to better incorporate expertise related to AI in ways that make sense within a given jurisdiction. With respect to RECs, for example, it might not make sense for every REC to recruit a member with expertise in AI methods. Rather, it will make more sense in some jurisdictions to consult with members of the scientific community with expertise in AI when research protocols are submitted that demand such expertise. Furthermore, RECs and other approaches to research governance in jurisdictions around the world will need to evolve in order to adopt the suggestions outlined above, developing processes that apply specifically to the ethical governance of research using AI methods in global health.

Research involving the development and implementation of AI technologies continues to grow in global health, posing important challenges for ethical governance of AI in global health research around the world. In this paper we have summarized insights from the 2022 GFBR, focused specifically on issues in research ethics related to AI for global health research. We summarized four thematic challenges for governance related to AI in global health research and nine suggestions arising from presentations and dialogue at the forum. In this brief discussion section, we present an overarching observation about power imbalances that frames efforts to evolve the role of governance in global health research, and then outline two important opportunity areas as the field develops to meet the challenges of AI in global health research.

Dialogue about power is not unfamiliar in global health, especially given recent contributions exploring what it would mean to de-colonize global health research, funding, and practice [ 30 , 31 ]. Discussions of research ethics applied to AI research in global health contexts are deeply infused with power imbalances. The existing context of global health is one in which high-income countries primarily located in the “Global North” charitably invest in projects taking place primarily in the “Global South” while recouping knowledge, financial, and reputational benefits [ 32 ]. With respect to AI development in particular, recent examples of digital colonialism frame dialogue about global partnerships, raising attention to the role of large commercial entities and global financial capitalism in global health research [ 21 , 22 ]. Furthermore, the power of governance organizations such as RECs to intervene in the process of AI research in global health varies widely around the world, depending on the authorities assigned to them by domestic research governance policies. These observations frame the challenges outlined in our paper, highlighting the difficulties associated with making meaningful change in this field.

Despite these overarching challenges of the global health research context, there are clear strategies for progress in this domain. Firstly, AI innovation is rapidly evolving, which means approaches to the governance of AI for health are rapidly evolving too. Such rapid evolution presents an important opportunity for governance leaders to clarify their vision and influence over AI innovation in global health research, boosting the expertise, structure, and functionality required to meet the demands of research involving AI. Secondly, the research ethics community has strong international ties, linked to a global scholarly community that is committed to sharing insights and best practices around the world. This global community can be leveraged to coordinate efforts to produce advances in the capabilities and authorities of governance leaders to meaningfully govern AI research for global health given the challenges summarized in our paper.

Limitations

Our paper includes two specific limitations that we address explicitly here. First, it is still early in the lifetime of the development of applications of AI for use in global health, and as such, the global community has had limited opportunity to learn from experience. For example, there were many fewer case studies, which detail experiences with the actual implementation of an AI technology, submitted to GFBR 2022 for consideration than was expected. In contrast, there were many more governance reports submitted, which detail the processes and outputs of governance processes that anticipate the development and dissemination of AI technologies. This observation represents both a success and a challenge. It is a success that so many groups are engaging in anticipatory governance of AI technologies, exploring evidence of their likely impacts and governing technologies in novel and well-designed ways. It is a challenge that there is little experience to build upon of the successful implementation of AI technologies in ways that have limited harms while promoting innovation. Further experience with AI technologies in global health will contribute to revising and enhancing the challenges and recommendations we have outlined in our paper.

Second, global trends in the politics and economics of AI technologies are evolving rapidly. Although some nations are advancing detailed policy approaches to regulating AI more generally, including for uses in health care and public health, the impacts of corporate investments in AI and political responses related to governance remain to be seen. The excitement around large language models (LLMs) and large multimodal models (LMMs) has drawn deeper attention to the challenges of regulating AI in any general sense, opening dialogue about health sector-specific regulations. The direction of this global dialogue, strongly linked to high-profile corporate actors and multi-national governance institutions, will strongly influence the development of boundaries around what is possible for the ethical governance of AI for global health. We have written this paper at a point when these developments are proceeding rapidly, and as such, we acknowledge that our recommendations will need updating as the broader field evolves.

Ultimately, coordination and collaboration between many stakeholders in the research ethics ecosystem will be necessary to strengthen the ethical governance of AI in global health research. The 2022 GFBR illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

Data availability

All data and materials analyzed to produce this paper are available on the GFBR website: https://www.gfbr.global/past-meetings/16th-forum-cape-town-south-africa-29-30-november-2022/ .

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Acknowledgements

We would like to acknowledge the outstanding contributions of the attendees of GFBR 2022 in Cape Town, South Africa. This paper is authored by members of the GFBR 2022 Planning Committee. We would like to acknowledge additional members Tamra Lysaght, National University of Singapore, and Niresh Bhagwandin, South African Medical Research Council, for their input during the planning stages and as reviewers of the applications to attend the Forum.

This work was supported by Wellcome [222525/Z/21/Z], the US National Institutes of Health, the UK Medical Research Council (part of UK Research and Innovation), and the South African Medical Research Council through funding to the Global Forum on Bioethics in Research.

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Shaw, J., Ali, J., Atuire, C.A. et al. Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research. BMC Med Ethics 25 , 46 (2024). https://doi.org/10.1186/s12910-024-01044-w

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